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#OpenAI

3 today

Nov 16

MondayToday3 items

  3. Anthropic's Claude Fable 5.2 doesn't generate images, it paints them

    Anthropic's Claude Fable 5.2 doesn't generate images the way other AI models do. Instead of computing pixels, the language model writes Python code that places hundreds of thousands of simulated brushstrokes on a virtual canvas, complete with bristle texture and paint application. A single photorealistic parking garage scene took roughly 700,000 strokes, according to Anthropic employee Jake Eaton.

Nov 15

Sunday

  1. datasette-llm 0.1a11

    Release: datasette-llm 0.1a11 datasette-llm is the intermediate plugin for Datasette that supports configuring LLMs for use with other Datasette plugins. This release adds support for OpenAI-compatible endpoints, so you can configure Datasette to use an LLM hosted anywhere that talks the OpenAI pseudo-standard web protocol.

Nov 14

Saturday

  2. Anthropic can already retrain Mythos with "a fraction of the compute originally needed," says former researcher Coxon

    Former OpenAI and Anthropic researcher Jacob Coxon points to a slide from Anthropic's IPO roadshow as a reason he left, saying it shows the company's algorithms are improving not just quickly but at an accelerating rate. Coxon continues to call for a pause on frontier model development so competitors can catch up and human-level AI can become a commodity.

  3. OpenAI reassigns robotics researchers to other teams as general-purpose models might make specialized robotics AI unnecessary

    OpenAI is dissolving its standalone robotics team for the second time, but not because it lacks data. General-purpose models like GPT-6 Astra can apparently control robots directly, making a dedicated unit unnecessary. The researchers are being redistributed across other teams in what the company frames as a way to accelerate its robotics efforts.

  11. XYBench: Helping with the problem behind the question

    We’re releasing XYBench, a benchmark of 8K+ questions that tests how AI assistants respond to requests based on misconceptions, such as asking how to thicken frosting that keeps sliding off cupcakes when the real problem is that the cupcakes are still too warm to frost. XYBench won the Best Resource Paper Award at EMNLP 2026.

  15. Nearly 70 percent of US agencies use generative AI, and unions are finally catching up with guardrails

    US public-sector unions are increasingly pushing through protections against AI surveillance and automated firings. In Oakland, a strike vote forced retraining programs instead of layoffs, and a transport union in Ohio won veto power over autonomous vehicles. California banned so-called bossware. All of this is happening while nearly 70 percent of US government agencies already use generative AI.

Nov 13

Friday

  5. OpenAI’s data suggests that frontier models are hiding their thoughts because developers optimize for capability and compute

    OpenAI's safety team systematically investigated why the chains of thought in frontier models like GPT-6 Astra are increasingly evading oversight. Four training steps drive the erosion, including architecture choices and reinforcement learning. The analysis shows that the loss of transparency is not a law of nature but also reflects tradeoffs around capability and cost.

Nov 12

Thursday

  5. OpenAI Codex on Amazon Bedrock

    A practical guide for enterprises rolling out OpenAI Codex to developers on AWS, with Amazon Bedrock as the model backend, covering the access, governance, and cost decisions that platform, security, and finance teams need to align on.

  7. Gemini Decisions API

    Gemini Decisions API Google join Jev and OpenAI in the decision model category with "Gemini Decision 1". This new model API is almost identical to Jev: it supports the same three types of questions (yes/no, choice, and rubric-scoring) and even reuses Jev's term "Noul" for a yes/no question.