AI Safety for Product Teams
4 papers on making AI models safe and reliable. Essential if you're shipping AI features that touch real users.
instructgpt — coming soon
The paper that created the RLHF paradigm — training on human preferences is now the industry standard for alignment.
Yuntao Bai et al.
Train AI with its own feedback to reduce need for human labels and increase precision in behavior control.
Why this paper
Self-supervised safety — teaching models to critique themselves using a written "constitution" of principles.
dpo — coming soon
Simpler than RLHF, just as effective. The technique most startups use when they want to align without a reward model.
Xiao Liu et al.
AgentBench shows LLMs like GPT-4 excel at acting autonomously, outpacing open-source rivals significantly.
Why this paper
You can't improve what you can't measure. The science of evaluating AI systems before you ship them.
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