NVIDIA Unveils ‘Mega’ Omniverse Blueprint for Building Industrial Robot Fleet Digital Twins

According to Gartner, the worldwide end-user spending on all IT products for 2024 was $5 trillion. This industry is built on a computing fabric of electrons, is fully software-defined, accelerated — and now generative AI-enabled. While huge, it’s a fraction of the larger physical industrial market that relies on the movement of atoms.
Today’s 10 million factories, nearly 200,000 warehouses and 40 million miles of highways form the “computing” fabric of our physical world. But that vast network of production facilities and distribution centers is still laboriously and manually designed, operated and optimized.
In warehousing and distribution, operators face highly complex
decision optimization
problems — matrices of variables and interdependencies across human workers, robotic and agentic systems and equipment. Unlike the IT industry, the physical industrial market is still waiting for its own software-defined moment.
That moment is coming.
Choreographed integration of human workers, robotic and agentic systems and equipment in a facility digital twin. Image courtesy of Accenture, KION Group.
NVIDIA today at CES announced “Mega,” an Omniverse Blueprint for developing, testing and optimizing physical AI and robot fleets at scale in a digital twin before deployment into real-world facilities.
Advanced warehouses and factories use fleets of hundreds of autonomous mobile robots, robotic arm manipulators and
humanoids
working alongside people. With implementations of increasingly complex systems of sensor and robot autonomy, it requires coordinated
training in simulation
to optimize operations, help ensure safety and avoid disruptions.
Mega offers enterprises a reference architecture of NVIDIA accelerated computing, AI,
NVIDIA Isaac
and
NVIDIA Omniverse
technologies to develop and test
digital twins
for testing AI-powered robot brains that drive robots,
video analytics AI agents
, equipment and more for handling enormous complexity and scale. The new framework brings software-defined capabilities to physical facilities, enabling continuous development, testing, optimization and deployment.
Developing AI Brains With World Simulator for Autonomous Orchestration
With Mega-driven digital twins, including a world simulator that coordinates all robot activities and sensor data, enterprises can continuously update facility robot brains for intelligent routes and tasks for operational efficiencies.
The blueprint uses
Omniverse Cloud Sensor RTX APIs
that enable robotics developers to render sensor data from any type of intelligent machine in the factory, simultaneously, for high-fidelity large-scale
sensor simulation
. This allows robots to be tested in an infinite number of scenarios within the digital twin, using
synthetic data
in a software-in–the-loop pipeline with
NVIDIA Isaac ROS
.
Operational efficiency is gained with sensor simulation. Image courtesy of Accenture, KION Group.
Supply chain solutions company KION Group
is collaborating
with
Accenture
and NVIDIA as the first to adopt Mega for optimizing operations in retail, consumer packaged goods, parcel services and more.
Jensen Huang, founder and CEO of NVIDIA, offered a glimpse into the future of this collaboration on stage at CES, demonstrating how enterprises can navigate a complex web of decisions using the Mega Omniverse Blueprint.
“At KION, we leverage AI-driven solutions as an integral part of our strategy to optimize our customers’ supply chains and increase their productivity,” said Rob Smith, CEO of KION GROUP AG. “With NVIDIA’s AI leadership and Accenture’s expertise in digital technologies, we are reinventing warehouse automation. Bringing these strong partners together, we are creating a vision for future warehouses that are part of a smart agile system, evolve with the world around them and can handle nearly any supply chain challenge.”
Creating Operational Efficiencies With Mega Omniverse Blueprint
Creating operational efficiencies, KION and Accenture are embracing the Mega Omniverse Blueprint to build next-generation supply chains for KION and its customers. KION can capture and digitalize a warehouse digital twin in Omniverse by using computer-aided design files, video, lidar, image and AI-generated data.
KION uses the Omniverse digital twin as a virtual training and testing environment for its industrial AI’s robot brains, powered by NVIDIA Isaac, tapping into smart cameras, forklifts, robotic equipment and digital humans. Integrating the Omniverse digital twin, KION’s warehouse management software can create and assign missions for robot brains, like moving a load from one place to another.
Graphical data is easily introduced into the Omniverse viewport showcasing productivity and throughput among other desired metrics. Image courtesy of Accenture, KION Group.
These simulated robots can carry out tasks by perceiving and reasoning in environments, and they’re capable of planning next motions and then taking actions that are simulated in the digital twin. The robot brains perceive the results deciding the next action, and this cycle continues with Mega precisely tracking the state and position of all the assets in the digital twin.
Delivering Services With Mega for Facilities Everywhere
Accenture, global leader in professional services, is adopting Mega as part of its AI Refinery for Simulation and Robotics, built on NVIDIA AI and Omniverse, to help organizations use AI simulation to reinvent factory and warehouse design and ongoing operations.
With the blueprint, Accenture is delivering new services — including Custom Robotics and Manufacturing Foundation Model Training and Finetuning; Intelligent Humanoid Robotics; and AI-Powered Industrial Manufacturing and Logistics Simulation and Optimization — to expand the power of physical AI and  simulation to the world’s factories and warehouse operators.  Now, for example, an organization can explore numerous options for their warehouse before choosing and implementing the best one.
“As organizations enter the age of industrial AI, we are helping them use AI-powered simulation and autonomous robots to reinvent the process of designing new facilities and optimizing existing operations,” said Julie Sweet, chair and CEO of Accenture. “Our collaboration with NVIDIA and KION will help our clients plan their operations in digital twins, where they can run hundreds of options and quickly select the best for current or changing market conditions, such as seasonal market demand or workforce availability.  This represents a new frontier of value for our clients to achieve using technology, data and AI.”
Join
NVIDIA at CES
.
See
notice
regarding software product information.
Categories:
Corporate
|
Robotics
Tags:
CES 2025
|
Metropolis
|
NVIDIA Isaac Sim
|
Omniverse

據資訊科技研究顧問公司 Gartner 指出，2024 年全球終端用戶在所有 IT 產品上的支出為五兆美元。這個產業建構在電子運算結構的基礎上，完全由軟體定義及加速，現在開始由生成式AI賦能。這個產業的規模雖然龐大，卻也只是依賴原子移動之大型實體工業市場的一小部分。
現下的一千萬間工廠、將近 20 萬個倉庫和 4,000 萬英哩長的高速公路，構成了我們實體世界的「運算」結構。這個由生產設施和配送中心組成的龐大網路，仍然是由人工進行設計、營運和最佳化的。
在倉儲和配送過程中，作業人員面臨著錯綜複雜的
決策最佳化
問題：變數矩陣還有人類工作者、機器人和代理系統及設備之間的相互依存關係。與 IT 產業不同的是，實體工業市場仍在等待自己的軟體定義時刻。
而這個時刻即將來臨。
在設施的數位孿生模型中，精心將人類工作者、機器人和代理系統與設備進行分工整合。圖片來源：Accenture、KION Group。
NVIDIA 今日在 CES 大會發表「Mega」，一個用於先在數位孿生模型中大規模開發、測試和最佳化實體 AI 與機器人機隊，再部署到實際設施的 Omniverse Blueprint。
先進的倉庫和工廠使用由數百個自主移動機器人、機械手臂和
人型
機器人組成的機隊，與人類一起工作。隨著感測器和機器人自駕系統越來越複雜，需要
在模擬環境裡進行協調訓練
，以最佳化營運，幫助確保安全和避免作業中斷。
Mega 為企業提供 NVIDIA 加速運算、AI、
NVIDIA Isaac
及
NVIDIA Omniverse
技術的參考架構，以開發和測試
數位孿生
，用於測試驅動機器人、
影片分析 AI 代理
、設備等的 AI 驅動機器人大腦，以處理這些極為複雜又規模龐大的作業。新框架可為實體設施帶來軟體定義的功能，以持續進行開發、測試、最佳化與部署等作業。
利用世界模擬器開發
AI
大腦，以進行自主協調
透過使用由 Mega 驅動的數位孿生，當中包括協調所有機器人活動和感測器資料的世界模擬器，企業可以持續更新設施的機器人大腦，以聰明地規畫行進路線和執行任務，提高運作效率。
這個藍圖使用
Omniverse Cloud
Sensor RTX
API
，使機器人開發人員能夠同時渲染來自工廠中任何類型智慧機器的感測器資料，以進行極為逼真的大規模感測器模擬。這麼一來便能使用
NVIDIA Isaac ROS
軟體在軟體迴路（SIL）管道中的
合成資料
，在數位孿生內產生不限數量的情境中進行測試機器人。
採用感測器模擬方式提高運作效率。圖片來源：Accenture、KION Group。
供應鏈解決方案公司凱傲集團（KION Group）與埃森哲（Accenture）及 NVIDIA 合作，率先採用 Mega 來改善零售、消費品、包裹服務等領域的營運。
NVIDIA 創辦人暨執行長黃仁勳在 CES 大會的舞台上展現這項合作的未來，介紹企業如何利用 Mega Omniverse Blueprint 駕馭複雜的決策網路。
凱傲集團執行長 Rob Smith 表示：「凱傲集團運用 AI 驅動的解決方案，將其視為完善客戶供應鏈與提高生產力策略不可或缺的一環。憑藉 NVIDIA 在 AI 方面的領導地位以及埃森哲在數位科技方面的專業知識，我們正在重塑倉儲自動化。與這些強大的夥伴攜手合作，我們正在創造未來倉庫的發展願景，這些倉庫是智慧敏捷系統的一部分，與身旁周遭的世界一同演進，幾乎可以處理任何供應鏈的挑戰。」
使用
Mega Omniverse Blueprint
創造運作效率
凱傲集團與埃森哲採用 Mega Omniverse Blueprint 為凱傲集團及其客戶建立下一代供應鏈，以提高運作效率。凱傲集團可以透過使用電腦輔助設計檔案、影片、光達、圖像和 AI 生成的資料，在 Omniverse 中捕捉和數位化一個倉庫的數位孿生。
在 NVIDIA Isaac 的驅動下，凱傲集團使用 Omniverse 數位孿生作為其工業 AI 機器人大腦的虛擬訓練和測試環境，利用智慧攝影機、推高機、機器人設備和數位人類。凱傲集團的倉儲管理軟體結合 Omniverse 數位孿生模型，可以為機器人大腦建立和分配任務，例如將貨物從一處搬到另一處。
可以輕鬆將圖形資料導入 Omniverse 視窗，展示生產力和處理量等其他所需的指標。圖片來源：Accenture、KION Group。
這些模擬出的機器人能夠感知環境及進行推理來執行任務，並且能夠規畫下一個動作，然後採取在數位孿生中模擬出的行動。機器人的大腦會感知結果以決定下一步的動作，而 Mega 會精確追蹤數位孿生中所有資產的狀態和位置，如此循環不息。
透過
Mega
為各地設施提供服務
全球專業服務領導廠商埃森哲採用 Mega，作為該公司以 NVIDIA AI 和 Omniverse 為基礎所開發出 AI Refinery for Simulation and Robotics 產品的一部分，協助企業利用 AI 模擬重塑工廠和倉庫的設計與持續經營。
埃森哲將透過這個藍圖提供新的服務，包括客製化機器人與製造基礎模型訓練與微調、智慧人型機器人，以及 AI 驅動的工業製造與物流模擬與最佳化，旨在將物理 AI 和模擬的強大功能擴展到全球的工廠和倉庫營運商。例如，現在一家企業可以在選擇並實施最佳方案之前，探索倉庫的多種選擇。
埃森哲董事長暨執行長 Julie Sweet 表示：「隨著企業進入工業 AI 時代，我們正幫助他們使用 AI 驅動的模擬和自主機器人，重塑設計新設施的流程和最佳化現有營運。我們與 NVIDIA 及凱傲集團合作，將協助客戶在數位孿生中規畫營運活動，客戶可以在數位孿生中運行上百種選擇內容，按照當前或不斷變化的市場情況（如季節性市場需求或勞動力可用性）快速選擇最佳方案。這代表著我們的客戶利用科技、資料和 AI 實現價值的新前沿。」
請見有關軟體產品資訊的
通知
。
Categories:
企業端
|
自主機器
Tags:
CES 2025
|
NVIDIA Isaac Sim
|
Omniverse


