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Today 8 items
Sep 23Wed
  1. Latent Space84

    [AINews] Claude Opus 5.5, the new default model for AINews — and everybody cuts prices 40-50%

    Anthropic released Claude Opus 5.5, the first model in the Claude 5.5 family, claiming it matches Fable 5.1 on most tasks, is about 30% faster than Opus 5, and 40% cheaper per task; token pricing dropped from $5/$25 to $4/$20, and it became the default model for Claude Code and the Claude app. OpenAI responded the same day with 50% price cuts on GPT-6 Sol and Luna.

    Why it matters: The article compiles Opus 5.5 pricing, benchmarks, and controversies, including third-party teardowns showing the 40% discount does not hold at max effort.

  2. Simon Willison22

    SF October 14th: A Birds of a Feather Session on Agentic Engineering

    Simon Willison and Jesse Vincent will co-host a Birds of a Feather event for coding agent developers in San Francisco on Wednesday, October 14, an informal agentic show-and-tell for sharing experiments. Sharing is encouraged but not required, product pitches are explicitly excluded, and unreleased work, quirky experiments, and unfinished projects without an obvious market are welcome.

  3. Simon Willison36

    Quoting @therealcornpop

    @therealcornpop pointed out on TikTok that AI-written scripts are easy to detect: not just formulaic patterns like "not X, but Y", three-part parallelism, or punctuation overload, but the more fundamental problem of empty content that lacks the author's own voice and genuine opinions.

  4. OpenAI News73

    Introducing GPT-6 Sol and Luna

    OpenAI has released two models, GPT-6 Sol and Luna, bringing frontier intelligence into everyday work, with the two models offering different balances of capability and cost.

    Why it matters: The official release positions the two product lines, helping readers understand the different capability-versus-cost trade-offs of the new models.

Sep 22Tue
  1. Simon Willison35

    llm-typesafe 0.1a0

    Simon Willison released llm-typesafe 0.1a0, an LLM plugin supporting TypeSafe AI's newly launched Jev model. It can be installed with `llm install llm-typesafe` and used by setting a typesafe API key.

  2. MIT Technology Review · AI55

    Don’t be fooled by this summer of AI hype

    Writing in MIT Technology Review, Timnit Gebru and Emily M. Bender argue that this summer's string of Anthropic and OpenAI claims — Claude Mythos's vulnerability-hunting ability, models' math breakthroughs, hacking incidents and engineer Jacob Coxon's departure remarks — differ greatly from the companies' statements once reviewed by experts.

  3. TrendForce Insights Semiconductor Industry Insights67

    By 2028, US Data Centers Could Have the Servers but Not the Power to Run Them

    Based on AI server shipments, TrendForce projects that global data center power demand capacity will reach 490.7GW by 2030, with the US at 272.4GW, while US grid deliverable capacity will be only 100.7GW, leaving a gap of more than 170GW, of which about 49GW stems from the grid being unable to deliver on schedule.

  4. Hugging Face Blog70

    Transformers now runs llama.cpp quants

    Hugging Face has announced that transformers can load GGUF models — passing a gguf_file to from_pretrained lets you run quantized checkpoints from the Hub on your local machine.

    Why it matters: Hugging Face provides official usage of GGUF in transformers plus benchmarks against llama.cpp, helping readers pick a viable local inference path.

  5. Hugging Face Blog48

    Jun Kim, oMLX creator and maintainer, joins Hugging Face to support the MLX community

    Jun Kim, creator and maintainer of oMLX, has joined Hugging Face. oMLX will shift from a side project to one with full-time maintenance and funding, while remaining Apache 2.0 open source and led by Jun. One team focus is simplifying the pipeline from transformers model definitions to reference MLX implementations, so new transformers models run on MLX faster.

  6. Simon Willison69

    Jev introduces a new shape of LLM - System One, aka Decision Models

    Last week TypeSafe AI released Jev, a new category of model it calls a System One model, which takes text input but outputs classifications, yes/no decisions, scores, and confidence as floating-point numbers. Jev charges only for input at $0.042 per million tokens, below GPT-5 Nano's $0.05/million, supports evaluating multiple questions in parallel, and suits tasks like classification, ranking, and search reranking.

  7. NVIDIA Blog30

    Why Deploying Physical AI at Scale Demands Safety at Every Layer

    NVIDIA explains that deploying Physical AI (autonomous vehicles, humanoids, and industrial robots) at scale requires a safety framework spanning hardware, software, AI behavior, and operating environments. ABI Research projects 49 million L3-L5 autonomous vehicles by 2035, and Omdia estimates about 60 million industrial robots will be deployed from 2026 to 2035.

Sep 21Mon
  1. Import AI49

    Import AI 473: The US's superintelligence strategy; human brain in a mouse skull; and machine hermeneutics

    RAND has released a lengthy report arguing that on the uncertain path to superintelligence the US should adopt a "Freedom of Action" strategy—that is, spend money now to preserve all options. The report distills seven prototype strategies across three major categories (coexistence, denial, acceleration) and lists five key uncertainties: proximity of danger, feasibility of coexistence, feasibility of restraint, decisive strategic advantage, and feasibility of suppression. The author comments that the US's current approach is close to the "acceleration" option, prioritizing speed with no safety measures.