Realistic AI Timelines
The conversation highlights the importance of setting realistic expectations for AI advancements, especially in light of past promises like self-driving cars. It emphasizes the need for a discerning approach to technology, particularly regarding the development of large language models (LLMs) and their applications. Understanding embeddings is crucial for those looking to build systems with LLMs, as it plays a vital role in semantic search and retrieval-augmented generation.In this clip
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Machine Learning Street Talk (MLST)
Jay Alammar on LLMs, RAG, and AI Engineering
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