Evaluating Trustworthiness
A diverse group of researchers collaborated to define and evaluate trustworthiness in language models, identifying eight key perspectives including toxicity, bias, and fairness. They developed a scalable toolbox for querying models, aiming to fill gaps in existing performance evaluations. This initiative seeks to enhance our understanding of model behavior and promote ethical AI practices.In this clip
From this podcast

The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Are Emergent Behaviors in LLMs an Illusion? with Sanmi Koyejo - 671
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