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  1. SemiAnalysis85

    Nvidia and the World Without Jensen: What a Post-Founder Nvidia Looks Like

    SemiAnalysis argues that Nvidia was built around Jensen Huang, who has left the CEO role after 33 years, and that his departure weakens the company's long-term bets, chip allocation deals and personal supply chain lockups. The piece says Nvidia had about 60 direct reports under Huang and lacks a deep bench of successors, with Colette Kress as interim CEO and Ian Buck and Jonah Alben floated as internal technical candidates. It also ties the timing to Washington: more than 1.5GW of restricted Nvidia chips are estimated to have reached China, and the Remote Access Security Act, which passed the House 369-22, is up for a Senate vote.

    Why it matters: SemiAnalysis examines how Nvidia's founder-centric structure, supply chain deals and China policy could change after Jensen Huang's exit, and why export control legislation is moving now.

  1. The Decoder80

    Anthropic says AI cut its Claude port to AMD GPUs from months to three days

    Anthropic says it ported Claude to AMD GPUs in three days with almost no human intervention, using its frontier model Mythos to write nearly 100 percent of the kernels itself. Co-founder Tom Brown says Anthropic now trains and runs Claude across AWS Trainium, Google TPUs, Nvidia GPUs and AMD GPUs, treating them as one interchangeable compute pool. The figures come from an investor presentation and have not been independently verified; Anthropic cites three days versus the six to twelve months traditional engineering needs, measured on prompt processing with AMD MI355X GPUs.

    Why it matters: Anthropic's claim that its own model ported Claude to AMD GPUs in three days offers a concrete test of whether AI can loosen CUDA's grip on chip choice.

  1. Simon Willison78

    Anthropic IPO roadshow video details multi-chip Claude training and serving strategy

    Anthropic kicked off its IPO roadshow yesterday, and its roadshow video disclosed previously unreleased details about how the business works, including a section on compute strategy with co-founder Tom Brown. Brown said Anthropic trains and serves Claude across AWS Trainium, Google TPUs, NVIDIA GPUs and AMD GPUs, and that when the company began working with AMD GPUs this year, a system called Mythos got Claude running on AMD in three days with basically no human intervention, porting or writing almost 100% of the kernels. He also described compute multipliers as a second driver of compute advantage, saying each multiplier stacks on the ones before it and that Claude may eventually discover them entirely by itself.

    Why it matters: Anthropic's IPO roadshow video details its multi-chip training and serving strategy across four chip families, including a Claude-assisted AMD port completed in three days.

  2. NVIDIA Blog60

    NVIDIA Contributes OpenShell Agent Runtime to CNCF and Adds DSX Kubernetes Tools

    NVIDIA is contributing OpenShell, its open source runtime for securing and governing autonomous agents, to the Cloud Native Computing Foundation as a Sandbox project, and is also contributing to Google-led Agent Substrate. NVIDIA announced three new DSX AI Factory Platform components: NVIDIA Kubernetes Engine and NVIDIA Kubernetes Recipes, now in public preview, and NVIDIA Snapshot, which restores checkpointed replicas in seconds without model reload or warmup. Crusoe tested GLM-5.3 on Crusoe Cloud and cut workload ready time from roughly eight minutes to 31 seconds, while Saturn Cloud reduced vLLM startup from between two and 8.5 minutes to six and 34 seconds.

    Why it matters: NVIDIA contributes its agent security runtime OpenShell to CNCF and adds Kubernetes tooling for GPU AI factories, with early Snapshot results cutting inference startup from minutes to seconds.

  1. Modal Blog71

    Modal crosses $1B annualized run rate and raises $750M Series D at $15.75B valuation

    Modal crossed $1B in annualized run rate and raised a $750M Series D led by Accel at a $15.75B post-money valuation, with all existing investors participating. The company says usage has tripled since its Series C five months ago and grown more than 15x year-over-year, and that its Sandboxes product alone is at a $300M run rate with close to 3 billion sandboxes spun up. Modal also describes rebuilding its own file system, container runtime, scheduler and networking on a capacity pool spanning 20+ clouds, and points to recent launches in multi-node training, Modal servers and generally available VMs for Sandboxes.

    Why it matters: Modal's post explains why AI workloads pushed it to rebuild its own file system, container runtime and scheduler across 20+ clouds, a concrete view of how the AI infrastructure stack is diverging from the cloud stack.

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