This Lex Fridman podcast features a conversation with Aravind Srinivas, CEO of Perplexity AI. The discussion centers on Perplexity's innovative approach to search and answer engines, its underlying technology (combining search and LLMs), and the future of AI and the internet. The conversation also explores the business models of search engines like Google and the potential for future breakthroughs in AI reasoning.
Perplexity AI as an Answer Engine: Perplexity prioritizes providing accurate, cited answers rather than lists of links, differentiating it from traditional search engines. It achieves this by combining traditional search with LLMs, ensuring every answer is backed by sources.
The Importance of Citations: The design philosophy emphasizes accuracy and reduces LLM hallucinations by requiring every statement to be sourced from multiple online references, mirroring academic paper writing standards.
Knowledge Discovery Engine: Srinivas views Perplexity not merely as a search or answer engine, but as a knowledge discovery engine, emphasizing the iterative nature of knowledge seeking and providing related questions to encourage deeper exploration.
Differentiation from Google: Perplexity avoids direct competition with Google by focusing on a different user experience and addressing aspects of search that Google's ad-driven model neglects, such as providing clear and concise answers to complex questions in areas with high ad spend (like insurance).
Future of AI: The conversation speculates on future breakthroughs in AI reasoning, potentially enabled by increased inference compute and the development of smaller, more efficient models focused on reasoning rather than pure memorization of facts. The potential impact of such advancements on various fields, including drug design, is explored.
