Software, APIs, and things you can use
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NVIDIA's research arm published the code for a loop where agents studied other agents' transcripts and cut their own token bill. Meanwhile South Korea's central bank measured who actually gets the AI jobs. NVLabs released SoL-Pi, an MIT-licensed extension for the Pi coding
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Beijing wrote its AI hardware ambitions into the 2026–2030 industrial blueprint on Tuesday, a former FTC chair told the labs they are already breakable under old law, and open-weight models went head-to-head with the frontier on real coding work. China's industry ministry and the
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A YC-backed inference shop just posted numbers showing the model on the label tells you almost nothing about how it performs. Meanwhile, a music startup raised money on the opposite bet: that abundance of AI-generated audio makes human taste worth more. Nari Labs reported the top scores on
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Hot Chips 2026 wrapped with a memory bet, and the funding calendar is unusually busy for a Monday. d-Matrix says stacking memory directly on the compute die beats HBM by 20x on bandwidth density. The startup's Raptor accelerator puts a TSMC N4 logic die face-to-face
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When an AI feature misbehaves, "just fine-tune it" is the most popular and most expensive wrong answer. This is the order of operations that tells you whether the weights are actually the problem — before you spend a fraction of your budget finding out. The tell is rarely
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Today's trending board is mostly about control, not capability: a code reviewer that Alibaba ran internally for two years, a verifier that refuses to let a model assert facts, a memory store for agents that forget on session close, a scanned skill registry, and a browser agent that
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The hardest part of reinforcement learning is not the algorithm. It is getting a trainer and a bunch of inference servers to keep passing weights back and forth without one of them stalling. Hugging Face just published a recipe that does it with three rented jobs, one storage bucket, an
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A system prompt is the block of instructions placed in front of a language model before the user says anything — the hidden briefing that decides who the model is pretending to be and what it is allowed to do. You never see it in ChatGPT, Claude, or a support chatbot.
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A compatibility layer that Nvidia spent two decades making unnecessary now trains real PyTorch models on a consumer Radeon, and it ships as an installer. A Windows stack built on ZLUDA + AMD's ROCm/HIP completed a real LibTorch reinforcement-learning run on an AMD Radeon RX 9060 XT,
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Today's trending list skews hard toward security: an autonomous pentest system, a red-team skill library for Claude, and a Rust CLI that solves the unglamorous problem of running five AI agents in the same repo without them stepping on each other. Worktrunk (Rust, 7,391 stars) — A
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A thread on r/LocalLLaMA surfaced a quiet line of instrumentation this week: the huggingface_hub Python library — the package most of the open-weights ecosystem uses to download models — detects which AI coding agent is driving your terminal and sends that name to Hugging Face's servers on
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An NPU is a chip built for one job: running the math that neural networks do, at a fraction of the power a general-purpose CPU or a graphics GPU would burn. The name covers anything from the block inside your phone's processor to a USB stick in