Madison Huang Author Page | NVIDIA Blog
Skip to content
Artificial Intelligence Computing Leadership from NVIDIA
Search for:
Toggle Search
Home
AI
Data Center
Driving
Gaming
Pro Graphics
Robotics
Healthcare
Startups
AI Podcast
NVIDIA Life
Most Popular
Animals Crossing: AI Helps Protect Wildlife Across the Globe
CUDA Accelerated: How CUDA Libraries Bolster Cybersecurity With AI
Agentic AI Leaders to Showcase Latest Advancements at NVIDIA GTC
Telenor Builds Norway’s First AI Factory, Offering Sustainable and Sovereign Data Processing
March Into Gaming With GeForce NOW’s 14 Must-Play Titles for Spring
Corporate Information
About NVIDIA
Corporate Overview
Technologies
NVIDIA Research
Investors
Social Responsibility
NVIDIA Foundation
Get Involved
Forums
Careers
Developer Home
Join the Developer Program
NVIDIA Partner Network
NVIDIA Inception
Resources for Venture Capitalists
Venture Capital (NVentures)
Technical Training
Training for IT Professionals
Professional Services for Data Science
News & Events
Newsroom
NVIDIA Blog
NVIDIA Technical Blog
Webinars
Stay Informed
Events Calendar
NVIDIA GTC
NVIDIA On-Demand
Explore our regional blogs and other social networks
Privacy Policy
Manage My Privacy
Legal
Accessibility
Product Security
Contact
Copyright © 2025 NVIDIA Corporation
USA - United States
Share This
Facebook
LinkedIn
Email
Share on Mastodon
Enter your Mastodon instance URL (optional)
Share

Madison Huang， 作者 NVIDIA 台灣官方部落格
Skip to content
Artificial Intelligence Computing Leadership from NVIDIA
搜尋關鍵字:
Toggle Search
平台
智慧機器
概覽
JETSON
嵌入式系統
機器人
JETSON
資料中心
產品
資料中心 GPU
DGX
HGX
EGX
NGC
虛擬 GPU
解決方案
人工智慧與深度學習
高效能計算
虛擬 GPU
分析
應用範例
開發者
技術
CUDA-X
NVIDIA AMPERE 架構
NVIDIA VOLTA
MAGNUM
多執行個體 GPU
NVIDIA NVLINK
深度學習與人工智慧
概覽
產業
概覽
自動駕駛
醫療保健與生命科學
AI 城市
機器人
開發者
產品
概覽
DGX 系統
NVIDIA GPU 雲
NVIDIA TITAN RTX
NVIDIA TITAN V
解決方案
概覽
數據科學
推論
教育課程
AI 新創
設計視覺化
概覽
GRID
QUADRO
高階渲染技術
專業的虛擬實境解決方案
技術
NVIDIA RTX
NVLINK
TURING 架構
虛擬 GPU 技術
HOLODECK
創作者適用的
醫療保健與生命科學
概覽
給開發者
醫療圖像處理
基因體學
自動駕駛汽車
概覽
DRIVE PX
汽車產業夥伴
遊戲與娛樂
GEFORCE 遊戲平台
概覽
20 系列顯示卡
16 系列顯示卡
電競筆記型電腦
G-SYNC 顯示器
給創作者
開發者
NVIDIA 開發者
開發者新聞
開發者部落格
開發者論壇
開源平台
深度學習機構
訓練課程
GPU 科技大會
CUDA
產業
遊戲開發
醫療保健與生技
高等教育
製造業
媒體娛樂
公共部門
零售業
智慧城市
超級運算
電信業
運輸業
所有產業
驅動程式
概覽
GEFORCE 驅動程式
所有 NVIDIA 驅動程式
支援
關於 NVIDIA
概覽
NVIDIA 合作夥伴網絡
AI 運算模型
公司訊息
徵才訊息
投資人
NVIDIA 合作夥伴
NVIDIA 部落格
加入我們
RSS Feeds
訂閱電子報
聯繫我們
產品安全
Madison Huang
NVIDIA 發表「Mega」Omniverse Blueprint，打造工業機器人機群數位孿生
據資訊科技研究顧問公司 Gartner 指出，2024 年全…
閱讀文章
鴻海科技集團在美國、墨西哥和台灣設立新工廠，擴大 Blackwell 測試和生產
為了滿足目前已全面投產的 Blackwell 的需求，全球最…
閱讀文章
日本市場創新者利用 NVIDIA AI 與 Omniverse 將實體 AI 應用於各產業
豐田汽車（Toyota）工廠裡的機器人搬運著重金屬材料。安川…
閱讀文章
三部電腦解決方案：驅動下一波 AI 機器人
ChatGPT 象徵生成式 AI 的大爆炸時刻。幾乎可以針對…
閱讀文章
鴻海科技集團使用 NVIDIA 人工智慧與 Omniverse 技術訓練機器人及簡化組裝作業
鴻海科技集團在世界各地經營著超過 170 處工廠，其中最新的…
閱讀文章
平台
人工智慧與深度學習
智慧機器
資料中心
設計視覺化
醫療保健
自動駕駛
GeForce 遊戲
SHIELD
產品
DGX-1
DRIVE PX2
GeForce GTX 20 系列
GRID
Jetson
Quadro
SHIELD TV
Tesla
開發者
開發者專區
CUDA
訓練課程
GPU 科技大會
探究地區性部落格及其他社交網路
隱私權政策
管理我的隱私
請勿出售或分享我的資料
服務條款
輔助使用
公司政策
產品安全
聯絡方式
Copyright © 2025 NVIDIA Corporation
Taiwan


NVIDIA Launches DRIVE AI Systems Inspection Lab, Achieves New Industry Safety Milestones

A new NVIDIA DRIVE AI Systems Inspection Lab will help automotive ecosystem partners navigate evolving industry standards for autonomous vehicle safety.
The lab, launched today, will focus on inspecting and verifying that automotive partner software and systems on the
NVIDIA DRIVE AGX
platform meet the automotive industry’s stringent safety and cybersecurity standards, including AI functional safety.
The lab has been accredited by the ANSI National Accreditation Board (
ANAB
) according to the ISO/IEC 17020 assessment for standards, including:
Functional safety (ISO 26262)
SOTIF (ISO 21448)
Cybersecurity (ISO 21434)
UN-R regulations, including UN-R 79, UN-R 13-H, UN-R 152, UN-R 155, UN-R 157 and UN-R 171
AI functional safety (ISO PAS 8800 and ISO/IEC TR 5469)
“The launch of this new lab will help partners in the global automotive ecosystem create safe, reliable autonomous driving technology,” said Ali Kani, vice president of automotive at NVIDIA. “With accreditation by ANAB, the lab will carry out an inspection plan that combines functional safety, cybersecurity and AI — bolstering adherence to the industry’s safety standards.”
“ANAB is proud to be the accreditation body for the NVIDIA DRIVE AI Systems Inspection Lab,” said R. Douglas Leonard Jr., executive director of ANAB. “NVIDIA’s comprehensive evaluation verifies the demonstration of competence and compliance with internationally recognized standards, helping ensure that DRIVE ecosystem partners meet the highest benchmarks for functional safety, cybersecurity and AI integration.”
The new lab builds on NVIDIA’s ongoing safety compliance work with Mercedes-Benz and JLR. Inaugural participants in the lab include Continental and Sony SSS-America.
“We are pleased to participate in the newly launched NVIDIA Drive AI Systems Inspection Lab and to further intensify the fruitful, ongoing collaboration between our two companies,” said Nobert Hammerschmidt, head of components business at Continental.
“Self-driving vehicles have the capability to significantly enhance safety on roads,” said Marius Evensen, head of automotive image sensors at Sony SSS-America. “We look forward to working with NVIDIA’s DRIVE AI Systems Inspection Lab to help us deliver the highest levels of safety to our customers.”
“Compliance with functional safety, SOTIF and cybersecurity is particularly challenging for complex systems such as AI-based autonomous vehicles,” said Riccardo Mariani, head of industry safety at NVIDIA. “Through the DRIVE AI Systems Inspection Lab, the correctness of the integration of our partners’ products with DRIVE safety and cybersecurity requirements can be inspected and verified.”
Now open to all NVIDIA DRIVE AGX platform partners, the lab is expected to expand to include additional automotive and robotics products and add a testing component.
Complementing International Automotive Safety Standards
The NVIDIA DRIVE AI Systems Inspection Lab complements the missions of independent third-party certification bodies, including technical service organizations such as TÜV SÜD, TÜV Rheinland and exida, as well as vehicle certification agencies such as VCA and KBA.
Today’s announcement dovetails with recent significant safety certifications and assessments of NVIDIA automotive products:
TÜV SÜD
granted the ISO 21434 Cybersecurity Process certification to NVIDIA for its automotive system-on-a-chip, platform and software engineering processes. Upon certification release, the
NVIDIA DriveOS
6.0 operating system conforms with ISO 26262 Automotive Safety Integrity Level (ASIL) D standards.
“Meeting cybersecurity process requirements is of fundamental importance in the autonomous vehicle era,” said Martin Webhofer, CEO of TÜV SÜD Rail GmbH. “NVIDIA has successfully established processes, activities and procedures that fulfill the stringent requirements of ISO 21434. Additionally, NVIDIA DriveOS 6.0 conforms to ISO 26262 ASIL D standards, pending final certification activities.”
TÜV Rheinland
performed an independent United Nations Economic Commission for Europe safety assessment of NVIDIA DRIVE AV related to safety requirements for complex electronic systems.
“NVIDIA has demonstrated thorough, high-quality, safety-oriented processes and technologies in the context of the assessment of the generic, non-OEM-specific parts of the SAE level 2 NVIDIA DRIVE system,” said Dominik Strixner, global lead functional safety automotive mobility at TÜV Rheinland.
To learn more about NVIDIA’s work in advancing autonomous driving safety, read the
NVIDIA Self-Driving Safety Report
.
Categories:
Driving
Tags:
Artificial Intelligence
|
CES 2025
|
Cybersecurity
|
NVIDIA DRIVE
|
Transportation

