AI Safety Daily is a weekday briefing on AI alignment, model evaluations, emerging risks, and governance. Each episode examines new safety research, independent testing, interpretability findings, red-team results, and evidence about how advanced AI systems behave. We follow scalable oversight, agent reliability, model security, misuse prevention, and safeguards against catastrophic risks, alongside the policies and deployment decisions that put those ideas into practice. Primary research and credible reporting anchor the discussion; measured results, researchers' interpretations, and speculative scenarios are kept distinct. For builders, researchers, and policy practitioners who want a clear account of what changed, how strong the evidence is, and which questions remain open.
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