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Navigating Machine Learning Careers: Insights from Meta to Consulting // Ilya Reznik // #286

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Exploring the Utility and Limitations of Large Language Models

This chapter explores the effectiveness and constraints of large language models, focusing on retrieval-augmented generation (RAG) as a means to provide context. It reinterprets 'hallucinations' in LLM outputs as artifacts of training data and examines the integration of various techniques, including reinforcement learning, to improve LLM functionality.

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