Mistral

12 days agoNews Editor

Mistral and NVIDIA team up on AI engineering tools, with physical and agentic AI benchmarks planned

Mistral has announced a partnership with NVIDIA aimed at bringing its AI models together with NVIDIA’s accelerated computing and physical modeling tools to reshape engineering workflows. The two companies said they will jointly build public benchmarks and open datasets for computer-aided engineering and electronic design automation, with the goal of standardizing how physical models and AI agents are evaluated. They also plan to use NVIDIA Omniverse for 3D simulation and asset creation. The collaboration is focused on industries including aerospace, automotive, and semiconductors, where the companies said they want to speed up simulation and create a closed-loop workflow linking simulation, AI model development, and engineering design. Neil Ashton, vice president of computational engineering at Mistral, said the combination of Mistral’s open-weight models, physical AI capabilities, and NVIDIA’s accelerated computing stack is expected to give engineers faster simulation cycles and rigorous open benchmarks.

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NVIDIA

24 days agoNews Editor

NVIDIA says developers are using AI models with Omniverse to build simulation applications

NVIDIA said developers are combining frontier AI models with the NVIDIA Omniverse library to turn simulation concepts into practical applications. According to the company, the work covers several parts of the development flow, including assembling assets, connecting physics and rendering engines, and checking whether scene behavior matches expectations. NVIDIA said the goal is to build applications that can be used to explore scenes, investigate failures, and improve designs. The company also said developers are speeding up the process by guiding AI agents and using the Omniverse platform for complex simulation development. The update outlines how Omniverse is being used alongside newer AI systems in simulation-related workflows.

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Physical AI

2 months agoNews Editor

Robots, Not Humans, Are Becoming the New Native Residents of Virtual Worlds

Antioch, a U.S. startup focused on training and validating robots inside digital environments that closely mirror the real world, closed a $32 million Series A on Sept. 8 led by Greylock. Combined with an $8.5 million seed round completed earlier this year, the company has raised $40.5 million in a little over a year. PANews said Antioch is part of a broader wave of companies drawing fresh capital as Physical AI becomes a new investment focus across the AI sector. The report argues that the infrastructure once grouped under the metaverse narrative never really disappeared. Instead, its center of gravity has shifted. NVIDIA’s Omniverse, once described as a foundation for the metaverse, is now defined on NVIDIA’s website as a set of libraries and microservices for building Physical AI applications, with product focus moving toward industrial digital twins, robot simulation and autonomous driving. PANews also points to a growing stack of specialized companies rebuilding a practical version of the virtual world: NavVis in spatial data capture, NdotLight in SimReady 3D assets for robot simulators, and Treble in acoustic simulation. The common thread is not immersion for consumers, but realism for machines. In this version of the virtual world, robots use simulation as a training ground before entering the physical world.

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NVIDIA

4 months agoNews Editor

NVIDIA says RTX Spark AI PCs could arrive this fall, with MediaTek and Taiwan suppliers in focus

NVIDIA said at SIGGRAPH 2026 that AI PCs and AI workstation products built on its RTX Spark chip could begin launching as early as this fall. The platform was developed with MediaTek and is positioned as a step toward moving AI agents from the cloud to edge devices. According to a report cited in the source article, ASUS and MSI are expected to be the first brands to roll out products, followed by Acer and GIGABYTE. The article also said NVIDIA’s Agent Toolkit has been integrated with the Omniverse library, allowing AI agents to train in GPU-accelerated physical environments and shortening development cycles for use cases such as robotics training, autonomous driving simulation, and smart factory deployment. In addition, the report outlined potential beneficiaries across Taiwan’s hardware supply chain, including brand vendors, thermal solution providers, and companies focused on high-speed connectivity and power management.

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Bit.Fan