AI safety and alignment

Red teaming, interpretability, RLHF, scalable oversight.

AI safety spans adversarial red teaming, mechanistic interpretability, RLHF/DPO improvements, and governance. Relaylit tracks Anthropic/OpenAI/DeepMind output plus academic contributions, filtered for substance over press release.

Example brief

"AI safety: mechanistic interpretability, red teaming, scalable oversight. Academic and lab-produced papers."

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Where Relaylit searches for this topic

arXiv

2.4M+ preprints in physics, mathematics, computer science, and quantitative disciplines.

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Semantic Scholar

200M+ academic papers with citation graphs and AI-extracted metadata across disciplines.

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AI safety and alignment

Example brief

Where Relaylit searches for this topic

arXiv

Semantic Scholar

Related topics

LLM agents and tool use

LLM evaluation and benchmarks

Your first ai safety and alignment digest lands this week.