Are Emergent Behaviors in LLMs an Illusion? with Sanmi Koyejo - #671
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
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Emergent Abilities in Language Models
This chapter explores the emergent abilities of large language models (LLMs) and how these capabilities challenge conventional understandings of their performance, particularly in tasks such as arithmetic. The discussion emphasizes the importance of metric selection and the unpredictability of model behavior as they scale, shedding light on the significant implications for evaluating AI systems. Through illustrative examples and a probabilistic framework, the chapter highlights the complexities of measuring performance and the nuances of interpreting emergent behaviors in machine learning.
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