معلومات عن هذه الحلقة
Vector Podcast website: https://vectorpodcast.com
Get your copy of John's new book "Prompt Engineering for LLMs: The Art and Science of Building Large Language Model–Based Applications": https://amzn.to/4fMj2Ef
John Berryman is the founder and principal consultant of Arcturus Labs, where he specializes in AI application development (Agency and RAG). As an early engineer on GitHub Copilot, John contributed to the development of its completions and chat functionalities, working at the forefront of AI-assisted coding tools. John is coauthor of "Prompt Engineering for LLMs" (O'Reilly).Before his work on Copilot, John's focus was search technology. His diverse experience includes helping to develop next-generation search system for the US Patent Office, building search and recommendations for Eventbrite, and contributing to GitHub's code search infrastructure. John is also coauthor of "Relevant Search" (Manning), a book that distills his expertise in the field.John's unique background, spanning both cutting-edge AI applications and foundational search technologies, positions him at the forefront of innovation in LLM applications and information retrieval.
00:00 Intro
02:19 John's background and story in search and ML
06:03 Is RAG just a prompt engineering technique?
10:15 John's progression from a search engineer to ML researcher
13:40 LLM predictability vs more traditional programming
22:31 Code assist with GitHub Copilot
29:44 Role of keyword search for code at GitHub
35:01 GenAI: existential risk or pure magic? AI Natives
39:40 What are Artifacts
46:59 Demo!
55:13 Typed artifacts, tools, accordion artifacts
56:21 From Web 2.0 to Idea exchange
57:51 Spam will transform into Slop
58:56 John's new book and Acturus Labs intro
Show notes:
- John Berryman on X: https://x.com/JnBrymn
- Acturus Labs: https://arcturus-labs.com/
- John's blog on Artifacts (see demo in the episode): https://arcturus-labs.com/blog/2024/11/11/cut-the-chit-chat-with-artifacts/
YouTube: https://youtu.be/60HAtHVBYj8
