I am not garymarcusing here. LLMs are proof that it is possible to distill intelligent reasoning behavior by doing statistics over human language patterns
AGI
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Learning world models from dropping a cup of water
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When @olivercameron was the first to teach us about world models (he just collected $300 million investment last week) in my head I was thinking: "If I drop a cup on the ground, with some water in it, and film that with a high speed camera, the world model would learn a lot about
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AGI expected by 2029/2030, others emerge rapidly in 2030s
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Looks like AGI 2029/2030 and then the others emerge rapidly across the 2030s.
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True reason for banning AI Fable and Mythos revealed after NSA breach
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"We're becoming completely paranoid!", "Friday it was panic, an AI entered almost all classified systems of the NSA in a few hours"
Twist in the case of the ban of Anthropic's AI Fable 5 and Mythos: the real reason behind it is finally revealed. -
New Product Raven: Self-Evolving Agent OS
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我又来剧透了
— 艾略特 (@elliotchen100) 21 juin 2026
从龙虾到爱玛氏，从爱玛氏到什么？
没错，我们马上要发布一个全新的产品：Raven。
它不是又一个「会调用很多工具」的 Agent。
它是一个会自我进化的 Agent OS。
大多数 Agent 的学习，停在技能层：多学一个工具，多记一条流程，多写一段 prompt。
Raven 不一样。… pic.twitter.com/KoO8KGMrPCHere I go again with a spoiler. From Lobster to Aimashi, from Aimashi to what? That's right, we are about to release a brand new product: Raven. It's not just another Agent that 'can call many tools'. It's a self-evolving Agent OS. Most Agents' learning stops at the skill level: learn one more tool, memorize one more process, write one more prompt. Raven is different.
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AI Domination: Open-source then General, and What’s Next?
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– 2016-2024: dominates open-source AI
– 2024-2027: dominates general AI and benefits massively from it – 2024-2026: dominates open-source AI
– 2026-2030: ?? It is not the domination of open-source AI OR the domination of general AI, it is the domination of AI -
End of programming, machines generate their own code
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Fin de la programmation.
— Stephane Mallard (@StephaneMallard) 21 juin 2026
Les machines qui génèrent leur propre code.
Nous y sommes. https://t.co/sO1JWjn1gNEnd of programming.
Machines that generate their own code.
We are there. -
LLMs behind human performance due to lack of regularization and integration
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Yes; I think the main reason that LLMs are so far behind our performance relative to the amount of data they get is that they don't regularize and integrate enough
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Kurzweil’s AGI predictions mixed with flawed connectome immortality
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Kurzweil mixed bold but solid predictions (given enough compute, a neocognitron like architecture can achieve AGI before 2030) with dogshit (digitizing the connectome is a near term way to human immortality). But both looked like the same kind of scifi to non experts.
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AI will soon know what to do better than us
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No. Very soon AI will know what to do better than us.