Invest Like The Best
Episode 363 Building An Answer Engine
Invest Like The Best

Episode 363: Building An Answer Engine

Invest Like The Best

Episode 363

Building An Answer Engine

Aravind Srinivas is the founder and CEO of Perplexity. We cover the advantages of an AI-powered answer engine over traditional search, the component mechanics used to build in this space, and how Perplexity's business model can compete with the likes of Google and OpenAI.

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(00:00:00) Welcome to Invest Like the Best 

(00:04:08) First Question - Redefining 'Great' in Search

(00:07:16) The Mechanics of Perplexity

(00:10:59) The Evolution of Perplexity From Wrapper to Robust Infrastructure

(00:13:19) The Future of Large Language Models (LLMs)

(00:22:39) The Business Model: From Growth to Monetization

(00:28:16) The Process of Building an Index

(00:35:55) The Impact of Scaling and Data Quality on AI Models

(00:40:00) Bottlenecks in AI Development

(00:47:06) The Talent Landscape in AI

(00:57:59) The Vision for the Future of Search

(01:00:19) Importance of Execution in AI Startups

Building An Answer Engine

Introduction

Patrick
My guest today is Aravind Srinivas. He is the founder and CEO of Perplexity, a startup that he describes as an answer engine built from scratch with AI, has set out for Perplexity to become the most powerful answer engine backed by up-to-date sources. He helps me pick apart the technology, describing the behind the scenes of what it takes to build Perplexity to reach its potential and compete along the likes of Google and OpenAI.

Our conversation goes deep into programming this kind of infrastructure, the competition around latency and constructing a business model around deep learning. There is so much on the horizon, so please enjoy my conversation with Aravind Srinivas.

Aravind's One-Minute Bio

Patrick
I thought a fun place to begin would be a game I like to play with people, which is I call it a one-minute bio. I'd love to hear the one-minute summary of your life up until the founding of perplexity just to set the context for all that we'll talk about.

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