惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

量子位
cs.AI updates on arXiv.org
cs.AI updates on arXiv.org
F
Fortinet All Blogs
博客园 - 聂微东
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
Hugging Face - Blog
Hugging Face - Blog
V
Visual Studio Blog
小众软件
小众软件
有赞技术团队
有赞技术团队
雷峰网
雷峰网
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
AWS News Blog
AWS News Blog
C
Cisco Blogs
美团技术团队
T
Threat Research - Cisco Blogs
C
CERT Recently Published Vulnerability Notes
人人都是产品经理
人人都是产品经理
宝玉的分享
宝玉的分享
Threat Intelligence Blog | Flashpoint
Threat Intelligence Blog | Flashpoint
酷 壳 – CoolShell
酷 壳 – CoolShell
Stack Overflow Blog
Stack Overflow Blog
W
WeLiveSecurity
D
DataBreaches.Net
博客园 - 司徒正美
Blog — PlanetScale
Blog — PlanetScale
IT之家
IT之家
云风的 BLOG
云风的 BLOG
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
Simon Willison's Weblog
Simon Willison's Weblog
Google DeepMind News
Google DeepMind News
T
The Blog of Author Tim Ferriss
Know Your Adversary
Know Your Adversary
NISL@THU
NISL@THU
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
The Cloudflare Blog
Vercel News
Vercel News
月光博客
月光博客
T
Tailwind CSS Blog
H
Help Net Security
aimingoo的专栏
aimingoo的专栏
P
Proofpoint News Feed
Application and Cybersecurity Blog
Application and Cybersecurity Blog
Spread Privacy
Spread Privacy
cs.CL updates on arXiv.org
cs.CL updates on arXiv.org
Cisco Talos Blog
Cisco Talos Blog
Microsoft Security Blog
Microsoft Security Blog
V
V2EX
WordPress大学
WordPress大学
Cyberwarzone
Cyberwarzone
Recent Announcements
Recent Announcements

