With New CEOs, Is Walmart or Target the Better Buy Going Forward?<\/a><\/p>\nThe event featured several examples meant to demonstrate how \u201cvirtual twins\u201d paired with AI could alter engineering and R&D workflows.<\/p>\n
Life sciences and food science: The executives discussed integrating NVIDIA AI with Dassault\u2019s BIOVIA, framing it around building a \u201cworld model\u201d grounded in biology, physics, and material science. Huang described the need to \u201cunderstand the language of life\u201d\u2014DNA, proteins, and cells\u2014and then use generative methods to translate and create new proteins, chemicals, and materials with desired properties.<\/p>\n
As an example, Pascal cited Bel Group (maker of Babybel), saying the company aims to produce healthier foods while consuming less water and complementing dairy proteins with non-dairy proteins. He said that where development previously required \u201chundreds of physical tests for one single product,\u201d the company can now \u201cgenerate automatically the protein from the virtual twins,\u201d resulting in faster innovation and what he described as more \u201ccertified decisions.\u201d<\/p>\n
Automotive simulation and emulation: Huang described combining \u201cprincipled simulations\u201d with AI prediction models\u2014what he called surrogate and emulation models\u2014to reduce runtime while staying grounded in physics. He pointed to NVIDIA\u2019s PhysicsNeMo as a \u201cphysics-aware AI model simulation system and AI framework,\u201d saying it can deliver predictions \u201c10,000 times faster.\u201d Pascal referenced Lucid as a customer example, saying the company embeds crash behavior, aerodynamics, and vehicle performance earlier in development so engineers design not just shape but also behavior, with certification in mind.<\/p>\n
Factories and robotics: Huang argued factories are becoming systems of millions of objects, robots, and AI, and said they will be \u201csimulated and operated completely inside a Virtual Twin.\u201d Pascal cited OMRON as an example of engineering a \u201csoftware-defined factory,\u201d emphasizing designing autonomy from day one to improve flexibility, resilience, and adaptability.<\/p>\n
Huang also discussed what he called \u201cAI factories,\u201d describing three fast-growing, interlinked industrial buildouts: chip factories (including packaging), computer factories that assemble supercomputers, and AI factories that use those systems to \u201cmanufacture the AIs.\u201d He said a \u201cgigawatt AI factory is about $50 billion,\u201d and claimed \u201ctens of gigawatts\u201d are being built globally. He characterized this as the \u201clargest industrial infrastructure buildout in human history.\u201d<\/p>\n
To reduce risk and improve first-time success, Huang said NVIDIA uses Dassault\u2019s MBSE (model-based systems engineering) along with mechanical design tools to plan and simulate data centers and their systems before construction, including running networks and supercomputers inside the virtual twin. He added that virtual twins can be used during operations as AI systems modulate performance, power, temperature, and cooling over time. Huang also said NVIDIA is \u201cthe first customer\u201d in this context.<\/p>\n
The leaders also discussed AI assistants\u2014referred to as \u201cvirtual companions\u201d\u2014that can help engineers move faster, including converting unstructured inputs (like images) into structured 3D data and parametric models. When asked whether this will replace engineers, Huang argued the opposite: designers will become managers and architects of teams of AI companions, and usage of Dassault tools could expand to include both human and AI users.<\/p>\n
Pascal cited NIAR (the National Institute for Aviation Research) as an example, suggesting virtual companions could ingest regulations and continuously verify conformity\u2014shifting compliance to \u201ccompliance by design.\u201d Huang contrasted language models with \u201cworld models,\u201d saying world models must obey the laws of physics, understand causality, and use simulation and examples to learn physical behavior.<\/p>\n
On protecting knowledge, Huang said future companions would codify a user\u2019s preferences and domain expertise and should not be public, likening it to the accumulated knowledge represented by his own inbox.<\/p>\n
Both executives closed by characterizing the partnership as a way to deliver \u201cknowledge factories\u201d that power virtual twins and AI companions with accelerated computing, enabling new categories of software-defined products and operations that they said would be difficult or impossible without real-time simulation and AI.<\/p>\n
NVIDIA Corporation, founded in 1993 and headquartered in Santa Clara, California, is a global technology company that designs and develops graphics processing units (GPUs) and system-on-chip (SoC) technologies. Co-founded by Jensen Huang, who serves as president and chief executive officer, along with Chris Malachowsky and Curtis Priem, NVIDIA has grown from a graphics-focused chipmaker into a broad provider of accelerated computing hardware and software for multiple industries.<\/p>\n
The company’s product portfolio spans discrete GPUs for gaming and professional visualization (marketed under the GeForce and NVIDIA RTX lines), high-performance data center accelerators used for AI training and inference (including widely adopted platforms such as the A100 and H100 series), and Tegra SoCs for automotive and edge applications.<\/p>\n
The article “NVIDIA CEO Jensen Huang Unveils Biggest-Ever Dassault Partnership to Power AI Virtual Twins<\/a>” was originally published by MarketBeat.<\/p>\n","protected":false},"excerpt":{"rendered":"NVIDIA logo NVIDIA and Dassault Syst\u00e8mes announced their largest-ever collaboration, with Dassault integrating NVIDIA CUDA\u2011X, NVIDIA AI (physical…\n","protected":false},"author":2,"featured_media":271592,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[20],"tags":[365,56230,363,364,153582,153581,366,18973,111,139,1042,118735,69,145,153584,153583],"class_list":{"0":"post-271591","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-artificial-intelligence","8":"tag-ai","9":"tag-ai-assistants","10":"tag-artificial-intelligence","11":"tag-artificialintelligence","12":"tag-automotive-engineering","13":"tag-dassault-systemes","14":"tag-generative-ai","15":"tag-jensen-huang","16":"tag-new-zealand","17":"tag-newzealand","18":"tag-nvidia","19":"tag-nvidia-omniverse","20":"tag-nz","21":"tag-technology","22":"tag-virtual-twin","23":"tag-virtual-twins"},"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/posts\/271591","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/comments?post=271591"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/posts\/271591\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/media\/271592"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/media?parent=271591"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/categories?post=271591"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/nz\/wp-json\/wp\/v2\/tags?post=271591"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
![\"NVIDIA](\"https:\/\/www.newsbeep.com\/nz\/wp-content\/uploads\/2026\/02\/ffe52edad9a5e7b3d1e9b401d3d13a68.jpeg\")
NVIDIA logo <\/p>\n