Jeff Dean: Integrating Google Search with LLM In-Context Learning
Dwarkesh Patel interviewed Jeff Dean and Noam Shazeer from Google, posing an intriguing question: What would it be like to merge Google Search with in-context learning? Jeff Dean’s response offered a fascinating perspective on the potential and challenges of such an integration. Understanding In-Context Learning Before diving into the discussion, it’s useful to define in-context learning. Also known as few-shot learning or prompt engineering, this technique allows a large language model (LLM) to generate more accurate responses by providing examples or instructions within the input prompt. The model processes these examples in real-time, adapting its output based on the given context. A key concept here is the context window —the number of tokens (pieces of text) an LLM can consider at once. Larger context windows allow AI models to process more information, such as entire research papers, lengthy conversations, or hours of video content. The Challenge of Combining Google Search wi...