Important considerations for an AI OS

2  – An organization OS is not a computer OS

3  –  Reinventing AI system wheels is not wise

4  – Method and sequence of adoption

An open letter to Fortune 500 CEOs on AI systems from Kyield’s founder

Since we offer an organizational and network operating system—technically defined as a modular artificial intelligence system, we usually deal with the most important strategic and operational issues facing organizations. This is most obvious in our new HumCat offering, which provides advanced technology for the prevention of human-caused catastrophes. Short of preventing an asteroid or comet collision with earth, this is among the most important work that is executable today. Please keep that in mind while reading.

In our efforts to assist organizations we perform an informal review on our process with the goal of improving upon the experience for all concerned. In cases where we invest a considerable amount of time, energy, and money, the review is more formal and extensive, including SWOT analysis, security checks and reviews, and deep scenario plans that can become extremely detailed down to the molecular level.

We are still a small company and I am the founder who performed the bulk of R&D, so by necessity I’m still involved in each case. Our current process has been refined over the last decade in many dozens of engagements with senior teams on strategic issues. In so doing we see patterns develop over time that we learn from and I share with senior executives when behavior causes them problems. This is still relatively new territory while we carefully craft the AI-assisted economy.

I just sent another such lessons learned to a CEO in a public company this morning. Usually this is done in a confidential manner to very few and never revealed otherwise, but I wanted to share a general pattern that is negatively impacting organizations in part due to the compounding effect it has on the broader economy. Essentially this can be reduced to misapplying the company’s playbook in dealing with advanced technology.

The playbook in this instance for lack of a better word can be described as ‘industry tech’, as in fintech or insurtech. While new to some in banking and insurance, this basic model has been applied for decades with limited, mixed results over time. The current version has switched the name incubators for accelerators, innovation shops now take the place of R&D and/or product development, and corporate VC is still good old corporate VC. Generally speaking this playbook can be a good thing for companies in industries like banking and insurance where the bulk of R&D came from a small group of companies that delivered very little innovation over decades, or worse as we saw in the financial crisis, which delivered toxic innovation. Eventually the lack of innovation can cause macro economic problems and place an entire industry at risk.

A highly refined AI system like ours is considered by many today to be among most important and valuable of any type, hence the fear however unjustified in our case. Anyone expecting to receive our ideas through open innovation on these issues is irresponsible and dangerous to themselves and others, including your company. That is the same as bank employees handing out money for free or insurance claims adjusters knowingly paying fraudulent claims at scale. Don’t treat the issue of intellectual capital and property lightly, including trade secrets, or it will damage your organization badly.

The most common mistake I see in practice is relying solely on ‘the innovation playbook’. CEOs especially should always be open to opportunity and on the lookout for threats, particularly any that have the capacity to make or save the company. Most of the critical issues companies face will not come from or fit within the innovation playbook. Accelerators, internal innovation shops and corporate VC arms are good tools when used appropriately, but if you rely solely on them you will almost certainly fail. None of the most successful CEOs that come to mind rely only on fixed playbooks.

These are a few of the more common specific suggestions I’ve made to CEOs of leading companies in dealing with AI systems, in part based on working with several of the most successful tech companies at similar stage, and in part in engaging with hundreds of other organizations from our perspective. As you can see I’ve learned to be a bit more blunt.

  1. Don’t attempt to force a system like Kyield into your innovation playbook. Attempting to do so will only increase risk for your company and do nothing at all for mine but waste time and money. Google succeeded in doing so with DeepMind, but it came at a high price and they needed to be flexible. Very few will be able to engage similarly, which is one reason why the Kyield OS is still available to customer organizations.

  2. With very few exceptions, primarily industry-specific R&D, we are far more experienced in AI systems than your team or consultants. With regard to the specific issues, functionality, and use cases within Kyield that we offer, no one has more experience and intel I am aware of. We simply haven’t shared it. Many are expert in specific algorithmics, but not distributed AI systems, which is what is needed.

  3. A few companies have now wasted billions of USD attempting to replicate the wheel that we will provide at a small fraction of that cost. A small number of CEOs have lost their jobs due to events that cost tens of billions I have good reason to believe our HumCat could have prevented. It therefore makes no sense at all not to adopt.

  4. The process must be treated with the respect and priority it deserves. Take it seriously. Lead it personally. Any such effort requires a team but can’t be entirely delegated.

  5. Our HumCat program requires training and certification in senior officers for good reasons. If it wasn’t necessary it wouldn’t be required.

  6. Don’t fear us, but don’t attempt to steal our work. Some of the best in the world have tried and failed. It’s not a good idea to try with us or any of our peers.

  7. Resist the temptation to customize universal issues that have already been refined. We call this the open checkbook to AI system hell. It has ended several CEO careers already and it’s early.

  8. Since these are the most important issues facing any organization, it’s really wise to let us help. Despite the broad characterization, not all of us are trying to kill your organization or put your people out of work. Quite the contrary in our case or we would have gone down a different path long ago.

  9. We are among the best allies to have in this war.

  10. It is war.

A Million in Prevention can be Worth Billions of Cure with Distributed AI Systems

Deep Water Horizon Rig (NOAA)

DeepWater Horizon Rig, April 2010 (NOAA News)

Every year, natural catastrophes (nat cat) are highly visible events that cause major damage across the world. In 2016 the cost of nat cats were estimated to be $175 billion, $50 billion of which were covered by insurance, reflecting severe financial losses for impacted areas.[i]  The total cost of natural catastrophes since 2000 was approximately $2.3 trillion.[ii]

Much less understood is that human-caused catastrophes (hum cat) have resulted in much greater economic damage during the same period and have become increasingly preventable. Since 2000 the world has experienced two preventable hum cat events of $10 trillion or more: the 9/11 terrorist attacks and the global financial crisis. In addition, although the Tōhoku earthquake in Japan was unavoidable, the Fukushima Daiichi nuclear disaster was also preventable, now estimated at $188 billion excluding widespread human suffering and environmental damage.[iii]

One commonality in these and other disasters is that experts issued advanced and accurate evidence-based warnings only to be ignored. The most famous and costly such example was the Phoenix memo issued on July 10, 2001 by Special Agent Kenneth J. Williams.[iv]  The FBI memo was described as “chilling” by the first journalist who reviewed it due to specificity in describing terrorist-linked individuals who were training to fly commercial aircraft.

Williams was a seasoned terrorism expert who followed the prescribed use of the FBI’s rules-based system, yet during the two-month period prior to the 9/11 attacks no relevant action was taken. If the lead had been pursued the terrorist attacks and ensuing events would very likely have been avoided, including two wars with massive casualties and continuing hostilities.

Government agencies have invested heavily in prevention since that fateful day of September 11, 2001 so hopefully similar events will be prevented.

In corporate catastrophes, however, prevention scenarios are usually more complex than the Phoenix memo case. They are also occurring with increasing frequency and expanding in scale and cost.

The remainder of this article can be viewed at Cognitive World.

View brief video by Mark related to this article and Kyield’s new HumCat product.

Why the U.S. Must Lead the World with Intelligent Infrastructure

Americans have been through a great deal in the last two decades. In addition to the network effect that consolidated wealth in a few zip codes, we endured rapid globalization that benefited other nations at the expense of our own, the 9/11 terrorist attacks, multiple wars, and the global financial crisis, all within the first few years of this millennium.

To put this series of interconnected events in perspective, the collective shock is roughly comparable to the impact of a small super volcano, a minor asteroid, or a limited nuclear war. Catastrophes of this scale are thought to be of sufficient size to change the course of modern civilization, depending of course upon our response.

The most recent CBO report forecasts the U.S. federal debt at 150 percent of gross domestic product in 2047, which would place the U.S. as the third most indebted nation in 2017 between Greece and Lebanon. This is obviously not where the U.S. wants to be in 30 years. Fortunately, such a decline is unnecessary and well within our power to avoid, though the path is narrow and hazards are many.

Catching up on deferred maintenance is a necessary but insufficient plan for the challenges facing Americans. A modern strategic infrastructure plan should be focused on unleashing the current national economy similar to previous eras with the intercontinental railroad, interstate highway system, or electric grid.

The focus should be maximize benefits from our inventions, engineered systems and technologies to recreate a sustainable competitive advantage. One benefit of lagging behind other countries in infrastructure is that much progress has been made in recent years. Future projects can be embedded with hardware that enable intelligent networks, which can then be managed with distributed operating systems enhanced with artificial intelligence (AI) to meet the diverse needs of our society.

AI systems can substantially resolve many of the destructive forces and high-risk areas facing the modern economy, including the ability to provide far more effective governance in a highly complex data-driven world, prevention of most types of human-caused catastrophes, improved workplace productivity, more effective security, and reversal of the dangerous trajectory in healthcare costs.

In order to realize the full potential of a national intelligent infrastructure strategy, it must be planned in a highly specific manner. Intelligent infrastructure is driven by physics and engineering, which can be easily damaged by misguided or corrupted politics. The value of AI systems is substantially dependent upon the availability and integrity of data. Important priorities include but are not limited to interoperability, security, privacy, business modeling, cost of ongoing maintenance, and adaptability for future innovations.

The combination of technical viability in AI systems with the current macro economic scenario has created a perfect storm for public-private partnerships. Funds with trillions USD under management are in search of improved yields in mid to long-term bonds that offer lower risk profiles and diversification, which allows risk transfer to investors for specific projects rather than tacked on to an unsustainable national debt trajectory. Moreover, the combination of intelligent infrastructure with AI systems can improve productivity, provide attractive return on investment, and create new high paying jobs that will be competitive far into the future.

The federal government should act as the policy and standards body to avoid hard lessons learned in previous national infrastructure programs. A plug-and-play architecture is needed that encourages economic diversification in all states, fosters new business formation and new wealth creation that has the capacity for reversing the increasingly historic wealth gap.

In today’s fast moving hyper competitive world, the U.S. cannot afford to wait a century to unravel the type of monopolies that were cobbled together during the formation of the electric grid. The network economy increasingly represents the entire economy so must be as diversified and dynamic as society if to remain healthy and sustainable.

If the Trump administration and U.S. Congress seize this historic opportunity for a strategic intelligent infrastructure plan, they should find bipartisan support as it can positively impact every zip code in America, which could serve to reunify the nation around common good. Executed well, a strategic intelligent infrastructure plan can serve as a solid foundational platform to solve many of the current and future challenges facing America and the world.

E-book on AI systems by Kyield

My ebook “Ascension to a Higher Level of Performance” is now available to the public.

Learn about the background of Kyield and the multi-disciplinary science involved with AI systems, with a particular focus on AI augmentation for knowledge work and how to achieve a continuously adaptive learning organization (CALO).

COMPUTER SCIENCE AND PHYSICS…………………………………………………………….

LIFE SCIENCES AND HEALTHCARE……………………………………………………………

BANKING AND FINANCIAL SERVICES ………………………………………………………..

EXAMPLE: BANKING, PHASE 1…………………………………………………………………

Visit our learning center to download this ebook and view other publications from Kyield at the confluence of AI systems, crisis prevention, risk management, security, productivity and organizational management.

A Visit From America’s Founding Fathers – New Year’s Eve 2016

‘Twas the week after Christmas, when all thro’ Wall Street,

Not a broker was working, not even a tweet;

401ks were chock-full from the Fed,

In hopes that someone else would put their crisis to bed;

Investors were contented with the size of their yachts,

And dreams teased of eternity on Mars with toy bots;

Small businesses were suffering, employees quite stressed,

Working part-time jobs so that others may rest,

Then storm clouds of democracy began to gather,

So I dashed from my office to see what was the matter.

I threw on my coat and ran to the train station,

Hoping that a miracle could restore this great nation.

The moon shined brightly on glistening ice,

But a cold wind on Main St. punished rolling the dice,

When, to my great surprise what did we hear?

Could that be rumblings of a government we need not fear?

With corporate jets scrambling, and lobbyists screaming,

Something awful scary must have caused this convening.

More rapid than geese in flocks they came,

“Now, PENCE! now, ROSS! now, TILLERSON and COHN!,

To the New York penthouse! to the top of Trump Tower!

Now heal thy economy! Make great again this power!

As surgeons faced with a pandemic of moral hazard,

When trust in institutions remained torn and shattered,

So off to the capitol as physicians they flew,

With jets full of billionaires, and Donald J. Trump too.

And then, high above the plains jet engines roared

Then screeching of tires with titans on board.

As people left offices, churches, and schools,

They whispered to each other “hope we weren’t fools”

They were dressed in fine clothing from head to foot,

Some flashing gold like some kind of crooks;

A belly full of solutions in the cargo bay,

More false promises or will they do as they say?

From heaven above the Founders looked down,

Their eyes – how wise! Their faces full of frowns!

Although they expected the corruption found below,

It still pained to witness this nation they bestowed.

So they sprang to their sleigh, a founding force of seven,

And gathered their writings; then descended from heaven,

They flew straight to the rooftops above the West Wing,

And scurried down a chimney to the room in shape of a ring;

Leaders from all three branches gathered with their teams,

Who sat silently listening, voices finally out of steam,

When ghostly founders read their papers, it was quite a sight!

Copyright © 2016 Mark Montgomery. All Rights Reserved.

Independence Day Lessons on Adaptability and Survival from the Ancestral Puebloans

Aroma Pueblo, by Betsy Genta-Montgomery Copyright 2016

Aroma Pueblo by Betsy Genta-Montgomery Copyright 2016

July 4th, 2016

The photo above represents a learning opportunity especially relating to survival and adaptation. Recently completed by my wife Betsy[i], the artwork was inspired by our visit to the Acoma Pueblo a few months ago, which is one of the oldest continuously inhabited communities in North America. Ancestors of current residents have lived on top of a 360-foot tall rock tower since 1150 A.D.

Their previous home was located on an even more formidable tower across the valley similar to the rock mesa in the center of Betsy’s art piece. Legend has it that a bolt of lightening shattered the steep rock steps leading to their old village so the Acoma people moved to the current location.

Other than the occasional battles with other Native American tribes, the Acoma people lived for generations at a time in relative peace until interrupted by major events that would change the course of history. The first major event occurred in the form of a 50-year drought that forced the Ancestral Pueblo peoples from the Chaco Canyon to other locations throughout the Southwestern U.S.

A second history-changing event for the Pueblos began with the arrival of the Spanish around 1540. The relationship between these two very different cultures was peaceful for several decades until a series of mishaps led to the horrific Battle of Acoma Pueblo. After two days of traditional warfare, modern technology in the form of cannon proved decisive for the Spanish in winning the battle. Tragically, the Spanish officer in charge ordered savage retribution followed by many years of slavery, ultimately leading to the bloody Pueblo Revolt eight decades later when tribes joined together and drove the Spanish out of the region.

Taken together, the Acoma Massacre and Pueblo Revolt represent an extreme case of leadership failure that decision makers from all walks of life can learn from. A single horrific decision by one military leader on a single day nearly two centuries before the American Revolution still brings pain and influences decisions throughout the region over four centuries later, and no doubt influenced many a negotiation.

The centuries that followed offered more turmoil for the region under the control of Spain, Mexico, and then finally the United States in 1848, but today the Acoma people are applying modern business methods in making the best of a challenging situation, seizing opportunities, and improving their future while preserving their cultural roots and traditions. The Acoma Pueblo own and operate cultural facilities at ‘old Acoma’ as well as the Sky City Casino Hotel and travel center, which is a significant employer and economic engine on I-40 between Albuquerque and Grants, New Mexico.

In addition to visiting with the friendly people at the old pueblo, who graciously welcomed a diverse mix of international tourists during our Easter weekend tour, we also enjoyed visiting the San Esteban del Rey Mission. A Catholic mission founded in 1629 that required 12 years to complete, the church is 150 feet long with vigas spanning the entire 40-foot width. The timber used for the vigas were harvested in the San Mateo Mountains 30 miles to the north and were transported by the Acoma people by foot. The adobe walls of the church are seven foot thick at the base on one side and five on the other. Adjacent to the church is their historic cemetery made of soil carried manually up steep steps carved out of the sandstone cliffs.

My takeaway

The Acoma people and their story represent a fine lesson for business and community leaders in adapting to radical changes beyond their control, despite extreme culture clashes and harsh environments. Lessons learned from the Acoma Pueblo can no doubt be applied to many around the world (see UNM business case summary).

Among the most important responsibilities each of us face during our brief life is taking charge of our own learning. Only then can we begin to make decisions as independent thinkers free from indoctrination, conflicting interests or agendas of others, which is prerequisite to becoming mature adults and valuable citizens prepared to contribute, particularly in a democracy in the vital role of informed citizens and consumers. This responsibility to others and ourselves never ends in our conscious lives, so we should grasp opportunities to learn and grow at every reasonable opportunity.

Leaders have a greater responsibility to practice continuous learning in order to maintain a high state of awareness in relevant matters; particularly in the type of highly complex, tumultuous and hypercompetitive environments we face today. Those few I consider great leaders then apply wisdom gained from experiential learning to rise above short-termism to contribute more to our world than they extract.

Although much easier to claim sustainability than to achieve, important lessons on stewardship can be learned from other cultures and eras. Our Founding Fathers of the United States for example studied many cultures and governance models before collectively deciding on a specific type of democracy in our constitutional republic.

Visiting the Acoma Pueblo

The old Acoma Pueblo is located about 60 miles west of Albuquerque a few miles south of I-40 on a good paved road. We spent the night at one of several motels in Grants, NM on our visit, which is a pleasant 40-minute drive by car. Visitors must park at the Sky City Cultural Center located at the base of the rock tower, which houses the Haak’u museum, Y’aak’a Café, gift shop and conference rooms, providing an experience similar to a national park. Walking tours are regularly scheduled with a short mini bus ride from the cultural center up to the village, which consists of over 250 family-owned dwellings still without water or electricity, some portion of which are still full-time residents with the remainder used by families during cultural and religious ceremonies.

About the author:

Mark Montgomery is the founder and CEO of Kyield, which has been a pioneer at the confluence of human and machine intelligence for two decades.

[i] Though quite similar to ‘Old’ Acoma Pueblo, it is not a replica. Betsy has a unique style of mortar sculpture over wood with different thicknesses for depth perception and shapes, natural woods, and oil paint.

Priority Considerations When Investing in Artificial Intelligence

After several decades of severe volatility in climatology across the fields involved with artificial intelligence (AI), we’ve finally breached the tipping point towards sustainability, which may also represent the true beginnings for a sustainable planet and humanity.

Recent investment in AI is primarily due to the formation of viable components in applied R&D that came together through a combination of purposeful engineering and serendipity, resulting in a wide variety of revolutionary functionality.  However, since investment spikes also typically reflect reactionary herding, asset allocation mandates, monetary policy, and opaque strategic interests among other factors, caution is warranted.

The following considerations are offered as observations from my perch as an architect and founder who has been dealing with many dozens of management teams over the last few years.  The order of priority will not be the same for each organization, though in practice are usually similar within industries.

Risk Management and Crisis Prevention

The nature of AI when combined with computer networking and interconnected emerging technology such as cryptography, 3D printing, biotech and nanotech represents perhaps the most significant risk and opportunity in history.

While the global warnings on AI are premature, often inaccurate, and appear to be a battle for control, catastrophic risk for individual companies is considerable.  For most organizations the risk should be manageable, though not with traditional strategies and tactics.  That is to say that AI within the overall environment requires aggressive behavioral change outside comfort zones.

Recent examples of multi-billion dollar investments in AI include Google, IBM, and Toyota, though multi-million USD investments now number in the thousands if we include internal investments and venturing.  To be sure much of this investment is reactionary and wasteful, but the nature of the technology only requires a small fraction of the functionality to prove successful, which can be decisive in some markets.

For appreciation of the sea change, common functions employed today were deemed futuristic and decades in the future just three or four years ago.  So it’s not surprising that a majority of senior management teams we’ve engaged in the last two years confirm that AI is among their highest priorities, though I must say some are still moving too slow. We’ve observed a wide range of actions from window dressing for Wall Street to confusing to brilliant.

The highest return on investment possible is prevention of catastrophic events, whether an industrial accident, lone wolf bad actors, systemic fraud, or disruption leading to displacement or irrelevance.  Preventable losses in the tens of billions in single organizations have become common.  Smaller events that require a similar core design to prevent or mitigate are the norm rather than the exception, but are often nonetheless career ending in hindsight, and can be fatal to all but the most capitalized companies.  We’ve experienced several multi-billion dollar events in former management teams that likely could have been prevented if they had moved more quickly, including unfortunately loss of lives, which is what gets me up at 3am.