The Next Platform: In-depth coverage of high end computing

Uncle Sam Awards $2 Billion-Plus To Quantum Companies, But Wants A Cut Oak Ridge Starts Weaving Together A Quantum, Classical HPC, And AI System Stack Dell Bulks Up Hardware As AI Infrastructure Shifts To On-Premises Cisco Wins Over AI Customers With Merchant Silicon And Optics With Its IPO Done, Cerebras Can Get Back To Pushing The AI Envelope HPE Throws VM Users A Lifeline, Unifying Containers And VM Management In Cloud Stack OpenAI, Microsoft And Friends Build A Better, More Scalable Ethernet Compute And Memory Price Hikes Drive IT Spending Way Higher Sometimes, Air Is The Only Way For AI Systems To Keep Their Cool Arista Rides AI Scale Out Networks, Moves Into Scale Across, And Awaits Scale Up If You Can Make A Compute Engine, You Can Sell A Compute Engine Cleveland Clinic Simulates Large Proteins With Quantum-Centric Supercomputing Broadcom Helps CPU And XPU Makers Go Vertical With Compute Microsoft Committed To Doubling AI Infrastructure In Two Years Google Is A Full Stack AI Player, And Is Playing Well AWS Will Be An OEM, Just Like Google And Maybe Microsoft New Google Networks Tuned Up For GenAI Inference And Training Microsoft And OpenAI Remain Friends, Are Looking To Hook Up With Others AI-Driven CPU Shortage Saves Intel’s Financial Cookies The GenAI Battle Shifts From Frontier Models To Agentic Platforms With TPU 8, Google Makes GenAI Systems Much Better, Not Just Bigger Cisco Scales Out Quantum Systems With A Quantum Network Switch The Second Time Will Be The IPO Charm For Cerebras Imagine An Army Of AI Minions Handling Incident Response AI Will Soon Drive A Third Of TSMC’s Business Bechtolsheim & Friends Breathe Life Into Pluggable Optics One Last Time How HPC And AI Digital Twins Accelerate Quantum Error Correction The Embrace Of AI In Design Transforms Cadence And Its Customers Nvidia Brings The Power Of Open Source AI Models To Quantum Computing Building The Imperfect Beast For Enterprises, GPUs Need Virtualization As Much As CPUs Ever Did CoreWeave Takes As Much Financial Engineering As It Does Datacenter Design Contemplating Meta’s Homegrown MTIA Compute Engine Roadmap Most Neoclouds, Sovereigns, And Enterprises Will Buy, Not Build, Their AI Stacks Broadcom And Google Benefit Mightily From Anthropic’s Meteoric Growth Rebellions AI Rings Up The Money To Rack Up AI Inference Systems Nvidia Software Pushes MLPerf Inference Benchmarks To New Highs Broadcom Makes Its Pitch To Run Kubernetes On VMware VCF The $2 Billion Nvidia Deal With Marvell Is About A Lot More Than NVLink Fusion Classiq Says Quantum Is On Its Way, But Patience Is Needed Demonstrating The Scientific Usefulness Of Quantum Systems We Need Servers – Lots Of Servers. . . . Arm Comes Full Circle With Homegrown, AI-Tuned Server CPU Riding The Memory Boom And Trying To Avoid The Bust Data Analytics Helps Make The Mighty Lionesses Roar Driving Down The AI System Roadmap With Nvidia The Open Agentic AI World According To Nvidia Nvidia Finally Admits Why It Shelled Out $20 Billion For Groq Nvidia Says OpenClaw Is To Agentic AI What GPT Was To Chattybots IBM Unrolls Blueprint For Quantum-Classical HPC Computing Women Get Data-Driven Health Boost As The FA Tackles Sports Science Four Months Into Its Comeback, Zapata Stakes Its Claim In Quantum Software Eridu Cuts To The AI Networking Chase With High Radix Switch System HPE Works Harder And Smarter To Chase Datacenter Profits We Need A Proper AI Inference Benchmark Test How AI Is Boosting Gender Equality In High Performance Racing Custom Compute Engine Biz Growing More Than Marvell Ever Hoped Broadcom May Become The Biggest Counterbalance To Nvidia Ayar Labs Gets $500 Million To Ramp Photonics Into 2028 AI Systems With Cisco Outshift, Agentic AI Is Teed Up For the Internet Of Cognition Nvidia Sees The Light On Silicon Photonics And Maybe Optical Switching AI Servers Finally Dominate Dell’s Systems Business VAST Data: What Controls The Data Is More Important Than What Stores It So Far, Nobody Turns Tokens Into Money Like Nvidia SambaNova Pits Its Engineering Against Nvidia For Agentic AI Some More Game Theory, This Time On The AMD-Meta Platforms Deal AMD Says “Helios” Racks And MI400 Series GPUs On Track For 2H 2026 CPU-Only Compute Still Matters To A Lot Of HPC Centers Taalas Etches AI Models Onto Transistors To Rocket Boost Inference Some Game Theory On That Nvidia-Meta Platforms Partnership AI Eats The World, And Most Of Its Flash Storage The Current AI Networking Wave Will Be A Tsunami Of Money By 2027 The Memory Crunch Pinches Cisco’s Profits Only A Few AI Platforms Can Survive The Greatest AI Show On Earth Cisco Doubles Up The Switch Bandwidth To Take On AI Scale Out And Eventually Scale Up Datacenter Spending Forecast Revised Upwards – Yet Again The Twin Engine Strategy That Propels AWS Is Working Well With GenAI Turbochargers, Google Is Shifting Its Cloud Into A Higher Gear AMD Finally Makes More Money On GPUs Than CPUs In A Quarter TACC Explores Mixed Precision And FP64 Emulation For HPC With Horizon Robotics Will Break AI infrastructure: Here's What Comes Next Oracle’s Financing Primes The OpenAI Pump Gartner Takes Another Stab At Forecasting AI Spending Microsoft Is More Dependent On OpenAI Than The Converse Big Blue Poised To Peddle Lots Of On Premises GenAI Microsoft Takes On Other Clouds With “Braga” Maia 200 AI Compute Engines Nvidia’s $2 Billion Investment In CoreWeave Is A Drop In A $250 Billion Bucket Intel Is Still Struggling In The Datacenter, But It Could Get Better Is Nvidia Assembling The Parts For Its Next Inference Platform? TSMC Has No Choice But To Trust The Sunny AI Forecasts Of Its Customers Cerebras Inks Transformative $10 Billion Inference Deal With OpenAI By Decade’s End, AI Will Drive More Than Half Of All Chip Sales Startup Quantum Elements Brings AI, Digital Twins To Quantum Computing D-Wave Makes Gate-Model Power Move With Quantum Circuits Buy Building The Future Of Software In The AI-Native Era Arista Modular Switches Aim At Scale Across Networks, Hit Scale Out, Too NextSilicon Takes Aim At CPUs And GPUs With “Maverick-2” Dataflow Engine How HPC Is Igniting Discoveries In Dinosaur Locomotion – And Beyond Oracle First In Line For AMD “Altair” MI450 GPUs, “Helios” Racks
Dassault And Nvidia Bring Industrial World Models To Physical AI
Jeffrey Burt Jeffrey Burt · 2026-02-05 · via The Next Platform: In-depth coverage of high end computing

During his more than two decades with Nvidia, Rev Lebaredian has had a ringside seat to the show that has been the evolution of modern AI, from the introduction of the AlexNet deep convolutional neural network that made waves by drastically lowering the error rate at the 2012 ImageNet challenge to the introduction of generative AI and now agentic AI, where systems can create AI assistance to help with knowledge work.

That said, the next step will be even more significant.

