@recurseparadox
research scientist at google deepmind. ಕನ್ನಡಿಗ. past: generative models @openai
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A person involved says the report will share the science behind Beam, but the write-up needs more time.
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A user calls Alex Graves the ‘OG’ while quote-posting another account.
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One post says researchers pivoted as some problems were solved or became irrelevant and new ones took their place.
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Microsoft AI says the mixture-of-experts model has 80 billion active parameters; post-training results are still to come.
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The researchers link the gap to imbalanced gradients under mean-squared-error training and propose an alternative regression method.
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The Nobel Prize organization says they were honored for discoveries concerning light-gated ion channels and optogenetics.
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A user quote-posted a link to an apex_ultra_ai post, adding only “👀” with no explanation.
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An essay coauthor argues that latent reasoning would undermine oversight by reducing the need for verbalized reasoning. A reply disputes any further loss of oversight, arguing that reinforcement learning already makes reasoning tokens uninterpretable.
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Yann LeCun stands by his view that autoregressive LLMs alone won't lead to human-level AI. He argues that current reasoning and self-improvement methods remain limited, and that humans and animals learn new skills far more efficiently.
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The poster says they've trained a frontier large language model and personally designed and synthesized custom viruses in a lab.
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Pranav Shyam replies that a massive effort would be worth pursuing.
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AI researchers and safety experts discuss reports of Astra using recurrent depth.
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Atlas generates videos with exact camera control and reconstructs 3D scenes from input images.
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Z.ai released the open model post-trained on its 743B base for coding and agentic tasks.
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ctok tool now matches Claude output for natural languages and programming languages.
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OpenAI president Greg Brockman posted the note on X.
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Keller Jordan states most big lab researchers read almost no papers from top AI venues.
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Internal Astra model produces Lean-certified proofs for ten open problems across math and theoretical computer science.
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Startup aims to scale domestic production of energy-efficient AI hardware under federal agreement.
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Model tops Agent Arena and open-weight leaderboards in multiple categories.