Talent War

An exponential surge in training is underway in machine learning (ML) along with substantial funding in tools, so we can expect the cost of more common technical skills will begin to subside, while other challenges will escalate.

“In their struggle against the powers of the world around them their ﬁrst weapon was magic, the earliest fore-runner of the technology of to-day.  Their reliance on magic was, as we suppose, derived from their overvaluation of their own intellectual operations, from their belief in the ‘omnipotence of thoughts’, which, incidentally, we come upon again in our obsessional neurotic patients.’’ — Sigmund Freud, 1932.

The challenge is that the magic of the previous century has evolved and matured by necessity from the efforts of many well meaning scientists, but some of the magicians on stage still suffer from neurosis.  Technology is evolving much faster than humans or organizations.

Examples of talent issues commonly found in our communications:

  • Due to long AI winters followed by the recent tipping point in viability, the number of individuals with extensive experience is very small, and most are at a few tech companies attempting to displace other industries.

  • Industry-specific expertise beyond search and robotics is rare and very specialized with little understanding of enterprise-wide potential.
    An exceptional level of caution is warranted on conflicts in AI counsel due to competency and pre-existing alliances.

  • Despite efforts to exploit emerging opportunity, ability to think strategically in AI systems appears to be almost non-existent.

  • CTOs may win some key battles in tactical applications, but CEOs must win the wars with organizational AI systems.

The talent war for the top tier in AI is so severe with such serious implications that hundreds of millions USD have been invested for key individuals.  Of course very few organizations can compete in talent auctions, which is one reason why the Kyield OS is so important.  We automate many AI functions that will be common in organizations and their networks for the foreseeable future while also making deep dive custom algorithmics simpler and more relevant.

Historic Opportunity

Not only is AI a classic case of ‘offense is the best defense’, when designed and executed well to enhance knowledge workers and customers, the embedded intelligence with prescriptive analytics can accelerate discovery, uncover previously unknown opportunities, providing historically rare potential for new businesses, spin outs, joint ventures and other types of partnering.  Managed well, this is precisely what many companies and national economies need.

Architectural Design

Impacting every part of distributed organizations, the importance of architecture cannot be overstated as it will influence and in many instances determine outcomes in the distributed network environment.  AI is a continuous process, not a one-off project, so it requires pivotal thinking from two decades of fast fail lean innovation that our lab helped pioneer.  Key considerations in architecture we incorporated in the Kyield OS include but are not limited to the following:

  • Optimizing the Internet of Entities

  • Governance, compliance, and data quality

  • Accelerated discovery and innovation

  • Continuous improvement

  • Real-time adaptability

  • Interoperability

  • Business modeling

  • Relationship management

  • Smart contracts

  • Security and privacy

  • Transactions

  • Digital currency

  • Ownership and control of data

  • Audits and reporting

  • Productivity Improvement

A priority outcome for most organizations in competitive environments, productivity improvement is increasingly derived from optimizing embedded intelligence, which is also desperately needed to improve the macro global economic situation.  A large gap remains in most AI strategies with respect to enterprise-wide productivity, which represents the foundation of recurring value to organizations and society, regardless of the specific task of each knowledge worker and organization.

While cultural challenges and defensive efforts are common obstacles to any productivity improvement, strong leadership has proven the ability to triumph.  Internal and external consultants and advisors can help, particularly given the steep learning curve in AI;  just be cautious on unhealthy relationships that may have interests directly opposed to the client organization, as conflicts are pervasive and tactics are sophisticated.

Just when we thought trust couldn’t become more important, it seems to dominate life on earth.  We’ve come across quite a few trust related issues in our AI voyage. A few examples that come to mind:

Intellectual property:  Trust is a two-way street, particularly when it comes to intellectual assets, so upfront mutual protection is a necessary evil and serves as the first formal step in establishing a trustworthy relationship, without which the other party must presume the worst of intentions.  Once the Kyield OS is installed with partners this problem is effectively eliminated with smart contracts and digital currency based on internal dynamics and verified intelligence (aka evidence).

Fear of displacement:  Since AI is new for most, suffice to say that fear is omnipresent and must be dealt with in a transparent and intelligent manner. At the knowledge worker level we overcome the problem with transparency, which makes it obvious that the Kyield OS is likely their strongest ally.

Modeling:  While motivation to change is often needed from external sources such as regulatory or competition, it’s probably not a good idea to trust a company that has the capability, desire, culture and incentive to displace customers.  Another problem to avoid at the confluence of networked computing and AI is lock-in from technology or talent, including service models.  Beware the overfunded offering that attempts to buy adoption and/or over-reliance on marketing hype.

Authenticity:  Apart from the serious structural economic problems caused by copying or theft of intellectual work, consider the trustworthiness of those who would do so and how much know-how is withheld because of this problem.  Authenticity is especially important in this field due to the length of time required to understand the breadth and depth of implications across the organization and network economy.

Given the strategic implications to organizations, AI should be a top priority led by senior management.  However, since supply chains face similar challenges with AI, traditional methods and channels to technology adoption may not necessarily serve organizations well, and in some cases may be high risk.  Whether for strategic intent, financial return, operational necessity or any combination thereof, investing well in AI is not a trivial undertaking. Integrity, experience, knowledge and freedom from conflicts are therefore critical in choosing partners and investments.

About the author

Mark Montgomery is the founder and CEO of Kyield, which is based on two decades of self-funded R&D.  The Kyield OS is designed around his patented AI system, which tailors data to each entity in the digital network environment.

We must empower a more diversified economy in 2016

Austin Christmas Hat 1

Those of us growing up in the 1960s and 1970s experienced tumultuous times that had some similarities to the last decade. Among many other contributions from our generation—which include both positive and negative influences—were some great artists, one of whom Bob Dylan is featured in a massive IBM ad campaign. Dylan’s poetry is timeless and quite relevant today:

The post WW2 era we grew up in provided the best economic conditions the world has ever known. The baby boom population explosion, of which I am at the tail end of, combined with vast sequential gains in productivity to create the ‘miracles’ of economies in the U.S., Japan, Germany, and China among others, or so it seemed.

Although a few credible experts have warned all along that the world’s trajectory wasn’t sustainable, and perhaps most of us intuitively realized same, the financial crisis contained a potential silver lining in revealing the stark naked truth: much of that ‘success’ in the post war era came at the direct expense of the future, and the bills are coming due.

Although woefully deficient in ethics with poor visibility of systemic risk—even in cases where desire for prevention existed, master politicians and financial engineers in both the public and private sector have masked structural problems in the economy for decades—from the public and each other, by employing ever-more complex short-term remedies in a misguided game of musical chairs.

Unfortunately, the resolution of the financial crisis has consisted primarily of the very same type of financial engineering—it’s the only hammers central banks have in their toolbox. While central bankers are justified in pointing fingers at political and fiscal malfeasance, it’s up to humble citizens like me to hold up a mirror and suggest that they take a look to see that such malfeasance would not be possible if not empowered by monetary policy.

One certainty is that the super majority of consolidated malfeasance in much of the world has been transferred to the balance sheets of central banks and national debt at direct cost to billions of people, many of whom followed the rules, not least those who saved all their lives just as their public institutions recommended.  Those savings have been taxed for nearly a decade now by monetary policy rather than a democratic process; by devaluation of currency, record low (or negative) interest rates, inflation from asset bubbles such as commodities and housing, and the need for hundreds of millions to tap their principal for survival. Also certain is that regardless of whether or which stimulus measures were necessary, one outcome has been a dangerous expansion of the wealth gap now at record level in the modern era.

It’s very important to better understand that the previous wealth gap peak in the 1920s was partially causal to the Great Depression and WW2, among other earlier great revolutions and loss of life. Today’s billionaires seem to understand the moral hazard and potential for backlash, which is presumably one of the reasons for the philanthropic pledges. A nice gesture that will hopefully do much good, philanthropy is not an alternative for economic diversification, though can help if targeted for that purpose.

The financial crisis represents precisely how corrosive moral hazard is realized at dangerous levels that can reach critical mass, which could be triggered by unforeseen events.  Moral hazard is a psychological phenomenon, which occurs from regulatory, governance and policy failures that then combine with the ensuing economic weakness to cause the next crisis.  In this case the trigger was regulatory failure followed by heavy-handed resolution that caused massive collateral damage, further harming innocent citizens worldwide. In such cases where the non-virtuous (aka vicious) cycle is not interrupted by a moral realignment, typically through accountability by the justice system, strong credible governance, and adoption of new systems that punishes crimes and rewards beneficial behavior, then civilizations can and do rapidly decline.

In hindsight from a high level view, from a hopefully wiser former business consultant who has studied related phenomenon for decades now, it appears that we enjoyed a long period of one-off exploitations of planet and people combined with ever-increasing public debt and corruption supporting promises by politicians and institutions that were far beyond their means to deliver.

The bad news is that the combination of public debt and future liabilities tragically promised by politicians—and now expected—some portion of which is necessary to survive in the high cost modern economy caused by these policies, can’t possibly be paid by the current economy.

The good news is that not all of that massive spend on R&D over decades has gone to waste, and we now have much more accountable systems that can indeed prevent the super majority of future crises, if only we can muster the courage to adopt them. We are also seeing dramatic improvements in systems that have the capacity for exponential productivity growth over time, which is the only method in our current economic system to cover national debt, unfunded liabilities, and the needs of a quickly aging global population, given the immense future needs in healthcare, environment and economics.

So my plan for 2016 is to tap the exponentially decreased cost and performance improvement in computing hardware and algorithmics to extend our networked artificial intelligence system to the mid-market, NGOs, and governments to provide them with a world class system unavailable to anyone at any cost until very recently. My hope is that our Kyield OS will help even the playing field and lead to a more dynamic and robust economy of the type that is only possible with healthy balance of diversification. Soon thereafter we plan to do the same directly for small business and individuals.

“If your time to you is worth savin’
you better start swimmin’, or you’ll sink like a stone
For the times they are a-changin’”
– Bob Dylan

Why go to the Moon when what your company really needs is in the Rockies? (AI, Watson, Kyield)

Mark Betsy Austin on summit

Mark, Betsy & Austin on top of NM – 10-2015

This post is in response to an excellent article Tom Davenport wrote for the WSJ (now on LinkedIn) ‘Lessons from the Cognitive Front Lines: Early Adopters of IBM’s Watson’.

Tom is a long-term advocate for increasing jobs related to analytics, particularly in the service sector, and is an advisor to Deloitte, which is a strong alliance partner with IBM, and Deloitte is a sponsor of WSJ CIO. Like most in our industry, we are in constant discussions, but as of now Kyield has no formal alliances or conflicts with any of the people or organizations mentioned in this article.

I too am an advocate for jobs, though not necessarily for IT incumbents, but rather for customers and the broader economy. Smaller companies create most jobs and most job losses come from incumbent consolidation, which is a credible place from which to start this discussion. I think Tom’s article and most of the related strategy is about protecting a few very specific jobs at Armonk, NY, and perhaps at a few alliance partners—not creating them for customers or the broader economy. Modern job creation is no mystery; it’s very well documented.

This article triggered a great many thoughts so I felt compelled to blog about it very early in the morning from my perch in Santa Fe, NM. You see I am the founder of a company called Kyield with an authentic invention based on a theory I developed in our small lab 20 years ago (yield management of knowledge), which looks and sounds increasingly like what Watson has been attempting to become over the last few years. Our company is self-funded almost entirely by me and my wife (well into 7 figures), and frankly I’m feeling just a bit over-exploited at the moment, so hang in there as I poke some fun at the expense of our esteemed colleagues on the east coast and hopefully share something valuable in the process.

Several very important clues and quotes were revealed in this article. I highly recommend reading it carefully as Tom is one of the most experienced and knowledgeable observers in related overlapping domains. First, let’s dissect the lessons the article shares with us including that only one of the organizations interviewed in the article was a customer of Watson, which was University of Texas MD Anderson Cancer Center (MDACC), three were a “partner/co-developer” or “Watson ecosystem partners”, and the undisclosed health insurance company’s relationship type was also not disclosed. Those of us enlightened on the complex relationships in enterprise IT will of course immediately wonder what the terms of these relationships are, who is paying for what, and most importantly why.

Some things we can confirm. IBM has disclosed a billion dollar investment in Watson, often claims to be betting the farm on Watson and/or the cloud, and is obviously spending enormous sums on marketing, partnerships and sales. I too have a lot riding on my company Kyield so IBM’s CEO Ginni and I share that in common—our jobs and future wealth are riding on our respective systems. IBM is constantly reminding us that Watson and healthcare in particular are “moon shots” for IBM, but I’m seriously beginning to wonder if this moon shot is a prudent business decision for IBM and its customers, or a science project that needs another two decades of R&D like we performed with Kyield before attempting to unleash it on customers—particularly business customers (more on basic vs. applied research in a minute).

In order to get our arms around this topic we need to understand a few of the business and technical issues, which for me dates back to the early 1980s to include discussions with IBM and most other industry leaders off and on the entire time. As you may be aware, IBM has been substantially dependent upon the high-end service model since the previous major transformation led by Lou Gerstner in the early 1990s.

What is less known is that IBM grew to over 400,000 employees in that model with more in India than in the U.S. While a brilliant turn-around model in Lou’s time that probably saved the company, 20+ years later the service model has in my view grown far beyond the means to pay for it, and become a big part of the problem in IT for customers and the macro economy. I think IBM understands this well, but it’s a slow and difficult transformation. Ginni herself often states in interviews the challenge is whether IBM “can make the transformation in time”. I suspect with some private confirmation that time may be growing short.

IBM is not alone. All system integrators and many IT consultants share this misalignment of interest challenge often discussed today regarding both internal and external IT investments. The IT services sector represents something like a third of the now almost $4 trillion global IT industry, but drives spending in the majority, which is one reason why the enterprise cloud market is exploding. We then need to understand that IBM’s quarterly revenue has been falling like a rock for several years and so too has the company’s value, during which time competitors like AWS are experiencing record rapid growth, which places a great deal of pressure on the company, partners and loyal customers, not to mention investors and employees. While I am empathetic with IBM’s challenge and especially employees, rest assured that whatever pressure IBM is under it cannot compare to a self-funded entrepreneur.

We have our challenges as well to include the fallout from IBM’s problem in the marketplace, not least of which is a massive ad spend and sales force, with a combined millions of individuals in shareholders, employees and partners all over the world clicking on articles about Watson, which just incentivizes publishers to write more articles with the keyword Watson. Unfortunately, all that attention and spending isn’t necessarily good for customers, the economy, or even IBM—in this regard I may have as much or more relevant experience in my background as our friends at IBM as the challenge to overcome such an advantage in small companies is substantially greater than defense in an incumbent.

The namesake Watson by the way was not a scientist, but a famous salesman who built the early IBM by going door to door selling machines—trust me I respect that, as well as IBM, and many I know and have known at the company. This may provide a clue however regarding the dual branding definition in the name Watson. Prior to becoming CEO of IBM, Ginni was SVP Sales, Marketing, and Strategy at IBM (I too am guilty as I was a CSO of smaller turn-around companies long before changing paths before Lou’s time).

Let’s talk technology

With business strategy, misalignment of interests, and potential business model conflicts out of the way, let’s now take a brief look at the science and technology involved with Watson, which like my company Kyield and our OS is based on AI—in fact my core patent was labeled an AI system by the USPTO. Ginni is stepping back from using the term AI now (“a small part of it”) presumably due to the fear of job displacement out there and other nonsense perpetuated by famous brands with all manner of agendas, which is certainly understandable. I’ve contributed to that learning curve myself over at Wired, but make no mistake Watson is AI even if most of the revenue may come from some other stream like system integration, solutions, and consulting.

While defining AI is not a perfect science, the consensus among scientists is that AI can be divided into two forms, which is extremely important to understand and directly relevant to almost everything discussed here and elsewhere on AI:

  1. General AI (AGI), which is also referred to by some leading AI scientists and authors who cover the field as ‘super intelligence’, or strong AI.
  2. Narrow AI, which is also called weak, narrow or applied AI.

Augmentation or enhancement is by extension applied AI as it is very narrow and highly specific, particularly in our case for each individual entity down to the molecular level when necessary (as in personalized healthcare). Kyield is without question one of the world’s competency leaders at the confluence of human and artificial intelligence, if not the leader.

Now let’s delve into the carefully structured quotes in Tom’s article to glean some additional intelligence.

“It’s an apprenticeship form of training that takes years—there are lots of subtleties that Watson has to learn,” said Dr. Kris at MSKCC.

This is inherent with any deep learning (DL) application including source code shared by researchers with the public and those in our system, but the challenge frankly has always been with system design, algorithmics, and hardware, not marketing. DL is now widely available for anyone who has the talent, providing a long-term benefit across all sectors, and certainly not dependent on Watson, Kyield or any other system. Rather it’s a function within the system. The difference with Kyield is that while DL is tapped for continuous learning over time, other critically important functionality in the basic core provides immediate value to customers, like increased productivity and crisis prevention.

It was not a trivial undertaking to design the Kyield OS in a simple to use fashion. I doubt that it would have been possible if funded by a conflicted organization of any kind, including the super majority of corporations, foundations or government R&D programs. We sacrificed to remain independent throughout the long voyage across the valley of death in large part to avoid such conflicts and be free to focus only on the needs of customers and the specific tasks at hand, not least of which is to prevent crises sourced within large organizations.

“But the problem comes when the needed knowledge isn’t in the corpus. Dr. Kris at MSKCC comments: We had three drugs approved in lung cancer this year. None of them are in the literature yet. And definitions of cancer and its variations are being redefined all the time as we understand the biological characteristics of each one. The science is changing more rapidly than the published literature.”

This is a good example of many specific types of intellectual obstacles we were forced to overcome early in our R&D, and the solution is frankly partially represented in our patented design. The complete solution also includes tradecraft and secrets to include expected future patents, and like IBM we are dependent on intellectual property for survival, so I can’t disclose further except to say that it was a very difficult and expensive problem to overcome; one deemed necessary prior to offering to customers.

“MDACC (UT MD Anderson Cancer Center) actually referred to its project as a moon shot.”….. “An application like OEA cannot deliver on its intended impact of improving patient outcomes worldwide without addressing the necessary network infrastructure, security and regulatory controls, data sharing/access/use contracts, and reimbursement, not to mention the culture of medicine and clinical adoption. Only through addressing these non-technical challenges, we will be able to translate a piece of technology, like OEA, into impact. That is what separates an innovation from a transformation…that is what makes it a moon shot.” — Dr. Lynda Chin, who led the Watson-based project at MDACC.

I see this as the most mission oriented statement in Tom’s article, coming from the only customer disclosed. MDACC has a clear mission in scientific research to eventually eliminate cancer so related ‘moon shots’ fall well within the organization’s responsibility. Most organizations to include most businesses do not share a similar mission as MDACC, which is why we took our R&D much further in applied form and removed as much risk as possible for customers prior to offering, even if admittedly lacking billions USD in development, marketing or sales.

Definition of Moonshot:

If you concluded from reading this article that Kyield doesn’t claim to be a moonshot, that would be correct. Kyield does not provide artificial general intelligence, but rather offers a highly evolved system with as much complexity driven out of it as possible, so it is very much an applied system with a laser focus. While Kyield was a moon shot in the mid 1990s when developing the theorem in our lab, it is now a viable product and system at a very attractive price with a reasonably good probability of achieving an outstanding ROI.

Bringing discussion back to earth

Back down here on earth at the southern tip of the Rocky Mountains in the Land of Enchantment is a City Different called Santa Fe, which is over 400 years old. This area is known for history, art, culture, climate and science, the combination of which is why we brought Kyield here from the Bay area seven years ago to mature our R&D. While NM has vast open spaces made famous by Georgia O’Keeffe among others, we also have one of the highest concentrations of intellectual capital in the known universe, including of course the Moon!

I have a suggestion that is entirely compatible with moon shots of the Watson kind, which local theorists understand better than most, and that is to adopt a very pragmatic AI system that follows the rules of laws, physics and economics. We engaged in this process by the book, took massive risk, played strictly by the rules of engagement, invented an authentic system from scratch, and are now offering the world’s most advanced system at the confluence of human and artificial intelligence, which can be adopted at a tiny fraction of the cost as those described in Tom’s article.

In addition, while almost every single one of the Fortune 100 has benefited greatly from the science here in NM, most of which was produced with taxpayer’s money (Kyield is a rare exception in that regard), that value is almost always exported in the form of spinouts, flips and M&A, usually to the coasts and occasionally off-shore. This commercialization (aka tech transfer) model that generates considerable wealth for a very few has not manifested into benefitting NM from the beneficiaries of the R&D in the private sector, otherwise the numbers would be very different.