NVIDIA 啟用 DRIVE AI 系統檢測實驗室，創下業界全新安全里程碑

全新啟用的 NVIDIA DRIVE AI 系統檢測實驗室（Systems Inspection Lab）將協助汽車生態系合作夥伴掌握不斷發展的自駕車安全產業標準。
於今日啟用的這處實驗室，將側重於檢測與驗證汽車合作夥伴在
NVIDIA DRIVE AGX
平台上的軟體與系統，是否符合汽車產業嚴格的安全與資安，包括人工智慧（AI）功能安全。
該實驗室已獲得美國國家標準協會認可委員會（
ANAB
）根據 ISO/IEC 17020 評估標準的認證，包括：
功能安全 （ISO 26262）
SOTIF （ISO 21448）
資安 （ISO 21434）
UN-R 法規，包括 UN-R 79、UN-R 13-H、UN-R 152、UN-R 155、UN-R 157 和 UN-R 171
AI 功能安全 （ISO PAS 8800 和 ISO/IEC TR 5469）
NVIDIA 車用產品部門副總裁 Ali Kani 表示：「NVIDIA 成立這個新的實驗室，將協助全球汽車產業生態系的合作夥伴發展出安全可靠的自動駕駛技術。在獲得 ANAB 認證後，實驗室將執行結合功能安全、資安與 AI 的檢測計畫，強化遵守業界安全標準的程度。」
ANAB 執行董事 R. Douglas Leonard Jr 表示：「ANAB 很榮幸成為 NVIDIA DRIVE AI 系統檢測實驗室的認證機構。NVIDIA 的綜合評估驗證其所展示出的能力與遵守國際公認標準，有助於確保 DRIVE 生態系統合作夥伴遵守功能安全、資安和 AI 整合的最高標準。」
此全新實驗室建立在 NVIDIA 與 Mercedes-Benz 和 JLR 持續進行的安全合規的基礎上。首批加入該實驗室的業者包括大陸集團（Continental）和 Sony SSS-America。
大陸集團零組件業務部門負責人 Nobert Hammerschmidt 表示：「我們很高興能加入新成立的 NVIDIA Drive AI 系統檢測實驗室，進一步強化我們雙方一路以來卓越的合作成果。」
Sony SSS-America 車用影像感測器部門負責人 Marius Evensen 表示：「自駕車能夠大幅提高用路安全。我們期待與 NVIDIA 的 DRIVE AI 系統檢測實驗室合作，協助我們為客戶提供最高等級的安全性。」
NVIDIA 產業安全部門負責人Riccardo Mariani 表示：「對於基於 AI 的自動駕駛車這一類複雜系統來說，遵守功能安全、SOTIF 和資安是一件特別挑戰的事。透過 DRIVE AI 系統檢測實驗室，我們可以檢測和驗證合作夥伴的產品是否有正確與 DRIVE 安全和資安要求進行整合。」
該實驗室目前開放全體 NVIDIA DRIVE AGX 平台合作夥伴使用，預計將加入更多汽車和機器人產品，並且將增加測試環節。
與國際汽車安全標準相輔相成
NVIDIA DRIVE AI 系統檢測實驗室與獨立第三方認證機構的任務相輔相成，包括 TÜV SÜD、TÜV Rheinland 和 exida 等技術服務機構，以及 VCA 和 KBA 等車輛認證機構。
今天宣布的消息與 NVIDIA 車用產品最近獲得的重要安全認證及評估結果不謀而合：
TÜV SÜD
授予 NVIDIA 汽車系統單晶片、平台與軟體工程流程 ISO 21434 網路安全流程認證。認證發布後，
NVIDIA DriveOS
6.0 作業系統符合 ISO 26262 車輛安全完整性等級（ASIL）D 標準。
TÜV SÜD Rail GmbH 執行長 Martin Webhofer 表示：「在自動駕駛時代，必須要符合網路安全流程的要求。NVIDIA 已經成功建立了符合 ISO 21434 嚴格要求的流程、活動和程序。通過最後的認證活動後，NVIDIA DriveOS 6.0 還符合 ISO 26262 ASIL D 標準。」
TÜV Rheinland
對 NVIDIA DRIVE AV 進行了與複雜電子系統安全要求相關的聯合國歐洲經濟委員會獨立安全評估作業。
TÜV Rheinland 全球功能安全汽車行動部門主管 Dominik Strixner 表示：「NVIDIA 在 SAE level 2 NVIDIA DRIVE 系統通用、非 OEM 專用零件的評估中，展現出全面、高品質、以安全為導向的流程與技術。」
若要進一步瞭解 NVIDIA 在推動自動駕駛安全方面的各項工作，請閱讀
NVIDIA 自動駕駛安全報告
。
Categories:
自動駕駛
Tags:
Artificial Intelligence
|
CES 2025
|
cybersecurity
|
NVIDIA DRIVE
|
Transportation


Calisa Cole Author Page | NVIDIA Blog
Skip to content
Artificial Intelligence Computing Leadership from NVIDIA
Search for:
Toggle Search
Home
AI
Data Center
Driving
Gaming
Pro Graphics
Robotics
Healthcare
Startups
AI Podcast
NVIDIA Life
Calisa Cole
Fast Lane to the Future: Automotive Leaders Showcase Advancements in Autonomous Driving at NVIDIA GTC
NVIDIA automotive partners from around the world will demonstrate groundbreaking developments in transportation and showcase next-generation vehicles at NVIDIA GTC, a global AI conference running March 17-21, in San Jose,…
Read Article
NVIDIA Launches DRIVE AI Systems Inspection Lab, Achieves New Industry Safety Milestones
A new NVIDIA DRIVE AI Systems Inspection Lab will help automotive ecosystem partners navigate evolving industry standards for autonomous vehicle safety. The lab, launched today, will focus on inspecting and…
Read Article
Driving Mobility Forward, Vay Brings Advanced Automotive Solutions to Roads With NVIDIA DRIVE AGX
Vay, a Berlin-based provider of automotive-grade remote driving (teledriving) technology, is offering an alternative approach to autonomous driving. Through the company’s app, a user can hail a car, and a…
Read Article
NVIDIA AI Summit Panel Outlines Autonomous Driving Safety
The autonomous driving industry is shaped by rapid technological advancements and the need for standardization of guidelines to ensure the safety of both autonomous vehicles (AVs) and their interaction with…
Read Article
From Embodied AI to Foundation Models, NVIDIA Research Showcases Cutting-Edge Advances at European Conference on Computer Vision
At the European Conference on Computer Vision (ECCV) running this week in Milan, the NVIDIA Research team is demonstrating groundbreaking innovations with 14 accepted publications. The topics presented range from…
Read Article
Ready to Roll: Nuro to License Its Autonomous Driving System
To accelerate autonomous vehicle development and deployment timelines, Nuro announced today it will license its Nuro Driver autonomous driving system directly to automakers and mobility providers. The Nuro Driver is…
Read Article
NVIDIA Blackwell and Automotive Industry Innovators Dazzle at NVIDIA GTC
Generative AI, in the data center and in the car, is making vehicle experiences safer and more enjoyable. The latest advancements in automotive technology were on display last week at…
Read Article
NVIDIA Drives AI Forward With Automotive Innovation on Display at CES
Amid explosive interest in generative AI, the auto industry is racing to embrace the power of AI across a range of critical activities, from vehicle design, engineering and manufacturing, to…
Read Article
From Guangzhou to Los Angeles, Automakers Dazzle With AI-Powered Vehicles
Good news for car lovers: Two acclaimed auto shows, taking place now through next week, are delighting attendees with displays of next-generation automotive designs powered by AI. Hundreds of thousands…
Read Article
Load More Articles
Most Popular
Animals Crossing: AI Helps Protect Wildlife Across the Globe
CUDA Accelerated: How CUDA Libraries Bolster Cybersecurity With AI
Agentic AI Leaders to Showcase Latest Advancements at NVIDIA GTC
Telenor Builds Norway’s First AI Factory, Offering Sustainable and Sovereign Data Processing
March Into Gaming With GeForce NOW’s 14 Must-Play Titles for Spring
Corporate Information
About NVIDIA
Corporate Overview
Technologies
NVIDIA Research
Investors
Social Responsibility
NVIDIA Foundation
Get Involved
Forums
Careers
Developer Home
Join the Developer Program
NVIDIA Partner Network
NVIDIA Inception
Resources for Venture Capitalists
Venture Capital (NVentures)
Technical Training
Training for IT Professionals
Professional Services for Data Science
News & Events
Newsroom
NVIDIA Blog
NVIDIA Technical Blog
Webinars
Stay Informed
Events Calendar
NVIDIA GTC
NVIDIA On-Demand
Explore our regional blogs and other social networks
Privacy Policy
Manage My Privacy
Legal
Accessibility
Product Security
Contact
Copyright © 2025 NVIDIA Corporation
USA - United States
Share This
Facebook
LinkedIn
Email
Share on Mastodon
Enter your Mastodon instance URL (optional)
Share

Calisa Cole， 作者 NVIDIA 台灣官方部落格
Skip to content
Artificial Intelligence Computing Leadership from NVIDIA
搜尋關鍵字:
Toggle Search
平台
智慧機器
概覽
JETSON
嵌入式系統
機器人
JETSON
資料中心
產品
資料中心 GPU
DGX
HGX
EGX
NGC
虛擬 GPU
解決方案
人工智慧與深度學習
高效能計算
虛擬 GPU
分析
應用範例
開發者
技術
CUDA-X
NVIDIA AMPERE 架構
NVIDIA VOLTA
MAGNUM
多執行個體 GPU
NVIDIA NVLINK
深度學習與人工智慧
概覽
產業
概覽
自動駕駛
醫療保健與生命科學
AI 城市
機器人
開發者
產品
概覽
DGX 系統
NVIDIA GPU 雲
NVIDIA TITAN RTX
NVIDIA TITAN V
解決方案
概覽
數據科學
推論
教育課程
AI 新創
設計視覺化
概覽
GRID
QUADRO
高階渲染技術
專業的虛擬實境解決方案
技術
NVIDIA RTX
NVLINK
TURING 架構
虛擬 GPU 技術
HOLODECK
創作者適用的
醫療保健與生命科學
概覽
給開發者
醫療圖像處理
基因體學
自動駕駛汽車
概覽
DRIVE PX
汽車產業夥伴
遊戲與娛樂
GEFORCE 遊戲平台
概覽
20 系列顯示卡
16 系列顯示卡
電競筆記型電腦
G-SYNC 顯示器
給創作者
開發者
NVIDIA 開發者
開發者新聞
開發者部落格
開發者論壇
開源平台
深度學習機構
訓練課程
GPU 科技大會
CUDA
產業
遊戲開發
醫療保健與生技
高等教育
製造業
媒體娛樂
公共部門
零售業
智慧城市
超級運算
電信業
運輸業
所有產業
驅動程式
概覽
GEFORCE 驅動程式
所有 NVIDIA 驅動程式
支援
關於 NVIDIA
概覽
NVIDIA 合作夥伴網絡
AI 運算模型
公司訊息
徵才訊息
投資人
NVIDIA 合作夥伴
NVIDIA 部落格
加入我們
RSS Feeds
訂閱電子報
聯繫我們
產品安全
Calisa Cole
NVIDIA 啟用 DRIVE AI 系統檢測實驗室，創下業界全新安全里程碑
全新啟用的 NVIDIA DRIVE AI 系統檢測實驗室（…
閱讀文章
NVIDIA 在 CES 上展示汽車創新，推動人工智慧向前發展
在生成式人工智慧（AI）引起爆炸性興趣的同時，汽車產業正競相…
閱讀文章
死之華合唱團前任鼓手奏出腦之韻律
注意聽好了，死之華合唱團的樂迷們: 如果你們有想過要窺探你們…
閱讀文章
平台
人工智慧與深度學習
智慧機器
資料中心
設計視覺化
醫療保健
自動駕駛
GeForce 遊戲
SHIELD
產品
DGX-1
DRIVE PX2
GeForce GTX 20 系列
GRID
Jetson
Quadro
SHIELD TV
Tesla
開發者
開發者專區
CUDA
訓練課程
GPU 科技大會
探究地區性部落格及其他社交網路
隱私權政策
管理我的隱私
請勿出售或分享我的資料
服務條款
輔助使用
公司政策
產品安全
聯絡方式
Copyright © 2025 NVIDIA Corporation
Taiwan