“The real value of AI is going to express itself when we apply it to the physical world, in the era that is coming that we call ‘physical AI,’” Lebaredian, vice president of Omniverse and simulation at Nvidia, said during a press briefing this week. “With physical AI grounded in the laws of physics, AI that understands the physical world and how things in the world operate, we can unlock incredible use cases from design and engineering, digital biology, material sciences, and the ultimate expression of physical AI, which is general robotics.”

However, he added, to do this, “we first have to model the world inside a computer. We need to represent the physical world accurately so that we can design, build, and operate things in the real world.”

For this, Nvidia is expanding its 25-year partnership with Dassault Systemes, a French company that over the past 45 years has developed digital twin technologies. The two companies will combine Nvidia’s AI infrastructure, open models, and software libraries with Dassault’s latest digital-twin technologies to create a shared AI platform that will become the foundation for the development of what they’re calling “industry world models.”

The companies announced the enhanced partnership at Dassault’s annual user conference – 3DExperience World – this week in Houston.

As defined by Nvidia and Dassault, these models will be able to simulate and operate highly complex systems. from tiny molecules in drugs to massive manufacturing facilities. The goal is to give industries like biology, materials science, engineering, and manufacturing scalable, accelerated, and intelligent simulation capabilities based on a unique industrial AI architecture, science-validated world models, and grounded in science and industrial knowledge.

“World models allow AI to understand cause and effect, imagine possible futures, and make smarter decisions,” Florence Hu-Aubigny, Dassault’s executive vice president of R&D, told journalists. “Industry world models go further. They embed the first principle – physics, engineering laws, and system constraints – with four decades of industrial knowledge and know-how we’ve accumulated with our clients. They combine multi-scale, multi-discipline modeling and simulation with AI, spanning materials, components, machines, factory, and the entire industrial ecosystem, including causality, reasoning, and intent. These science-validated AI models guarantee that everything they generate aligns with the real-world industrial world.”

It comes a year after Dassault introduced its 3D Universes – which the company represents as “3D UNIV+RSES” – that include its latest digital twin technologies, generative AI to automatically generate and refine designs, and real-time data from sensors and IoT devices integrated with the virtual twin.

“With 3D Universes, our new value proposition is to become the knowledge factories, factories for learning and generating,” Hu-Aubigny said. The company’s Gen7 platform – introduced last year – and “3D universes are becoming the virtual twin factories of the world, powered by industry world models, revealed by a new way of working the virtual companion to accelerate by effective and sustainable and efficient innovation.”

Dassault’s virtual companions are key to Dassault’s 3D Universe vision, AI-based and context-aware assistants for industrial users that are integrated into its 3DExperience platform. The company. The company has three of them – Aura for business, Leo for engineering challenges, and Marie, which provides deep scientific expertise – that understand intent, can reason with the industry world model, and orchestrate actions.

What Dassault needed to propel this vision of virtual twins, industry world models, and virtual companions were AI factories and technologies at scale, she said, leading to the expanded Nvidia partnership. It will be a step forward for these industries, creating simulation environments built for their businesses rather than trying to adapt more general-purpose AI to suit the job.

This comes at a time when manufacturers are speeding up their adoption and use of AI. Rockwell Automation found in its State of Smart Manufacturing report last year that 56 percent of manufacturers are piloting AI-based smart manufacturing technologies, while 20 percent are using them at scale and another 20 percent are planning to invest. In addition, 95 percent have invested or plan to invest in AI, machine learning, generative AI, or casual AI in the next five years.

With the expanded partnership, Dassault will establish and deploy AI factories built using Nvidia’s infrastructure and offered to organizations under its Outscale cloud brand on three continents. The AI factories will include the ability to run AI models on Dassault’s 3DExperience platform from the cloud to ensure the sovereignty of the users, ensuring data privacy and intellectual property protection.

Meanwhile, Nvidia will use Dassault’s model-based systems engineering (MBSE) technology to design AI factories, with its Rubin platform being up first. The MBSE technology also will be integrated into Nvidia’s Omniverse DSX Blueprint, its open reference design and simulation framework for building and running gigawatt-scale AI datacenters.

The company’s pointed to several uses cases to outline the benefits of the combined technologies. Nvidia’s BioNeMo platform will work with Dassault’s Biovia world models to advance the discovery of new molecules and materials in biology and materials research, while Dassault’s Simulia AI-based virtual twins will use Nvidia’s CUDA-X libraries and AI physics libraries to help designers and engineers more accurately and instantly predict outcomes.

Nvidia’s Omniverse physical AI libraries will be integrated into Dassault’s Delmia virtual twin for global production systems for autonomous and software-defined production systems and Nvidia’s AI technologies and Nemotron open models will be combined with the 3DExperience platform, industry world models will be combined with Dassault’s industry world models and virtual companions of the 3DExperience agentic platform.