Building a Search Engine for AI: Addressing Complex Query Needs

3min Snip

00:00

Play full episode

Summary

Transcript

Episode notes

A search engine specifically designed for AI needs to cater to complex query demands that differ from those of human users. AI searches are precise, requiring detailed outputs instantly, unlike humans who prefer simple queries. AI can process numerous results quickly, needing a search engine to return a variety of high-quality results in bulk. While humans seek diverse information when searching, AI seeks specific details, necessitating a search engine that provides precise outcomes. Additionally, AI prefers full-page content over links and titles for efficiency. Connecting AI to traditional search engines like Google may not meet its advanced requirements, indicating the necessity for a search engine tailored to AI's distinct characteristics and needs.

In this episode, Nathan sits down with Will Bryk, CEO of Exa.ai. They discuss how Exa enables complex, research-based searches that differ from traditional keyword-based search, how their AI uses neural and non-neural methods, why they are using their own vector database, and more. Try the Brave search API for free for up to 2000 queries per month at https://brave.com/api

LINKS:

- Exa.ai: https://exa.ai/

X/SOCIAL:

@WilliamBryk (William)

@labenz (Nathan)

@ExaAILabs (Exa)

SPONSORS:

Oracle Cloud Infrastructure (OCI) is a single platform for your infrastructure, database, application development, and AI needs. OCI has four to eight times the bandwidth of other clouds; offers one consistent price, and nobody does data better than Oracle. If you want to do more and spend less, take a free test drive of OCI at https://oracle.com/cognitive

Omneky is an omnichannel creative generation platform that lets you launch hundreds of thousands of ad iterations that actually work customized across all platforms, with a click of a button. Omneky combines generative AI and real-time advertising data. Mention "Cog Rev" for 10% off www.omneky.com

The Brave search API can be used to assemble a data set to train your AI models and help with retrieval augmentation at the time of inference. All while remaining affordable with developer first pricing, integrating the Brave search API into your workflow translates to more ethical data sourcing and more human representative data sets. Try the Brave search API for free for up to 2000 queries per month at https://brave.com/api

ODF is where top founders get their start. Apply to join the next cohort and go from idea to conviction-fast. ODF has helped over 1000 companies like Traba, Levels and Finch get their start. Is it your turn? Go to http://beondeck.com/revolution to learn more.

TIMESTAMPS

(00:00:00) - Preview

(00:01:52) - Exploring the landscape of information retrieval tools

(00:14:19) - Exa: AI librarian for the web

(00:15:32) - Sponsors: Oracle | Omneky

(00:16:57) - AI Project Ideas

(00:22:26) - What does search built for AI mean?

(00:25:40) - Ranking with neural and non-neural methods

(00:30:50) - Sponsors: Brave | On Deck

(00:33:13) - Best practices for Exa prompting

(00:34:01) - The power of keyword search

(00:37:26) - Breaking down complex queries

(00:34:37) - The evolution of search engines

(00:39:53) - The business side of Exa

(00:40:17) - The challenges of building a web scale index

(00:39:53) - The business side of Exa

(00:50:59) - Vector DBs

(00:58:17) - Wrap

This show is produced by Turpentine: a network of podcasts, newsletters, and more, covering technology, business, and culture — all from the perspective of industry insiders and experts. We’re launching new shows every week, and we’re looking for industry-leading sponsors — if you think that might be you and your company, email us at erik@turpentine.co.