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Friday

Thursday

  4. A6 a6-047 · Baseten Engineering Blog

    Baseten Engineering Blog Community Articles Roundup

    The Baseten Engineering Blog Community section brings together multiple articles, covering topics such as open-source inference for You.com, AI model selection lessons from Notion and Gamma, inference in the era of continual learning, model fine-tuning and a conversation with Hollywood, the Baseten inference stack at NVIDIA Dynamo Day, and building agents on Baseten with LangChain Agent Builder + GLM 4.7.

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    #a6-editorial#English text is being prepared.
  6. Latent Space

    OpenAI Team Responds to Computer Use Progress Doubts, Recaps One-Week Sprint on Decisions API

    In a podcast after OpenAI DevDay, Ari Weinstein, who is in charge of the Computer Use agent, responded to Dwarkesh's doubts about Computer Use progressing slowly, saying it is now completely different from a few months ago because the model has become better at debugging and retrying, and can write JavaScript to execute multiple steps at once while combining screenshots, accessibility, DOM, and Playwright. He also mentioned that Dots provides each Dot with a cloud Linux virtual computer, and that Computer Use has entered the Agents API. Nikunj Handa, head of the OpenAI API team, introduced updates to GPT-6 such as asynchronous tool calling, mid-turn steering, WebSockets, UltraFast inference, prompt caching and pre-warming, and compaction, and said the Decisions API is based on Luna weights, with no new model trained, and took only about a week from the emergence of the idea to a prototype.

    In a podcast after OpenAI DevDay, Ari Weinstein, who is in charge of the Computer Use agent, responded to Dwarkesh's doubts about Computer Use progressing slowly, saying it is now completely different from a few months ago because the model has become better at debugging and retrying, and can write JavaScript to execute multiple steps at once while combining screenshots, accessibility, DOM, and Playwright. He also mentioned that Dots provides each Dot with a cloud Linux virtual computer, and tha

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    #newsletter#Industry news#Agents#OpenAI

Wednesday

  7. QbitAI

    The Father of OpenAI Reasoning Noam Brown's Latest Interview: Mathematics Is Just an Appetizer for the Multi-Agent Era

    OpenAI researcher and core o1 author Noam Brown said in the latest podcast that multi-agent systems are a way to change inference-time compute from serial scaling to parallel scaling, but in solving the Millennium Prize Problems, multi-agent systems account for at most 10% of the credit; the core is still that the model itself is sufficiently powerful. He revealed that when 5.6 was released, they had a truly formed multi-agent system for the first time, provided in the form of Ultra Mode, with 4 Agents by default and adjustable higher; with 4 Agents, the problem-solving speed is about twice as fast, and tests scaled up to as many as 16 Agents.

    OpenAI researcher and core o1 author Noam Brown said in the latest podcast that multi-agent systems are a way to change inference-time compute from serial scaling to parallel scaling, but in solving the Millennium Prize Problems, multi-agent systems account for at most 10% of the credit; the core is still that the model itself is sufficiently powerful. He revealed that when 5.6 was released, they had a truly formed multi-agent system for the first time, provided in the form of Ultra Mode, with 4

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    #chinese#Industry news#Agents#Reasoning