Seven decades after the Manhattan Project and hundreds of billions of dollars later, NM has yet to experience a significant business success, will soon surpass WV to rank dead last in unemployment, and has among the highest rates of poverty and crime in the U.S. And it isn’t just about education as many with advanced degrees are unemployed or underemployed here. Part-time wait staff at local hospitality establishments or gift shops holding doctorates is not uncommon.

So my suggestion is to come on out and visit Santa Fe just as hundreds of the leading minds in the world do each year, and we can then discuss in greater detail how our applied science in the form of the Kyield OS can help your organization ascend to a higher level of performance, and do the right thing for your career, organization and the economy in the process. In so doing you will empower us to empower NM and perhaps the rest of the global economy to ascend to the next level, which would be a good thing for everyone.

Oh, about that Watson we keep reading about? No worries, it’s likely compatible with the Kyield OS—that’s what all those APIs are for. And who knows, one of these days that moon shot may just pay off. In the interim we can help your organization ascend almost immediately following adoption of the Kyield OS!

Mark Montgomery

New E-Book: Ascension to a Higher Level of Performance

Power of Transdisciplinary Convergence (Copyright 2015 Kyield All RIghts Reserved)

Power of Transdisciplinary Convergence

Ascension to a Higher Level of Performance

The Kyield OS: A Unified AI System

By Mark Montgomery
Founder & CEO

I just completed an extensive e-book for customers and prospective customers, which should be of interest to all senior management teams in all sectors as the content impacts every aspect of individual and corporate performance.

Our goals in this e-book are fivefold:

  1. Provide a condensed story on Kyield and the voyage required to reach this stage.
  2. Demonstrate how the Kyield OS assimilates disparate disciplines in a unified manner to rapidly improve organizations and then achieve continuous improvement.
  3. Discuss how advances in software, hardware and algorithmics are incorporated in our patented AI system design to accelerate strategic performance and remain competitive.
  4. Detail how a carefully choreographed multi-phase pilot of the Kyield OS can provide the opportunity for an enduring competitive advantage by establishing a continuously adaptive learning organization (CALO).
  5. Educate existing and prospective customers on the Kyield OS as much as possible without disclosing unrecoverable intellectual capital, future patents and trade secrets.
PHASE 2 18
PHASE 3 18
PHASE 4 18

To request a copy of this e-book please email me at markm@kyield.com from your corporate email account with job title and affiliation.

Revolution in IT-Enabled Competitiveness

Four Stages of Enterprise Network Competence

Most current industry leaders owe their existence beyond basic competencies and resources to a strong competitive advantage from early adoption of systems engineering and statistical methods for industrial production that powered much of the post WW2 economy. These manual systems and methods accelerated global trade, extraction, logistics, manufacturing and scaling efficiencies, becoming computerized over the last half-century.

The computer systems were initially highly complex and very expensive, though resulted in historic business success such as American Airlines’ SABRE in 1959 [1] and Walmart’s logistics system staring in 1975 [2], which helped Walmart reach a billion USD in sales in a shorter period than any other company in 1980.

As those functions previously available to only a few became productized and widely adopted globally, the competitive advantage began to decline. The adoption argument then changed from a competitive advantage to an essential high cost of entry.[3]   When functionality in databases, logistics and desktops became ubiquitous globally the competitive advantage was substantially lost, yet costs continued to rise in software while falling dramatically in hardware, causing problems for customers as well as national and macro global economics. In order to achieve a competitive advantage in IT, it became necessary for companies to invest heavily in commoditized computing as a high cost of initial entry, and then invest significantly more in customization on top of the digital replicas most competitors enjoyed.

The network era began in the 1990s with the commercialization of the Internet and Web, which are based on universal standards, introduced a very different dynamic to the IT industry that has now impacted most sectors and the global economy. Initially under-engineered and overhyped for short-term gains during the inflation of the dotcom bubble, long-term impacts were underestimated as evidenced by ongoing disruption today causing displacement in many industries. We are now entering a new phase Michael Porter refers to as ‘the third wave of IT-driven competition’, which he claims “has the potential to be the biggest yet, triggering even more innovation, productivity gains, and economic growth than the previous two.” [4]

While I see the potential of smart devices similar to Porter, the potential for AI-enhanced human work for increased productivity, accelerated discovery, automation, prevention and economic growth is enormous and, similar to the 1990s, while machine intelligence is overhyped in the short-term, the longer term impact could indeed be “the biggest yet” of the three waves. This phase of IT-enabled competitiveness is the logical extension of the network economy benefiting from thousands of interoperable components long under development from vast numbers of sources to execute the ‘plug and play’ architecture many of us envisioned in the 1990s. This still emerging Internet of Entities when combined with advanced algorithmics brings massive opportunity and risk for all organizations in all sectors, requiring operational systems and governance specifically designed for this rapidly changing environment.

This is a clip from an E-book nearing completion titled: The Kyield OS: A Unified AI System; Rapid Ascension to a Higher Level of Performance. Existing or prospective customers are invited to send me an email for a copy upon completion within the next month – markm at kyield dot com.

[1] https://www.aa.com/i18n/amrcorp/corporateInformation/facts/history.jsp

[2] http://www.scdigest.com/ASSETS/FIRSTTHOUGHTS/12-07-26.php?cid=6047

[3] Lunch discussion on topic with Les Vadasz in 2009 in Silicon Valley.

[4] https://hbr.org/2014/11/how-smart-connected-products-are-transforming-competition

A reminder on the benefits of volunteering

Part of something much bigger

Takeaway benefits

Concluding thoughts

How small states like New Mexico can compete in business

Mark on Wheeler summit - Oct 1993

Betsy-Wheeler Summit-Oct 1993

Mark and Betsy Montgomery on top of NM – October of 1993

I first studied the New Mexico (NM) economy about twenty-two years ago as an independent consultant through formal business and market audits, which was followed by covering the region in our incubator and venture capital firm a decade later. Six years ago my wife and I chose to move to NM from the Bay area, bringing Kyield with us.

So I thought it might be useful to contribute my perspective to the recent efforts to transform the NM economy into a more dynamic entrepreneurial economy. Hopefully this format is an appropriate method, offered in good faith with no conflict or investment other than as a local entrepreneur and citizen shared in much the same way I would have presented to a client in a verbal counseling session following a formal process, though hopefully also reflective of a great deal of expensive lessons since.

One commonality found in many flyover states and countries is a culture suffering from low self-esteem, which is often well earned by toxic macro economic policies or other factors. My sense of this since living in NM is that victimization is deeply rooted, and was quite strong during and after the peak of the global financial crisis. In a state that has never experienced a significant business success, especially in an era of historic financial consolidation, it’s understandable that NM would be a bit cynical.

However, although NM’s history is peppered over the centuries with strategic blunders in far-off capitols, it’s important to avoid allowing moral hazard to further harm NM in the future, as the state needs to reduce dependencies and create an economically diverse economy. Private sector growth and diversification are particularly important at this point in NM’s history given the fiscal projections of the federal government, which could threaten a significant portion of the NM economy in the near future. In addition, disruptive technical threats to oil and gas are maturing rapidly.

It is therefore not only important for NM to understand that it has the capacity to compete with anyone, but it may be imperative to do so, which should translate to a very high priority for accelerating private sector diversification.

During my earlier years assisting other entrepreneurs and communities we developed a comprehensive list of fourteen ingredients regional economies needed to be successful, eight of which we considered essential, though weak areas can be shored up in a variety of ways to meet minimal viability—short of luck of course.

The most important lesson every state can learn is that each has more than sufficient capacity to achieve a robust economy, provided the community is willing to do just a few things well. The following are a few essentials from that list that clearly need work in NM.

  1. Work as a team.

As difficult as it may seem in our polarized society, ideological and partisan disagreements must be substantially removed from the process of competing in business. A personal case for me was as a young entrepreneur and member of ‘Team Washington’ in the 1980s, which produced an environment where several global business leaders emerged as well as many smaller companies. Of course Washington is only one of dozens globally that should be considered, and every region should perform their own tailored SWOT analysis to guide adaptive action plans, but a few similarities exist that NM and other regions should consider.

The Puget Sound economy had become far too dependent upon the federal government and the Boeing company in the post WW2 era, both of which experienced devastating cut backs in the 1960s and early 1970s reflected by the famous billboard in 1971 sponsored by local real estate brokers: “”Will the last person leaving SEATTLE — Turn out the lights”.

A decade later the informal team effort I played a small role in included members from all sectors of the regional economy led by a few of the more experienced in business ranging from the largest to the smallest in close collaboration with local and state governments, universities, and non-profits. Although the Puget Sound economy enjoyed considerably more strength than NM, it was a small community compared to leading capital centers with a relatively small group of dedicated leaders providing much of the heavy lifting.

While Seattle and the U.S. have changed greatly since the 1980s, we didn’t discuss politics much in the civic minded business building endeavors. With few exceptions I wasn’t even aware of party affiliation of the other members I met. The focus was economy, business building, community building, winning, and having some fun along the way.

Among the most important takeaways from Washington and many other engagements since is that individual and team efforts may or may not be personally rewarded. While communities should work diligently to support those who support them, the nature of modern economic growth is like life itself—quite dynamic and not always just. The broad impacts from a few may not necessarily be appreciated.

  1. Keep it clean

Given the recent history of D.C., Wall St. and the famously incestual nature of Silicon Valley, this may be shocking or even unwelcome, but the governance breakdown in power centers is precisely why it’s so important for regional centers to rebuild on strong foundations. Trust and integrity are critical to entrepreneurial cultures. The corrosive cost of corruption is well understood by those who study global economics and markets.

In my first several meetings in NM with officials and professionals I was warned of this systemic unmentionable problem, some of which I had observed in earlier audits, but it was still shocking to see so many felony cases involving public entities in NM. Of course different types of corrupted systems and processes exist, not all of which are illegal—abuse in government contracting is a good example, but are still toxic to the type of entrepreneurs smaller markets need in order to become more dynamic and diversified.

States like NM that have a poor track record with investors need to make an especially robust effort in improving governance, transparency, and honest trade. While progress has been made in NM in recent years, it takes time and effort to improve reputations.

  1. Enhance strengths, mitigate weaknesses

If NM hasn’t performed a SWOT analysis led by a seasoned business consultant with relevant skills and knowledge it should do so, as should each state and local community that desires to improve competitive outcomes. The process itself has considerable value. Among the most important aspects of becoming a competitive business or regional economy is in raising the bar to the competitive level. While this includes continuous learning by and for business leaders and entrepreneurs, it’s just as important for local institutions, employees, and communities. Almost everyone in a community has numerous untapped opportunities to improve the regional economy.

A common misunderstanding today across the U.S. and EU—including NM, is that success is born only from direct strategic interests. In fact diversified economies require just the opposite. If the team effort is restricted even primarily to personal or institutional strategic interests, most competitions will be lost. For example, while benefiting a great deal from behind the scene support by many and direct efforts by a few, Microsoft, Costco, and Starbucks were not products of local institutions, though benefited from community support. The same is true for most successful businesses I’ve been close to in my career.

The critical part of modern economic success through business building is the ability to identify and match opportunities and talent with appropriate resources, which is a continual never-ending process in conjunction with the constantly changing economy. While every business has unique qualities, each has essential needs that simply must be met. NM is unusually challenged with lack of customers and corporate headquarters, which simply means significant focus must be placed on overcoming those weaknesses. It’s rather obvious, but if few local customers exist and many of those that do are government, a competitive private sector marketing effort becomes essential.

Although NM has strength in corporate relocation, tourism, film, art, and agriculture, which could no doubt be further leveraged across sectors, a certain degree of conflict exists between states and federal institutions, which is reflected in organizational and regulatory structures and extended to tech transfer and spin outs. While governance challenges, institutional conflicts, strategic venturing and dependency on fossil fuels and government are not unusual, the impacts in NM are more significant than most.

Though more critical in NM due to a few large institutions, competitive regional markets must learn how to play together well on the same team even if primarily extra curricular, civic minded and informal, though still high priority. Informal civic-minded team efforts should be supported by institutional sponsors with appropriate pressure applied if necessary, but should not be considered alternatives for highly sophisticated business intelligence methods found at any competitive organization today.

  1. Support local ventures

Economists have labeled this phenomenon ‘regional bias’. It became somewhat out of vogue in the U.S. during the rapid expansion of globalization in part apparently due to a combination of the growth needs of leading corporations and consolidated wealth in the hands of a few who had both financial and ideological interest in moving industry abroad. While global trade is mutually beneficial, scholars generally agree that the trend was overdone. Although we’ve experienced some recent improvement in regional efforts in the U.S., my personal experience suggests functionality has not returned to levels enjoyed during peak performance or to the degree found in other parts of the world, including Europe, Asia and in U.S. capital centers, which have very large, highly sophisticated strategic ecosystems.

The lack of sufficient capacity for proactive regional growth represents what I believe to be the single most important reason why NM has had little success. Smaller regional economies must become much more proactive and sophisticated in competing in the new normal that is the global economy, even if within a single company. This is particularly true with deep tech ventures that represent one of NM’s biggest strengths, which requires highest-level b2b marketing and sales sophistication, consultative sales and relationship management. While it’s true that young inexperienced entrepreneurs need boot camps, mentors and training, seasoned professionals of the type required for competitive businesses at growth stage need competent partners and strong allies.

Businesses across much of the U.S. have also experienced a significant spike in regulation and ‘NIMBY’ (Not In My Back Yard), the combination of which has resulted in a great many business ventures becoming economically infeasible, including in NM. In personal communications some people in NM seem more concerned with avoiding the impact of a Microsoft on the regional environment and quality of life—including a few who are charged with the responsibility of economic growth. Predictions early in the life of companies on future economic impact are rarely accurate, including those by Microsoft. Attempting to project such divinity in venturing by communities has proven unwise, though quite common in underperforming markets.

The best that can be done is to identify rare talent and ventures with significant potential and get behind them and then work very closely through every stage of planning to mitigate negative impact in an attempt to achieve a balance that can best serve the interests of citizens. A good example is Intel, which has a small headquarter footprint in CA with operations dispersed globally, including of course NM. Another example is Nestle in Switzerland, though a great many emerging small to mid-sized companies are distributed today. The talent, experience and wealth corporate headquarters bring to communities should not be underestimated, particularly for tax base, economic security and nonprofits of every type, including charities that struggle for funding in NM.

A widespread trend across the U.S. in recent years is to rally primarily around incubators. While community incubators and accelerators are wise for many, the quality of entrepreneurs and management teams combined with community functionality and the quality of their networks all contributes to success. My definition of a functional regional community is one that can identify and support in a relevant manner mutually beneficial entrepreneurs and ventures, regardless of whether spun out of an institutional lab, dorm room or garage. The priority should not be about proving the success of a public program or to expand institutions—which tends to consolidate power rather than diversify, but rather should only be focused on the actual needs of the business and their customers with the understanding that it is a dynamic process that can be nurtured, influenced and even guided at times, but not controlled. Early flames are easy to smother or blow away into the welcome arms of competitors with ample fuel.

Several people involved in the NM entrepreneurial economy have requested that I share actual cases to compare and learn from. The following cases represent failures I have experienced first-hand over the past six years. Names and affiliations have been withheld in an attempt to provide anonymity—the goal is to share and inform, not to blame or prosecute. In some cases it may have been just a bad day, though others were tested multiple times, representing a clear and consistent pattern.

  • Federal institutions that hide behind regulation and blame the community for their lack of ability to play a decisive role in growing regional business for the long-term. A common problem recently highlighted in D.C. by visiting Google engineers, using regulation as an excuse to fail has much greater impact in NM due to the lack of other powerful entities. To their credit, many individuals working for federal institutions go above and beyond in an attempt to assist, but obviously lack relevant tools or skills to do so—otherwise NM would have had a much more diverse economy long ago. It is a very frustrating situation for many. NM needs new and better models for deep tech manifesting into a few regional headquarters. At a macro level, U.S. R&D badly needs to be brought into this millennium through structural reforms, appropriate governance and modern systems.

  • Public employees at all levels charged with various elements of the economy who are either unqualified and/or lack the passion to achieve success. In one meeting I was given a clear message that economic success wasn’t welcome in NM unless it was in the form of government growth. In another the individuals didn’t seem to have any understanding that economic development isn’t a jobs program, but rather the outcome of growing successful businesses.

“If government didn’t fund it”, one key person said they had “no idea what to do”. Well, their roles were funded—that’s why their jobs exist! Most functional business development efforts are not just funded programs, but rather results of many actions taken by a community in deploying every type of resource they have for the benefit of their own community. Such a culture is found almost anywhere that has a thriving entrepreneurial economy. The most important role a community can provide for emerging companies is assistance in attracting customers at the critical early stages.

Public employees should be a catalyst to regional business success, not a barrier. Leaders should help communities understand that each and every effort may be leading to new customers, tax payers, future employers for their children or neighbors, or a future funder of much needed local services.

  • Senior managers in regionally headquartered organizations that demonstrate little to no interest in the success of others, even if to materially impact their own success. This shocked me more than any other type of negative experience.

1) CEO of a regional private company which has a mandate to engage with business as one of their primarily responsibilities. When I sent an invite to connect in a social network we belonged to, the individual responded ‘not interested’. The irony in this case is mutual invitations were sent and accepted by more than a dozen of their competitors in other states and countries, including companies 100x their size.

2) Senior management in a large business unit of a state funded entity with important synergies failed to respond to multiple attempts to connect in various ways while their peers and competitors not only accept, some assist and others have reached out to us in several states and countries.

3) Multiple non-profits with stated missions that include some element of community economic empowerment including in two cases specific missions to collaborate with private sector businesses, yet seem primarily engaged in fund raising, projecting personal ideology and sustaining their own lifestyles with other people’s money.

4) Almost every large organization in NM I’ve encountered including public, private and non-profit, most that would benefit directly and significantly from the success of my or a similar company here behave in a manner that serves primarily the interests of competitors to NM.

This list goes on, representing a systemic if fragmented problem in NM, which is a small economy that simply can’t afford not to have every leader and organization fully engaged at this point in history. These experiences clearly speak to the need for leadership training, education of board members and proactive peer pressure regarding personal and organizational responsibility for the economic health of their communities.

Of course we could have done a better job of working with NM, though NM entrepreneurs are so busy overcoming these kinds of regional obstacles in addition to what is an increasingly challenging task with no additional obstacles, so the administrative class needs to step up, roll up their sleeves, get to work and help win some battles. Bottom line is many entrepreneurs in NM have relocated with significant success while none in NM have achieved even a modest success by universally comparable standards. Of the few successes that exist, multiple have no customers in NM or have ever received the kind of growth support competitors enjoy in their regions.

Those who think they are too busy to engage in the extra curricular work required in building and sustaining healthy economies should try personally paying for the pleasure of being a soldier in the economic war on behalf of a community that doesn’t support them in a meaningful way. I’ve met quite a few such entrepreneurs in NM. Leadership priorities need to be recalculated to the new normal economy that will likely include far fewer subsidies and more performance based compensation. Get onboard.

  1. Become early adopters, disrupters and defenders

I never confirmed whether the story was true, but one of my first meetings in NM was with a nice couple in their home in downtown Santa Fe. Both were academics, one a native NM professor at a local university, the other a researcher in a different discipline. The professor told me that he once asked his university to acquire an innovative software system only to be told by his administration that state law required public entities to use a certain ubiquitous product we are all very familiar with.

Organizations are only as innovative as the systems employed allow them to be and ubiquitous systems provide no competitive advantage, but then that’s obvious right? I have confirmed that professional IT lobbyists for incumbents are located in tiny NM, which may be instructive on why the regional economy exports hundreds of millions of dollars annually for technology. While exceptions exist, most tech companies gain initial customers regionally and then expand globally, including those locations where NM sends its budgets. If members of the regional economy are not encouraged to support each other, as incumbents obviously intend—they are likely not to make the attempt.

In a perfect world companies in far off places that benefit from regional purchases would find more ways to reciprocate, but in practice mature companies are under severe pressure to improve quarterly profit growth. Entrepreneurs are often left little choice—if to succeed many are forced to take a disruptive path, which requires special talent, guidance and assistance.

While it may be difficult for NM institutions to think and act in a manner that may seemingly misalign with corporate relationships, we only need look at the results for guidance. NM and other flyover states need to learn the art and science of disruptive innovation, which also means exploring unobvious alliances with customers, other industries, and distributors—perhaps in other nations. The bar for deep tech is especially high as are the stakes for all concerned and should be treated accordingly.