Now See This: NVIDIA Launches Blueprint for AI Agents That Can Analyze Video

The next big moment in AI is in sight — literally.
Today, more than 1.5 billion enterprise level cameras deployed worldwide are generating roughly 7 trillion hours of video per year. Yet, only a fraction of it gets analyzed.
It’s estimated that less than 1% of video from industrial cameras is watched live by humans, meaning critical operational incidents can go largely unnoticed.
This comes at a high cost. For example, manufacturers are losing trillions of dollars annually to poor product quality or defects that they could’ve spotted earlier, or even predicted, by using AI agents that can perceive, analyze and help humans take action.
Interactive AI agents with built-in visual perception capabilities can serve as always-on video analysts, helping factories run more efficiently, bolster worker safety, keep traffic running smoothly and even up an athlete’s game.
To accelerate the creation of such agents, NVIDIA today announced early access to a new version of the
NVIDIA AI Blueprint
for
video search and summarization
. Built on top of the
NVIDIA Metropolis
platform — and now supercharged by
NVIDIA Cosmos Nemotron
vision language models (VLMs),
NVIDIA Llama Nemotron
large language models (LLMs) and
NVIDIA NeMo Retriever
— the blueprint provides developers with the tools to build and deploy AI agents that can analyze large quantities of video and image content.
The blueprint integrates the
NVIDIA AI Enterprise
software platform — which includes
NVIDIA NIM
microservices for VLMs, LLMs and advanced AI frameworks for
retrieval-augmented generation
— to enable batch video processing that’s 30x faster than watching it in real time.
The blueprint contains several agentic AI features — such as chain-of-thought reasoning, task planning and tool calling — that can help developers streamline the creation of powerful and diverse visual agents to solve a range of problems.
AI agents with video analysis abilities can be combined with other agents with different skill sets to enable even more sophisticated agentic AI services. Enterprises have the flexibility to build and deploy their AI agents from the edge to the cloud.
How Video Analyst AI Agents Can Help Industrial Businesses
AI agents with visual perception and analysis skills can be fine-tuned to help businesses with industrial operations by:
Increasing productivity and reducing waste:
Agents can help ensure standard operating procedures are followed during complex industrial processes like product assembly. They can also be fine-tuned to carefully watch and understand nuanced actions, and the sequence in which they’re implemented.
Boosting asset management efficiency through better space utilization:
Agents can help optimize inventory storage in warehouses by performing 3D volume estimation and centralizing understanding across various camera streams.
Improving safety through auto-generation of incident reports and summaries:
Agents can process huge volumes of video and summarize it into contextually informative reports of accidents. They can also help ensure personal protective equipment compliance in factories, improving worker safety in industrial settings.
Preventing accidents and production problems:
AI agents can identify atypical activity to quickly mitigate operational and safety risks, whether in a warehouse, factory or airport, or at a traffic intersection or other municipal setting.
Learning from the past:
Agents can search through operations video archives, find relevant information from the past and use it to solve problems or create new processes.
Video Analysts for Sports, Entertainment and More
Another industry where video analysis AI agents stand to make a mark is sports — a $500 billion market worldwide, with hundreds of billions in projected growth over the next several years.
Coaches, teams and leagues — whether professional or amateur — rely on video analytics to evaluate and enhance player performance, prioritize safety and boost fan engagement through player analytics platforms and data visualization. With visually perceptive AI agents, athletes now have unprecedented access to deeper insights and opportunities for improvement.
During his CES opening keynote, NVIDIA founder and CEO Jensen Huang demonstrated an AI video analytics agent that assessed the fastball pitching skills of an amateur baseball player compared with a professional’s. Using video captured from the ceremonial first pitch that Huang threw for the San Francisco Giants baseball team, the video analytics AI agent was able to suggest areas for improvement.
https://blogs.nvidia.com/wp-content/uploads/2025/01/3568870_CES25_Agentic_AI_MetropolisSection_720p_10mb.mp4
The $3 trillion media and entertainment industry is also poised to benefit from video analyst AI agents. Through the
NVIDIA Media2 initiative
, these agents will help drive the creation of smarter, more tailored and more impactful content that can adapt to individual viewer preferences.
Worldwide Adoption and Availability
Partners from around the world are integrating the blueprint for building AI agents for video analysis into their own developer workflows, including Accenture,
Centific
, Deloitte, EY,
Infosys
,
Linker Vision
,
Pegatron
,
TATA Consultancy Services (TCS)
,
Telit Cinterion
and
VAST
.
Apply for early access
to the NVIDIA Blueprint for video search and summarization.
See
notice
regarding software product information.
Editor’s note:
Omdia
is the source for 1.5 billion enterprise-level cameras deployed.
Categories:
Generative AI
Tags:
Artificial Intelligence
|
CES 2025
|
Industrial and Manufacturing
|
Media and Entertainment
|
Metropolis
|
NVIDIA AI Enterprise
|
NVIDIA Blueprints
|
NVIDIA NIM

NVIDIA 推出能夠分析影片內容的 AI 代理藍圖

人工智慧（AI） 的下一個重要時刻就在我們眼前。
目前全球部署企業級攝影機的數量已經超過 15 億具，每年產生約 7 兆小時的影片內容。不過我們只分析了其中一小部分。
經估算，人類只有即時看了不到 1% 工業級攝影機所產生出的影片內容，代表重要作業事故多被忽略。
這將帶來高昂代價。像是製造商每年因產品品質不佳或瑕疵而損失數兆美元，不過若能使用能夠感知、分析及協助人類採取行動的 AI 代理，他們本可提早發現或甚至預測這些問題。
內建視覺感知能力的互動式 AI 代理可充當隨時待命的影片分析人員，協助工廠提高運作效率、加強工人安全、保持交通暢順，甚至提升運動員的比賽表現。
NVIDIA 今日宣布開放搶先體驗用於
影片搜尋與摘要
的新版
NVIDIA AI Blueprint
，以加快開發這一類的代理。這個藍圖（blueprint）建構在
NVIDIA Metropolis
平台之上，由
NVIDIA Cosmos Nemotron
視覺語言模型（VLM）、
NVIDIA Llama Nemotron
大型語言模型（LLM）及
NVIDIA NeMo Retriever
支援，為開發人員提供建置與部署可分析大量影片與圖像內容的 AI 代理的工具。
這個藍圖整合了
NVIDIA AI Enterprise
軟體平台能夠批量處理影片，其處理速度是即時觀看的 30 倍。NVIDIA AI Enterprise包括用於 VLM、LLM 的
NVIDIA NIM
微服務，以及用於
檢索增強生成
的先進 AI 框架。
在這個藍圖裡有數種代理型 AI 功能，例如思維鏈推理、任務規畫和工具呼叫，可協助開發人員輕鬆建立強大且多樣化的視覺代理，以解決一系列問題。
具備影片分析能力的 AI 代理可以搭配其他有著不同技能組合的代理使用，以提供更複雜的代理型 AI 服務。 企業可以靈活地從邊緣到雲端建立和部署自己的 AI 代理。
影片分析
AI
代理如何協助工業領域裡的企業
具備視覺感知與分析技能的 AI 代理可以透過下列方式微調後，協助企業進行工業運作：
提高生產力與減少浪費：
代理可以協助確保在產品組裝等複雜的工業流程中遵循標準作業程序。並能微調仔細觀察和理解細微的動作，還有執行順序。
提高空間利用率來提升資產管理效率：
代理可以估算 3D 體積，集中瞭解多個攝影機串流內容，協助改善倉庫庫存。
自動產生事故報告和摘要以提高安全性：
代理可以處理大量視訊與總結成情節內容豐富的事故報告。並能協助確保工廠內的個人防護裝備符合規定，改善工業環境中的工人作業安全。
預防意外與生產問題：
無論是在倉庫、工廠或機場，或是在交通路口或其他市政環境，AI 代理都能發現異常活動，以快速降低作業與安全風險。
從過去學習：
AI 代理可以搜尋作業影片檔案，從過去找到相關資訊，利用這些資訊來解決問題或建立新的流程。
分析體育娛樂等產業的影片內容
另一個影片分析 AI 代理可以大展拳腳的產業便是體育，在全球市值高達 5,000 億美元，預計在未來幾年內將有數千億美元的成長。
教練、球隊，以及無論職業或業餘聯盟都仰賴影片分析功能，以評估和提升球員表現、優先考量安全性，並且透過球員分析平台和資料可視化技術來提高球迷參與度。有了視覺感知的 AI 代理，運動員現在可以獲得更深入的看法和改進機會，這是過去做不到的。
NVIDIA 創辦人暨執行長黃仁勳在 CES 大會的開幕主題演講中，展示了一個 AI 影片分析代理，這款代理能夠評估業餘棒球選手與職業棒球選手的快速投球技巧。利用黃仁勳為舊金山巨人隊開球儀式所擷取的影片，視訊分析 AI 代理能夠提出需要改進的地方。
https://blogs.nvidia.com.tw/wp-content/uploads/sites/19/2025/01/JHH-pitch-metropolis-trim-final.mp4
影片分析 AI 代理也將嘉惠市價三兆美元的媒體與娛樂產業。這些代理透過
NVIDIA Media2 計畫
將有助於推動建立更聰明、更符合個人需求且更有影響力的內容，以適應個別觀眾的喜好。
全球合作夥伴正在將建立影片分析 AI 代理的藍圖整合到他們自己的開發人員工作流程中，包括埃森哲（Accenture）、Centific、德勤、Infosys、
Linker Vision
、和碩、TATA Consultancy Services（TCS）、Telit Cinterion 和
VAST
。
請在
此申請搶先體驗 NVIDIA 影片搜尋與摘要用藍圖
。
請見有關軟體產品資訊的
通知
。
Categories:
生成式人工智慧
Tags:
Artificial Intelligence
|
CES 2025
|
Industrial and Manufacturing
|
Media and Entertainment
|
Metropolis
|
NVIDIA AI Enterprise
|
NVIDIA Blueprints
|
NVIDIA NIM


Adam Scraba Author Page | NVIDIA Blog
Skip to content
Artificial Intelligence Computing Leadership from NVIDIA
Search for:
Toggle Search
Home
AI
Data Center
Driving
Gaming
Pro Graphics
Robotics
Healthcare
Startups
AI Podcast
NVIDIA Life
Adam Scraba
Adam Scraba drives worldwide evangelism and marketing for NVIDIA's accelerated computing platform in applying AI to video analysis to solve critical problems across a breadth of industries, from urban planning and transportation to retail and energy. Previously, Adam was responsible for leading NVIDIA's business development and strategic alliances for smart and safe city initiatives worldwide. He has led dozens of customers and developers along the transformational journey to leverage AI, from startups to Fortune 500 companies.
NoTraffic Reduces Road Delays, Carbon Emissions With NVIDIA AI and Accelerated Computing
More than 90 million new vehicles are introduced to roads across the globe every year, leading to an annual 12% increase in traffic congestion — according to NoTraffic, a member…
Read Article
Now See This: NVIDIA Launches Blueprint for AI Agents That Can Analyze Video
The next big moment in AI is in sight — literally. Today, more than 1.5 billion enterprise level cameras deployed worldwide are generating roughly 7 trillion hours of video per…
Read Article
Give AI a Look: Any Industry Can Now Search and Summarize Vast Volumes of Visual Data
Editor’s note: The name of NIM Agent Blueprints was changed to NVIDIA Blueprints in October 2024. All references to the name have been updated in this blog. Enterprises and public…
Read Article
AI Gets Physical: New NVIDIA NIM Microservices Bring Generative AI to Digital Environments
Millions of people already use generative AI to assist in writing and learning. Now, the technology can also help them more effectively navigate the physical world. NVIDIA announced at SIGGRAPH…
Read Article
Taiwan Electronics Giants Drive Industrial Automation With NVIDIA Metropolis and NIM
Taiwan’s leading consumer electronics giants are making advances with AI automation for manufacturing, as fleets of robots and millions of cameras and sensors drive efficiencies across the smart factories of…
Read Article
Staying in Sync: NVIDIA Combines Digital Twins With Real-Time AI for Industrial Automation
Real-time AI is helping with the heavy lifting in manufacturing, factory logistics and robotics. In such industries — often involving bulky products, expensive equipment, cobot environments and logistically complex facilities…
Read Article
Electronics Giants Tap Into Industrial Automation With NVIDIA Metropolis for Factories
The $46 trillion global electronics manufacturing industry spans more than 10 million factories worldwide, where much is at stake in producing defect-free products. To drive product excellence, leading electronics manufacturers…
Read Article
NVIDIA Metropolis Ecosystem Grows With Advanced Development Tools to Accelerate Vision AI
With AI at its tipping point, AI-enabled computer vision is being used to address the world’s most challenging problems in nearly every industry. At GTC, a global conference for the…
Read Article
Lights! Camera! Insight! Four Scenes From the Marriage of Computer Vision and Edge Computing
Whether you’re managing stadiums, cities or global corporations, edge AI is critical to improve  operational efficiency. That’s the message from people drawn from each of these fields who will share…
Read Article
Most Popular
Animals Crossing: AI Helps Protect Wildlife Across the Globe
CUDA Accelerated: How CUDA Libraries Bolster Cybersecurity With AI
Agentic AI Leaders to Showcase Latest Advancements at NVIDIA GTC
Telenor Builds Norway’s First AI Factory, Offering Sustainable and Sovereign Data Processing
March Into Gaming With GeForce NOW’s 14 Must-Play Titles for Spring
Corporate Information
About NVIDIA
Corporate Overview
Technologies
NVIDIA Research
Investors
Social Responsibility
NVIDIA Foundation
Get Involved
Forums
Careers
Developer Home
Join the Developer Program
NVIDIA Partner Network
NVIDIA Inception
Resources for Venture Capitalists
Venture Capital (NVentures)
Technical Training
Training for IT Professionals
Professional Services for Data Science
News & Events
Newsroom
NVIDIA Blog
NVIDIA Technical Blog
Webinars
Stay Informed
Events Calendar
NVIDIA GTC
NVIDIA On-Demand
Explore our regional blogs and other social networks
Privacy Policy
Manage My Privacy
Legal
Accessibility
Product Security
Contact
Copyright © 2025 NVIDIA Corporation
USA - United States
Share This
Facebook
LinkedIn
Email
Share on Mastodon
Enter your Mastodon instance URL (optional)
Share

