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Sunday

  1. Story1 reports · 1 facts

    Flapping Airplanes Completes $1 Billion Financing

    Flapping Airplanes Inc. announced the completion of $1 billion in new financing. According to a SiliconANGLE report on October 22, 2026, Bloomberg said its valuation reached $6 billion; the company was founded about a year ago and has no commercial product yet. The report said that in its first year it mainly invested in research and development of new GPU primitives, and its megakernel framework can simultaneously complete full training, inference, and game running within a single kernel, allowing memory-bound inference and compute-bound training to overlap on the same chip. The Series A round was co-led by Index Ventures and Lux Capital, with Sequoia Capital and GV, investors in the $180 million seed round in January, continuing to participate, and Nvidia and others also on the list of institutional investors. There are currently no subsequent development facts.

    ts megakernel framework can simultaneously complete full training, inference, and game running within a single kernel, allowing memory-bound inference and compute-bound training to overlap on the same chip. The Series A round was co-led by Index Ventures and Lux Capital, with Sequoia Capital and GV, investors in the $180 million seed round in January, continuing to participate, and Nvidia and others also on the list of institutional investors. There are currently no subsequent development facts.

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  2. Story1 reports · 1 facts

    Daytona Completes $60 Million Series B Funding Round

    Daytona, which provides cloud infrastructure for AI agents, has completed a $60 million Series B funding round. According to a Tech.eu report on October 20, 2026, the round was led by FirstMark, valuing the company at $1 billion, with cumulative funding reaching $91 million. Its platform provides isolated Linux, Windows, and macOS computing environments for agents through a single API, supporting task pausing, resuming, and continued exploration, with customers including Anthropic, OpenAI, NVIDIA, Cursor, and Cognition. The company says its revenue run rate grew 25-fold from January to September, and the new funds will be used to expand its agent cloud platform, scale up computing capacity, and hire in San Francisco, Croatia, and Singapore. There are currently no subsequent developments.

    isolated Linux, Windows, and macOS computing environments for agents through a single API, supporting task pausing, resuming, and continued exploration, with customers including Anthropic, OpenAI, NVIDIA, Cursor, and Cognition. The company says its revenue run rate grew 25-fold from January to September, and the new funds will be used to expand its agent cloud platform, scale up computing capacity, and hire in San Francisco, Croatia, and Singapore. There are currently no subsequent developments.

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  3. Story1 reports · 1 facts

    Matt Turck announced that he is leading Daytona's Series B funding round

    Matt Turck announced that he is leading Daytona's Series B funding round. According to Fortune Tech, Daytona, which provides cloud sandboxes for AI agents, has completed a $60 million Series B funding round at a valuation of $1 billion, led by FirstMark, bringing its total funding to approximately $91 million. Matt Turck said that FirstMark led the Series A round earlier this year and is now leading the Series B round as well. The report also said that Daytona's customers include Anthropic, OpenAI, Nvidia, Cursor, Cognition, Meta, and Cohere; CEO Burazin said the company's revenue run rate grew 25-fold between January and September, and said it can provision a new sandbox for an agent within 60 milliseconds.

    tion of $1 billion, led by FirstMark, bringing its total funding to approximately $91 million. Matt Turck said that FirstMark led the Series A round earlier this year and is now leading the Series B round as well. The report also said that Daytona's customers include Anthropic, OpenAI, Nvidia, Cursor, Cognition, Meta, and Cohere; CEO Burazin said the company's revenue run rate grew 25-fold between January and September, and said it can provision a new sandbox for an agent within 60 milliseconds.

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  4. Story1 reports · 1 facts

    Meta releases technical details of the Prometheus supercluster

    Meta's engineering team has published technical details of the Prometheus supercluster. Located in New Albany, Ohio, the cluster currently consists of hundreds of thousands of GPUs and operates as a single machine, with plans to scale to approximately 1 million GPUs. Meta confirmed that the first phase has already used the cluster to train the Muse family of foundation models (including Muse Wonder), with Muse Wonder achieving pretraining goodput of over 85% and reinforcement learning goodput of over 90%. Meta also disclosed two platforms: Catalina, based on NVIDIA GB200 NVL72, and Clemente, based on GB300 NVL72, as well as the upcoming Vera Rubin NVL72 platform.

    s of GPUs and operates as a single machine, with plans to scale to approximately 1 million GPUs. Meta confirmed that the first phase has already used the cluster to train the Muse family of foundation models (including Muse Wonder), with Muse Wonder achieving pretraining goodput of over 85% and reinforcement learning goodput of over 90%. Meta also disclosed two platforms: Catalina, based on NVIDIA GB200 NVL72, and Clemente, based on GB300 NVL72, as well as the upcoming Vera Rubin NVL72 platform.