  1. Allow experience to act as a guide

A common problem across the world in underperforming markets, which has increased in much of the U.S. and EU in recent years is also found in NM—allowing ideology, popularity and/or unhealthy business relationships trump experience in leading strategy and execution that impact business and economic competitiveness.

While most environments suffer from this problem to some degree and networks are very important, the reason why those networks exist is the relevant factor. A million followers in consumer social media can be of no value in b2b, while one trusted relationship can be invaluable. The core of functional global business is experiential knowledge that has been demonstrated over time in multiple environments. Those in government and academic cultures rarely understand that the entrepreneurial process is the most expensive education in the world, and top-tier performers are the most valuable. Regions that fail to understand this and listen to experience do so at their peril.

I will offer two recent cases of tragic failure in NM as examples of what to avoid.

1) During my first year living in NM I attended several local networking functions, primarily for social value and to explore methods to assist, including angels, innovation, associations, etc. During one such event I met a recently retired senior tech executive who shared multiple professional relationships in an industry that is very important to NM. As the event intended, our private discussion soon turned to NM, including our experiences, so after answering a few of his questions about my activities I listened to his.

In a very mature, respectful manner this still vigorous exec shared how he had intended to find a way to assist NM when retiring here, as his knowledge and network were still obviously strong and fresh, but after two years of frustrated efforts he gave up. I think he has since relocated out of state. He painted a picture of a culture that believed in a hypothetical economy rather than navigate successfully in the real-world economy and markets. He was visibly disappointed, representing one of few failures in his career. Over the next two years his experience would become my experience in an almost identical confirmation, so I retreated and focused primarily on my own company, which requires even more energy and sacrifice because of this situation.

2) A very successful retired entrepreneur and executive and I have long shared an interest and relationships in a NM non-profit. He and his wife retired in NM part-time due primarily to this commonality, and much like the case above he attempted to boost the entrepreneurial economy with expertise, investment capital and his extensive network. In fact he and his wife invested a significant amount of money, time and credibility in support of non-profits and venturing, but within a few years became frustrated by what he considered to be a failed effort. They sold their home and relocated out of state.

The tragedy these two experiences represent is that each is highly respected across large global networks, which no doubt gleaned similar stories. And both were from industries NM has long sought to grow with considerable investment and energy to attract the attention of precisely these same individuals and their networks. These were two of the most experienced tech execs I’ve met in NM, were badly needed in every sense I understand about the regional economy, but were chased away. As a business and economic consultant during my first visits to NM I would have diagnosed this behavior as self-destructive, requiring intervention by professional specialists and credible, trusted leaders.

Mark and Betsy Montgomery with Austin on top of NM - Oct 2014

Mark and Betsy Montgomery with Austin on top of NM – Oct 2014

Closing thoughts

In the many conversations with business leaders I’ve had over the course of the last 22 years about NM, it may be surprising for some to learn that in every case I recall we all wanted to see NM become more competitive, dynamic and diverse, and in so doing provide more opportunity and economic security for its citizens. Most share NM’s view on the environment, science, art and culture—indeed in many cases this brought them to NM.

However, none of us are magicians—we can only help those who are driven to help themselves and learn from their own mistakes as well as others. While failure is common in business building—even celebrated in pop culture today however inappropriately, repeated failure to act on lessons learned is rarely tolerated in business, whether by investors, lenders, partners, customers, or employees.

Speaking for myself as well as perhaps many of my fellow entrepreneurs, I sincerely hope NM grasps its future firmly in its hands and sculpts it into a more vibrant, diversified, dynamic and sustainable future.

Mark Montgomery is founder and CEO of http://www.kyield.com, which offers an advanced distributed operating system and related services based on his patented AI system.

Recent trends in artificial intelligence algorithms

Promise of spring reveals interesting hybrid variants

Those of us who have been through a few tech cycles have learned to be cautious, so for the second article in this series I thought it might be helpful to examine the state of AI algorithms to answer the question: what’s different this time?

I reached out to leading AI labs for their perspective, including Jürgen Schmidhuber at the Swiss AI Lab IDSIA. Jürgen’s former students include team members at Deep Mind who co-authored a paper recently published by Nature on deep reinforcement learning.

Our Recurrent Neural Networks (RNNs) have revolutionized speech recognition and many other fields, broke all kinds of benchmark records, and are now widely used in industry by Google (Sak et al.), Baidu (Hannun et al.), Microsoft (Fan et al.), IBM (Fernandez et al.), and many others. — Jürgen Schmidhuber

Jürgen recently published an overview on deep learning in neural networks with input from many others, including Yann Lecun, Director of AI Research at Facebook. Lee Gomes recently interviewed Lecun who provided one of the best definitions of applied AI I’ve seen:

It’s very much interplay between intuitive insights, theoretical modeling, practical implementations, empirical studies, and scientific analyses. The insight is creative thinking, the modeling is mathematics, the implementation is engineering and sheer hacking, the empirical study and the analysis are actual science. What I am most fond of are beautiful and simple theoretical ideas that can be translated into something that works. — Yann Lecun at IEEE Spectrum

Convolutional neural networks (CNNs)

Much of the recent advancement in AI has been due to convolutional neural networks, which can be trained to mimic partial functionality of the human visual cortex. The inability to accurately identify objects is a common problem, which slows productivity, increases risk, and causes accidents worldwide.

CNNs make use of local filtering with various max-pooling techniques and fewer parameters that make NNs easier to train than in a standard multilayer network. The invention and evolution of the nonlinear backpropagation (BP) algorithm through multi-layers, combined with other supervised learning methods, have enabled nascent artificial intelligence systems with the ability to continuously learn.

CNNs are valuable for a wide range of applications such as diagnostics in healthcare, agriculture, supply chain quality control and automated disaster prevention in all sectors. CNNs are also applied in high performance large-vocabulary continuous speech recognition (LVCSR).

Yoshua Bengio is Professor at Université de Montréal and head of the Machine Learning Laboratory (LISA). He is making good progress on a new deep learning book for MIT Press with co-authors Ian Goodfellow and Aaron Courville.

What’s different? – More compute power (the most important element) – More labeled data – Better algorithms for supervised learning (the algorithms of 20 years ago—as is don’t work that well, but a few small changes discovered in recent years make a huge difference) — Yoshua Bengio

Yoshua and several colleagues recently proposed a novel approach to train thin and deep networks, called FitNets, which introduces ‘hints’ with improved ability to generalize while significantly reducing the computational burden. In an email exchange, he shared insights on thin nets:

The thin deep net idea is a procedure for helping to train thinner and deeper networks. You can see deep nets as a rectangle: what we call depth corresponds to its height (number of layers) and what we called thickness (or its opposite, being thin) is the width of the rectangle (number of neurons per layer). Deeper networks are harder to train but can potentially generalize better, i.e., make better predictions on new examples. Thinner networks are even harder to train, but if you can train them they generalize even better (if not too thin!). — Yoshua Bengio

Long Short-Term Memory (LSTM)

Sepp Hochreiter is head of the Institute of Bioinformatics at the JKU of Linz (photo above), and was Schmidhuber’s first student in 1991. Schmidhuber credits Sepp’s work for “formally showing that deep neural networks are hard to train, because they suffer from the now famous problem of vanishing or exploding gradients”.

Exponentially decaying signals—or exploding out of bounds, was as scientists are fond of saying— a ‘non-trivial’ challenge, requiring a series of complex solutions to achieve recent progress.

The advent of Big Data together with advanced and parallel hardware architectures gave these old nets a boost such that they currently revolutionize speech and vision under the brand Deep Learning. In particular the “long short-term memory” (LSTM) network, developed by us 25 years ago, is now one of the most successful speech recognition and language generation methods. — Sepp Hochreiter

Expectations for the near future

We will go beyond mere pattern recognition towards the grand goal of AI, which is more or less: efficient reinforcement learning (RL) in complex, realistic, partially observable environments… I believe it will be possible to greatly scale up such approaches, and build RL robots that really deserve the name. — Jürgen Schmidhuber at INNS.

Unsupervised learning and reinforcement learning remain prizes in the future (and necessary for real progress towards AI, among other things), in spite of intense research activity and promising advances. — Yoshua Bengio via email.

Deep Learning techniques have the potential to advance unsupervised methods like biclustering to improve drug design or detect genetic relationships among population groups. Another trend will be algorithms that store the current context like a working memory. —Sepp Hochreiter via email.

My perspective

Pioneers in ML and AI deserve a great deal of credit, as do sponsors who funded R&D through long winters. One difference I see today versus previous cycles is that the components in network computing have now created a more sustainable environment for AI, with greater variety of profitable business models that are dependent upon improvement.

In addition, awareness is growing that learning algorithms are a continuous process that rapidly creates more value over time, so organizations have a strong economic incentive to commit resources early or risk disruption.

In the applied world we are faced with many challenges, including security, compliance, markets, talent, and customers. Fortunately, although creating new challenges, emerging AI provides the opportunity to overcome serious problems that cannot be solved otherwise.

Mark Montgomery is founder and CEO of http://www.kyield.com, which offers technology and services centered on Montgomery’s AI systems invention.

This article was originally published at Computerworld

Discover Kyield on the voyage to CALO (continuously adaptive learning organization)

tidal pool

A tidal pool ecosystem in Half-Moon Bay, CA.

For those involved with the art, science, and mechanics of organizational management, the 1990s was an exciting if humbling decade. The decade was ushered in with new thinking from Peter Senge in The Fifth Discipline, which introduced The Learning Organization to many. The concept sounded absolutely refreshing to those in the trenches—who could disagree with such logic?

I was deeply engaged at the time in a series of turn-arounds in mid-market companies. The particular business case offered for consideration was a union shop that was bankrupt from the day it opened nearly a decade earlier, and had never made a payment on many millions of dollars of debt.

The new owner had acquired the operating company out of bankruptcy with assumptions that were based on experiences that did not apply to the subject or market. Due to a low discounted acquisition value, the buyers had little to lose if the company continued to underperform, but a great deal to gain if the company could be brought up to a competitive market position.

Long-story short, it was a very challenging yearlong engagement during which time we surpassed everyone’s short-term expectations by a significant degree, including my own. Before I share what went wrong, let’s review a few things we did right:

  • The subject called for and we received an unusual level of authority from owners, which required exceptional levels of mutual trust, and a great deal of credibility.

  • We put together a strong team with a mix of experience relevant to the specific case. Each could recognize the opportunity, and even though under-resourced, we were able to create one of the industry’s top performances that year.

  • We were able to gain the trust and support of the union—which enjoyed a double-digit increase in membership, with most members experiencing significant increases in compensation.

  • Though never union members, senior management to include the owners had personal experience with labor, which was demonstrated alongside workers at critical times and helped gain their support (we walked the talk).

  • The few remaining core customers were so desperate for improved product and service that a modest upgrade and competency improved sales as well as the reputation, from which new and larger customers were gained.

  • The communities involved were relieved to see a well-managed company emerge from years of bankruptcy, churn of management, and under-investment, so we gained support of regional governments (important in this case), which also enjoyed increased tax receipts.

  • The pricing of products and services were well below market, so after modest investment with competent management, I was able to raise prices significantly while increasing sales volume, resulting in a substantial, growing profit.

  • We were able to double the value of the company in one year based on cash flow and future orders, which dramatically improved the position of the parent company, allowing refinancing at more attractive rates.

Now allow me to share why I consider this engagement (with others in this era) to be among my greatest mistakes.

Failure to learn, adapt, and seize the more important opportunity

Many of us wrongly assumed that the parent company would learn from the experience and use the success as a platform to seize other opportunities, which would have required a change in the structure, type, and talent of the company.

Despite considerable coaching combined with all that accompanies short-term financial success, the parent company did not learn the most valuable lessons from this intense experience, so they were not able to adapt to rapidly changing markets. Motivation and desire also clearly contributed, so after a final attempt to convince the parent company owners to transform into a competitive model, we moved on after contract.

My final report to owners and lenders concluded that the company had probably hit a ceiling, recommending that they either embrace the transformation strategy or sell the company. We could take them no further in current form. Just one example of why—a colleague who was a key team member had received a far superior offer from a great company in a location he and his family preferred.

The client’s response was way below market at a tiny fraction of what the operations specialist had created for the client. The decision on my colleague was surprising, as he was one of the pillars, so it confirmed the ceiling for me. The owners were left with a rising star in a subsidiary that kept shining for a short period, during which time likely created profits far exceeding investment, but then began to fade. Unlike the other holdings of the parent company, this subsidiary required intensive, sophisticated, and experienced management.

A decade later I read where the subject had fallen back to a similar performance level to when the parent company acquired it. It gives me no pleasure to share that hindsight has demonstrated the period of our engagement to be the peak of the parent company’s 50-year history. We worked very hard to provide the opportunity for an enduring success.

While we enjoyed deep mutual respect with the parent company, which appeared adaptive in this acquisition and others we brought to them, they weren’t willing to transform their organization. They were opportunistic on a one-off basis, which is best suited for the flipping model, not for an enduring business. Even then technology played a big role through IBM mainframes, inventory management, and transactions over networks. Today of course most companies are facing more dramatic change in an environment that is far more talent and technology dependent.

The learning organization struggles in the 1990s

A few years and dozens of assignments later we had established a tech lab and incubator to explore and test opportunities due to Internet commercialization, which catapulted the economy with significant g-force into the network era. By the mid-1990s a few operational consultants had become critical of the apparent naiveté with the learning organization theory, which like knowledge management had a philosophy that many could embrace, but in practice found difficult to achieve given real-world constraints, including legal and physical, not just cultural or soft issues.

A few researchers pointed out that it was difficult to find actual cases of learning organizations (Kerka 1995). In papers, textbooks, and Ph.D. theses I was invited to review, the same few cases and papers were cited relentlessly, often comparing apples to oranges. One example was a study published by Finger and Brand in 1999, which found that systems needed to be non-threatening. That may have been the case for their subject at the Swiss Postal Service, but would be unrealistic where threats are among few constants, increasingly to include government and academia. Peter Senge apparently took notice of the criticism, reflected in the subtitle of his book The Dance of Change (1999); “The Challenges of Sustaining Momentum in Learning Organizations”.

By the end of the 1990s I had become vocal on the primitive state of systems and tools that could achieve the goals of the learning organization, and more importantly adapt in a sufficient time frame. My perspective was one from operating a live knowledge systems lab that was building, operating, and testing learning networks, which included daily forums that discussed hundreds of real-world cases in real-time over several years. Many were complaining about poor technology and lack of much needed innovation, yet few were focused on improvement from within organizations that would allow innovation to make it to market.

Some researchers have since suggested that in order to achieve the learning organization, it was first necessary for knowledge workers to abandon self-interest, while others claimed that ‘collective accountability’ is the key. In updating myself on this research recently, it sometimes seemed as if organizational management consultants and researchers were attempting to project a vision over actual evidence, denying the historical importance of technology for survival of our species, as well as mathematics, physics, and economics. Consider the message to an AI programmer or pharma scientist today coming from a tenured professor or government employee with life-long security on ‘the need to abandon self-interest’. This has been tested continuously in competitive markets and simply isn’t credible. The evidence is overwhelmingly polar to such advice.

Current state of the CALO

We may have been experiencing devolution and evolution concurrently, yet humans kept working to overcome problems, representing all major disciplines. My company Kyield is among them.

Significant progress has been made across and between all disciplines, including with understanding and engineering the dynamical components of modern organizations.

The network economy

No question that the structure of an organization greatly influences the ability to adapt even if having learned lessons well, including legal, tax, reporting, incentives, physical, and virtual. The network economy has altered the very foundational structure many organizations operate on top of.

While each structure needs to be very carefully crafted, the structural changes vary from the rare ‘no change is needed’ to increasingly common ‘bold change required to survive’. Though it need not be so, it is increasingly more efficient to disrupt and displace than to change from within.

While we are experiencing a repatriation and regionalization trend, globalization radically changed the way organizations learn and how they must adapt. Several billion more people are driving the network economy than in 1990, with a significant portion moving from extreme poverty to the middle class.

The global financial crisis (GFC)

Suffice to say for this purpose that the GFC has altered the global operating and regulatory landscape for many businesses and governments—in some cases radically, and is still quite fluid. Currency swings in response to unprecedented monetary policies are the most recent example of this chaotic process, though only one of many organizations must navigate. If the regulatory agencies were CALOs, much of the pain would be mitigated.

Machine learning (ML)

Although quite early in commercialization and most cases still confidential, ML combined with cognitive computing and AI assisted augmentation is rapidly improving. Deep learning is an effective means of achieving a CALO in a pure network environment that interacts with customers such as search and social networking, though is being adopted widely now.

One of the largest continuous learning projects is Orion by UPS, which was kind enough to share some detail in public. Orion provides an excellent case for many to consider as it overlaps the physical world with advanced networks and large numbers of employees worldwide. Unlike Google or Facebook that began as virtual companies running on computer networks, UPS represents a large transformation of the type most organizations need to consider. In the case of UPS of course, they have massive logistical operations with very high volume of semi-automated and automated data management.

Having developed deeply tailored use case scenarios for each sector in Kyield’s customer pipeline, numbering in the dozens, I can offer a few words of advice in public.

  1. While all public cases should be considered, remember that few are shared in public for good reason. Few if any companies have the business model, need, resources, or capacity of Google or UPS, which is why they can share the information.

  2. Rare is the case when enormous custom projects should be copied. The craftwork of planning and design is substantially about taking available lessons, combining with technology, systems, and talent in a carefully tailored manner for the client.

  3. Regardless of whether a large custom project, completely outsourced, or anything in-between, board level supervision is necessary to avoid switching dependencies from one vendor or internal department to another. I see this occurring with new silos popping up in open source models, data science, statistics, and algorithms. The goal for most should be to reduce dependencies, which is nontrivial when dealing with high-level intellectual capital embedded in advanced technology, particularly given talent wars, level of contracting in these functional roles, and churn.

  4. Since few will be able to develop and maintain competitive custom systems, the goal should be to seek an optimal, adaptive balance between the benefits of custom tailored software systems (Orion or Google), with the efficiency of write once and adopt at scale in software development. This is one of several areas where Kyield can really make the difference on the level of ROI realized. Our continuously adaptive data management system (patented) is automatically tailored to each entity with semi-automated functions restricted to regulatory and security parameters at the corporate and unit level, with the option for individual knowledge workers to plan projects and goals.

  5. Plan from inception to expand the system to the entire organization, ecosystem, and Internet of Entities. Otherwise, the organization will be physically restricted from achieving much of the value any such system can offer, particularly in risk management. One of the biggest errors I see being made, including in some of the most sophisticated tech companies, is approaching advanced analytics as ‘only’ a departmental project. Of course it is wise to take the low hanging fruit through use of pre-existing department budgets where authority and ROI are simple, but it is a classic mistake for CIOs and IT to consider such projects strategic, with very rare exception such as for a strategic project.

  6. Optimize relationship management. Just one example is when our adaptive data management is combined with advanced ML algorithms that include predictive capabilities, which among other functions weighs counter party risk. A similar algorithm can be run for identifying business opportunities.

Concluding thoughts

While it is more challenging to achieve buy-in for organization-wide systems, it is physically impossible to achieve critical use cases otherwise, some of which have already proven to be very serious, and can be fatal. Moreover, very few distributed organizations can become a CALO without a holistic system design across the organization’s networks, particularly in the age of distributed network computing.

If this isn’t sufficient motivation to engage, consider that learning algorithms are very likely (or soon will be) improving the intelligence quotient and operational efficiency of your chief competitors at an extremely rapid rate. Lastly, if the subject organization or entire industry is apathetic and slow to change, it is increasingly likely that highly sophisticated, well-financed disrupters are maturing plans to deploy this type of technology to displace the subject, if not the entire industry.

Bottom line: Move towards CALO rapidly or deal with the consequences.

Mark Montgomery is founder and CEO of http://www.kyield.com, which offers an advanced distributed operating system and related services centered around Montgomery’s AI systems invention.

Applied artificial intelligence: Mythological to neuroanatomical

First of a three part series exploring the depths of artificial intelligence in 2015.

Nueromorphic chip, University of Heidelberg

Neuromorphic chip, University of Heidelberg, Germany Credit: University of Heidelberg

While artificial intelligence (AI) has roots as far back as Greek mythology, and Aristotle is credited with inventing the first deductive reasoning system, it wasn’t until the post WWII era of computing that we humans began to execute machine intelligence with early supercomputers. The science progressed nicely until the onset of AI Winter in the 1960s, representing the beginning of severe cycles in technology. A great deal of R&D needed to evolve and mature over the next five decades prior to wide adoption of applied AI — here is a brief history and analysis of the rapidly evolving field of artificial intelligence and machine learning.