Adam Scraba， 作者 NVIDIA 台灣官方部落格
Skip to content
Artificial Intelligence Computing Leadership from NVIDIA
搜尋關鍵字:
Toggle Search
平台
智慧機器
概覽
JETSON
嵌入式系統
機器人
JETSON
資料中心
產品
資料中心 GPU
DGX
HGX
EGX
NGC
虛擬 GPU
解決方案
人工智慧與深度學習
高效能計算
虛擬 GPU
分析
應用範例
開發者
技術
CUDA-X
NVIDIA AMPERE 架構
NVIDIA VOLTA
MAGNUM
多執行個體 GPU
NVIDIA NVLINK
深度學習與人工智慧
概覽
產業
概覽
自動駕駛
醫療保健與生命科學
AI 城市
機器人
開發者
產品
概覽
DGX 系統
NVIDIA GPU 雲
NVIDIA TITAN RTX
NVIDIA TITAN V
解決方案
概覽
數據科學
推論
教育課程
AI 新創
設計視覺化
概覽
GRID
QUADRO
高階渲染技術
專業的虛擬實境解決方案
技術
NVIDIA RTX
NVLINK
TURING 架構
虛擬 GPU 技術
HOLODECK
創作者適用的
醫療保健與生命科學
概覽
給開發者
醫療圖像處理
基因體學
自動駕駛汽車
概覽
DRIVE PX
汽車產業夥伴
遊戲與娛樂
GEFORCE 遊戲平台
概覽
20 系列顯示卡
16 系列顯示卡
電競筆記型電腦
G-SYNC 顯示器
給創作者
開發者
NVIDIA 開發者
開發者新聞
開發者部落格
開發者論壇
開源平台
深度學習機構
訓練課程
GPU 科技大會
CUDA
產業
遊戲開發
醫療保健與生技
高等教育
製造業
媒體娛樂
公共部門
零售業
智慧城市
超級運算
電信業
運輸業
所有產業
驅動程式
概覽
GEFORCE 驅動程式
所有 NVIDIA 驅動程式
支援
關於 NVIDIA
概覽
NVIDIA 合作夥伴網絡
AI 運算模型
公司訊息
徵才訊息
投資人
NVIDIA 合作夥伴
NVIDIA 部落格
加入我們
RSS Feeds
訂閱電子報
聯繫我們
產品安全
Adam Scraba
Adam Scraba drives worldwide evangelism and marketing for NVIDIA's accelerated computing platform in applying AI to video analysis to solve critical problems across a breadth of industries, from urban planning and transportation to retail and energy. Previously, Adam was responsible for leading NVIDIA's business development and strategic alliances for smart and safe city initiatives worldwide. He has led dozens of customers and developers along the transformational journey to leverage AI, from startups to Fortune 500 companies.
NVIDIA 推出能夠分析影片內容的 AI 代理藍圖
人工智慧（AI） 的下一個重要時刻就在我們眼前。 目前全球部…
閱讀文章
將 AI 視覺化：任何產業現在都能搜尋並摘要大量的視覺資料
全球各地的企業與公部門組織都在開發人工智慧代理（AI age…
閱讀文章
AI 變得真實：新的 NVIDIA NIM 微服務將生成式 AI 引入數位環境
數百萬人已經使用生成式人工智慧（AI）來協助寫作和學習。現在…
閱讀文章
台灣電子公司巨頭使用 NVIDIA Metropolis 與 NIM 推動發展工業自動化
多家台灣大型消費性電子產品製造商在人工智慧（AI）自動化製造…
閱讀文章
多家電子製造業領導業者採用 NVIDIA Metropolis for Factories 實現工業自動化
全球逾千萬家工廠合力造就出市值 46 兆美元的電子製造業，他…
閱讀文章
NVIDIA Metropolis 生態系不斷壯大，加入多項先進開發工具加速視覺人工智慧領域發展
隨著人工智慧的發展腳步來到臨界點，人工智慧驅動的電腦視覺技術…
閱讀文章
汽車工業如何向電影導演借取靈感來打造更安全的汽車
車廠長久以來都是使用 GPU 來打造外觀更好看的汽車，而現在…
閱讀文章
Quadro K6000 改變影像工作流程的面貌與速度
雖然距離聖誕節還有幾個月，但繪圖師和設計師們已將全新的 NV…
閱讀文章
平台
人工智慧與深度學習
智慧機器
資料中心
設計視覺化
醫療保健
自動駕駛
GeForce 遊戲
SHIELD
產品
DGX-1
DRIVE PX2
GeForce GTX 20 系列
GRID
Jetson
Quadro
SHIELD TV
Tesla
開發者
開發者專區
CUDA
訓練課程
GPU 科技大會
探究地區性部落格及其他社交網路
隱私權政策
管理我的隱私
請勿出售或分享我的資料
服務條款
輔助使用
公司政策
產品安全
聯絡方式
Copyright © 2025 NVIDIA Corporation
Taiwan


NVIDIA and Partners Launch Agentic AI Blueprints to Automate Work for Every Enterprise

New NVIDIA AI Blueprints for building agentic AI applications are poised to help enterprises everywhere automate work.
With the blueprints, developers can now build and deploy custom AI agents. These AI agents act like “knowledge robots” that can reason, plan and take action to quickly analyze large quantities of data, summarize and distill real-time insights from video, PDF and other images.
CrewAI, Daily, LangChain, LlamaIndex and Weights & Biases are among leading providers of agentic AI orchestration and management tools that have worked with NVIDIA to build blueprints that integrate the
NVIDIA AI Enterprise
software platform, including
NVIDIA NIM
microservices and NVIDIA NeMo, with their platforms. These five blueprints — comprising a
new category of partner blueprints for agentic AI
— provide the building blocks for developers to create the next wave of AI applications that will transform every industry.
In addition to the partner blueprints, NVIDIA is introducing its own new AI Blueprint for PDF to podcast, as well as another to build
AI agents for video search and summarization
. These are joined by four additional
NVIDIA Omniverse Blueprints
that make it easier for developers to build simulation-ready digital twins for physical AI.
To help enterprises rapidly take AI agents into production, Accenture is announcing
AI Refinery for Industry
built with NVIDIA AI Enterprise, including
NVIDIA NeMo
, NVIDIA NIM microservices and
AI Blueprints
.
The AI Refinery for Industry solutions — powered by Accenture AI Refinery with NVIDIA — can help enterprises rapidly launch agentic AI across fields like automotive, technology, manufacturing, consumer goods and more.
Agentic AI Orchestration Tools Conduct a Symphony of Agents
Agentic AI
represents the next wave in the evolution of generative AI. It enables applications to move beyond simple chatbot interactions to tackle complex, multi-step problems through sophisticated reasoning and planning. As explained in NVIDIA founder and CEO Jensen Huang’s
CES keynote
, enterprise AI agents will become a centerpiece of AI factories that generate tokens to create unprecedented intelligence and productivity across industries.
Agentic AI orchestration is a sophisticated system designed to manage, monitor and coordinate multiple AI agents working together — key to developing reliable enterprise agentic AI systems. The agentic AI orchestration layer from NVIDIA partners provides the glue needed for AI agents to effectively work together.
The new partner blueprints, now available from agentic AI orchestration leaders, offer integrations with
NVIDIA AI Enterprise
software, including NIM microservices and NVIDIA NeMo Retriever, to boost retrieval accuracy and reduce latency of agent workflows. For example:
CrewAI
is using new Llama 3.3 70B NVIDIA NIM microservices and the NVIDIA NeMo Retriever embedding NIM microservice for its blueprint for code documentation for software development. The blueprint helps ensure code repositories remain comprehensive and easy to navigate.
Daily’s
voice agent blueprint, powered by the company’s open-source Pipecat framework, uses the
NVIDIA Riva
automatic speech recognition and text-to-speech NIM microservice, along with the Llama 3.3 70B NIM microservice to achieve real-time conversational AI.
LangChain
is adding Llama 3.3 70B NVIDIA NIM microservices to its structured report generation blueprint. Built on LangGraph, the blueprint allows users to define a topic and specify an outline to guide an agent in searching the web for relevant information, so it can return a report in the requested format.
LlamaIndex’s
document research assistant for blog creation blueprint harnesses NVIDIA NIM microservices and NeMo Retriever to help content creators produce high-quality blogs. It can tap into agentic-driven
retrieval-augmented generation
with NeMo Retriever to automatically research, outline and generate compelling content with source attribution.
Weights & Biases
is adding its W&B Weave capability to the AI Blueprint for AI virtual assistants, which features the Llama 3.1 70B NIM microservice. The blueprint can streamline the process of debugging, evaluating, iterating and tracking production performance and collecting human feedback to support seamless integration and faster iterations for building and deploying agentic AI applications.
Summarize Many, Complex PDFs While Keeping Proprietary Data Secure
With trillions of PDF files — from financial reports to technical research papers — generated every year, it’s a constant challenge to stay up to date with information.
NVIDIA’s
PDF to podcast AI Blueprint
provides a recipe developers can use to turn multiple long and complex PDFs into AI-generated readouts that can help professionals, students and researchers efficiently learn about virtually any topic and quickly understand key takeaways.
The blueprint — built on NIM microservices and text-to-speech models — allows developers to build applications that extract images, tables and text from PDFs, and convert the data into easily digestible audio content, all while keeping data secure.
For example, developers can build AI agents that can understand context, identify key points and generate a concise summary as a monologue or a conversation-style podcast, narrated in a natural voice. This offers users an engaging, time-efficient way to absorb information at their desired speed.
Test, Prototype and Run Agentic AI Blueprints in One Click
NVIDIA Blueprints empower the world’s more than 25 million software developers to easily integrate AI into their applications across various industries. These blueprints simplify the process of building and deploying agentic AI applications, making advanced AI integration more accessible than ever.
With just a single click, developers can now build and run the new agentic AI Blueprints as
NVIDIA Launchables
. These Launchables provide on-demand access to developer environments with predefined configurations, enabling quick workflow setup.
By containing all necessary components for development, Launchables support consistent and reproducible setups without the need for manual configuration or overhead — streamlining the entire development process, from prototyping to deployment.
Enterprises can also deploy blueprints into production with the
NVIDIA AI Enterprise
software platform on data center platforms including Dell Technologies, Hewlett Packard Enterprise, Lenovo and Supermicro, or run them on accelerated cloud platforms from Amazon Web Services, Google Cloud, Microsoft Azure and Oracle Cloud Infrastructure.
Accenture and NVIDIA Fast-Track Deployments With AI Refinery for Industry
Accenture is introducing its new AI Refinery for Industry with 12 new industry agent solutions built with NVIDIA AI Enterprise software and available from the
Accenture NVIDIA Business Group
. These industry-specific agent solutions include revenue growth management for consumer goods and services, clinical trial companion for life sciences, industrial asset troubleshooting and B2B marketing, among others.
AI Refinery for Industry offerings include preconfigured components, best practices and foundational elements designed to fast-track the development of AI agents. They provide organizations the tools to build specialized AI networks tailored to their industry needs.
Accenture plans to launch over 100 AI Refinery for Industry agent solutions by the end of the year.
Get started with
AI Blueprints
and join
NVIDIA at CES
.
See
notice
regarding software product information.
Categories:
Generative AI
Tags:
Artificial Intelligence
|
CES 2025
|
NVIDIA AI Enterprise
|
NVIDIA Blueprints
|
NVIDIA NeMo
|
NVIDIA NIM
|
Physical AI
|
Riva

