Yale researchers investigate causes of AI chatbot errors and ways to improve reliability
By
By Mike Cummings
Crisp on the outside, thoughtful on the inside. A keeper.
Summary
Yale researchers are investigating why large language models (LLMs) make errors, including hallucinations and misinterpretations, and are working to develop methods to make AI systems safer, more reliable, and more accountable. Two multidisciplinary teams are studying the roots of chatbot mistakes and misalignment with user intentions, aiming to improve trustworthiness in AI systems.
Key quotes
· 3 pulledThey hallucinate. They misinterpret. They make mistakes.
Two multidisciplinary teams of researchers associated with Yale are seeking to understand why AI systems become misinformed or misaligned with users' intentions.
The goal is to develop ways to make AI systems safer, more reliable, and more accountable.
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