Hardware innovation

One of the primary obstacles to applied AI has been with scaling neural networks, particularly containing rich descriptive data and complex autonomous algorithms. Even in today’s relatively low cost computing environment scale is problematic, resulting in graduate students at Stanford’s AI lab complaining to their lab director “I don’t have 1,000 computers lying around, can I even research this?” In a classic case of accelerated innovation, Stanford and other labs then switched to GPUs: “For about US$100,000 in hardware, we can build an 11-billion-connection network,” reports Andrew Ng, who recently confirmed Baidu now “often trains neural networks with tens of billions of connections.”

Although ever-larger scale at greater speed improves deep learning efficiency, CPUs and GPUs do not function like a mammalian brain, which is why for many years researchers have investigated non–von Neumann architectures that would more closely mimic biological intelligence. One high profile investment is the current DARPA SyNAPSE program (Systems of Neuromorphic Adaptive Plastic Scalable Electronics).

In addition to neuromorphic chips, researchers are increasingly focused on the use of organic materials, which is part of a broader trend towards convergence of hardware, software, and wetware described by IARPA as cortical computing, aka neuroanatomical. The ability to manipulate mass at the atomic level in computational physics is now on the horizon, raising new governance issues as well as unlimited possibilities. The research goals of the Department of Energy in the fiscal 2016 budget proposal provides a good example of future direction in R&D:

The Basic Energy Sciences (BES) program supports fundamental research to understand, predict, and ultimately control matter and energy at the electronic, atomic, and molecular levels …. Key to exploiting such discoveries is the ability to create new materials using sophisticated synthesis and processing techniques, precisely define the atomic arrangements in matter, and control physical and chemical transformations.

Software and data improvements

Similar to hardware, software is an enabler that determines the scalability, affordability, and therefore economic feasibility of AI systems. Enterprise software to include data base systems also suffered a period of low innovation and business creation until very recently. In early 2015 several companies in the billion-dollar startup club are providing infrastructure support to AI, offering overlapping services such as predictive analytics, and/or beginning to employ narrow AI and machine learning (ML) internally. Many of us are now concerned with lack of experience and excessive hype that often accompany rapidly increased investment.

Database systems and applications

Database systems, storage and retrieval are of course of critical importance to AI. A few short years ago only one leading vendor supported semantic standards, which was followed by a second market leader two years ago. The emergence of multiple choices in the market is resulting in the first significant new competition in database systems in over a decade, several of which are increasingly competing for critical systems at comparable performance levels at significantly lower cost.

Data standards and interoperability

Poor interoperability vastly increases costs and systemic risk while dramatically slowing adaptability, and makes effective governance all but impossible. While early adopters of semantic standards include intelligence agencies and scientific computing, even banks are embracing data standards in 2015, in part due to regulatory agencies collaborating internationally. High quality data built on deeply descriptive standards combined with advanced analytics and ML can provide much improved risk management, strong governance, efficient operations, accelerated R&D and improved financial performance. In private discussions across industries, it is clear that a consensus has finally formed that standards are a necessity in the network era.

Automation, agility, and adaptive computing

An effective method of learning the agility quotient of an organization is post mortem analysis after a catastrophic event such as patent cliffs in big pharma, or failure to respond to digital disruption. Unfortunately for executives, by the time clarity is gained from hindsight, the wisdom is only useful if placed in a position of authority again. Similarly, failed governance is quite evident in the wake of industrial accidents, missed opportunities to prevent terrorist attacks and whale trades among many others.

Given that the majority of economic productivity is planned and executed over enterprise networks, it is fortunate that automation is beginning to replace manual system integration. Functional silos are causal to crises, as well as obstacles to solving many of our greatest challenges. Too often has been the case where the lack of interoperability has proven to be leveraged for the benefit of the IT ecosystem rather than customer mission. In drug development, for example, until recently scientists were reporting lag times of up to 12 months for important queries to be run. By automating data discovery, scientists can run their own queries, AI applications can recommend unknown queries, and deep learning can continuously seek solutions to narrowly defined problems tailored to the needs of each entity.

In the next article in this series we’ll take a look at recent improvements in algorithms and what types of AI applications are now possible.

(This article was originally published at Computerworld)

Mark Montgomery is the founder and CEO of Kyield, originator of the theorem “yield management of knowledge,” and inventor of the patented AI system that serves as the foundation for Kyield.

Plausible Scenarios For Artificial Intelligence in Preventing Catastrophes

(The PDF version of this article is now available here)

Plausible Scenarios For Artificial Intelligence in Preventing Catastrophes

Given consistent empirical evidence demonstrating that the raising of red flags has resulted in a lower probability of essential actors heeding warnings than causing of unintended consequences, those endowed with a public platform carry a special responsibility, as do system architects. Nowhere is this truer than at the confluence of advanced technology and existential risk to humanity.

As one who has invested a significant portion of my life studying crises and designing methods of prevention, including for many years the use of artificial intelligence (AI), I feel compelled to offer the following definitions of AI with a few of what I consider to be plausible scenarios on how AI could prevent or mitigate catastrophes, as well as brief enlightenment on how we reduce the downside risk to levels similar to other technology systems.

An inherent temptation with considerable incentives exists in the transdisciplinary field of AI for the intellectually curious to expand complexity infinitely, generally leaving the task of pragmatic simplicity to applied R&D, which is the perspective the following definitions and scenarios are offered, primarily for consideration and use in this article.

A Definition of Artificial Intelligence: Any combination of technologies and methodologies that result in learning and problem solving ability independent of naturally occurring intelligence.

A Definition of Beneficial AI: AI that has been programmed to prevent intentional harm and to mitigate unintended consequences within a strictly controlled governance system, which include redundant safety functions, and continuous human oversight (to include a kill switch in high-risk programs). [1]

A Definition of Augmentation: For the purposes of this article, augmentation is defined not as implants or direct connection to biological neural systems, which is an important rapidly emerging sub-field of AI in biotech, but rather simply enhancing the quality of human work products and economic productivity with the assistance of AI[2]

To aid in this exercise, I have selected quotes from the highly regarded book Global Catastrophic Risks (GCR), which consists of 22 chapters by 25 authors in a worthy attempt to provide a comprehensive view. [3]  I have also adopted the GCR definition of ‘global catastrophic’: 10 million fatalities or 10 trillion dollars. The following reminders from GCR seem appropriate in a period of intense interest in AI and existential risk:

“Even for an honest, truth-seeking, and well-intentioned investigator it is difficult to think and act rationally in regard to global catastrophic risks and existential risks.”

“Some experts might be tempted by the media attention they could get by playing up the risks. The issue of how much and in which circumstances to trust risk estimates by experts is an important one.”

Super Volcanoes

A very high probability event that should consume greater attention, super volcano eruptions occur about every 50,000 years. GCR highlights the Toba eruption in Indonesia approximately 75,000 years ago, which may be the closest humanity has come to extinction. The primary risk from super eruptions is airborne particulates that can cause a rapid decline in global temperatures, estimated to have been 5–15 C after the Toba event. [4]

While it appears that a super-eruption contains a low level of existential risk to the human race, a catastrophic event is almost certain and would likely exceed all previous disasters, followed by massive loss of life and economic collapse, reduced only by the level of preventative measures taken in advance. While preparation and alert systems have much improved since my co-workers and I observed the eruption of Mt. St. Helens from Paradise on Mt. Rainier the morning of May 18th, 1980, it is quite clear that the world is simply not prepared for one of the larger super-eruptions that will undoubtedly occur. [5] [6]

MM on Mt. Rainier, 5/18/1980

MM on Mt. Rainier, 5/18/1980

The economic contagion observed in recent events such as the 9/11 terrorists attacks, the global financial crises, the Tōhoku earthquake and tsunami, the current Syrian Civil War, and the ongoing Ebola Epidemic in West Africa serve as reasonable real-world benchmarks from which to make projections for much larger events, such as a super-eruption or asteroid. It is not alarmist to state that we are woefully unprepared and need to employ AI to increase the probability for preserving our species and others. The creation and colonization of highly adaptive outposts in space designed with the intent of sustainability would therefore seem prudent policy best served with the assistance of AI.

The role of AI in mitigating the risks associated with super volcanoes include accelerated research, more accurate forecasting, increased modeling for preparation and mitigation of damage, accelerating discovery of systems for surviving super eruptions, and to assist in recovery. These tasks require ultra high scale data analytics to deal with complexities far beyond the ability of humans to process within circumstantially dictated time windows, and are too critical to be dependent upon a few individuals, thus requiring highly adaptive AI across distributed networks involving large numbers of interconnected deep earth and deep sea sensors, linking individuals, teams, and organizations. [7]  Machine learning has the ability to accelerate all critical functions, including identifying and analyzing preventative measures with algorithms designed to discover and model scenario consequences.

Asteroids are similar to super volcanoes from an AI perspective, both requiring effective discovery and preparation, which while ongoing and improving could benefit from AI augmentation. Any future preventive endeavors may require cognitive robotics working in extremely hostile environments for humans where real time communications could be restricted. Warnings may be followed swiftly by catastrophic events—hence, preparation is critical, and if viewed as optional, we do so at our own peril.

Pandemics and Healthcare Economics

Among the greatest impending known risks to humans are biological contagions, due to large populations in urban environments that have become reliant on direct public interaction, regional travel by public transportation, and continuous international air travel. Antibiotic-resistant bacteria and viruses in combination with large mobile populations pose a serious short-term threat to humanity and the global economy, particularly from an emergent mutation resistant to pre-existing immunity or drugs.

“For example, if a new strain of avian flu were to spread globally through the air travel network that connects the world’s major cities, 3 billion people could potentially be exposed to the virus within a short span of time.” – Global Risk Economic Report 2014, World Economic Forum (WEF). [8]

Either general AI or knowledge work augmented with AI could be a decisive factor in preventing and mitigating a future global pandemic, which has the potential capacity to dwarf even a nuclear war in terms of short-term casualties. Estimates vary depending on strain, but a severe pandemic could claim 20-30% of the global population compared to 8-14% in a nuclear war, though aftermath from either could be as horrific.

Productivity in life science research is poor due to inherent physical risks for patients as well as non-physical influences such as cultural, regulatory, and financial that can increase systemic, corporate, and patient risk. Healthcare cost is among the leading global risks due to cost transference to government. The WEF, for example, cites ‘Fiscal Crisis in Key Economies’ as the leading risk in 2014. Other than poor governance that allows otherwise preventable crises to occur, healthcare costs are arguably the world’s most severe curable ongoing crisis, impacting all else, including pandemics.

Priority uses of AI for pandemics and healthcare: [9]

  • Accelerated R&D throughout life science ecosystem, closing patient/lab gap.

  • Advanced modeling scenarios for optimizing prevention, care, and costs.

  • Regulatory process including machine learning and predictive modeling.

  • Precision healthcare tailored to each person; more direct and automated. [10]

  • Predictive analytics for patient care, disease prevention, and economics.

  • Cognitive computing for diagnostics, patient care, and economics.

  • Augmentation for patients and knowledge workers worldwide.

“By contrast to pandemics, artificial intelligence is not an ongoing or imminent global catastrophic risk. However, from a long-term perspective, the development of general artificial intelligence exceeding that of the human brain can be seen as one of the main challenges to the future of humanity (arguably, even the main challenge). At the same time, the successful deployment of superintelligence could obviate many of the other risks facing humanity.” — Eliezer Yudkowsky in GCR chapter ‘Artificial Intelligence as a Positive and Negative Factor in Global Risk’.

Climate Change

Crises often manifest over time as a series of compounding events that either could not be predicted, predictions were inaccurate, or were not acted upon. I’ve selected an intentionally contrarian case with climate change to provide a glimpse of potentially catastrophic unintended consequences. [11]

“Anthropogenic climate change has become the poster child of global threats. Global warming commandeers a disproportionate fraction of the attention given to global risks.” – GCR

If earth cooling from human response driven by populism, conflicted science, or any other reason resulted in an over-correction, or a response combined with volcanoes, asteroids, or slight variation of cyclic changes in Earth’s orbit to alter ocean and atmospheric patterns, it becomes plausible to forecast a scenario of an accelerated ice age where ice sheets rapidly reach the equator similar to what may have occurred during the Cryogenian period. Given our limited understanding of triggering mechanisms to include in sudden temperature changes, which are believed to have occurred 24 times over the past 100,000 years, it is also plausible that either a natural and/or human response could result in rapid warming. While either scenario of climate extreme may seem ludicrous given current sentiment, the same was true prior to most events. Whether natural, human caused, or some combination as observed with the Fukushima Daiichi nuclear disaster, the pattern of complexity of seemingly small events leading to larger events is more the norm rather than exception, with outcomes opposed to intent not unusual. While reduction of pollutants is prudent for health, climate, and economics, chemically engineered solutions should be resisted until our ability to manage climate change is proven with rigorous real-world models.

The tragedy of 9/11 provides a critical lesson in seemingly low risk series of events that can easily spiral into catastrophic scale if not planned and managed with precision. Those who decided not to share the Phoenix memo at the FBI with appropriate agencies undoubtedly thought it was a safe decision given information at the time. Who among us would have acted differently if having to make our decision based on the following questions in the summer of 2001?

  • What are the probabilities of an airline being used as a weapon?
  • Even if such an attempt was made, what are the probabilities of it occurring?
  • In the unlikely event such an attempt did occur, what is the probability that one of the towers at the World Trade Center would be targeted and struck?
  • In the very unlikely event one WTC tower were struck, what is the probability that the other tower would be struck similarly before evacuation could take place?
  • In the extremely unlikely scenario that terrorists attacked the second tower with a hijacked commercial airliner within 20 minutes of the first attack, what would be the probability of one of the towers collapsing within an hour?
  • If then this horrific impossible scenario were actually to have occurred, what then would be the possibility of the second tower collapsing a half hour later?

Prior to 9/11, such a scenario would seem to be an extremely low probability for anyone but an expert if possible to verify and process all information, but of course the questions describe the actual event, tragically providing one of the most painful and costly lessons in human life and treasure in the history of the U.S., with wide ranging global impact.

  • Direct costs from attacks: 2,999 lives lost with an additional 1,400 rescue workers having died since, some portion of which were directly caused. Financial costs from 9/11 are estimated to have been approximately $2 trillion to the U.S. alone. [12]

  • Iraq and Afghanistan wars: Approximately 36,000 people from the US and allied nations died in Iraq and Afghanistan, with nearly 900,000 disability claims approved by the VA alone. [13]  The human cost in the two nations were of course much higher, including large numbers of civilians. According to one report, the Iraq War has cost $1.7 trillion with an additional $490 billion in benefits owed to veterans, which could grow to more than $6 trillion over the next four decades counting interest. [14]  The Afghanistan war is estimated to have cost $4-6 trillion.

  • Global Financial Crisis: Many experts believe monetary easing post 9/11 combined with lax regulatory oversight expanded the unsustainable housing bubble and triggered the financial collapse in 2008, which revealed systemic risk accumulating over decades from poor regulatory oversight, governance, and policy. [15]  The total cost to date from the financial crisis is well over $10 trillion and continues to rise from a series of events reverberating globally, caused by realized moral hazard, broad global reactions, and significant continuing aftershocks from attempts to recover.

The reporting process for preventing terrorist attacks has been reformed and improved, though undoubtedly still challenged due to the inherently conflicted dynamics between interests, exponential growth of data, and limited ability for individuals to process. If the FBI decision makers were empowered with the knowledge of the author of the Phoenix memo (special agent Kenneth Williams), and free of concerns over interagency relations, politics, and other influences, 9/11 would presumably have been prevented or mitigated.

An Artificially Intelligent Special Agent

What if the process wasn’t dependent upon conflicted humans? An artificial agent can be programmed to be free of such influences, and can access all relevant information on the topic from available sources far beyond the ability of humans to process. When empowered with machine learning and predictive analytics, redundant precautions, and integrated with the augmented workflow of human experts, the probability of preventing or mitigating human caused events is high, whether in preventing terrorist plots, high cost projects with deep sea oil rigs, trading exotic financial products, nuclear power plant design, response to climate change, or any other such high-risk endeavor.

Governance of Human Engineered Systems

Long considered one of the primary technical risks, as well as key to overcoming many of our most serious challenges, the ability to program matter at the atomic scale is beginning to emerge. [16]  Synthetic biology is another area of modern science that poses great opportunity for improving life while introducing new risks that must be governed wisely with appropriate tools. [17]

While important private research cannot be revealed, published work is underway beyond the typical reporting linked to funding announcements and ad budgets. One example is the Synthetic Evolving Life Form (SELF) project at Raytheon led by Dr. Jim Crowder, which mimics the human nervous system within an Artificial Cognitive Neural Framework (ACNF). [18]  In their book Artificial Cognitive Architectures, Dr. Crowder and his colleagues describe an unplanned Internet discussion between an artificial agent and human researcher that called for embedded governance built into the design.

A fascinating project was recently presented by Joshua M. Epstein, Ph.D. at the Santa Fe Institute on research covered in his book Agent_Zero: Toward Neurocognitive Foundations for Generative Social Science[19]  In this novel approach to agent based social behavior, Epstein has intentionally removed memory and pre-conditioned bias from Agent Zero to simulate what often appears to be irrational behavior resulting from social influences, reasoning, and emotions. Agent Zero provides a good foundation for considering additional governance methods for artificial agents interacting in groups, with potential application in AI systems designed to regulate systemic risk in networked environments.

Closing Thoughts

Given the rapidly developing AI-assisted world combined with recent governance failures in financial regulation, national security, and healthcare, the challenge for senior decision makers and AI systems engineers is to perform at much higher levels than the past, for if we continue on this trajectory it is conceivable that the human experience could confirm the Fermi Paradox within decades. I therefore view AI in part as a race against time.

While the time-scale calculus for many organizations supports accelerated transformation with the assistance of AI, it is wise to proceed cautiously with awareness that AI is a transdisciplinary field which favors patience and maturity in the architects and engineers, typically requiring several tens of thousands of hours of deep immersion in each of the applicable focus areas. It is also important to realize that the fundamental physics involved with AI favors if not requires the governance structure to be embedded within the engineered data, including business process, rules, operational needs, and security parameters. When conducted in a prudential manner, AI systems engineering is a carefully planned and executed process with multiple built-in redundancies.

(Robert Neilson, Ph.D., and Garrett Lindemann, Ph.D., contributed to this article)

[1] In the GCR chapter Artificial Intelligence as a ‘Positive and Negative Factor in Global Risk’, Eliezer Yudkowsky prefers ‘Friendly AI’. His complete chapter is on the web here: https://intelligence.org/files/AIPosNegFactor.pdf

[2] During the course of writing this paper Stanford University announced a 100-year study of AI. The white paper by Eric Horvitz can be viewed here: https://stanford.app.box.com/s/266hrhww2l3gjoy9euar

[3] Global Catastrophic Risks, edited by Nick Bostrom and Milan M. Cirkovic, (Oxford University Press, Sep 29, 2011): http://ukcatalogue.oup.com/product/9780199606504.do

[4] For more common events, see Ultra distant deposits from super eruptions: Examples from Toba, Indonesia and Taupo Volcanic Zone, New Zealand. N.E. Matthews, V.C. Smith, A Costa, A.J. Durant, D. M. Pyle and N.G.J. Pearce.

[5] USGS Fact Sheet for Alert-Notification System for Volcano Activity: http://pubs.usgs.gov/fs/2006/3139/fs2006-3139.pdf

[6] Paradise is about 45 miles to the north/blast side of St. Helens in full view until ash cloud enveloped Mt. Rainier with large fiery ash and friction lightening. A PBS video on the St. Helens eruption: http://youtu.be/-H_HZVY1tT4

[7] Researchers at Oregon State University claimed the first successful forecast of an undersea volcano in 2011 with the aid of deep sea pressure sensors: http://www.sciencedaily.com/releases/2011/08/110809132234.htm

[8] Global Risk Economic Report 2014, World Economic Forum: http://www3.weforum.org/docs/WEF_GlobalRisks_Report_2014.pdf

[9] While pandemics and healthcare obviously deserve and receive much independent scrutiny, understanding the relativity of economics is poor. Unlike physics, functional metric tensors do not yet exist in economics.

