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NVIDIA releases surgical generative simulation model Cosmos3-H-Dreams
NVIDIA has released the surgical generative simulation model Cosmos3-H-Dreams. The model is specialized from the 16-billion-parameter Cosmos3-H-Embodied-Nano for action-conditioned video generation of cholecystectomy. Official information shows that the model was trained with 28 action dimensions, 832 x 480 video, and 10 Hz action alignment, and was distilled into two student checkpoints, four-step and two-step; the two-step version was trained separately and offers faster inference but lower image quality. NVIDIA also provides the FlashDreams streaming runtime, as well as methods for adapting the model to proprietary data and controllers, and states that the model is a research simulator, not a validated clinical system. There are currently no subsequent development facts.
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View story:NVIDIA releases surgical generative simulation model Cosmos3-H-Dreams
Evan Conrad says NVIDIA cannot build its own compute trading market
On October 21, 2026, SF Compute CEO Evan Conrad argued on the Latent Space podcast that NVIDIA cannot build its own compute trading market. His reasoning is that companies with large hardware or inference businesses find it difficult to operate a neutral exchange. In the same appearance, Conrad also said that the compute market must first achieve physical delivery—that is, actually delivering usable GPU compute—before discussing financialization; otherwise, market manipulation and basis risk are likely to arise. He explained that SF Compute is expanding from subleasing GPU clusters to building its own cloud operations capability in order to achieve physical delivery of GPU contracts, so that buyers receive usable compute rather than cash settled against an index; the company does not hold hardware in order to remain neutral, and it already supports customers in partitioning InfiniBand fabric online themselves. He also said that SF Compute has placed 5% of its capacity on the order book, that customers who spend $100 to buy capacity can on average recover $25 by reselling it, and that hundreds of millions of dollars in volume has already been traded. There are currently no subsequent developments.
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View story:Evan Conrad says NVIDIA cannot build its own compute trading market
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NVIDIA releases real-time surgical world model Cosmos3-H-Dreams
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On October 16, 2026, the German federal government plans to cooperate with Nvidia on industrial AI applications and is prepared to invest a sum in the triple-digit millions of euros. The project focuses on what Nvidia calls "physical AI," that is, AI such as robots and automated industrial equipment that can interact with the real world, while also developing high-performance AI models for the factory of the future; German companies such as Siemens also plan to participate. On October 20, the German federal government and NVIDIA signed a joint declaration of intent to cooperate on frontier models for physical AI and drive the scaled deployment of industrial AI in Germany and Europe; NVIDIA also announced plans to invest in four German startups—Agile Robots, Avelios Medical, Mirelo, and Reflex Aerospace—as part of its nearly $10 billion European investment. On October 21, at GTC Berlin, NVIDIA announced that European ecosystem partners are adopting the NVIDIA DSX AI factory platform.
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View story:The German federal government plans to cooperate with Nvidia
Altera and Nvidia jointly develop Holoscan Sensor Bridge
Altera has launched FPGAs for the Nvidia Holoscan Sensor Bridge (HSB), targeting the physical AI market including robotics and autonomous driving. The architecture connects in the order of sensors, FPGA, Ethernet, and GPU; the FPGA aggregates multi-protocol sensor data and handles low-latency tasks such as localization, motor control, and image preprocessing, then writes directly into Nvidia GPU memory over Ethernet, bypassing the CPU to reduce latency. Altera offers four FPGA families—Cyclone, Agilex 3, Agilex 5, and Agilex 7—and is collaborating with Terasic and Critical Link to develop a sensor board and SOM ecosystem.
