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Tuesday

  5. Rohan PaulSelected

    The U.S. Department of Homeland Security requires civilian agencies to remove DeepSeek and its derivative products

    The U.S. Department of Homeland Security, pursuant to the 2018 Federal Acquisition Supply Chain Security Act, requires U.S. civilian agencies to remove DeepSeek and DeepSeek-related products, as well as third-party products and services developed using DeepSeek, from information technology systems. DHS states that DeepSeek's hosted models store data on servers in China, with every prompt and response passing through that service, and that the data may be combined with public information to form actionable intelligence targeting U.S. personnel and government programs; for model weights running on U.S. servers, the ban relies on warnings that the models may contain malware or other vulnerabilities. Exceptions require an application submitted 60 days in advance with sufficient justification, and systems in national security systems and secure isolated information systems are outside the scope of the order; the only Chinese model named in the order is DeepSeek, while Kimi and Qwen face similar distillation allegations.

    The U.S. Department of Homeland Security, pursuant to the 2018 Federal Acquisition Supply Chain Security Act, requires U.S. civilian agencies to remove DeepSeek and DeepSeek-related products, as well as third-party products and services developed using DeepSeek, from information technology systems. DHS states that DeepSeek's hosted models store data on servers in China, with every prompt and response passing through that service, and that the data may be combined with public information to form

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    #ai-news#English text is being prepared.#DeepSeek
  6. Ant Group's inclusionAI: New GitHub repository

    Ant Group's inclusionAI publishes the sglang_ling_v3 repository on GitHub

    Ant Group's inclusionAI launches the sglang_ling_v3 repository on GitHub. Its contents are based on the open-source inference framework SGLang, which targets large language models, vision-language models, and diffusion models, and is optimized for agent workloads, large-scale serving, and RL rollout. The repository README shows that SGLang supports GPU, TPU, NPU, CPU, and Apple Silicon, and includes the built-in image and video generation engine SGLang Diffusion.

    PyPI version

    Ant Group's inclusionAI launches the sglang ling v3 repository on GitHub. Its contents are based on the open-source inference framework SGLang, which targets large language models, vision-language models, and diffusion models, and is optimized for agent workloads, large-scale serving, and RL rollout. The repository README shows that SGLang supports GPU, TPU, NPU, CPU, and Apple Silicon, and includes the built-in image and video generation engine SGLang Diffusion.

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    #engineering#English text is being prepared.#English text is being prepared.#Open-source ecosystem
  8. Claude Code：GitHub Releases

    Claude Code v2.1.304 released

    Claude Code v2.1.304 adds a guided `/auto-mode-setup` setup that can read the project and recent sessions to let auto mode understand the environment, and now supports Bedrock, Vertex, Foundry, the Claude apps gateway, and sessions with telemetry disabled. This version also adds `/claude-api managed-agents-secure`, which checks Managed Agents configuration against Anthropic's public security guidelines without making any changes. In addition, it fixes several issues, including Linux sandbox command startup, the `rm -r` mounted-drive safety prompt, and plugins continuing to run beyond `--max-turns`.

    Claude Code v2.1.304 adds a guided /auto-mode-setup setup that can read the project and recent sessions to let auto mode understand the environment, and now supports Bedrock, Vertex, Foundry, the Claude apps gateway, and sessions with telemetry disabled. This version also adds /claude-api managed-agents-secure , which checks Managed Agents configuration against Anthropic's public security guidelines without making any changes. In addition, it fixes several issues, including Linux sandbox command

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    #engineering#Product updates#English text is being prepared.#Anthropic
  10. AWS Machine Learning

    Amazon SageMaker JumpStart 2026 Progress Review

    From January to September 2026, Amazon SageMaker JumpStart added more than 100 models from 30 providers, of which Alibaba (Qwen) contributed 29, NVIDIA 17, Mistral 7, Google 6 Gemma 4 variants, IBM 4, and Cohere 4. The new models cover multimodal, speech, image, and video generation, and introduce quantized and compact models such as GLM-5.2 FP8 and JetBrains Mellum2-12B to reduce inference costs.

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    #lab#Product updates#English text is being prepared.#English text is being prepared.

Monday

  1. Shao Meng

    pstack adds a formal verification meta-skill

    pstack v0.15.27 adds /create-formal-verification-skill, a meta-skill that automatically generates a customized verification skill and a matching verification suite based on the characteristics of the system to be verified. For example, it generates a TLA+-based approach for state machines and concurrent behavior, and a Kani-based approach for Rust undefined behavior. The feature is still in beta, and the author has already found several bugs while using it to model their own code with TLA+. poteto believes that the two historical bottlenecks of modeling and spec synchronization are well suited to being taken over by LLMs, and that formal verification can give agents strong feedback that is "mathematically impossible to violate."

    pstack v0.15.27 adds /create-formal-verification-skill, a meta-skill that automatically generates a customized verification skill and a matching verification suite based on the characteristics of the system to be verified. For example, it generates a TLA+-based approach for state machines and concurrent behavior, and a Kani-based approach for Rust undefined behavior. The feature is still in beta, and the author has already found several bugs while using it to model their own code with TLA+. pote

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    #hot-signal#Product updates#Agents#English text is being prepared.
  5. SemiAnalysis

    SemiAnalysis predicts 50GW of new global data center capacity in 2027

    SemiAnalysis predicts that global data center new capacity will reach 50GW in 2027, equivalent to the entire cumulative global market before 2024 being built within a single year. Its data center industry model shows that 60GW is currently under construction, of which more than 24GW is in the late stages of construction, with most to be delivered in 2027; so far in 2026, just under $1 trillion in data center leases have been signed, providing funding support for construction in 2027 to 2028. The report also mentions that prefabricated modular design has compressed the construction cycle to under 10 months, and holds that the power problem has been largely solved through means such as self-built generation, with the new bottleneck in 2027 to 2028 potentially shifting to memory and logic chips.

    SemiAnalysis predicts that global data center new capacity will reach 50GW in 2027, equivalent to the entire cumulative global market before 2024 being built within a single year. Its data center industry model shows that 60GW is currently under construction, of which more than 24GW is in the late stages of construction, with most to be delivered in 2027; so far in 2026, just under $1 trillion in data center leases have been signed, providing funding support for construction in 2027 to 2028. The

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    #analysis#English text is being prepared.#English text is being prepared.#English text is being prepared.

Sunday