The Stack Overflow Podcast
Semantic search without the napalm grandma exploit
Aug 18, 2023
Alex and Kyle discuss building AI gateway and search APIs for Overflow AI, including the new search experience on Stack Overflow for teams. They explore the use of embeddings and large language models. The conversation also touches on hidden prompts in the industry and improvements in APIs. They express excitement for the rapidly changing industry and shaping the future of Stack Overflow.
29:39
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Quick takeaways
- Fine-tuning prompts and leveraging existing data are crucial for accurate knowledge retrieval using large language models (LLMs).
- Using vector databases and embeddings can improve search efficiency and accuracy when indexing large language models.
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Introduction and Overview
In this episode of the Stack Overflow podcast, the hosts discuss the recent announcements regarding the launch of Overflow AI and its impact on Stack Overflow. They are joined by Michael and Alex, who explain their roles in leading the data science and data engineering teams working on Overflow AI. The conversation focuses on the different levels of leveraging large language models (LLMs), including solving prompts, using embeddings, and building custom models. The discussion highlights the importance of fine-tuning prompts and augmentation using existing data, rather than relying solely on LLMs for knowledge retrieval. The hosts also explore the challenges of contextualizing search results and the role of hidden prompts.
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