NVIDIA 與合作夥伴推出代理型 AI 藍圖， 協助每個企業自動執行工作

用於建立代理型 AI 應用程式的全新 NVIDIA AI Blueprints，已經準備好協助各地的企業自動執行各項工作。
開發人員現在使用這些藍圖可以建立和部署客製化的 AI 代理。這些代理能像「知識機器人」一般推理、規畫及採取行動，從影片、PDF 和其他圖像中快速分析大量資料，做出總結及即時提取寶貴看法。
CrewAI、Daily、LangChain、LlamaIndex 及 Weights & Biases 等領先的代理型 AI 協調與管理工具供應商與 NVIDIA 合作建立藍圖，將
NVIDIA AI Enterprise
軟體平台（包括
NVIDIA NIM
微服務和 NVIDIA NeMo）與自家平台進行整合。這五個藍圖是
代理型 AI 的合作夥伴藍圖全新類別
，為開發人員創造下一波將改變各行各業的 AI 應用程式提供了建構模塊。
除了合作夥伴藍圖之外，NVIDIA 還推出了自己全新適用於 PDF to podcast 的 AI Blueprint ，以及另一個
適用於影片搜尋與摘要的 AI 代理藍圖
。另外還有四個
NVIDIA
Omniverse Blueprints
，可讓開發人員更輕鬆為實體 AI 建立模擬就緒的數位孿生。
為協助企業快速將 AI 代理導入生產環境，埃森哲（Accenture）宣布使用 NVIDIA AI Enterprise 打造
AI Refinery for Industry
，包括
NVIDIA NeMo
、NVIDIA NIM 微服務與
AI Blueprints
。
由 Accenture AI Refinery 與 NVIDIA 驅動的 AI Refinery for Industry 解決方案，可協助汽車、科技、製造業、消費品等領域的企業快速啟動代理型 AI。
代理型
AI
協調工具指揮著代理交響樂
代理型 AI
代表著生成式 AI 發展的下一波浪潮。它能讓應用程式不只是進行簡單的聊天機器人互動，而是能夠進行精密的推理與規畫，解決複雜的多步驟問題。正如 NVIDIA 創辦人暨執行長
黃仁勳在 CES 大會主題演講
中所說的，企業級 AI 代理將成為 AI 工廠的核心，這些工廠將產生出 詞元，為各行各業創造前所未有的智慧與生產力。
代理型 AI 協調是一個精密複雜的系統，專門用來管理、監控和協調多個 AI 代理協同作業 – 這是開發可靠的企業代理型 AI 系統的關鍵。NVIDIA 合作夥伴所推出的代理型 AI 協調層提供 AI 代理有效合作所需的黏合劑。
代理型 AI 協調領導廠商現已推出新的合作夥伴藍圖，可與
NVIDIA AI Enterprise
軟體整合，包括 NIM 微服務及 NVIDIA NeMo Retriever，以提高檢索精準度和減少延遲。例如：
CrewAI
使用全新 Llama 3.3 70B NVIDIA NIM 微服務及 NVIDIA NeMo Retriever 嵌入式 NIM 微服務，開發該公司的軟體開發程式碼文件藍圖。該藍圖有助於確保程式碼儲存庫保持無所不包且易於導覽的狀態。
Daily
的語音代理藍圖由該公司的開源 Pipecat 架構所驅動，使用
NVIDIA
Riva
自動語音辨識與文字轉語音 NIM 微服務，以及 Llama 3.3 70B NIM 微服務來提供即時對話 AI。
LangChain
將 Llama 3.3 70B NVIDIA NIM 微服務加入其結構化報告生成藍圖。該藍圖以 LangGraph 為基礎，使用者可以定義主題與指定大綱，引導代理在網路上搜尋相關資訊，用要求的格式傳回報告。
LlamaIndex
用於部落格創作藍圖的文件研究助理，利用 NVIDIA NIM 微服務和 NeMo Retriever 協助內容創作者製作優質的部落格內容。它可以利用 NeMo Retriever 的代理驅動
檢索增強生成
功能，自動進行研究、擬定大綱和產生具吸引力的內容，並且註明資料來源。
Weights & Biases
將該公司的 W&B Weave 功能加入 AI 虛擬助理的 AI 藍圖，該藍圖採用 Llama 3.1 70B NIM 微服務。該藍圖可簡化除錯、評估、反覆調整和追蹤生產效能，以及收集人類回饋的流程，以支援在建立和部署代理型 AI 應用程式之際，能夠完美進行整合和更快重複進行調整。
在確保專屬資料安全的同時，對許多複雜的
PDF
檔案擷取摘要
每年都會產生出上兆份 PDF 檔案（從財務報告到技術研究論文），要隨時掌握最新資訊一直都是一件不容易的事。
開發人員可以使用 NVIDIA 的 PDF to podcast AI Blueprint 將多個冗長又複雜的 PDF 文件，轉換成 AI 生成的讀出內容，幫助專業人士、學生和研究人員有效瞭解幾乎任何主題，以及快速掌握其中的關鍵重點。
這個藍圖以 NIM 微服務和文字轉語音模型為基礎，讓開發人員能夠建立應用程式，從 PDF 檔案中提取影像、表格和文字，並且將資料轉換為易於理解的語音內容，同時確保資料安全。舉例來說，開發人員可以建立 AI 代理，能夠理解語順脈絡、找出其中的重點，並且產生獨白或對話式 Podcast，以自然語音簡單敘述摘要。這樣讓使用者能夠用一種吸引人且省時的方式，以他們想要的速度吸收資訊。
一鍵測試、製作原型與運行代理型
AI Blueprints
NVIDIA Blueprints 讓全球超過 2500 萬名軟體開發人員可以輕鬆將 AI 整合到各產業的應用程式中。這些藍圖簡化了建置和部署代理型 AI 應用程式的流程，讓人更容易使用到先進的 AI 整合項目。
開發人員現在只要按一下滑鼠，就能以 NVIDIA Launchables 的方式建立和運行新的代理型 AI Blueprints。這些 Launchables 可以讓人按照需求進入有先定義好組態內容的開發人員環境，以便快速設定工作流程。
這些 Launchables 內有開發所需的所有元件，支援一致且可重複的設定，無需手動設定或間接成本，簡化從原型設計到部署的整個開發流程。
企業還能在 Dell Technologies、Hewlett Packard Enterprise、Lenovo 和 Supermicro 等業者推出的資料中心平台上，利用
NVIDIA AI Enterprise
軟體平台將藍圖部署至生產環境，或是在 Amazon Web Services、Google Cloud、Microsoft Azure 和 Oracle Cloud Infrastructure 的加速雲端平台上運行藍圖。
埃森哲
與
NVIDIA
利用
AI Refinery for Industry
快速部署
埃森哲推出全新的 AI Refinery for Industry，利用 NVIDIA AI Enterprise 軟體打造 12 個全新的產業代理解決方案，並且由
埃森哲 NVIDIA 事業群
提供。這些針對特定產業的代理解決方案包括消費品與服務的營收成長管理、生命科學的臨床試驗伴隨服務、工業資產故障排患與 B2B 行銷等。
AI Refinery for Industry 產品包括預先配置元件、最佳做法和基礎元素，用於快速開發 AI 代理。它們提供工具給組織，以建立符合其產業需求的專門 AI 網路。
埃森哲計畫在今年底前推出超過 100 個 AI Refinery for Industry 代理解決方案。
開始使用
AI Blueprints 並參加
NVIDIA 在 CES 大會的各項活動
。
請見有關軟體產品資訊的
通知
。
Categories:
生成式人工智慧
Tags:
Artificial Intelligence
|
CES 2025
|
NVIDIA AI Enterprise
|
NVIDIA Blueprints
|
NVIDIA NeMo
|
NVIDIA NIM
|
Riva


Justin Boitano Author Page | NVIDIA Blog
Skip to content
Artificial Intelligence Computing Leadership from NVIDIA
Search for:
Toggle Search
Home
AI
Data Center
Driving
Gaming
Pro Graphics
Robotics
Healthcare
Startups
AI Podcast
NVIDIA Life
Justin Boitano
NVIDIA and Partners Launch Agentic AI Blueprints to Automate Work for Every Enterprise
New NVIDIA AI Blueprints for building agentic AI applications are poised to help enterprises everywhere automate work. With the blueprints, developers can now build and deploy custom AI agents. These…
Read Article
A Not-So-Secret Agent: NVIDIA Unveils Blueprint for Cybersecurity
Editor’s note: The name of NIM Agent Blueprints was changed to NVIDIA Blueprints in October 2024. All references to the name have been updated in this blog. Artificial intelligence is transforming…
Read Article
From Prototype to Prompt: NVIDIA Blueprints Fast-Forward Next Wave of Enterprise Generative AI
Editor’s note: The name of NIM Agent Blueprints was changed to NVIDIA Blueprints in October 2024. All references to the name have been updated in this blog. The initial wave…
Read Article
License for the AI Autobahn: NVIDIA AI Enterprise 3.0 Introduces New Tools to Speed Success
From rapidly fluctuating demand to staffing shortages and supply chain complexity, enterprises have navigated numerous challenges the past few years. Many companies seeking strong starts to 2023 are planning to…
Read Article
AI Software Pioneers From the Edge to the Cloud Join NVIDIA at HPE Discover
AI technologies are seeing broad industry adoption across manufacturing, retail, financial services, healthcare, the public sector and more. A recent O’Reilly study found that retail and finance lead in AI…
Read Article
Dream State: Cybersecurity Vendors Detect Breaches in an Instant With NVIDIA Morpheus
In the geography of data center security, efforts have long focused on protecting north-south traffic — the data that passes between the data center and the rest of the network….
Read Article
How Suite It Is: NVIDIA and VMware Deliver AI-Ready Enterprise Platform
As enterprises modernize their data centers to power AI-driven applications and data science, NVIDIA and VMware are making it easier than ever to develop and deploy a multitude of different…
Read Article
How NVIDIA EGX Is Forming Central Nervous System of Global Industries
Massive change across every industry is being driven by the rising adoption of IoT sensors, including cameras for seeing, microphones for hearing, and a range of other smart devices that…
Read Article
Taking Point: IBM, NVIDIA Collaborate at the Network’s Edge
NVIDIA is expanding its long-standing collaboration with IBM to accelerate the deployment of edge networks. Businesses are deploying these networks around the world as they switch on IoT sensors and…
Read Article
Load More Articles
Most Popular
Animals Crossing: AI Helps Protect Wildlife Across the Globe
CUDA Accelerated: How CUDA Libraries Bolster Cybersecurity With AI
Agentic AI Leaders to Showcase Latest Advancements at NVIDIA GTC
Telenor Builds Norway’s First AI Factory, Offering Sustainable and Sovereign Data Processing
March Into Gaming With GeForce NOW’s 14 Must-Play Titles for Spring
Corporate Information
About NVIDIA
Corporate Overview
Technologies
NVIDIA Research
Investors
Social Responsibility
NVIDIA Foundation
Get Involved
Forums
Careers
Developer Home
Join the Developer Program
NVIDIA Partner Network
NVIDIA Inception
Resources for Venture Capitalists
Venture Capital (NVentures)
Technical Training
Training for IT Professionals
Professional Services for Data Science
News & Events
Newsroom
NVIDIA Blog
NVIDIA Technical Blog
Webinars
Stay Informed
Events Calendar
NVIDIA GTC
NVIDIA On-Demand
Explore our regional blogs and other social networks
Privacy Policy
Manage My Privacy
Legal
Accessibility
Product Security
Contact
Copyright © 2025 NVIDIA Corporation
USA - United States
Share This
Facebook
LinkedIn
Email
Share on Mastodon
Enter your Mastodon instance URL (optional)
Share