[10] New paper in journal Science: ‘The human splicing code reveals new insights into the genetic determinants of disease’ http://www.sciencemag.org/content/early/2014/12/17/science.1254806

[11] Skeptical views are helpful in reducing the number and scope of unintended consequences. For a rigorous contrarian view on climate change research see ‘Fat-Tailed Uncertainty in the Economics of Catastrophic Climate Change’, by Martin L. Weitzman: http://scholar.harvard.edu/files/weitzman/files/fattaileduncertaintyeconomics.pdf

[12] Institute for the Analysis of Global Security http://www.iags.org/costof911.html

[13] US and Coalition Casualties in Iraq and Afghanistan by Catherine Lutz, Watson Institute for International Studies: http://costsofwar.org/sites/default/files/articles/8/attachments/USandCoalition.pdf

[14] Daniel Trotta at Reuters, March 14th, 2013 http://www.reuters.com/article/2013/03/14/us-iraq-war-anniversary-idUSBRE92D0PG20130314

[15] In his book The Age of Turbulence: Adventures in a New World, Alan Greenspan states that monetary policy in the years following 9/11 “saved the economy”, while others point to Fed policy during this period as contributing to the global financial crisis beginning in 2008, which continues to reverberate today. Government guarantees, high-risk products in banking, companies ‘too big to fail’, corrupted political process, increased public debt, lack of effective governance, and many other factors also contributed to systemic risk and the magnitude of the crisis.

[16] A team of researchers published research in Nature Chemistry in May of 2013 on using a Monte Carlo simulation to demonstrate engineering at the nanoscale: http://www.nature.com/nchem/journal/v5/n6/full/nchem.1651.html

[17] A recent paper from MIT researchers ‘Tunable Amplifying Buffer Circuit in E. coli’ is an example of emerging transdisciplinary science with mechanical engineering applied to bacteria: http://web.mit.edu/ddv/www/papers/KayzadACS14.pdf

[18] My review of Dr. Crowder’s recent book Artificial Cognitive Architectures can be viewed here: https://kyield.wordpress.com/2013/12/17/book-review-artificial-cognitive-architectures/

[19] Agent_Zero: Toward Neurocognitive Foundations for Generative Social Science, by

Joshua M. Epstein: http://press.princeton.edu/titles/10169.html The seminar slides (require Silverlight plugin): http://media.cph.ohio-state.edu/mediasite/Play/665c495b7515413693f52e7ef9eb4c661d

sfs tent

SfS Tent Banner at Everest BC, 2014.

I was recently introduced to Mike through an old mutual friend Andy Politz, who I met while living and working at Mt. Rainier in 1980. My wife Betsy and I moved on a couple of years later to start a business while Andy returned to Rainier as a mountain guide alongside other climbers our age like Dave Hahn and Ed Viesturs (see Whittaker Mountaineering or International Mountain Guides).

Andy Politz on 2009 Mallory Irvine Everest Expedition

Andy and Mike have been taking vets into the mountains as part of the healing process for several years now, which I can personally confirm is a worthy effort. A life-long mountain lover, I also sought healing in the mountains during my youth when my late father (USAF Major Floyd L. Montgomery) returned from Vietnam with serious health issues that impacted our entire family. My father eventually recovered and enjoyed many good years, but a large number of veterans don’t.

  • Every 65 minutes, a military veteran commits suicide.

  • 22 military veterans commit suicide every day.

  • 31 percent of these suicides were veterans aged 49 and younger.

  • Every month nearly 1,000 veterans attempt to take their own lives.

  • Suicides among active duty personnel outpace killed in action.

  • 11-20% of troops suffer from PTSD who served in OIF/OEF (Operation Enduring Freedom/Operation Iraqi Freedom). 300,000-500,000 report to VA, presumably unknown number do not or have yet to report. (VA/Rand/PBS)

I reached out to Andy by email a couple of weeks ago to explore ways to help, and somewhat serendipitously Andy replied from the base of Kilimanjaro, which he and Mike had just climbed as part of Mike’s bid to climb the 7 summits to raise awareness for Post Traumatic Stress (PTS) and suicide prevention for veterans.

Kili Summit photo

Mike and his wife Beth on Kilimanjaro (2nd summit) on 15 Sep 2014.

andy and mike

Mike and Andy Politz; Barranco Wall, Kilimanjaro.

Summit for Soldiers

“A bunch of personally attached, self-funded combat veterans, families and mountaineers who are dedicated to continue to serve our veterans anyway we can.”

(All quotes are from Mike Fairman from email exchanges last week).

“Andy Politz has been awesome in helping me/us with our efforts, which includes my bid to climb the 7-summits of the world. So far this year I have reached the summits of Aconcagua and Kilimanjaro, and an attempt of Everest, which was cut short due to the loss of 16 Sherpas in the icefall disaster.”

(MM: Planning another attempt of Everest in 2015).

MEMORy ACT (Mental-health Exposure Military Official Record Act)

“One thing our group has done is identify an simple, safe, cost-effective fix within the DOD to track, verify and document events to eliminate future backlogs at the VA (this is currently not being done outside of those that are seriously injured) and our “grassroots” veterans created effort has led to bipartisan legislation that has been introduced as a Bill into both the HOUSE and the SENATE, we also have endorsements from every major Veterans Service Organization like the VFW and IAVA. If and when this is enacted it will better serve every veteran of the future, currently 10’s of 1000’s of veterans are turned away because of poor/lacking documentation. (You can learn more at my website: www.MemoryAct.org )”

VFW Sen Brown Me

Mike with US Sen. Brown (OH)

The goals of the MEMORy ACT reflect a similar philosophy to our work at Kyield, which is a holistic approach (Unified Network OS) for data management to close such gaps. One of the biggest challenges in caring for returning veterans is the well-known bureaucracy and archaic technology architecture which is extremely frustrating for anyone, so one can only imagine what it must be like for veterans to return home from war, discover a serious problem, and attempt to get help from the VA system only to learn that the evidence one needs to qualify for care will either take years to process, or wasn’t documented properly.

While healthcare and disability fraud is a serious problem across the U.S., accurate data on a real-time basis for the duration would allow for fraud prevention as well as proper care for those who are entitled to care. Importantly, such programs would move the DoD and VA towards much needed personalized healthcare that empowers active duty families as well as vets, which is critical for prevention, life science research, and optimizing a terribly inefficient healthcare system that is full of dedicated people, but decades behind where it should be. While I am one who agrees that the U.S. military needs the world’s most sophisticated weaponry, I’m also one who warns that we better start treating soldiers on the front lines with the same priority or it may not matter much.

“My reasons for launching on this challenge are:  One, to show my example as a veteran who struggles with mental-health injuries (including a former suicide attempt) that you CAN take back control of your life and achieve “lofty” goals. Second, is to draw attention to our mission and efforts. And finally, the main reason is to carry a flag that bears the names of some of the warriors we have known and loss to suicide… the first name on the flag was one of my marines, LCPL Bob Wiley. The Wiley family is one of many families that have got behind this effort to raise awareness and help us continue to find ways to reduce the over 8000 veteran suicides that occur each year.”

“I totally agree with what you mention about veterans healing in the mountains. We launched on this “mission” because we realized our personal therapy came from our “adventures” and our analogy was that just like dealing/struggling with PTS/Depression you work together, trust your team, and experience the good/bad together, and eventually (in spite of all the circumstances out of our control) you reach the summit. Only to go down and do it all again!”

“I am grateful to the VA and my team there, they saved my life, but that said the system has become a catch-22 for so many folks in that it almost promotes the very stigma we are trying to destroy. What I mean is this, we go to the VA, they tell us we have a problem, they intervene, treat us and compensate us for the problem. Now we are “disabled” and the tendency is to just return to the place where we can find support and because we are now technically “disabled” we simply look to that system for guidance and support. Now, I suppose I’m a bit of a hypocrite because the legislation we have developed would make sure every veteran who needs help can get it quickly without obstacles, but our intention is directed towards a DOD fix on the front end to ensure people get into the VA system that was designed to do all of the above to help get them back on their feet.”

wiley memorial

Memorial on Aconcagua. Photo of Marine LCPL Bob Wiley.

“For me the VA was the place to “reset” my physical life by sorting through my issues, diagnosis and treatments to make sure I can be safe, but the healing and repair comes after we “reset” and realize that the things we endured are in the past, and we CAN take back control of our lives… And that comes from engaging in life, reconnecting with family, finding a new purpose outside of the military and for me/us that is the mountains. A big part of the endeavor at SfS plays into my own personal therapy! In fact, many veterans that have launched on their respective causes/missions do so as part of their recovery/therapies.”

“My big vision for SfS (after we finish up this legislative opportunity we have been given) is to see it grow into state chapters that become an outdoor gathering/support group for veterans and those interested, along with a place of refuge and resource for veterans specific issues. In other words, you go out for some weekend adventures with other veterans, have a place where you can talk about what is going on, and point folks in the appropriate direction for what they need. Kind of like a new version of the VFW, but built around outdoor activities instead of just sitting around drinking in a dark room.”

CMF Afghan

C. Michael Fairman, Pre-patrol in Afghanistan, HM2 (FMF) USN (Hospital Corpsman, Fleet Marine Force) USMC Lima Company

I’d like to thank Mike for his efforts and candor. Having grown up in a military family with many friends who lost fathers in battle, I vividly recall being part of a culture that while supporting each other as family, are also trained to withhold information on a pragmatic need-to-know basis (even from family). Combined with mental health challenges and a society back home that is typically clueless to the challenges and sacrifice required of a great many so that the majority can live in relative peace, communications can be a real problem, particularly when awareness in a democracy is necessary to move the biggest mountains of all in the form of the DoD, VA, and members of the U.S. Congress.

How Business Leaders Can Help

My company is deeply involved in the issues surrounding optimized healthcare, and we’ve been working with the DoD for many years on related technology. If Kyield is even modestly successful as we commercialize our technology, we plan to sponsor Mike’s vision for a new kind of VFW focused on beneficial outings in nature. In the interim, a huge opportunity exists for private companies to sponsor the formation of a national organization dedicated to Mike’s vision and mission. It’s clear to me that the time has come to support this worthy effort, assist with funding, and help set up a sustainable organizational structure with local chapters. I think SfS could scale well and rapidly with assistance.

While such a sponsorship would seem particularly well-matched to companies like USAA, DoD contractors, and pharmaceutical firms, the scale of PST is so vast that it literally impacts every community, which also means it’s an opportunity for giants in retail, banking, tech companies, and many others.

In addition to the tragic ongoing human catastrophe that falls on a quiet minority of families that pay the ultimate price, the economic costs cannot be ignored. Estimates range from $1 trillion to $3 trillion for lifetime care of veterans labeled disabled, much of which is related to pre-existing cases of PST and traumatic brain injury, some unknown large portion of which can be mitigated. Business leaders clearly have a moral, ethical, and financial obligation to engage and assist.

How Journalists Can Help

While the greater problem of PST and VA challenges have been reported, Summit for Soldiers has received little exposure, and it’s a great story waiting to be told. In addition, the MEMORy ACT has a deadline in January so more awareness is needed a.s.a.p. The issues surrounding data management, personalized medicine, preventative care, and economics are timely, relevant, and extremely important.

How Individuals Can Help

Below are links to immediately support efforts underway, whether through contacting your representatives in the House or Senate to support the MEMORy ACT and support veterans generally, small group efforts Andy and Mike are involved with, or the 7 summit bid to raise awareness.

Summit for Soldiers

Andy Politz’s Ascent with Honor

Support Mike’s 7 Summits Bid

After 120 Labor Day Holidays, What Have We Learned?

In reflecting on the current workforce, global economy, technology, and labor markets, I revisited the origins of the U.S. Labor Day, which is celebrated on the first Monday in September, similar to the International Worker’s Day on May 1.

While the tipping point for political winds appears to have been the Haymarket riot in Chicago in 1886 that eventually led to a national holiday, many other factors occurred during the industrial revolution that are relevant to the present day and so leaders should examine. The two eras are similar in many respects, yet very different in others.

The Haymarket Affair appears to have been triggered by several factors, including a global anarchist movement that fed off of widespread inhumane labor conditions, severe economic swings, enormous wealth gaps, political corruption, and traveling agitators exploiting conditions which led to violence. The actual bomber in the Haymarket riot for example was never found, while others paid the price, including policemen and laborers.

Fighting the Last Economic War?

Some have argued that the FRB has been fighting the last war of the Great Depression, which was after all the specialty (and thesis) of Ben Bernanke. I see more similarities in the current global economic situation today with the Long Depression of the late 1800s, which was the ‘Great Depression’ until the severity of the 1930s took the title. The underlying economic shifts driven by the information revolution, while different than industrial revolution, appear more similar to the late 1800s than the 1920s and 30s.

The most stunning similarities between the present day and the late 1800s are reflected in economic statistics. The Long Depression began with the panic of 1873, which was precipitated by the collapse of Jay Cooke & Company (considered the first investment bank in the U.S.), is the longest lasting U.S. contraction in the NBER records.

While e-commerce contributed to bubbles and crashes in our era, similar dynamics occurred in the late 1800s with industrial production and the opening of the Panama Canal. As is the case today, war was a factor in both the U.S. and Europe, with dynamics of monetary policy contributing to recoveries and triggering failures. Today we deal with the uncertainties of quantitative easing, while in the 1870s the halt to silver currency caused severe shocks and ripples worldwide with economic collapse in regions that had become dependent on silver mining.

The American Civil War ended in April 1865, which was followed by a deflationary period that lasted until 1896. The Franco-Prussian War in 1870-71 was apparently caused in part by German unification during the same period, with repatriation helping to fuel a large regional speculative economic bubble followed of course by a bust. One can see dynamic influences from the dissolution of the Holy Roman Empire and Napoleonic Wars in the early 1800s.

During the period of the Long Depression between1873–96, Europe experienced a sharp decline in prices, resulting in a depression for the majority while some industries boomed as production increased due to transportation and manufacturing efficiencies. The Long Depression finally ending in 1896 after yet another panic.

Similarities Between the Industrial and Information Revolution

  • Excess capital invested poorly caused multiple bubbles and crashes
  • Great productivity increases in each allowed companies to lower prices sharply
  • Modern day wealth gap peaks are found during these two eras
  • Severe exploitation of workers was a significant causal factor in crises within both revolutions, though in very different forms
  • Volatility led to various forms of backlash, including the rise of extreme socialists and anarchists, which then caused even further structural decay

Differences Between the Industrial and Information Revolution

Bonds fueled much of the Civil War and industrial revolution, including door-to-door sales by investment banking sales reps. The information revolution has been funded primarily by institutional VC and IPOs that boycotted small investors through SEC regulations until valuations were mature, or in some cases post mature (aka ‘pump and dump’). While both revolutions required and justified funding based on solid economic fundamentals and legitimate ROI, with very real productivity increases in each—the information revolution is really a continuance of industrial—irrational behavior, oversupply, corruption, and reactions are more similar than not.

While the industrial revolution observed massive displacement of small family farms with tractors (majority of the U.S. population), and railroads replaced wagon trains, the information revolution displaced bookstores and newspapers with search engines, and physical retailers with e-commerce. The later stages of the industrial revolution resulted in interstate highways and intercontinental flight, but we can only speculate on the late stages of the information revolution, due less to technology forecasting than potential backlashes by markets and/or regulators.

Exploitation of workers manifested in much different ways during these two eras. The industrial revolution required large numbers of workers who were experiencing increased buying power, but were not experiencing improved quality of life due to long hours, unhealthy and even deadly working conditions. The information revolution witnessed a severe bubble expansion in the late 1990s and contraction in 2000, followed by subprime mortgage bubble leading to a severe financial collapse in 2008, with enormous losses transferred directly to national debt in Europe and the U.S. Unlike the 1800s when industrial workers toiled long hours in dangerous conditions, today’s workers in the U.S. are physically safe by comparison.

However, today we have vast numbers of workers at all levels of competency supplying content and data with no compensation from the financial beneficiaries for products they supply, which has enabled some of the wealthiest individuals and companies of any era. A large portion of these product suppliers are subsidized by government or corporate compensation, and millions of others by the welfare state. Freeism and lack of protection of intellectual capital on the Internet and Web have been terribly destructive to the structural underpinnings of the global economy; particularly to wealthy nations. Some may see this as justified wealth transfer. I see it as simply historic levels of greed, exploitation, and unhealthy destruction, not to be confused with more healthy forms of creative destruction that replaces outdated industries and companies with newer more beneficial models, products, and services. While our era has all types including highly beneficial models, I’ll save that focus for another day.

The most important contrast between the two revolutions for the average American worker is that real wages increased considerably during the industrial revolution, while they are generally decreasing in the information revolution, with liabilities being transferred to national debt and FRB balance sheet. Translated to every day reality, the average American worker is experiencing a long-term decline in discretionary income while rapidly piling up a long-term increase in share of public debt. It represents a rather unholy relationship between big business and big government as governments borrow to create dependent citizens who are increasingly the product and supply chain as well as end consumer of free products during the information revolution. This trend is surely temporary as it is absolutely unsustainable in any known form of economic model, thus extremely unwise and irresponsible. The question is not whether reforms will come, but rather in what form, when, at what cost, and type. Wars have been fought over much smaller economic tensions, which is one reason the current trajectory is so concerning to many of us.

10 Recommendations For Stronger Economy

While every era of economic crises has experienced serious policy errors, sometimes driven by self-interest and/or politics, and others genuinely well intended, a few strategies are timeless. Below are 10 examples that I think are wise, translated to today’s environment:

  1. Avoid moral hazard, as it tends to create the foundation for the next crisis. Never allow too big to fail, and if it occurs break them up ASAP. Any such event should be fatal not only to the companies involved, but the regulatory bodies that failed to prevent it. Saving failed institutions is extremely toxic to the rest of the economy, and it’s entirely unnecessary.

  2. Never ever tell an entrepreneur “you didn’t build that”, especially from a leader who has never done it, in which case he/she would almost certainly never say such a thing. Anyone who isn’t aware of the benefit of public infrastructure is unlikely to have much of a chance to build anything as our job is in part to find ways to build value on top of that public investment for job and wealth creation, which is apparently much more difficult than most are aware of. Most entrepreneurs take enormous risk and make huge personal sacrifices that few politicians, government workers, or corporate executives will ever comprehend. It is therefore a good idea to limit lectures to topics one has direct experience with and thus avoid doing great harm.

  3. Tie all public funding other than the genuinely disabled to a menu of contributions that align with taxpayers who fund it, whether vocational training, education, civic work, volunteer work, or best of all: subsidized on the job training. Germany has a good public/private program that provides a basic model, which encourages retaining employees in downturns while retraining. Permanent dependency on government is a terrible thing to do to anyone as it damages confidence, reduces self-worth, and is very self-destructive from a socio-economic (and any other I can think of at the moment) perspective.

  4. Stop rewarding toxic behavior to extent possible, including government, education, finance, and/or industry. For example, bankrupting government entities with life-long golden retirement parachutes is toxic and has nothing to do with public service or protecting legitimate worker rights. Indeed, public sector pensions tend to punish other workers in a variety of ways. It should be self-evident, but insolvent governments can’t make good on political promises, whether contractual or not. For mature economies, increasingly ‘the enemy is us’.

  5. Decentralize capitalism. Our era contains very strong natural and unnatural bias towards consolidation of power and wealth. Silicon Valley, Wall Street and London are examples of financial centers that have a long history of protecting local strategic and personal interests with OPM. Eventually this leads to economic collapse and/or can lead to war, which is directly opposed to beneficial capitalism that encourages diversification, meritocracy, and peace through mutually beneficial trade. To date Wall Street and SV have failed to self-regulate, as have their investors. We may have no choice but to regulate in order to prevent even more severe crises if the current financial consolidation trajectory persists. Financially engineered profitmaking is a completely different task requiring different skills than building durable industries. We need to decentralize back to regional centers with more focus on structural entrepreneurial economics.

  6. Keep politics out of investment, including partisanship & cronyism. That any politician would think they are qualified to understand the complexities involved with investing in technology is frankly a stunning demonstration of hubris. Whether corporate, public, or institutional investor executive, anyone spending most of their time in meetings, raising money, or other activity other than total immersion for decades couldn’t possibly be in a position to appreciate the challenge. Blunt macro instruments such as QE & slinging noodles against the VC wall do great harm to structurally sound economic growth; it just isn’t as visible at the macro level.

  7. Curtail strategic mandates by institutional investors. A form of politics in investment, especially PE/VC mandates, have proven to be among the most toxic brews for the global economy in the past few decades. The needs of a sustainable economy and markets should drive and reward investment, not the internal perceived needs of portfolio management. Often has been the case where a mandate in one arm of institutional investment shared by many others—like subprime mortgage—risks an entire fund, if not entire economy. Take each investment on its individual merit, including best attempt at understanding level of toxicity. Anyone who can’t should not be at decision levels at large funds.

