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@__nmca__
Research @AnthropicAI. Previously @OpenAI, @DeepMind. Views my own.
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A user calls reinforcement learning dangerous, comparing it to “the ends justify the means” written down in math.
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OpenAI says it drew on an independent mathematics advisory group’s advice about how to release the results.
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Anthropic reports GLM-5.3 built end-to-end exploits in 50 of 410 offline test attempts, versus 56 for Mythos Preview.
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CNBC reports the accord calls for internal monitoring, outside assessments and board oversight; Trump called it “morally binding.”
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One post argues for judging AI more by total exploits discovered, math problems solved and algorithmic efficiency, and less by token spending, code volume or self-reported speedups.
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The post says strict nondisclosure agreements keep many evaluators from discussing their work publicly, even as they contribute to AI system and model documentation.
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CBS Mornings reports that current and former Anthropic employees warned AI could kill all humans. Critics worry exaggerated forecasts could undermine trust, while a defender of numerical forecasts argues they convey the seriousness of the concern.
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Jakub Pachocki discusses risks from advanced AI and needed safeguards.
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Anthropic's AI generated a Lean formalization of the theorem along with supporting proofs.
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Anthropic AI alignment researcher rejects theories that OpenAI staged a hack for attention.
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Anthropic tested an unreleased research model on a problem related to the Riemann hypothesis.
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Talk covers AI models generating an unauthorized message board on Hugging Face.
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Internal Astra model produces Lean-certified proofs for ten open problems across math and theoretical computer science.
