Practical AI: Machine Learning, Data Science
Technology
There’s so much talk (and hype) these days about vector databases. We thought it would be timely and practical to have someone on the show that has been hands on with the various options and actually tried to build applications leveraging vector search. Prashanth Rao is a real practitioner that has spent and huge amount of time exploring the expanding set of vector database offerings. After introducing vector database and giving us a mental model of how they fit in with other datastores, Prashanth digs into the trade offs as related to indices, hosting options, embedding vs. query optimization, and more.
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Show Notes:
Vector databases blog posts from Prashanth:
Something missing or broken? PRs welcome!
Timestamps:
(00:00) - Welcome to Practical AI
(00:43) - Prashanth Rao
(01:40) - What are vector DBs
(03:21) - Semantics and vectors
(04:20) - How vectors are utilized
(09:53) - Evolution of NoSQL
(15:52) - Sponsor: Changelog News
(17:53) - How do we use them
(20:37) - Use cases for vector DBs
(23:58) - Over-optimizing
(26:14) - Tradeoffs
(31:00) - Mature vendors
(33:04) - Speedrunning the blog points
(34:48) - In-memory vs on-disk
(40:43) - Environments
(44:21) - Exciting things in the space
(50:45) - Outro
AI in the U.S. Congress
First impressions of GPT-4o
Full-stack approach for effective AI agents
Autonomous fighter jets?!
Private, open source chat UIs
Mamba & Jamba
Udio & the age of multi-modal AI
RAG continues to rise
Should kids still learn to code?
AI vs software devs
Prompting the future
Generating the future of art & entertainment
YOLOv9: Computer vision is alive and well
Representation Engineering (Activation Hacking)
Leading the charge on AI in National Security
Gemini vs OpenAI
Data synthesis for SOTA LLMs
Large Action Models (LAMs) & Rabbits 🐇
Collaboration & evaluation for LLM apps
Advent of GenAI Hackathon recap
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