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[MUSIC]
Aravind, welcome to Stanford.
>> Thank you for having me.
I'm from Berkeley, so hopefully you
don't mind >> [LAUGH] >> At least
wanted to represent with the blue.
>> [LAUGH] >> But
it's great to be here, thank you.
>> We're happy to have you here.
Now many of us in the audience
are active perplexity users.
>> Thank you.
>> Especially with free perplexity
Pro for all Stanford students.
>> [APPLAUSE] >> So we couldn't be
AI-generated overview
Aravind Srinivas, CEO and co-founder of Perplexity AI, discusses building the world's first answer engine at Stanford Graduate School of Business. Perplexity differentiates itself through academic-style citations for every answer, refusing to manipulate core search results with advertising. Srinivas advocates for using existing AI models rather than building proprietary ones, noting a 2x cost reduction every four months in API pricing. The company's monetization strategy places ads in suggested follow-up questions rather than answers themselves, and implements a revenue-sharing model with publishers similar to Spotify. Srinivas emphasizes hiring talented individuals seeking their first major success rather than proven experts, maintaining extreme bias for action, and personally using the product extensively (10+ queries daily). He credits his academic background at UC Berkeley for shaping Perplexity's citation-focused approach and commitment to democratizing knowledge access.
Perplexity's core differentiation is maintaining unbiased answers while monetizing through suggested follow-up questions, never allowing advertisers to influence the actual answer content—a departure from Google's model where ads and results share the same unit.
Building foundation AI models requires either $10 billion in funding or choosing a different path entirely; Perplexity bet on model commoditization and API costs declining 2x every four months, which proved correct as competing model-building startups failed.
Academic citation culture directly inspired Perplexity's product design—every sentence in academic papers requires source attribution, translating to AI responses where every statement needs verifiable web sources with domain authority.
Effective fundraising for Perplexity involved zero traditional pitch decks; instead, Srinivas sent investors direct product links, securing commitments from figures like Yann LeCun in 10 minutes of product usage after camping outside his office.