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AI Trends 2024: Machine Learning & Deep Learning with Thomas Dietterich - #666

The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

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Understanding Hallucinations in Language Models

This chapter explores the phenomenon of 'hallucination' in large language models (LLMs), tracing its origins in image captioning to its implications in text generation. The discussion highlights the challenges of differentiating true hallucinations from other errors, the cascading effects of these errors, and the importance of uncertainty estimation in model outputs. Furthermore, it examines recent research and strategies for improving model accuracy and reliability through enhanced confidence mapping and prompt engineering.

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