We’re excited to announce a strategic partnership and investment from Mitsubishi Electric 🇯🇵⚡ By combining their deep domain knowledge and vast amounts of data in the manufacturing sector with Sakana AI’s technology, we’re taking a significant step toward bringing Agentic AI into physical industries. Following our ongoing work in the finance and defense sectors, we view physical AI in manufacturing as our third major pillar. We look forward to working closely with their team to solve complex, real world challenges and deploy these systems in core industries. businesswire.com/news/home/2… Sakana AI (@SakanaAILabs) 三菱電機株式会社より出資を受けました。 prtimes.jp/main/html/rd/p/00… 本パートナーシップを通じて、三菱電機が培ってきた製造現場のドメインナレッジや膨大なデータと、Sakana AIの最先端のAI技術を掛け合わせます。これにより、製造業を中心とする基幹産業の高度化に資するソリューション提供を進めて いきます。 私たちは、これまで取り組んできた金融や防衛領域に続く第3の柱として、フィジカルAIを含む製造領域でのAI活用を位置付けています。今後も、日本の強みを生かした革新的なAI技術の社会実装に取り組んでまいります。 三菱電機専務執行役の武田聡氏からは、今回の出資が実社会での具体的な課題解決におけるAIの可能性を拡げる重要な一歩になることを確信している、とのお言葉をいただきました。 — https://nitter.net/SakanaAILabs/status/2037118877612859545#m
AUTOMATION
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Using AI to move from answers to execution for businesses
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Most people use AI like a search engine. That’s the lowest value use case. The real leverage comes when AI moves from answering questions to supporting execution. For small and mid-sized businesses, the shift is practical: Use it to structure decisions.
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AI Disrupts Speaker Agencies as Disintermediation Accelerates
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You're right about the middlemen—most of them no longer add any value. I see it in my line of work: speaker agencies with their exorbitant commissions are suffering from disintermediation. Whereas for years, it was a goldmine. AI is rendering them obsolete.
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Promptable World Events: Dynamic Simulation Control for Enterprise Training
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Then there is “promptable world events.” Inside the simulation, you can dynamically: → Change the weather
→ Modify objects
→ Introduce or alter characters
→ Trigger new scenarios in real time Think about the enterprise implications: → Training embodied agents
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Using AI May Automate Your Own Job Away
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"Those who do not use AI will be replaced by those who use AI" Do you remember that punchline to justify training employees in the use of AI? Well, it's false: by using AI, each person contributes to automating their own job. AI will do everything.
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AI Scientist V1 Completed Before o1-Preview, Models More Capable Now
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The AI Scientist V1 was completed months before o1-preview and reasoning models were released. The models have clearly gotten much more capable since then. Very excited for where things are headed for AI and automated research! Sakana AI (@SakanaAILabs) The AI Scientist: Towards Fully Automated AI Research, Now Published in Nature Nature: nature.com/articles/s41586-0… Blog: sakana.ai/ai-scientist-natur… When 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. From 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. Soon 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. Today, 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! This 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. Crucially, 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. Building upon our previous open-source releases (github.com/SakanaAI/AI-Scien…), 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. This 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! @_chris_lu_ @cong_ml @RobertTLange @_yutaroyamada @shengranhu @j_foerst @hardmaru @jeffclune — https://nitter.net/SakanaAILabs/status/2036840833690071450#m
→ View original post on X — @_yutaroyamada, 2026-03-26 08:53 UTC
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Trucks Transformed into Drone Command Hubs: Road to Sky
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From Road to Sky: Trucks Transformed into #Drone Command Hubs
— Ronald van Loon (@Ronald_vanLoon) 26 mars 2026
via @ZappyZappy7
#Engineering #ArtificialIntelligence #Innovation #Technology pic.twitter.com/C4dViOQiK1From Road to Sky: Trucks Transformed into #Drone Command Hubs
via @ZappyZappy7 #Engineering #ArtificialIntelligence #Innovation #Technology -
Playwright Interactive Skills Implementation Discussion
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this should by and large already be possible with playwright interactive no? anything you’d like to add/ change? https://
github.com/openai/skills/
tree/main/skills/.curated/playwright-interactive
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OpenAI Skills and Sub-Agents: What’s Missing?
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to a large extent this is all already possible with openai/skills paired with sub agents no? anything that’s missing?
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What Tools Should Integrate With Codex Next?
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We are expanding Codex’s toolkit – what tools would you love to see work with codex the most?
