Navigating Database Choices for Vector Storage

This chapter explores the performance of Amazon's scalable Postgres in comparison to vector databases like Pinecone. The discussion emphasizes the trade-offs between using Postgres with vector capabilities versus dedicated vector databases, advocating for the importance of selecting the right tool for optimal efficiency and speed.

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In this sponsored episode of The Cognitive Revolution, Nathan interviews Andrei Oprisan, Engineering Lead at Agent.ai. They explore the cutting-edge world of AI agents and their impact on the future of work. Andrei shares insights on language model limitations, best practices for building AI agents, and Agent AI's vision as a professional network for AI agents. The conversation covers technical details like fine-tuning models, vector database choices, and privacy-preserving techniques. Don't miss this deep dive into AI's role in transforming industries and the skills needed in an AI-augmented workplace.

Check out Agent.ai website here: https://agent.ai

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SPONSORS:

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RECOMMENDED PODCAST:

This Won't Last - Eavesdrop on Keith Rabois, Kevin Ryan, Logan Bartlett, and Zach Weinberg's monthly backchannel ft their hottest takes on the future of tech, business, and venture capital.

Spotify: https://open.spotify.com/show/2HwSNeVLL1MXy0RjFPyOSz

CHAPTERS:

(00:00:00) About the Show

(00:00:22) Sponsors: Weights & Biases Weave

(00:01:28) About the Episode

(00:05:36) Introduction and AI Agents Overview

(00:07:02) Current State of AI Agents

(00:11:30) Building and Optimizing AI Agents

(00:19:01) Sponsors: Oracle | Brave

(00:21:05) Agent.ai Platform and Marketplace

(00:31:12) Sponsors: Omneky | Squad

(00:32:38) Customization and Context for Agents