Justin Boitano， 作者 NVIDIA 台灣官方部落格
Skip to content
Artificial Intelligence Computing Leadership from NVIDIA
搜尋關鍵字:
Toggle Search
平台
智慧機器
概覽
JETSON
嵌入式系統
機器人
JETSON
資料中心
產品
資料中心 GPU
DGX
HGX
EGX
NGC
虛擬 GPU
解決方案
人工智慧與深度學習
高效能計算
虛擬 GPU
分析
應用範例
開發者
技術
CUDA-X
NVIDIA AMPERE 架構
NVIDIA VOLTA
MAGNUM
多執行個體 GPU
NVIDIA NVLINK
深度學習與人工智慧
概覽
產業
概覽
自動駕駛
醫療保健與生命科學
AI 城市
機器人
開發者
產品
概覽
DGX 系統
NVIDIA GPU 雲
NVIDIA TITAN RTX
NVIDIA TITAN V
解決方案
概覽
數據科學
推論
教育課程
AI 新創
設計視覺化
概覽
GRID
QUADRO
高階渲染技術
專業的虛擬實境解決方案
技術
NVIDIA RTX
NVLINK
TURING 架構
虛擬 GPU 技術
HOLODECK
創作者適用的
醫療保健與生命科學
概覽
給開發者
醫療圖像處理
基因體學
自動駕駛汽車
概覽
DRIVE PX
汽車產業夥伴
遊戲與娛樂
GEFORCE 遊戲平台
概覽
20 系列顯示卡
16 系列顯示卡
電競筆記型電腦
G-SYNC 顯示器
給創作者
開發者
NVIDIA 開發者
開發者新聞
開發者部落格
開發者論壇
開源平台
深度學習機構
訓練課程
GPU 科技大會
CUDA
產業
遊戲開發
醫療保健與生技
高等教育
製造業
媒體娛樂
公共部門
零售業
智慧城市
超級運算
電信業
運輸業
所有產業
驅動程式
概覽
GEFORCE 驅動程式
所有 NVIDIA 驅動程式
支援
關於 NVIDIA
概覽
NVIDIA 合作夥伴網絡
AI 運算模型
公司訊息
徵才訊息
投資人
NVIDIA 合作夥伴
NVIDIA 部落格
加入我們
RSS Feeds
訂閱電子報
聯繫我們
產品安全
Justin Boitano
NVIDIA 與合作夥伴推出代理型 AI 藍圖， 協助每個企業自動執行工作
用於建立代理型 AI 應用程式的全新 NVIDIA AI B…
閱讀文章
「代理」兼「特工」：NVIDIA 發布網路安全新藍圖
人工智慧（AI）正在藉由全新的生成式 AI 工具和功能改變網…
閱讀文章
從原型到提示：NVIDIA NIM Agent Blueprints 將快速推動企業級生成式 AI 的下一波浪潮
在各項網路服務中使用生成式人工智慧（AI），促成生成式 AI…
閱讀文章
人工智慧高速公路通行證：NVIDIA AI Enterprise 3.0 導入新工具，以協助企業更快取得成功
從快速變動的需求到人手短缺和複雜的供應鏈，企業在過去幾年裡經…
閱讀文章
NVIDIA EGX 如何形成全球產業的中央神經系統
物聯網感測器（包括用於觀看的攝影機，用於聽覺的麥克風）以及一…
閱讀文章
IBM 與 NVIDIA 在網路邊緣展開合作
IBM Edge Application Manager 是…
閱讀文章
AWS Outposts 派遣 GPU 進駐你的資料中心
NVIDIA T4 GPU 現在起支援混合 AWS 雲端環境…
閱讀文章
我們如何憑藉 Google 與 VMware 釋放雲端化桌面的完整潛力
就在 NVIDIA 公布要藉由採用 Tegra K1 處理器…
閱讀文章
登入 GRID：24 小時免費試用 NVIDIA GRID (影片)
虛擬桌面將是十分好用的桌面。NVIDIA 現在北美地區推出 …
閱讀文章
客戶與合作夥伴讓 NVIDIA GRID 技術成為 Citrix Synergy 年度大會的熱門話題
新功能、新的合作夥伴、客戶精彩的故事。2013 年 NVID…
閱讀文章
更多文章
平台
人工智慧與深度學習
智慧機器
資料中心
設計視覺化
醫療保健
自動駕駛
GeForce 遊戲
SHIELD
產品
DGX-1
DRIVE PX2
GeForce GTX 20 系列
GRID
Jetson
Quadro
SHIELD TV
Tesla
開發者
開發者專區
CUDA
訓練課程
GPU 科技大會
探究地區性部落格及其他社交網路
隱私權政策
管理我的隱私
請勿出售或分享我的資料
服務條款
輔助使用
公司政策
產品安全
聯絡方式
Copyright © 2025 NVIDIA Corporation
Taiwan


NVIDIA Announces Nemotron Model Families to Advance Agentic AI

Artificial intelligence is entering a new era — agentic AI — where teams of specialized agents can help people solve complex problems and automate repetitive tasks.
With custom AI agents, enterprises across industries can manufacture intelligence and achieve unprecedented productivity. These advanced AI agents require a system of multiple generative AI models optimized for agentic AI functions and capabilities. This complexity means that the need for powerful, efficient, enterprise-grade models has never been greater.
To provide a foundation for enterprise agentic AI, NVIDIA today announced the Llama Nemotron family of open large language models (
LLMs
). Built with Llama, the models can help developers create and deploy AI agents across a range of applications — including customer support, fraud detection, and product supply chain and inventory management optimization.
To be effective, many AI agents need both language skills and the ability to perceive the world and respond with the appropriate action.
With new
NVIDIA Cosmos Nemotron
vision language models (VLMs) and NVIDIA NIM microservices for
video search and summarization
, developers can build agents that analyze and respond to images and video from autonomous machines, hospitals, stores and warehouses, as well as sports events, movies and news. For developers seeking to generate physics-aware videos for robotics and autonomous vehicles, NVIDIA today separately announced
NVIDIA Cosmos world foundation models
.
Open Llama Nemotron Models Optimize Compute Efficiency, Accuracy for AI Agents
Built with Llama foundation models — one of the most popular commercially viable open-source model collections, downloaded over 650 million times — NVIDIA Llama Nemotron models provide optimized building blocks for AI agent development. This builds on NVIDIA’s commitment to developing state-of-the-art models, such as
Llama 3.1 Nemotron 70B
, now available through the
NVIDIA API catalog
.
Llama Nemotron models are
pruned and trained with NVIDIA’s latest techniques
and high-quality datasets for enhanced agentic capabilities. They excel at instruction following, chat, function calling, coding and math, while being size-optimized to run on a broad range of NVIDIA accelerated computing resources.
“Agentic AI is the next frontier of AI development, and delivering on this opportunity requires full-stack optimization across a system of LLMs to deliver efficient, accurate AI agents,” said Ahmad Al-Dahle, vice president and head of GenAI at Meta. “Through our collaboration with NVIDIA and our shared commitment to open models, the NVIDIA Llama Nemotron family built on Llama can help enterprises quickly create their own custom AI agents.”
Leading AI agent platform providers including SAP and ServiceNow are expected to be among the first to use the new Llama Nemotron models.
“AI agents that collaborate to solve complex tasks across multiple lines of the business will unlock a whole new level of enterprise productivity beyond today’s generative AI scenarios,” said Philipp Herzig, chief AI officer at SAP. “Through SAP’s Joule, hundreds of millions of enterprise users will interact with these agents to accomplish their goals faster than ever before. NVIDIA’s new open Llama Nemotron model family will foster the development of multiple specialized AI agents to transform business processes.”
“AI agents make it possible for organizations to achieve more with less effort, setting new standards for business transformation,” said Jeremy Barnes, vice president of platform AI at ServiceNow. “The improved performance and accuracy of NVIDIA’s open Llama Nemotron models can help build advanced AI agent services that solve complex problems across functions, in any industry.”
The NVIDIA Llama Nemotron models use
NVIDIA NeMo
for distilling, pruning and alignment. Using these techniques, the models are small enough to run on a variety of computing platforms while providing high accuracy as well as increased model throughput.
The Llama Nemotron model family will be available as downloadable models and as
NVIDIA NIM
microservices that can be easily deployed on clouds, data centers, PCs and workstations. They offer enterprises industry-leading performance with reliable, secure and seamless integration into their agentic AI application workflows.
Customize and Connect to Business Knowledge With NVIDIA NeMo
The Llama Nemotron and Cosmos Nemotron model families are coming in Nano, Super and Ultra sizes to provide options for deploying AI agents at every scale.
Nano
: The most cost-effective model optimized for real-time applications with low latency, ideal for deployment on PCs and edge devices.
Super
: A high-accuracy model offering exceptional throughput on a single GPU.
Ultra
: The highest-accuracy model, designed for data-center-scale applications demanding the highest performance.
Enterprises can also customize the models for their specific use cases and domains with NVIDIA NeMo microservices to simplify data curation, accelerate model customization and evaluation, and apply guardrails to keep responses on track.
With
NVIDIA NeMo Retriever
, developers can also integrate
retrieval-augmented generation
capabilities to connect models to their enterprise data.
And using
NVIDIA Blueprints for agentic AI
, enterprises can quickly create their own applications using NVIDIA’s advanced AI tools and end-to-end development expertise. In fact, NVIDIA Cosmos Nemotron, NVIDIA Llama Nemotron and NeMo Retriever supercharge the new
NVIDIA Blueprint for video search and summarization
, announced separately today.
NeMo, NeMo Retriever and NVIDIA Blueprints are all available with the
NVIDIA AI Enterprise
software platform.
Availability
Llama Nemotron and Cosmos Nemotron models will be available soon as hosted application programming interfaces and for download on
build.nvidia.com
and Hugging Face.
Access
for development, testing and research is free for members of the NVIDIA Developer Program.
Enterprises can run Llama Nemotron and Cosmos Nemotron NIM microservices in production with the NVIDIA AI Enterprise software platform on accelerated data center and cloud infrastructure.
Sign up to get notified about
Llama Nemotron
and
Cosmos Nemotron
models, and join
NVIDIA at CES
.
See
notice
regarding software product information.
Categories:
Generative AI
Tags:
Artificial Intelligence
|
CES 2025
|
Cosmos
|
NVIDIA Blueprints
|
NVIDIA NIM

NVIDIA 宣布推出 Nemotron 模型系列，以推動代理型 AI 的發展

人工智慧（AI）將進入代理式 AI 的新時代，專業代理組成的團隊在這個時代中可以協助人們解決複雜問題與自動執行重複性高的工作。
藉由客製化 AI 代理，各產業的企業可以打造智慧並實現前所未有的生產力。這些先進的 AI 代理需要一套針對代理 AI 功能和能力進行優化的多個生成式 AI 模型。這種複雜性意味著對強大高效的企業級模型的需求從未如此強烈。
為了為企業代理 AI 提供基礎，NVIDIA 於今日發表 Llama Nemotron 開放式大型語言模型（LLM）系列。這些使用 Llama 開發出的模型可以協助開發人員在各種應用程式中建立與部署 AI 代理，包括客戶支援、偵測詐欺活動，以及產品供應鏈與庫存管理最佳化。
許多 AI 代理若要發揮功效，必須同時具備語言技能和感知世界，以及採取適當行動做出反應的能力。
開發人員使用全新的 NVIDIA Cosmos Nemotron 視覺語言模型（VLM）與用於
影片搜尋與摘要
的 NVIDIA NIM 微服務，便能建立代理程式來分析和回應來自自主機器、醫院、商店與倉庫，以及運動賽事、電影與新聞的圖像與影片內容。針對想要為機器人與自動駕駛車產生物理感知影片的開發人員，NVIDIA 今天另外發表了
NVIDIA Cosmos 世界基礎模型
。
開放式
Llama Nemotron
模型可
最佳化
AI
代理的運算效率與精確度
NVIDIA Llama Nemotron 模型基於 Llama 基礎模型構建，Llama 是最受歡迎且具商業可行性的開源模型集合之一，已被下載超過 6.5 億次。這些模型為 AI 代理開發提供了最佳化的構建模塊。這是基於 NVIDIA 對開發最先進模型的承諾，例如 Llama 3.1 Nemotron 70B，現已透過 NVIDIA API 目錄提供。
採用
NVIDIA 的最新技術與高品質資料集來修剪與訓練
Llama Nemotron 模型，以增強代理能力。它們在指令追蹤、聊天、函式呼叫、編碼和數學方面表現優異，又有最佳的體積大小，可在各種 NVIDIA 加速運算資源上運行。
Meta 副總裁暨 GenAI 部門主管 Ahmad Al-Dahel 表示：「代理型 AI 是 AI 發展下一個前沿，要抓住這一機遇，需要對 LLM 系統進行全堆疊最佳化，以提供高效精確的 AI 代理。我們與 NVIDIA 合作，再加上我們對開放模型的共同承諾，建構在 Llama 上的 NVIDIA Llama Nemotron 系列可協助企業快速建立自己的客製化 AI 代理。」
包括 SAP 和 ServiceNow 在內的領先 AI 代理平台供應商預計先成為首批使用全新 Llama Nemotron 模型的公司之一。
SAP 的 AI 長 Philipp Herzig 表示：「能夠跨越多個業務線合作解決複雜任務的 AI 代理，將超越當今的生成式人 AI 應用場景，將企業生產力提升到一個全新的層次。。數以億計的企業使用者將透過 SAP 的 Joule 與這些代理互動，用更快的速度完成目標。NVIDIA 全新的開放式 Llama Nemotron 模型系列將促進開發多種專門 AI 代理，進而改變業務流程。」
ServiceNow 平台 AI 部門副總裁 Jeremy Barnes 表示：「AI 代理讓組織能夠事半功倍，為業務轉型樹立新標準。NVIDIA 的開放式 Llama Nemotron 模型所提高的效能與精確度，有助於建立先進的 AI 代理服務，解決任何產業跨職能的複雜問題。」
NVIDIA Llama Nemotron 模型使用
NVIDIA NeMo
進行蒸餾、修剪和對齊。運用這些技術讓模型體積小到足以在各種運算平台上執行，同時提供高準確度與更高的模型傳輸量。
將以可下載模型和
NVIDIA NIM
微服務的形式提供 Llama Nemotron 模型系列，可輕鬆部署於雲端、資料中心、個人電腦和工作站。它們可為企業提供領先業界的效能，且能夠可靠安全且完美地整合至其代理型 AI 應用程式工作流程中。
使用
NVIDIA NeMo
客製化與連接業務知識
Llama Nemotron 和 Cosmos Nemotron 模型系列有 Nano、Super 和 Ultra 三個體積大小，提供各種規模的 AI 代理部署選擇。
Nano：成本效益最高的模型，針對低延遲的即時應用程式進行最佳化，非常適合部署在 PC 和邊緣裝置上。
Super：在單一 GPU 上提供卓越傳輸量的高精準度模型。
Ultra：精準度最高的模型，專為要求最高效能的資料中心規模應用而設計。
企業還能使用 NVIDIA NeMo 微服務針對特定的使用個案與領域客製化模型，以簡化資料管理、加速模型客製化與評估，並且應用防護機制以確保回應順利進行。
開發人員使用
NVIDIA
NeMo Retriever
，還可以整合
檢索增強生成
（RAG）功能，將模型與企業資料串連起來。
而企業使用
適用於代理型 AI 的 NVIDIA Blueprints
，可以利用 NVIDIA 先進的 AI 工具及端對端開發專業技術，快速建立自己的應用程式。事實上，NVIDIA Cosmos Nemotron、NVIDIA Llama Nemotron 與 NeMo Retriever 為今日另行發表的全新
適用於影片搜尋和摘要的 NVIDIA Blueprint
功能增添了強大動力。
NeMo、NeMo Retriever 與 NVIDIA Blueprints 皆可透過
NVIDIA AI Enterprise
軟體平台使用。
上市時間
Llama Nemotron 和 Cosmos Nemotron 模型將即將以託管 API 的形式提供，可在
build.nvidia.com
和 Hugging Face 下載使用。NVIDIA 開發人員計畫的成員可免費
取得
以進行開發、測試與研究。
企業可以使用 NVIDIA AI Enterprise 軟體平台，在加速資料中心與雲端基礎架構上，在生產環境中運行 Llama Nemotron 與 Cosmos Nemotron NIM 微服務。
註冊以獲得關於
Llama Nemotron
及
Cosmos Nemotron
模型的通知，並且參加
NVIDIA 在 CES 大會的精彩活動
。
請見有關軟體產品資訊的
通知
。
Categories:
生成式人工智慧
Tags:
Artificial Intelligence
|
CES 2025
|
Cosmos
|
NVIDIA Blueprints
|
NVIDIA NIM