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Wednesday

  1. Story1 reports · 1 facts

    Porsche and others announce joint construction of a shared data flywheel for autonomous driving

    Porsche, Volkswagen Group brands and CARIAD announce the joint construction of a shared data flywheel for autonomous driving development. The news was announced on October 21, 2026 at the NVIDIA GTC Berlin conference, with Porsche leading initial implementation and ecosystem integration, and Voxel51, NVIDIA and Microsoft participating. According to Voxel51, the group's connected fleet generates data each day equivalent to 11,000 ordinary drivers, and the goal of the cooperation is to reduce repetitive real-vehicle testing by up to 90% and shorten AI regression testing cycles by up to 85%. In terms of division of labor, Voxel51 provides the data layer and supports six workflows including multimodal retrieval, automatic annotation and scenario filtering, NVIDIA provides tools such as Cosmos Data Factory and Omniverse NuRec, and Microsoft Azure provides cloud and computing power. The cooperation is currently at the announcement stage, with no subsequent progress disclosed.

    Volkswagen Group brands and CARIAD announce the joint construction of a shared data flywheel for autonomous driving development. The news was announced on October 21, 2026 at the NVIDIA GTC Berlin conference, with Porsche leading initial implementation and ecosystem integration, and Voxel51, NVIDIA and Microsoft participating. According to Voxel51, the group's connected fleet generates data each day equivalent to 11,000 ordinary drivers, and the goal of the cooperation is to reduce repetitive r

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Tuesday

  1. Story1 reports · 1 facts

    DeepSeek open-sources inference framework DeepInfer

    On October 20, 2026, DeepSeek announced the open-sourcing of its internal production-grade inference framework, DeepInfer. According to Latent Space, the framework powers DeepSeek-V4.1-Flash, is customized based on vLLM, supports distributed inference, speculative decoding, SWA Bounded Replay, and structured output, and targets the NVIDIA SM100 and Huawei Ascend 950 platforms; the published single-cluster production figures are 155 trillion tokens processed per day, a 96% input cache hit rate, 400 ms first-token latency, and a generation speed of 230 tokens/s. The report also noted that components such as KV cache management and load balancing have not yet been fully open-sourced. The next day, DeepSeek published the DeepInfer technical report on Zhihu, disclosing internal details including the hardware selection for Prefill and Decode and the KVCache targets, and providing data showing a single cluster serving 155 trillion Tokens/day at $38 per card per hour at off-peak prices. The framework is currently open-sourced, but the KV cache system, Prefill/Decode disaggregation, and load balancing required for a complete service are not fully included in this open-source project.

    framework powers DeepSeek-V4.1-Flash, is customized based on vLLM, supports distributed inference, speculative decoding, SWA Bounded Replay, and structured output, and targets the NVIDIA SM100 and Huawei Ascend 950 platforms; the published single-cluster production figures are 155 trillion tokens processed per day, a 96% input cache hit rate, 400 ms first-token latency, and a generation speed of 230 tokens/s. The report also noted that components such as KV cache management and load balancing ha

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  2. Story2 reports · 1 facts

    Meta says it is training the Muse foundation model on the Prometheus supercomputing cluster

    Meta announced that the first phase of its gigawatt-scale supercomputing cluster Prometheus has been completed in New Albany, Ohio, and is being used to train the Muse series of foundation models, including Muse Wonder. The cluster currently consists of hundreds of thousands of GPUs, with a full-scale target of about 1 million, and has deployed two generations of platforms, NVIDIA GB200 NVL72 (Catalina) and GB300 NVL72 (Clemente), with Vera Rubin NVL72 to be introduced later. Meta says Muse Wonder's pre-training goodput exceeds 85%, reinforcement learning goodput exceeds 90%, and the interruption rate has been reduced by 99% from its mid-2025 peak. Subsequent reports added that during Muse Wonder training, an interruption occurred on average only about every 47K GPU hours; Meta said that in a cluster of this scale, even a single host failing to meet performance standards would slow down an entire training round, so Prometheus was designed for large-scale fault tolerance.

    including Muse Wonder. The cluster currently consists of hundreds of thousands of GPUs, with a full-scale target of about 1 million, and has deployed two generations of platforms, NVIDIA GB200 NVL72 (Catalina) and GB300 NVL72 (Clemente), with Vera Rubin NVL72 to be introduced later. Meta says Muse Wonder's pre-training goodput exceeds 85%, reinforcement learning goodput exceeds 90%, and the interruption rate has been reduced by 99% from its mid-2025 peak. Subsequent reports added that during Mus

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