This brief essay, originated by the work on the Neuromorphics Lab in the DARPA SyNAPSE project, describes our early effort in the study of alternative computing schemes that will make use of massive memristive-based devices coupled with low-power CMOS processes to efficiently compute neural activation and learning in novel computing devices. The answer was to couple fuzzy inference with dense memristive memory. This combination can provide extensive power and silicon real estate savings while maintaining a high degree of accuracy in the resulting precision of the computations. Read the rest of this entry »
August 9, 2011|
December 5, 2010|
The online version of the IEEE Spectrum article describing our work on the MoNETA project (withing the DARPA SyNAPSE grant) has been out for a bit more than a week, and the story is starting to generate many comments and being picked up by blogs and magazines (see Slashdot and Popular Science). May be it's time to summarize what is happening, and starting to address the many comments related to the article. Ben and I will start a series of posts on the topic, this one being the first. Read the rest of this entry »
November 19, 2009|
IEEE Spectrum has published an interesting article titled "IBM Unveils a New Brain Simulator: A big step forward in a project that aims for thinking chips". The post describes IBM’s Almaden Research Center latest simulation effort announced at the Supercomputing Conference (SC09), where they unveiled that "that they have created the largest brain simulation to date on a supercomputer. The number of neurons and synapses in the simulation exceed those in a cat’s brain; previous simulations have reached only the level of mouse and rat brains." Read the rest of this entry »
July 16, 2009|
A recent article on the WSJ (In Search for Intelligence, a Silicon Brain Twitches) reviews the Blue Brain project based at the École Polytechnique Fédérale de Lausanne in Switzerland. The Blue Brian project, led for the last four years by Henry Markram, has focused in building a biologically accurate rat cortical column. Read the rest of this entry »
July 8, 2009|
Justin Mullins is the author of a nice post on the Memristor, appeard on 7/8/2009 on New Scientist. It does a nice job in describing the story of the memristor, from his theoretical discovery in 1971 by Leon Chua at the University of California, Berkeley, to his utilization by Stan Williams and Greg Snider at the HP Labs in Palo Alto, to the implementation of neural models, which involves the department that hosts the Neurdons!... Read the rest of this entry »
February 4, 2009|
In december 2008, a video post has been published on Abovetopsecret.com with the title “DARPA & IBM building a “global brain” “cognitive computer” for “monitoring people”. In this video, the leader of the IBM SyNAPSE project, Dharmendra Modha, talks about SyNAPSE.
January 26, 2009|
Dharmendra S Modha is the Principal Investigator in one of the three DARPA SyNAPSE grants, the one awarded to IBM. Modha is the Manager of the Cognitive Computing facility at IBM. Here is the full article from his blog.
December 2, 2008|
Making Computers Based on the Human Brain
How the biology of gray matter is having an increasing influence on computer design
November 27, 2008|
Dr. Snider and his colleagues at HP have built an integrated hybrid circuit with both transistors and memristors. Memristor crossbars are a very promising technology that can ultimately lead to building very dense hybrid chips, several times denser than synapses in the human cortex. Also, memristors have shown the potential to mimic the learning functions of synapses in neural networks. Memristors will the key technology that HP and its academic partner, Boston University, will leverage in the SyNAPSE grant.
November 23, 2008|
On November 20, 2008, the NY Times has published a short article entitled "Hunting for a Brainy Computer". Steve Lohr interviews the leader of the IBM team. IBM's Blue Gene has been used to simulate large-scale neural models (see the Blue Brain Project, led by Henry Markram). However, it is easy to mix supercomputers, IBM, and SyNAPSE in a big pot, thinking that they are the same. In reality, the Blue Gene is the example of how not to simulate the brain. This machine, as large as a room, whose power consumption is the same as the sum of the brains of a small city, can barely simulate a cortical column. As this article does not stress much (unlike other cited in this blog), the hardware problem will be solved (hopefully) by nanotechnologies, in particular by porting to nano the immense number of synapses that will link the millions of neurons implemented in the chip. No comment on "Dorothy looking for the Wizard of Oz" and "Want a really intelligent digital assistant"... It is worth mentioning that even with a chip twice the density and half the power consumption that the one SyNAPSE seeks to have in seven years available TODAY in the hands of the best modelers in the world, it is hard to think that we have the necessary modeling skills to implement that is suggested below.