Kari Briski Author Page | NVIDIA Blog
Skip to content
Artificial Intelligence Computing Leadership from NVIDIA
Search for:
Toggle Search
Home
AI
Data Center
Driving
Gaming
Pro Graphics
Robotics
Healthcare
Startups
AI Podcast
NVIDIA Life
Kari Briski
Kari Briski is the vice president of generative AI software for enterprise at NVIDIA, where she oversees strategy, roadmaps and requirements for AI software and services. Briski has over 25 years of experience in software development and 20 years as a leader in technology product management, working at IBM before joining NVIDIA in 2016. She holds a bachelor’s degree in computer engineering from the University of Pittsburgh.
How Scaling Laws Drive Smarter, More Powerful AI
Just as there are widely understood empirical laws of nature — for example, what goes up must come down, or every action has an equal and opposite reaction — the…
Read Article
NVIDIA Releases NIM Microservices to Safeguard Applications for Agentic AI
AI agents are poised to transform productivity for the world’s billion knowledge workers with “knowledge robots” that can accomplish a variety of tasks. To develop AI agents, enterprises need to…
Read Article
NVIDIA Announces Nemotron Model Families to Advance Agentic AI
Artificial intelligence is entering a new era — agentic AI — where teams of specialized agents can help people solve complex problems and automate repetitive tasks. With custom AI agents,…
Read Article
NVIDIA Launches NIM Microservices for Generative AI in Japan, Taiwan
Nations around the world are pursuing sovereign AI to produce artificial intelligence using their own computing infrastructure, data, workforce and business networks to ensure AI systems align with local values,…
Read Article
Lightweight Champ: NVIDIA Releases Small Language Model With State-of-the-Art Accuracy
Developers of generative AI typically face a tradeoff between model size and accuracy. But a new language model released by NVIDIA delivers the best of both, providing state-of-the-art accuracy in…
Read Article
How NVIDIA AI Foundry Lets Enterprises Forge Custom Generative AI Models
Businesses seeking to harness the power of AI need customized models tailored to their specific industry needs. NVIDIA AI Foundry is a service that enables enterprises to use data, accelerated…
Read Article
Mistral AI and NVIDIA Unveil Mistral NeMo 12B, a Cutting-Edge Enterprise AI Model
Mistral AI and NVIDIA today released a new state-of-the-art language model, Mistral NeMo 12B, that developers can easily customize and deploy for enterprise applications supporting chatbots, multilingual tasks, coding and…
Read Article
NVIDIA Announces CUDA-X AI SDK for GPU-Accelerated Data Science
Data scientists working in data analytics, machine learning and deep learning will get a massive speed boost with NVIDIA’s new CUDA-X AI libraries. Unlocking the flexibility of Tensor Core GPUs,…
Read Article
NGC Containers Now Available for More Users, More Apps, More Platforms
Call it a virtuous circle. GPUs are accelerating increasing numbers of data science and HPC workloads. This has enabled a wide range of scientific breakthroughs, including five of this year’s…
Read Article
Most Popular
Animals Crossing: AI Helps Protect Wildlife Across the Globe
CUDA Accelerated: How CUDA Libraries Bolster Cybersecurity With AI
Agentic AI Leaders to Showcase Latest Advancements at NVIDIA GTC
Telenor Builds Norway’s First AI Factory, Offering Sustainable and Sovereign Data Processing
March Into Gaming With GeForce NOW’s 14 Must-Play Titles for Spring
Corporate Information
About NVIDIA
Corporate Overview
Technologies
NVIDIA Research
Investors
Social Responsibility
NVIDIA Foundation
Get Involved
Forums
Careers
Developer Home
Join the Developer Program
NVIDIA Partner Network
NVIDIA Inception
Resources for Venture Capitalists
Venture Capital (NVentures)
Technical Training
Training for IT Professionals
Professional Services for Data Science
News & Events
Newsroom
NVIDIA Blog
NVIDIA Technical Blog
Webinars
Stay Informed
Events Calendar
NVIDIA GTC
NVIDIA On-Demand
Explore our regional blogs and other social networks
Privacy Policy
Manage My Privacy
Legal
Accessibility
Product Security
Contact
Copyright © 2025 NVIDIA Corporation
USA - United States
Share This
Facebook
LinkedIn
Email
Share on Mastodon
Enter your Mastodon instance URL (optional)
Share

Kari Briski， 作者 NVIDIA 台灣官方部落格
Skip to content
Artificial Intelligence Computing Leadership from NVIDIA
搜尋關鍵字:
Toggle Search
平台
智慧機器
概覽
JETSON
嵌入式系統
機器人
JETSON
資料中心
產品
資料中心 GPU
DGX
HGX
EGX
NGC
虛擬 GPU
解決方案
人工智慧與深度學習
高效能計算
虛擬 GPU
分析
應用範例
開發者
技術
CUDA-X
NVIDIA AMPERE 架構
NVIDIA VOLTA
MAGNUM
多執行個體 GPU
NVIDIA NVLINK
深度學習與人工智慧
概覽
產業
概覽
自動駕駛
醫療保健與生命科學
AI 城市
機器人
開發者
產品
概覽
DGX 系統
NVIDIA GPU 雲
NVIDIA TITAN RTX
NVIDIA TITAN V
解決方案
概覽
數據科學
推論
教育課程
AI 新創
設計視覺化
概覽
GRID
QUADRO
高階渲染技術
專業的虛擬實境解決方案
技術
NVIDIA RTX
NVLINK
TURING 架構
虛擬 GPU 技術
HOLODECK
創作者適用的
醫療保健與生命科學
概覽
給開發者
醫療圖像處理
基因體學
自動駕駛汽車
概覽
DRIVE PX
汽車產業夥伴
遊戲與娛樂
GEFORCE 遊戲平台
概覽
20 系列顯示卡
16 系列顯示卡
電競筆記型電腦
G-SYNC 顯示器
給創作者
開發者
NVIDIA 開發者
開發者新聞
開發者部落格
開發者論壇
開源平台
深度學習機構
訓練課程
GPU 科技大會
CUDA
產業
遊戲開發
醫療保健與生技
高等教育
製造業
媒體娛樂
公共部門
零售業
智慧城市
超級運算
電信業
運輸業
所有產業
驅動程式
概覽
GEFORCE 驅動程式
所有 NVIDIA 驅動程式
支援
關於 NVIDIA
概覽
NVIDIA 合作夥伴網絡
AI 運算模型
公司訊息
徵才訊息
投資人
NVIDIA 合作夥伴
NVIDIA 部落格
加入我們
RSS Feeds
訂閱電子報
聯繫我們
產品安全
Kari Briski
Kari Briski is the vice president of generative AI software for enterprise at NVIDIA, where she oversees strategy, roadmaps and requirements for AI software and services. Briski has over 25 years of experience in software development and 20 years as a leader in technology product management, working at IBM before joining NVIDIA in 2016. She holds a bachelor’s degree in computer engineering from the University of Pittsburgh.
擴展定律如何推動更有智慧又更強大的 AI 發展
就像是人們普遍理解的自然經驗定律一樣，例如有上必有下，或者每…
閱讀文章
NVIDIA 發表為代理型 AI 應用提供安全防護的 NIM 微服務
AI 代理為全球數十億名知識工作者提供可完成各種任務的「知識…
閱讀文章
NVIDIA 宣布推出 Nemotron 模型系列，以推動代理型 AI 的發展
人工智慧（AI）將進入代理式 AI 的新時代，專業代理組成的…
閱讀文章
NVIDIA 全新NIM 微服務，協助台灣多家產業組織提升效率和安全性
世界各地都在追求發展主權 AI，利用自己的運算基礎設施、資料…
閱讀文章
NVIDIA 在日本與台灣推出用於生成式 AI 的 NIM 微服務
世界各國都在追求發展主權 AI，利用自己的運算基礎設施、資料…
閱讀文章
輕量級冠軍：NVIDIA 發表有著最先進精確度的小型語言模型
生成式人工智慧（AI）的開發者通常得面臨要取捨模型大小還是精…
閱讀文章
NVIDIA AI Foundry 如何協助企業打造客製化的生成式 AI 模型
企業若想利用人工智慧（AI）的力量，需根據其特定產業需求客製…
閱讀文章
NVIDIA 宣布將推出用於 GPU 加速資料科學的 CUDA-X AI SDK
NVIDIA 全新推出的 CUDA-X AI 函式庫，將為從…
閱讀文章
NGC 容器現在開放更多使用者、更多應用程式、更多平台使用
在 SC18 發表的全新多節點容器、與 Singularit…
閱讀文章
平台
人工智慧與深度學習
智慧機器
資料中心
設計視覺化
醫療保健
自動駕駛
GeForce 遊戲
SHIELD
產品
DGX-1
DRIVE PX2
GeForce GTX 20 系列
GRID
Jetson
Quadro
SHIELD TV
Tesla
開發者
開發者專區
CUDA
訓練課程
GPU 科技大會
探究地區性部落格及其他社交網路
隱私權政策
管理我的隱私
請勿出售或分享我的資料
服務條款
輔助使用
公司政策
產品安全
聯絡方式
Copyright © 2025 NVIDIA Corporation
Taiwan