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Wednesday

  1. FactRelated story

    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

Friday

  1. Story7 reports · 3 facts

    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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Tuesday

  1. FactRelated story

    English translation is being prepared.

    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

  2. FactRelated story

    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

Sunday

  1. Story1 reports · 1 facts

    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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Monday

  1. FactRelated story

    English translation is being prepared.

    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

  4. FactRelated story

    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

  6. FactRelated story

    Nvidia joins forces with six financial institutions to establish an AI infrastructure financing 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 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

Monday

  1. Story1 reports · 1 facts

    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

    Matched fieldsTitle