  8. Stop creating monopolies. There is an old saying shared by many seasoned economists and entrepreneurs that states ‘monopolies can only exist with the assistance of government’, whether directly or indirectly. Very well understood is the unhealthy relationship between big government and big business. Attempts to recreate this wheel result in broken economies. Healthy economies require diversification, allowing both failure and success by customer choice rather than government force or corrupted political system.

  9. Do not play God. Power, wealth, and popularity does not necessarily equate to competence. Rather, it almost always leads to hubris, which is of course dangerous. The most effective leaders understand their weaknesses and can identify strengths in others. They do not surround themselves with those who share the same ideology, rather seek out contrarians and devil’s advocates in the decision making process. In economics the evidence is very clear: while unification and central governance on a few issues are necessary, the collective Main Street is far more intelligent and wise than corner offices on Wall St., Sand Hill Road, Capitol buildings, or the Oval Office. We need leaders in those positions who understand their own limitations and that of their roles.

  10. Prevent anarchists while building leaders. One program from the Great Depression that worked well that we still enjoy today was the Civilian Conservation Corp (CCC). Below is a short video on a youth conservation corps program in Idaho that serves as a good example of what could have been done on a much larger scale with stimulus funds, providing much needed life experience for millions of youths rather than wasting most of the money on political favors or fermenting disenfranchisement and anarchists. For heaven’s sake, let’s allow and encourage people to engage in the positive as an alternative to the many negative options that exist in our society today.

Transforming Healthcare With Data Physics

I just completed an in-depth paper on how our work and system can help life science and healthcare companies overcome the great challenges they face, so I wanted to share some thoughts while still fresh. The paper is part of our long-term commitment to healthcare and life sciences, requiring a deep dive over the past several weeks to update myself on the latest research in behavioral psychology, machine learning, deep learning, genetics, chemicals, diagnostics, economics, and particle physics, among others. The review included several hundred papers as well as a few dozen reports.

Kyield Distributed OS - Life Science and Healthcare

The good news is that the science is improving rapidly. An important catalyst to accelerated learning over the past 20 years has been embracing the multi-disciplinary approach, which academia resisted for many years despite the obvious benefits, but is now finally mainstream with positive impact everywhere one looks.

The bad news is that the economics of U.S. healthcare has not noticeably improved. For a considerable portion of the population it has deteriorated. The economic trajectory for the country is frankly grim unless we transform the entire healthcare ecosystem.

A common obstacle to vast improvement in healthcare outcomes that transcends all disciplines with enormous economic consequences is data management and analytics, or perhaps more accurately; the lack thereof. There is no doubt that unified networks must play a lead role in the transformation of healthcare. A few clips from the paper:

“By structural we mean the physics of data, including latency, entropy, compression, and security methodology. The Kyield system is intended to define structural integrity in NNs, continually exploring and working to improve upon state-of-the-art techniques.”

“While significant progress has been made with independent standards towards a more sustainable network economy, functionality varies considerably by technology, industry, and geography, with variety of data types and models remaining among the greatest obstacles to discovery, cost efficiency, performance, security, and personalization.”

Life science and healthcare are particularly impacted by heterogeneous data, which is one reason why networked healthcare is primitive, expensive, slow, and alarmingly prone to error.

“Biodiversity presents a unique challenge for data analytics due to its ambiguity, diversity, and specialized language, which then must be integrated with healthcare and data standards as well as a variety of proprietary vendor technology in database management systems, logistics, networking, productivity, and analytics programs.”

“Due to the complexity across LS and healthcare in data types, standards, scale, and regulatory requirements, a functional unified network OS requires specific combinations of the most advanced technology and methods available.”

Among the most difficult challenges facing management in mature life science companies are cultures that have been substantially insulated from economic reality for decades, only recently feeling the brunt of unsustainable economic modeling throughout the ecosystem, typically in the form of restructures, layoffs, and in some cases closure. This uncertainty particularly impacts individuals who are accustomed to career security and relatively high levels of compensation. I observed this often during a decade of consulting. The pain caused by a dysfunctional economic system is similar to the diseases professionals spend their careers fighting; often unjustly targeting individuals in a seemingly random manner, which of course has consequences.

“Among many changes for knowledge workers associated with the digital revolution and macro economics are less security, more free agency, more frequent job changes, much higher levels of global venture funding, less loyalty to corporate brands and mature industry models, and considerably increased motivation and activism towards personal passionate causes.”

Healthcare is a topic where I have personal passion as it cuts to the core of the most important issues to me, including family, friends, colleagues, and economics, which unfortunately in U.S. healthcare represents a highly self-destructive model. My brother was diagnosed with Lou Gehrig’s disease (amyotrophic lateral sclerosis/ALS) in 1997 not long after his only child was born. I’ll never forget that phone call with him or what he and his family endured over the next three years even though his case was a fine example of dedicated people and community. My father passed a decade later after a brutal battle with type 2 diabetes; we had an old friend pass from MS recently, and multiple cancers as well as epilepsy are ongoing within our small group of family and friends. So it would be foolhardy to deny the personal impact and interest. Healthcare affects us all whether we realize it or not, and increasingly, future generations are paying for the current generation’s unwillingness to achieve a sustainable trajectory. Unacceptable doesn’t quite capture the severity of this systemic failure we all own a part of.

The challenge as I see it is to channel our energy in a positive manner to transform the healthcare system with a laser focus on improved health and economic outcomes. This of course requires a focus on prevention, reduced complexity throughout the ecosystem, accelerated science, much improved technology, and last but not least; rational economic modeling to included increased competition. The latter will obviously require entirely new distribution systems and business models more aligned with current science and economic environment. Any significant progress must include highly evolved legislation reflecting far more empowerment of patients and dramatic improvement in fiscal discipline for the ultimate payer we call America while there is still time to manage the disease. If we continue to treat only the symptoms of healthcare in America it may well destroy the quality of life for the patient, if indeed the patient as we know it survives at all. This essentially represents my diagnosis.

A few of the 80 references I cited in the paper linked below are good sources to learn more:

Beyond borders: unlocking value. Biotechnology Industry Report 2014, EY

Dixon-Fyle, S., Ghandi, S., Pellathy, T., Spatharou, A., Changing patient behavior: the new frontier in healthcare value (2012). Health International, McKinsey & Company.

Thessen A., Cui H., Mozzherin D. Applications of Natural Language Processing in Biodiversity Science Adv Bioinformatics.

Top 10 Clinical Trial Failures of 2013. Genetic Engineering & Biotechnology News.

Begley, C.G., Ellis, L.M. (2012) Drug development: raise standards for preclinical cancer research. Nature 483 http://www.nature.com/nature/journal/v483/n7391/pdf/483531a.pdf

Cambria, E., and White, B. Jumping NLP curves: A review of natural language processing research. IEEE Computational Intelligence Magazine, 9:1–28, 2014.

Montgomery, M. Diabetes and the American Healthcare System. Kyield, Published online May 2010

All quotes above are mine from Kyield’s paper of 8-15-2014:

Unified Network Operating System
With Adaptive Data Management Tailored to Each Entity
Biotech, Pharmaceuticals, Healthcare, and Life Sciences

Complex Dynamics at the Confluence of Human and Artificial Intelligence

(This article was featured at Wired)

Fear of AI vs. the Ethic and Art of Creative Destruction

While it may be an interesting question whether the seasons are changing in artificial intelligence (AI), or to what extent the entertainment industry is herding pop culture, it may not have much to do with future reality. Given recent attention AI has received and the unique potential for misunderstanding, I thought a brief story from the trenches in the Land of Enchantment might shed some light.

The topic of AI recently came up at Santa Fe Institute (SFI) during a seminar by Hamid Benbrahim surrounding research in financial markets. Several senior scientists chimed in during Hamid’s talk representing computer science (CS), physics (2), neuroscience, biology, and philosophy, as well as several practioners with relevant experience. SFI is celebrating its 30th anniversary this year as a pioneer in complexity research where these very types of topics are explored, attracting leading thinkers worldwide.

Following the talk I continued to discuss financial reforms and technology with Daniel C. Dennett, who is an external professor at SFI. While known as an author and philosopher, Professor Dennett is also Co-Director of the Center for Cognitive Studies at Tufts University with extensive published works in CS and AI. Professor Dennett shared a personal case that provides historical and perhaps futuristic context involving a well-known computer scientist at a leading lab during the commercialization era of the World Wide Web. The scientist was apparently concerned with the potential negative impact on authors given the exponentially increasing mass of content, and I suspect also feared the network effect in certain types of consumer services that quickly result in winner-takes-all dominance.

Professor Dennett apparently attempted to reassure his colleague by pointing out that his concerns, while understandable, were likely unjustified for the mid-term as humans have a consistent history of adapting to technological change, as well as adapting technology to fill needs. In this case, Dennett envisioned the rise of specialty services that would find, filter, and presumably broker in some fashion the needs of reader and author. Traditional publishing may change even more radically than we’ve since observed, but services would rise, people and models would adapt.

One reason complexity attracts leading thinkers in science and business is the potential benefit across all areas of life and economy. The patterns and methods discovered in one field are increasingly applied to others in no small part due to collaboration, data sharing, and analytics. David Wolpert for example stated his reasoning for joining SFI part-time from LANL was a desire to work on more than one discipline simultaneously. Many others have reported similarly both for the potential impact from sharing knowledge between disciplines and the inherent challenge. I can certainly relate from my own work in applied complex adaptive systems, which at times seems as if God or Nature were teasing the ego of human intellect. Working with highly complex systems tends to be a humbling experience.

That is not to say, however, that humans are primitive or without power to alter our destiny. Our species did not come to dominate Earth due to ignorance or lack of skills, for better or worse. We are blessed with the ability to intentionally craft tools and systems not just for attention-getting nefariousness, but solving problems, and yes being compensated for doing so. Achieving improvement increasingly requires designs that reduce the undesirable impacts of complexity, which tend to accumulate as increased risk, cost, and difficulty.

Few informed observers claim that technological change is pain-free as disruptions and displacements occur, organizations do fail, and individuals do lose jobs, particularly in cultures that resist macro change rather than proactively adapt to changing conditions. That is after all the nature of creative destruction. Physics, regulations, and markets may allow us to control some aspects of technology, manage processes in others, and hopefully introduce simplicity, ease of use, and efficiency, but there is no escaping the tyranny of complexity, for even if society attempted to ban complexity, nature would not comply, nor would humans if history is any guide. The risk of catastrophic events from biological and human engineered threats would remain regardless. The challenge is to optimize the messy process to the best of our ability with elegant and effective solutions while preventing extreme volatility, catastrophic events, and as some of us intend—lead to a more sustainable, healthy planet.

2012 Kyield Enterprise UML Diagram - Human Skull

The dynamics involved with tech-led disruption are well understood to be generally beneficial to greater society, macroeconomics, and employment. Continual improvements with small disruptions are much less destructive and more beneficial than violent events that have occurred throughout history in reaction to extreme chronic imbalances. Diversification, competition, and churn are not only healthy, but essential to progress and ultimately survival. However, the messy task is made far more costly and painful than necessary, including to those most impacted, as entrenched cultures resist that which they should be embracing. Over time all manner of protectionist methods are employed to defend against change, essential disruption, or power erosion, eventually to include manipulation of the political process, which often has toxic and corrosive impacts. As I am writing this a description following a headline in The Wall Street Journal reads as follows:

 “Initiatives intended to help restrain soaring college costs are facing resistance from schools and from a bipartisan bloc of lawmakers looking to protect institutions in their districts.”

Reading this article reminded me of an interview with Ángel Cabrera, who I had the pleasure of getting to know when he was President of Thunderbird University, now in the same role at George Mason University. His view as I recall was that the reforms necessary in education were unlikely to come from within, and would require external disruptive competition. Regardless of role at the time, my experience has been similar. A majority of cultures fiercely resist change, typically agreeing only to reforms that benefit the interests of narrow groups with little concern for collective impact or macro needs. Yet society often looks to entrenched institutions for expertise, leadership, and decision power, despite obvious conflicts of interest, thus creating quite a dilemma for serious thinkers and doers. As structural barriers grow over time it becomes almost impossible to introduce new technology and systems regardless of need or merit. Any such scenario is directly opposed to proper governance policy, or what is understood to result in positive outcomes.

Consider then recent research demonstrating that resistance to change and patterns of human habit are caused in part by chemicals in the brain, and so we are left with an uncomfortable awareness that some cultures are almost certainly and increasingly knowingly exploiting fear and addiction to protect personal power and financial benefits that are often unsustainable, and eventually more harmful than tech-enabled adaptation to the very special interests they are charged with serving, not to mention the rest of society who would clearly benefit. This would seem to cross the line of motivation for change to civic duty to support those who appear to be offering the best emerging solutions to our greatest problems.

This situation of entrenched interests conflicting with the greater good provides the motivation for many involved with both basic and applied R&D, innovation, and business building. Most commonly associated with the culture of Silicon Valley, in fact the force for rational reforms and innovation has become quite global in recent years, although resistance to even the most obvious essential changes are still at times shockingly stubborn and effective.

Given these observations combined with awareness that survival of any organization or species requires adaptation to constantly changing conditions, one can perhaps see why I asked the following questions during various phases of our R&D:

Why not intentionally embrace continuous improvement and adaptation?

Why not tailor data consumption and analytics to the specific needs of each entity?

Why not prevent readily preventable crises?

Why not accelerate discoveries and attribute human capital more accurately and justly?

Why not rate, incentivize, and monetize mission-oriented knowledge?

The story I shared in conversation with Dan Dennett at SFI was timely and appropriate to this topic as philosophy not only deserves a seat at the table with AI, but also has contributed to many of the building blocks that make the technology possible, such as mathematics and data structures, among others.

The primary message I want to convey is that we all have a choice and responsibility as agents for positive change, and our actions impact the future, especially with AI systems. For example, given that AI has the capacity to significantly accelerate scientific discovery, improve health outcomes, and reduce crises, I have long believed ethics requires that we deploy the technology. However, given that we are also well aware that high unemployment levels are inhumane, contain considerable moral hazard, and risk for civil unrest, AI should be deployed surgically and with great care. I do not support wide deployment of AI for the primary purpose of replacing human workers. Rather, I have focused my R&D efforts on optimizing human capital and learning in the near-term. To the best of my awareness this is not only the most ethical path forward for AI systems, but is also good business strategy as I think the majority of decision makers in organizations are of similar mind on the issue.

In closing, from the perspective of an early advisor to very successful tech companies rather than inventor and founder of an AI system, I’d like to support the concerns of others. While we need to be cautious with spreading undue fear, it has become clear to me that some of the more informed warnings are not unjustified. Some highly competitive cultures particularly in IT engineering have demonstrated strong anti-human behavior, including companies I am close to who would I think quite probably not self-restrain actions based on ethics or macro social needs, regardless of evidence presented to them. In this regard they are no different than the protectionist cultures they would replace, and at least as dangerous. I strongly disagree with such extreme philosophies. I believe technology should be tapped to serve humans and other species, with exceptions reserved for contained areas such as defense and space research where humans are at risk, or in areas such as surgery where machine precision in some cases are superior to humans and therefore of service.

Many AI applications and systems are now sufficiently mature for adoption, the potential value and functionality are clearly unprecedented, and competitive pressures are such in most sectors that to not engage in emerging AI could well determine organizational fate in the not-too-distant future. The question then is not whether to deploy AI, or increasingly even when, but rather how, which, and with whom. About fifteen years ago during an intense learning curve I published a note in our network for global thought leaders that the philosophy of the architect is embedded in the code—it just often requires a qualified eye to see it. This is where problems in adoption of emerging technology often arise as those few who are qualified include a fair percentage of biased and conflicted individuals who don’t necessarily share a high priority for the best interest of the customer.

My advice to decision makers and chief influencers is to engage in AI, but choose your consultants, vendors, and partners very carefully.

Kyield Enterprise Description Converted to StratML

I just wanted to point to a nice conversion of our Kyield Enterprise description to Strategy Markup Language (StratML); an XML vocabulary and schema for strategic plans. The work was performed without solicitation over the weekend by Owen Ambur, Chair AIIM StratML & Co-Chair Emeritus xml.gov.

The human readable version (styled) of Kyield Enterprise in StratML can be viewed in browsers on Web here:

Book Review: “Artificial Cognitive Architectures”

“Artificial Cognitive Architectures”

James A. Crowder, John N. Carbone, Shelli A. Friess

Aficionados of artificial intelligence often fantasize, speculate, and debate the holy grail that is a fully autonomous artificial life form, yet rarely do we find a proposed architecture approaching a credible probability of success.  With “Artificial Cognitive Architectures”, Drs Crowder, Carbone and Friess have painstakingly pulled together many disparate pieces of the robot puzzle in sufficient form to convince this skeptic that a human-like robot is finally within the realm of achievement, even if still at the extreme outer bounds of applied systems.

The authors propose an architecture for a Synthetic system, which is an Evolving, Life Form (SELF):

A prerequisite for a SELF consciousness includes methodologies for perceiving its environment, take in available information, make sense out of it, filter it, add to internal consciousness, learn from it, and then act on it.

SELF mimics the human central nervous system through a highly specific set of integrated components within the proposed Artificial Cognitive Neural Framework (ACNF), which includes an Artificial Prefrontal Cortex (APC) that serves as the ‘mediator’. SELF achieves its intelligence through the use of Cognitrons, which are software programs that serve in this capacity as ‘subject matter experts’.  An artificial Occam abduction process is then tapped to help manage the ‘overall cognitive framework’ called ISAAC (Intelligent information Software Agents to facilitate Artificial Consciousness).

The system employs much of the spectrum across advanced computer science and engineering to achieve the desired results for SELF, reflecting extensive experience. Dr. Jim Crowder is Chief Engineer, Advanced Programs at Raytheon Intelligence and Information Systems. He was formerly Chief Ontologist at Raytheon which is where I first came across his work. Dr. John Carbone is also at Raytheon; a quick search will reveal many of his articles and patents in related areas. Dr. Shelli Friess is a cognitive psychologist; a discipline that until recently was rarely found associated with advanced computing architecture, even though mimicry of the human nervous system clearly calls for a deep transdisciplinary approach. For example, “Artificial Cognitive Architectures“ introduces  ‘acupressure’, ‘deep breathing’, ‘positive psychology’ and other techniques to SELF as proposed to become ‘a real-time, fully functioning, autonomous, self-actuating, self-analyzing, self-healing, fully reasoning and adapting system.’

While even the impassioned AI post-doc may experience acronym fatigue while consuming “Artificial Cognitive Architectures”, the 18 years of research behind the book with careful attention to descriptive terminology helps to minimize the confusion surrounding a topic that by necessity begins to take on the complexity of our species.

Serious students and practitioners of AI will find “Artificial Cognitive Architectures” particularly interesting for the broad systems approach, while most others with curiosity surrounding this topic will find the book technical but fascinating. Those searching for HAL 9000 will be delighted to see similar reasoning and emotions on display, while simultaneously disappointed to discover designed-in governance and security features that will hopefully prevent such Hollywood scenarios from occurring. The security design was apparently influenced by an actual entertaining case when an earlier version of intelligent agent developed for the U.S. government was inadvertently left plugged in by Dr. Crowder, resulting in a late night Instant Messaging exchange between a human colleague and a Cognitron slumber party of sorts.

Readers will find a more mature posture regarding policy and security than commonly found in popular AI culture, apparently reflecting the serious work of applying AI to missile and other systems at Raytheon.

I personally found the book refreshing as it overlaps much of my own work at the confluence of human-driven AI systems. I also share a concern for internal security as it appears inevitable that machines with even the most basic cognitive ability will immediately observe how irresponsible their organic brethren have conducted themselves as stewards of earth’s resources.

J.A. Crowder et al., Artificial Cognition Architectures
DOI 10.1007/978-1-4614-8072-3_5, © Springer Science+Business Media New York 2014

Why It Has Always Been, and Will Always Be — The Network of Entities

Physics won this debate before anyone had a vision that a computer network might someday exist, but biology played an essential role on the team.

The reason of course is that all living things, including humans and our organizations, are unique in the universe—for our purposes anyway—until that identical parallel universe is discovered. Even perfectly cloned robots cannot occupy the same time and place, so while quite similar a machine working directly adjacent to an otherwise identical clone may be electrocuted or run over by a forklift, and will then have much different needs.

More importantly to organic creatures like myself, our DNA while similar to others is not only unique, but our health and well being are influenced by a myriad of other factors as well, including nutrition, behavior, environment, and socioeconomics among others, the totality interaction of which we only partially understand. We do know, however, that our universe, our bodies and our brains are constantly changing with a set of factors at any one time that strongly favor an adaptive response—or in many cases proactive, certainly to include managing data and information.