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View story:Altera and Nvidia jointly develop Holoscan Sensor Bridge
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NVIDIA releases surgical generative simulation model Cosmos3-H-Dreams
NVIDIA has released the surgical generative simulation model Cosmos3-H-Dreams. The model is specialized from the 16-billion-parameter Cosmos3-H-Embodied-Nano for action-conditioned video generation of cholecystectomy. Official information shows that the model was trained with 28 action dimensions, 832 x 480 video, and 10 Hz action alignment, and was distilled into two student checkpoints, four-step and two-step; the two-step version was trained separately and offers faster inference but lower image quality. NVIDIA also provides the FlashDreams streaming runtime, as well as methods for adapting the model to proprietary data and controllers, and states that the model is a research simulator, not a validated clinical system. There are currently no subsequent development facts.
NVIDIA has released the surgical generative simulation model Cosmos3-H-Dreams. The model is specialized from the 16-billion-parameter Cosmos3-H-Embodied-Nano for action-conditioned video generation of cholecystectomy. Official information shows that the model was trained with 28 action dimensions, 832 x 480 video, and 10 Hz action alignment, and was distilled into two student checkpoints, four-step and two-step; the two-step version was trained separately and offers faster inference but lower im
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NVIDIA Completes 104-Qubit Fault-Tolerant Quantum Computing Simulation on JUPITER
NVIDIA announced that it has completed a 104-qubit fault-tolerant quantum computing simulation on the JUPITER supercomputer at the Jülich Supercomputing Centre in Germany, calling it the largest full simulation of a fault-tolerant quantum processor to date. The simulation validated the magic state cultivation method, requiring 90% fewer physical qubits than previous methods and running under realistic noise conditions. The research team first developed the method on the GB200 NVL72 system at NVAQC, then scaled it to 8,192 GPUs on JUPITER, using cuQuantum and CUDA-Q to complete the computation. Currently, the only source for this event is NVIDIA's official announcement, with no subsequent independent developments yet.
NVIDIA announced that it has completed a 104-qubit fault-tolerant quantum computing simulation on the JUPITER supercomputer at the Jülich Supercomputing Centre in Germany, calling it the largest full simulation of a fault-tolerant quantum processor to date. The simulation validated the magic state cultivation method, requiring 90% fewer physical qubits than previous methods and running under realistic noise conditions. The research team first developed the method on the GB200 NVL72 system at NVA
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Evan Conrad says NVIDIA cannot build its own compute trading market
On October 21, 2026, SF Compute CEO Evan Conrad argued on the Latent Space podcast that NVIDIA cannot build its own compute trading market. His reasoning is that companies with large hardware or inference businesses find it difficult to operate a neutral exchange. In the same appearance, Conrad also said that the compute market must first achieve physical delivery—that is, actually delivering usable GPU compute—before discussing financialization; otherwise, market manipulation and basis risk are likely to arise. He explained that SF Compute is expanding from subleasing GPU clusters to building its own cloud operations capability in order to achieve physical delivery of GPU contracts, so that buyers receive usable compute rather than cash settled against an index; the company does not hold hardware in order to remain neutral, and it already supports customers in partitioning InfiniBand fabric online themselves. He also said that SF Compute has placed 5% of its capacity on the order book, that customers who spend $100 to buy capacity can on average recover $25 by reselling it, and that hundreds of millions of dollars in volume has already been traded. There are currently no subsequent developments.
On October 21, 2026, SF Compute CEO Evan Conrad argued on the Latent Space podcast that NVIDIA cannot build its own compute trading market. His reasoning is that companies with large hardware or inference businesses find it difficult to operate a neutral exchange. In the same appearance, Conrad also said that the compute market must first achieve physical delivery—that is, actually delivering usable GPU compute—before discussing financialization; otherwise, market manipulation and basis risk are
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Altera and Nvidia jointly develop Holoscan Sensor Bridge
Altera has launched FPGAs for the Nvidia Holoscan Sensor Bridge (HSB), targeting the physical AI market including robotics and autonomous driving. The architecture connects in the order of sensors, FPGA, Ethernet, and GPU; the FPGA aggregates multi-protocol sensor data and handles low-latency tasks such as localization, motor control, and image preprocessing, then writes directly into Nvidia GPU memory over Ethernet, bypassing the CPU to reduce latency. Altera offers four FPGA families—Cyclone, Agilex 3, Agilex 5, and Agilex 7—and is collaborating with Terasic and Critical Link to develop a sensor board and SOM ecosystem.
