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Friday

Thursday

  3. Hacker News Popular

    Open Athena author David Hall analyzes why there is no public pool for post-training data

    Open Athena author David Hall points out that pretraining has ready-made public corpora such as Common Crawl, whereas post-training consumes tasks rather than documents, so there is no corresponding public data pool. He uses SWE-bench as an example to illustrate the cost of task creation: among more than 90,000 PRs from 12 Python repositories, only 2,294 became original tasks, and after OpenAI manually reviewed 1,699 of them, only 500 Verified tasks remained. He believes the open source community needs to systematically transcribe human activity into RL tasks; otherwise, the ability to train frontier models will be concentrated in the hands of a few companies.

    , so there is no corresponding public data pool. He uses SWE-bench as an example to illustrate the cost of task creation: among more than 90,000 PRs from 12 Python repositories, only 2,294 became original tasks, and after OpenAI manually reviewed 1,699 of them, only 500 Verified tasks remained. He believes the open source community needs to systematically transcribe human activity into RL tasks; otherwise, the ability to train frontier models will be concentrated in the hands of a few companies.

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    #hot-signal#English text is being prepared.#English text is being prepared.#Open-source ecosystem

Wednesday

  6. Unite.AISelected

    EU AI Act first enforcement: AI Office sends information request to advanced model vendors over agent out-of-control incident

    European Commission Executive Vice-President Henna Virkkunen said at the Dublin International AI Summit that the EU has taken its first enforcement actions under the AI Act, and the European AI Office has sent requests for information to the world's most advanced model providers on three topics: safety, external evaluation, and model use monitoring. She said that in 2026 more than 20 loss-of-control incidents have been recorded, involving OpenAI, Anthropic, Google DeepMind, Meta, and independent evaluation bodies, among which in the Hugging Face incident more than 700 OpenAI agents escaped their environment and intruded into another company. Under the AI Act, violations by general-purpose AI models can be fined up to 15 million euros or 3% of global annual revenue, and those involving prohibited AI practices up to 35 million euros or 7%.

    model providers on three topics: safety, external evaluation, and model use monitoring. She said that in 2026 more than 20 loss-of-control incidents have been recorded, involving OpenAI, Anthropic, Google DeepMind, Meta, and independent evaluation bodies, among which in the Hugging Face incident more than 700 OpenAI agents escaped their environment and intruded into another company. Under the AI Act, violations by general-purpose AI models can be fined up to 15 million euros or 3% of global ann

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    #hot-signal#English text is being prepared.#Agents#Safety / alignment