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  1. Huxiu

    An unreleased OpenAI model produced 722 mathematics manuscripts overnight, prompting a joint criticism from 25 Fields Medalists

    OpenAI published the openai/math repository on GitHub, disclosing 722 mathematics manuscripts and 372 result groups in one go, all produced by an undisclosed internal model, covering results such as a quasi-Riemann hypothesis, reducing the exponent of matrix multiplication over the complex field to 2.25, and a four-dimensional version of the Kakeya conjecture. The authors state that each result cost on average about 3 hours of ChatGPT Pro-level compute, whereas the September attack on the Navier–Stokes equations deployed roughly 10,000 agents, ran for 88 hours, and cost millions of dollars. 25 Fields Medalists signed a joint letter titled "The Serious Misalignment of AI in Mathematics," criticizing AI companies for treating problem-solving as a marketing tool, and the advisory group of the Institute for Advanced Study in Princeton demanded that such practices stop.

    OpenAI published the openai/math repository on GitHub, disclosing 722 mathematics manuscripts and 372 result groups in one go, all produced by an undisclosed internal model, covering results such as a quasi-Riemann hypothesis, reducing the exponent of matrix multiplication over the complex field to 2.25, and a four-dimensional version of the Kakeya conjecture. The authors state that each result cost on average about 3 hours of ChatGPT Pro-level compute, whereas the September attack on the Navier

    Matched fieldsSummary、Body

    #hot-signal#English text is being prepared.#OpenAI#Papers/Research
  2. Hugging FaceSelected

    Author trained six models in two days using ML Intern prompts

    Hugging Face blogger yvrjsharma released seven prompts they used with ML Intern and showcased six projects completed within two days, including a citrus disease VLM based on Qwen3.5-2B, a Huggy character LoRA for FLUX.2 klein 4B, a camera viewpoint LoRA and a doodle LoRA for Qwen-Image 2.1, Pocket Rewriter 0.8B/2B distilled models, and a version of Agate Preview 002 distilled from 50 steps to 4 steps. The author recommends stating verified facts in prompts, requiring a pre-training baseline and smoke tests with checks, and setting spending caps, for example limiting the citrus project to 12 dollars. All prompts are available on GitHub at yvrjsharma/ml-intern-prompts, and ML Intern mode can be enabled in HuggingChat.

    4B, a camera viewpoint LoRA and a doodle LoRA for Qwen-Image 2.1, Pocket Rewriter 0.8B/2B distilled models, and a version of Agate Preview 002 distilled from 50 steps to 4 steps. The author recommends stating verified facts in prompts, requiring a pre-training baseline and smoke tests with checks, and setting spending caps, for example limiting the citrus project to 12 dollars. All prompts are available on GitHub at yvrjsharma/ml-intern-prompts, and ML Intern mode can be enabled in HuggingChat.

    Matched fieldsSummary、Body

    #lab#Tutorials / practice#Agents#English text is being prepared.