Research posts from Redwood Research on catastrophic AI risk, focused on AI control, monitoring of agentic models, and red-teaming of safety systems. Readers get technical write-ups of papers, experiments and engagements with AI developers, including methods, results and open questions.
Website: https://blog.redwoodresearch.org
Essays and research from Princeton-affiliated authors arguing that AI is a transformative but normal technology rather than a path to superintelligence. Issues cover AI agent evaluation, the economics of automation versus augmentation, and a critical look at the AI safety movement.
A weekly roundup of AI developments covering model releases, safety and alignment incidents, cybersecurity events and AI policy, with extended commentary on individual stories. It also includes occasional standalone deep dives, such as analysis of AI legislation and company conduct.
Transformer reports on the politics and policy of advanced AI, mixing original reporting, interviews and tests of AI models with analysis of legislation and company strategy. Readers get coverage of Congress, AI safety debates and frontier labs' behavior.
Ramez Naam writes long-form analysis on AI, energy, climate and technology, with recent issues examining whether AI can recursively self-improve into superintelligence. He argues from available data and models, and contrasts a singleton AI future with a plural one.
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