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@SakanaAILabs

AIによるAI研究の実現へ:AIサイエンティスト論文が @Nature 誌に掲載 https://t.co/VXCLEFf9R2 Sakana AIが常に挑んでいるのは、最先端のAIで何ができるのかという可能性の最前線を探ることです。それを象徴する成果の一つが、AI自身がAI研究を行う「AIサイエンティスト」でした。 この度、2024年のAIサイエンティストと2025年の「v2」を統合し、さらに実験を重ねて取りまとめた論文が @Nature 誌に掲載されたことを大変嬉しく思います。 本論文では、モデル性能の向上に伴い科学論文の質も向上するという「科学のスケーリング則」を報告しました。これは今のAIに何ができるかだけでなく、これからの進展を予期させる重要な知見であると考えています。人間とAIが共同して、可能性の「木」を深く高速に探索し、新たな発見が次々に生まれる未来が来ることは間違いありません。 この研究は、日本のAIラボであるSakana AIと、世界的なAI研究者たちとの共同研究による成果です。 日本における日本のためのAI企業を目指すSakana AIは、先日公開したSakana Chatのように誰もが使える基盤技術を提供しつつ、同時に世界のAI研究を切り拓く研究を両立させていきたいと考えています。 Nature論文という最高の形で公開できることを励みに、これからも日本のAIと科学の進歩に貢献できるよう取り組んでまいります。 Nature論文: https://t.co/nNfpSV4Gga

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    "text": "The AI Scientist: Towards Fully Automated AI Research, Now Published in Nature\n\nNature: https://t.co/nNfpSV5e5I\nBlog: https://t.co/i6h8LVQOdl\n\nWhen we first introduced The AI Scientist, we shared an ambitious vision of an agent powered by foundation models capable of executing the entire machine learning research lifecycle.\n\nFrom inventing ideas and writing code to executing experiments and drafting the manuscript, the system demonstrated that end-to-end automation of the scientific process is possible.\n\nSoon after, we shared a historic update: the improved AI Scientist-v2 produced the first fully AI-generated paper to pass a rigorous human peer-review process.\n\nToday, we are happy to announce that “The AI Scientist: Towards Fully Automated AI Research,” our paper describing all of this work, along with fresh new insights, has been published in @Nature!\n\nThis Nature publication consolidates these milestones and details the underlying foundation model orchestration. It also introduces our Automated Reviewer, which matches human review judgments and actually exceeds standard inter-human agreement.\n\nCrucially, by using this reviewer to grade papers generated by different foundation models, we discovered a clear scaling law of science. As the underlying foundation models improve, the quality of the generated scientific papers increases correspondingly. This implies that as compute costs decrease and model capabilities continue to exponentially increase, future versions of The AI Scientist will be substantially more capable.\n\nBuilding upon our previous open-source releases (https://t.co/H1tBT14Yx8), this open-access Nature publication comprehensively details our system's architecture, outlines several new scaling results, and discusses the promise and challenges of AI-generated science.\n\nThis substantial milestone is the result of a close and fruitful collaboration between researchers at Sakana AI, the University of British Columbia (UBC) and the Vector Institute, and the University of Oxford. Congrats to the team!\n\n@_chris_lu_ @cong_ml @RobertTLange @_yutaroyamada @shengranhu @j_foerst @hardmaru @jeffclune",
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