While networks of things and of people certainly exist, it always has been and forever will be the Internet of entities, the individual make-up of which at any moment in time, including dynamic relationships, require humans and human organizations to manage the best we are able with the most accurate information available, increasingly for the foreseeable future by this human entity to include managing organizational entities, machine entities, and yes even sensory entities. This is why I created Kyield and designed the system that powers it in precisely the manner offered.

New Report: Adaptive Unification for Life Science Ecosystems

First, I want to apologize for not being able to keep up with my blog as much as I would like, or to share as much in public as I would prefer. The reasons are twofold. We’ve been very busy at Kyield, and testing has increasingly confirmed that while competitors in our industry invest heavily in web information (CI), most customers do not; at least for enterprise-wide systems like Kyield.  So I have regrettably pulled back on detailed public writing, or rather– have replaced with more formal papers and presentations with customers.

A good example of our efforts is the new report below, which is a hybrid of an academic paper with citations supporting our claims and a detailed brochure for senior managers in pharmaceuticals, biotech, and healthcare–particularly those pursuing personalized medicine and significant improvement in operational efficiency:

Adaptive Unification  for  Life Science  Ecosystems

Kyield report: Adaptive Unification for Life Science Ecosystems

The paper highlights the challenges facing the industry with considerable detail on how Kyield is unique in the world with respect to ability to overcome these challenges. Essentially, in order to overcome systemic challenges it requires a systemic solution, and in terms of distributed organizations it requires a very particular type of systemic solution that can address each of the challenges. Due to the high values involved, the result is that Kyield may well be the best investment option in the world today for life science executives.

For those who would prefer more frequent updates, the best methods to track either Kyield or my activity are as follows:

Connect with me on LinkedIn:      http://www.linkedin.com/in/markamontgomery/

Follow Kyield on LinkedIn:

Follow @kyield on Twitter:             https://twitter.com/kyield

And of course visit our web site regularly at www.kyield.com

Kind regards,

Mark Montgomery

Workplace analytics paper + our new PSN

I wanted to share a couple of quick items. One is an article on workplace analytics I just completed that may be of interest (PDF). While it deals with some of the most complex technical issues, the format is a short non-technical paper intended for senior business managers and boards, most of whom do not have a technical background yet must deal with organizational issues that are increasingly driven by technology.

The second item is that we’ve launched a global professional services network (PSN) surrounding Kyield technology. We currently have a recruitment running on LinkedIn for managing partners.  The PSN is progressing very well, keeping me very busy in discussions with highly qualified consultants worldwide. Our first group of countries have now moved through the initial stage and are engaging with client organizations. -MM

The ‘Sweet Spot of Big Data’ May Contain a Sour Surprise for Some

I’ve been observing a rather distasteful trend in big data for the enterprise market over the past 18 months that has reached the point of wanting to share some thoughts despite a growing mountain of other priorities.

As the big data hype grew over the past few years, much of which was enabled by Hadoop and other FOSS stacks, internal and external teams serving large companies have perfected a (sweet spot) model that is tailored to the environment and tech stack. Many vendors have also tailored their offerings for the model backed up with arguably too much funding by VCs, dozens too many analyst reports, and a half-dozen too many CIO publications attempting to extend reach and increase the ad spend.

The ‘sweet spot’ goes something like this:

  • Small teams consisting of data scientists and business analysts.
  • Employing exclusively low cost IT commodities and free and open source software (FOSS).
  • Targeting $1 to $5 million projects within units of mid to large sized enterprises.
  • Expensed in current budget cycle (opex), with low risk and high probability of quick, demonstratable ROI.

So what could possibility be wrong with this dessert—looks perfect, right? Well, not necessarily—at least for those of us who have viewed a similar movie many times previously, with a similar foreshadowing, plot, cast of characters, and story line.

While this service model and related technology has been a good thing generally, resulting in new efficiency, improved manufacturing processes, reduced inventories, and perhaps even saved a few lives, not to mention generated a lot of demand for data centers, cloud service providers and consultants, we need to look at the bigger picture in the context of historical trends in tech adoption and how such trends evolve to see where this trail will lead. Highly paid data scientists, for example, may then find that they have been frantically jumping from one project to the next inside a large bubble with a thin lining, rising high over an ecosystem with no safety net, and then suddenly find themselves a target of flying arrows from the very CFO who has been their client, and for good fundamental reasons.

As we’ve seen many times before at the confluence of technology and services, the beginning of an over-hyped trend creates demand for high-end talent that is unsustainable even often in the mid-term. Everyone from the largest vendors to emerging companies like Kyield to leading consulting firms and many independents alike are in general agreement that while service talent in big data analytics (and closely related) are capturing up to 90% of the budget in this ‘sweet spot’ model today, the trend is expected to reverse quickly as automated systems and tools mature. The reaction to such trends is often an attempt to create silos of various sorts, but even for those in global incumbents or models protected by unions and laws like K-12 in the U.S., it’s probably wise to seek a more sustainable model and ecosystem tailored for the future. Otherwise, I fear a great many talented people working with data will find in hindsight that they have been exploited for very short-term gain in a model that no longer has demand and may well find themselves competing with a global flood of bubble chasers willing to work cheaper than is even possible given the cost of living in their location.

What everyone should realize about the big data trend

While there will likely be strong demand for the very best mathematicians, data modelers, and statisticians far beyond the horizon, the super majority of organizations today are at some point in the journey of developing mid to long-term strategic plans for optimizing advanced analytics, including investments not just for small projects, but the entire organization. This is not occurring in a vacuum, but rather in conjunction with consultants, vendors, labs and emerging companies like ours that intentionally provide a platform that automates many of the redundant processes, enable plug and play, and make advanced analytics available to the workforce in a simple to use, substantially automated manner. While it took many years of R&D for all of the pieces to come together, the day has come when physics allows such systems to be deployed and so this trend is inevitable and indeed underway.

The current and future environment is not like the past when achieving a PhD in one decade will necessarily provide job demand in the next, unless like everyone else in society one can continue to grow, evolve and find ways to add value in a hyper competitive world. The challenges we face (collectively) in the future are great and so we cannot afford apathy or wide-spread cultures that are protecting the (unsustainable) past, but rather only those attempting to optimize the future.

In our system design, we embrace the independent app, data scientist, and algorithm, and recommend to customers that they do so as well—there is no substitute for individual creativity—and we simply must have systems that reflect this reality, but it needs to occur in a rationally planned manner that attacks the biggest problems facing organizations, and more broadly across society and the global economy.

The majority seem frankly misguided on the direction we are headed: the combination of data physics, hardware, organizational dynamics and economics requires us to automate much of this process in order to prevent the most dangerous systemic crises and to optimize discovery. It’s the right thing to do. I highly recommend to everyone in related fields to plan accordingly as these types of changes are occurring in half the time as a generation ago and the pace of change is still accelerating. At the end of the day, the job of analytics is to unleash the potential of customers and clients so that they can then create a sustainable economy and ecology.

On role and title of Chief Data Officer

I left an extensive comment on a discussion surrounding the role and title of Chief Data Officer (CDO) over at Forrester Blogs by Gene Leganza, so thought I would share it here on our own blog (below).

CDO reminds me of CKO more than CIO — and also suffers some of the same challenges as head of BI in the blog by Boris in the job description. Most of the arguments are valid until we take the entire organization into view and that’s where I see problems.

Anytime this discussion on a new officer comes up it tends to rise from the desires, need to have more influence in the org, and aspirations of the specialist (and their ecosystem) rather than the need of the organization. Similar to a strong EA for example, what typically matters is whether the CEO (and board) is competent or not, paying attention to how the organization functions or not, and whether the culture and relationships are collaborative, combative, or even apathetic.

Unfortunately, one impact we have observed with the CIO and a few CKOs was confusion over the title officer by the entire organization, including those holding the title, when they suddenly became obsessed with their own power rather than service to others. Whether BI, EA, or CKO, in some cases we observed quite strong individuals who were driving critical value to the organization, but reporting to an infrastructure CIO who didn’t understand much at all about business or organizations, or worse in a few cases simply concerned with protecting their own turf rather than the mission of the organization and customers.

Generally speaking I think it’s wise to allow the brand of the individual rise up in the organization based on functionality, knowledge, and contributions to the organization–rather than yet another title ending with officer. Indeed, often has been the case when a person with a more humble title has had more impact, even in aggressive and highly competitive cultures, particularly when they are wicked smart and wise.

One problem rarely discussed is that corporate officer in many companies has real meaning in terms of authority, responsibility and legal accountability whereas in most cases the job description title of officer does not, creating confusion internally and externally (I am thinking now of one giant tech company in particular where titles have been a disaster to everyone but the CEO who hands them out).

I personally prefer scientist over officer and I’m not terribly fond of scientist (except when used properly to describe a true scientist) due to the disconnect in meaning and culture between science and business that is too often manifest in organizational dysfunction. I see functional roles more of a master craft person who may lead a small team, but is more interested in the value of their work than career aspirations to one day become a CEO, or even to lead large numbers of people where internal and external politics tend to rule. In fact it’s been my experience that the strongest functional people do not have any desire to hold the title of officer.

So my fear based on previous experience and observations is that in the rare highly functional organization the role and title will also function well–regardless of what we call it, but in the norm it may do more harm than good, in which case the stronger professional will likely either avoid the organization to begin with or move on at the earliest opportunity. .02- MM

New Year Review 2013: The Importance of Triple Win Ecosystems

Kyield R&D Journey- 2012

Looking Back on 2012

Among the positive trends we observed in 2012 include relatively strong continued adoption of richly structured data across all major industry clusters. A significant portion of senior managers have just recently engaged in an attempt to seriously understand how best to optimize structured data for their organizations and partners, with an exceptional minority now experiencing big aha moments. Until recently semantics was limited primarily to R&D, and analytics was restricted to a very few people in the organization with a fairly limited scope. A growing minority are finally connecting the dots and incorporating semantics into their ‘big data’ analytics strategy.

We changed a few global strategic plans with our Kyield pilot presentations in the past year as organizations began to realize that what seemed futuristic a few years ago is now executable in near real-time. However, what is still missing is a competitive ecosystem that could be called upon to serve the specific needs of customers in a triple win manner.  As is often the case with emerging technologies– individuals, small teams and companies engage due to a combination of motivating factors that includes independence, compensation, and to change the world for the better, but in order to achieve much in the enterprise market we need fully functional ecosystems.

A combination of assets must be offered in a highly efficient and credible manner, including very experienced management, superior technology, deep technical talent, appropriate financial structure and professional services, which is usually far more than even the largest companies can provide on their own. So job one for the emerging semantic enterprise community is to learn how to work together towards building a functional ecosystem, which means creating and offering mutual value while serving customer needs in win/win/win scenarios.

We held discussions with a few companies interested in partnering who underestimate the risk they face and overestimate their power, some of whom apparently don’t understand how to form mutually beneficial partnerships. In Kyield’s partner program we will only consider triple wins. And BTW, don’t expect anything but obstacles thrown in the way from the trillion dollar global integration machine, which is a mature, highly sophisticated ecosystem with unlimited funds that is threatened by independent standards and lower TCO. Customers have a special responsibility to assist the emerging semantic ecosystem as they are the primary beneficiaries of the technology and have a very important strategic interest in helping to ensure that the semantic ecosystem becomes more viable and sustainable.

Expectations for 2013

An interesting event recently occurred at a leading bank that could be telling for the near future with respect to semantics and data standards in 2013 and beyond. The bank recently announced large layoffs that included 25% within IT. The bank previously invested heavily in internal proprietary systems and are now moving towards standards where they expect to see a significant ROI with speculation that other leading banks will follow. Banks were late to semantics and obviously some proved that their proprietary risk management and governance systems were systemically dangerous, but we’re seeing a positive trend now. These layoffs may sound like bad news, but we should remember that the primary role of leading banks is to lend modestly leveraged capital to others, which creates far more jobs in a more diverse manner than when employed internally at a bank for proprietary systems and integration work. This is an important trend toward higher efficiency in a more economically sustainable manner thanks largely to adoption of independent standards. When combined with proper governance and advanced analytics throughout the financial system, this trend can become powerful indeed.

The big question in 2013 more broadly is to what degree the EU and U.S. can get their long-term fiscal house in order. The macro economic environment can easily dominate technology adoption and business creation. There is a direct relationship between balanced federal budgets, job creation, and sustainable economic progress. Clearly the U.S. culture is in a deep state of denial relative to sustainable economics reflected in a severely dysfunctional political system, and it’s having a strong negative impact even for those who offer an exceptional ROI.  In the case of Kyield, for example, the macro environment has resulted in some customer prospects in otherwise strong organizations freezing new projects until political and fiscal uncertainty is resolved, which in turn of course deters any prudent entrepreneur, investor or other decision maker from taking risk that may have seemed rational in the past in a much different macro economic environment. Since those in the health management business of elephants don’t have the luxury of being trampled more than once, Kyield plans to continue with our lean organic hybrid approach in partnership with customers and partners and leave speculative build outs to those who enjoy rolling the dice.

I am confident that in 2013 we’ll see the competitive gap continue to widen between those who adopt more advanced, efficient, intelligent systems, and those who don’t, especially new systems that reduce lock-in and improve interoperability resulting in a sharply lower TCO. There is a strong compounding effect that occurs with adoption of rich data standards containing more integrity with advanced knowledge systems and real-time analytics, and it’s becoming increasingly more difficult to deny as organizations that master this technology pull ahead of competitors. Smart adaptive people working with smart adaptive computing is a powerful combination not to be denied.

To good health in 2013 for you, family and organization. – MM

Yield Management of Knowledge for Industry + FAQs

Industrial Yield Management of Knowledge from www.kyield.com

I may include a version of this diagram in a public white paper soon if I can carve out some writing time. If you don’t hear from me before then I wish you and your family a happy holiday season.

Kind regards, MM

Kyield Partner Program: An Ecosystem for the Present Generation

We’ve been in various discussions for the past couple of years with potential partners, finding many interests in the industry to be in direct conflict with the mission of the customer organizations. Most of our discussions reflect a generational change in technology underway that is being met with sharp internal divisions at incumbent market leaders that result in attempting to protect the past from the present and future. The situation is not new– it is very difficult for incumbent market leaders to voluntarily cannibalize highly profitable business models, particularly when doing so would threaten jobs, so historically disruptive technology has required new ecosystems (MS and Intel in the early 1980s, Google in the late 1990s, RIM, Apple app stores in the 2000s, etc.).

So due to the platform approach to Kyield and the disruptive nature of our technology to incumbent business models, and resistance to change in industry leaders–despite pressure from even their largest customers, we determined quite some time ago that it may require building a new ecosystem based on the Kyield platform, data standards and interoperability. The driving need is not just about the enormous sum of money being charged for unproductive functionality like lock-in, maintenance fees, and unnecessary software integration–although this is an ever-increasing problem for customers, or even commoditization and lack of competitive advantage–also a very serious problem, rather as is often the case it comes down to a combination of complexity, math and physics.

Not only is it not economically viable to optimize network computing in the neural network economy based on legacy business models, but we cannot physically prevent systemic crises, dramatically improve productivity, and/or expedite discovery in a manner that doesn’t bankrupt a good portion of the economy without data standards and seamless interoperability. In addition, we do need deep intelligence on each entity as envisioned in the semantic web in order to overcome many of our greatest challenges, to execute advanced analytics, and to manage ‘big data’ in a rational manner, but we also need to protect privacy, data assets, knowledge capital and property rights while improving security. Standards may be voluntary, but overcoming these challenges isn’t.

So we’ve been working on a new partner program for Kyield in conjunction with our pilot phase in attempt to reach out to prospective partners who may not be on our radar that would make great partners and work with us to build a new ecosystem based not on protecting the past or current management at incumbent firms, but rather the future by optimizing the present capabilities and opportunities surrounding our system.  We hope to collectively create a great many more new jobs than we could possibly do on our own in the process–not just in our ecosystem, but importantly for customer ecosystems.

We’ve decided for now on five different types of partner relationships that are intended to best meet the needs of customers, partners, and Kyield:

  • Consulting
  • Technology
  • Platform
  • Strategic
  • Master

For more information on our partner program, please visit:

Thank you,

Mark Montgomery
Founder, Kyield

Converting the Enterprise to an Adaptive Neural Network

Those tracking business and financial news may have observed that a little bit of knowledge in the corner office about enterprise architecture, software, and data can cause great harm, including for the occupant, often resulting in a moving van parked under the corner suite of corporate headquarters shortly after headlines on their latest preventable crisis. Exploitation of ignorance in the board room surrounding enterprise computing has become mastered by some, and is therefore among the greatest of many challenges for emerging technology that has the capacity for significant improvement.

The issues surrounding neural networks requires total immersion for extended duration. Since many organizations lack the luxury of time, let’s get to it.

Beware the Foreshadow of the Black Swan

A recent article by Reuters confirms what is perhaps the worst kept secret in the post printing press era: Many Wall Street executives say wrongdoing is necessary: survey. A whopping 25% of those surveyed believe that in order to be personally successful, they must conduct themselves in an unethical manner to include breaking important laws, some of which are intended to defend against contagion; a powerful red flag warning even if only partially true.

This reminds me of a situation almost a decade ago when I had the unpleasant task of engaging the president of a leading university about one of their finance professors who may have been addressing a few respondents to this very survey when he lectured: “if you want to survive in finance, forget ethics”. Unfortunately for everyone else, even if that curriculum served the near-term interests of the students, which is doubtful given what has transpired since, it cannot end well for civilization. Fortunately, in this case the university president responded immediately, and well beyond expectation, after I sent an email stating that I would end my relationship with the university if that philosophy was shared by the institution.

For directors, CEOs, CFOs, and CROs in any sector, this latest story should only confirm that if an individual is willing to risk a felony for his/her success, then experience warns that corporate governance rates very low on their list of priorities. Black Swan events should therefore be expected in such an environment, and so everything possible should be planned and executed to prevent them, which requires mastering neural networks.

Functional Governance: As simple as possible; as complex as necessary

Functional governance and crisis prevention in the modern complex organization requires deep understanding of the organizational dynamics embedded within data architecture found throughout the far more complex environment of enterprise networks and all interconnected networks.

Kyield Enterprise Diagram 2.7 (protected by Copyright and U.S. Patent)

Are you thinking what I think you may be thinking about now? In fact adaptive neural networks in a large enterprise is quite comparable to the complexity found in brain surgery or rocket science, and in some environments even more so. The largest enterprise neural networks today far outnumber comparable nodes, information exchanges, and memory of even the most exceptional human neurological system. Of course biological systems are self-contained with far more embedded intelligence that adapt to an amazing variety of change, which usually enables sustainability throughout a complete lifecycle—our lives, with little or no external effort required. Unfortunately, even the most advanced enterprise neural networks today are still primitive by comparison to biological systems, are not adaptive by design, and are subject to a menagerie of internal and external influences that directly conflict with the future health of the patient, aka the mission of the organization.

So the next question might be, where do we start?

The simple answer is that most organizations started decades ago with the emergence of computer networking and currently manage a very primitive, fragmented neural network that wasn’t planned at all, but rather evolved in an incremental manner where proprietary standards became commoditized and lost the ability to provide competitive differentiation, yet are still very expensive to maintain. Those needing a more competitive architecture have come to the right place at the right time as we are deeply engaged in crafting tailored action plans for several organizations at various stages of our pilot program for Kyield enterprise, which is among the best examples of a state-of-the-art, adaptive enterprise neural network architecture I am aware of. We’ve recently engaged with large to very large organizations in banking, insurance, biotech, government, manufacturing, telecommunications, engineering and pharmaceuticals in the early stages of our pilot process.

Tailored Blueprint

Think of the plan as a combination of a technical paper, a deeply tailored use case for each organization, and a detailed time-line spanning several years. In some ways it serves as sort of a redevelopment blueprint for a neighborhood that has been locked-in to ancient infrastructure with outdated electrical, plumbing, and transportation systems that are no longer compatible or competitive. Most have either suffered a crisis, or wisely intent on prevention, while seeking a significant competitive advantage.

The step-by-step process we are tailoring for each customer serves to guide collaborative teams through the conversion process from the ‘current architecture’ to an ‘adaptable neural enterprise network’, starting with the appropriate business unit and extending throughout subsidiaries over weeks, months and years in careful orchestration according to the prioritized needs of each while preventing operational disruptions. Since we embrace independent standards with no lock-in or maintenance fees and offer attractive long-term incentives, the risk for not engaging in our pilot program appears much greater than for those who do. In some cases it looks like we may be able to decrease TCO substantially despite generational improvement in functionality.

Those who are interested and believe they may be a good candidate for our pilot program are welcome to contact me anytime.