Altera has launched FPGAs for the Nvidia Holoscan Sensor Bridge (HSB), targeting the physical AI market including robotics and autonomous driving. The architecture connects in the order of sensors, FPGA, Ethernet, and GPU; the FPGA aggregates multi-protocol sensor data and handles low-latency tasks such as localization, motor control, and image preprocessing, then writes directly into Nvidia GPU memory over Ethernet, bypassing the CPU to reduce latency. Altera offers four FPGA families—Cyclone,
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The German federal government plans to cooperate with Nvidia
On October 16, 2026, the German federal government plans to cooperate with Nvidia on industrial AI applications and is prepared to invest a sum in the triple-digit millions of euros. The project focuses on what Nvidia calls "physical AI," that is, AI such as robots and automated industrial equipment that can interact with the real world, while also developing high-performance AI models for the factory of the future; German companies such as Siemens also plan to participate. On October 20, the German federal government and NVIDIA signed a joint declaration of intent to cooperate on frontier models for physical AI and drive the scaled deployment of industrial AI in Germany and Europe; NVIDIA also announced plans to invest in four German startups—Agile Robots, Avelios Medical, Mirelo, and Reflex Aerospace—as part of its nearly $10 billion European investment. On October 21, at GTC Berlin, NVIDIA announced that European ecosystem partners are adopting the NVIDIA DSX AI factory platform.
On October 16, 2026, the German federal government plans to cooperate with Nvidia on industrial AI applications and is prepared to invest a sum in the triple-digit millions of euros. The project focuses on what Nvidia calls "physical AI," that is, AI such as robots and automated industrial equipment that can interact with the real world, while also developing high-performance AI models for the factory of the future; German companies such as Siemens also plan to participate. On October 20, the Ge
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On October 19, 2026, Nvidia released open-weight models for always-on agents and edge computing. According to TechCrunch AI, the Nemotron 3.5 Super VL is a 120-billion-parameter enterprise-grade agent model, which Nvidia says can achieve accuracy comparable to Nemotron 3 Ultra on instruction-following and tool-calling tasks; two lightweight Bolt models are designed to run locally on AI PCs equipped with RTX Spark chips and on DGX Spark workstations. The report said Super VL and Nemotron 3.5 Bolt 74B-A9B 24GB are already available, and the smallest Bolt E4B will launch later this month. On October 21, Nvidia announced an expansion of its open model portfolio covering language, robotics, biology and quantum computing, positioned around European sovereign intelligence; the portfolio includes Nemotron 3.5 Super VL and Nemotron 3.5 Bolt, among others. The report said Super VL is now available on Hugging Face, ModelScope, OpenRouter and build.nvidia.com, and Bolt E4B 4GB is expected to be available on October 23.
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View story:Nvidia releases open-weight models for enterprise agents and PCs
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NVIDIA completes 104-qubit fault-tolerant quantum computing simulation on JUPITER
NVIDIA announced that it has completed a 104-qubit fault-tolerant quantum computing simulation on the JUPITER supercomputer at the Jülich Supercomputing Centre in Germany, calling it the largest full simulation of a fault-tolerant quantum processor to date. The simulation validated the magic state cultivation method, requiring 90% fewer physical qubits than previous methods and running under realistic noise conditions. The research team first developed the method on the GB200 NVL72 system at NVAQC, then scaled it to 8,192 GPUs on JUPITER, using cuQuantum and CUDA-Q to complete the computation. Currently, the only source for this event is NVIDIA's official announcement, with no subsequent independent developments yet.
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View story:NVIDIA Completes 104-Qubit Fault-Tolerant Quantum Computing Simulation on JUPITER