Feb 15, 2024 · 43m · big-technology

Perplexity CEO Aravind Srinivas: How AI Challenges Google

Aravind Srinivas · 27m spoken Alex Kantrowitz · 9m spoken
0:00 / 0:00
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In this episode of the Big Technology Podcast, Perplexity AI CEO Aravind Srinivas discusses how generative answer engines are disrupting traditional web search and Google's core business model. He examines the shifting economics of digital information retrieval, AI foundation model dynamics, publisher attribution, and the future of conversational search.

How this conversation actually went

Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. Alex holds 25.1% of the talking time here. How this is scored →

Alex as informed peer 3.9 Guest teaching 4.4 Guest disagreement 1.7 Alex pushing back 2.8
05100:0015:0030:000:40–5:08 · Alex as informed peer 4/10 Startup Adoption Barriers and the Boundless TAM of Information Alex questions why fewer generative AI startups are breaking through given the hype, citing Character AI's apparent lack of usage. Srinivas politely corrects the host's framing, explaining the demographics and use cases of Character AI versus utility products.5:08–10:07 · Alex as informed peer 4/10 Google's Innovator Dilemma and Business Model Constraints Alex asks about Google's internal culture and talent issues. Srinivas delivers a detailed breakdown of the Innovator's Dilemma, explaining how changing the ten-blue-links model directly threatens Google's CPC/CPM business model and stock valuation.10:07–12:17 · Alex as informed peer 3/10 The Silicon Valley AI Talent War and Tech Layoffs Alex asks about recruiting from Google amidst layoffs. Srinivas shares an anecdote about a 4x counteroffer and speculates on how Google handles high-compensation layoffs.12:18–16:37 · Alex as informed peer 4/10 Redefining Search into Conversational Problem Solving Alex prompts Srinivas to define what makes conversational search different from traditional search. Srinivas explains how modern search acts like an advisor rather than ten competing salespeople.16:41–22:40 · Alex as informed peer 5/10 Navigational Search, Answer Engines, and Wikipedia Integration Alex pushes back on the total addressable market and whether Perplexity can replace Google completely or just coexist with it. Srinivas articulates the spectrum between navigational search engines and answer engines.22:40–26:07 · Alex as informed peer 3/10 Levelling the Playing Field: Model Intelligence Over Raw User Data Alex highlights Google's massive user data advantage. Srinivas directly reframes the premise, arguing that LLMs drastically reduce the need for raw user data and equalize competition against incumbents.26:09–30:12 · Alex as informed peer 6/10 Content Attribution, Publisher Relations, and Real-Time Information Alex draws on his experience as a publisher to question publisher relations, content attribution, and site crawling rights. Srinivas outlines Perplexity's academic citation model and acknowledges publisher monetization remains an open question.30:13–35:14 · Alex as informed peer 5/10 Rethinking Digital Advertising, E-Commerce, and User Alignment Alex cites Google ad revenue figures and challenges the intrusion of ads into conversational AI. Srinivas responds with a vision of transactional conversion and commerce assistance.35:15–42:42 · Alex as informed peer 4/10 Securing Backing from Jeff Bezos and the Memo Process Alex inquires about fundraising from Jeff Bezos and the upcoming model landscape from OpenAI, Anthropic, and Meta. Srinivas breaks down expected AI capability milestones such as multimodality, reliability, and reasoning.42:43–43:04 · Alex as informed peer 1/10 Podcast Conclusion and Where to Find Perplexity Standard brief podcast outro wrapping up the episode and sharing Perplexity's web address.0:40–5:08 · Guest teaching 5/10 Startup Adoption Barriers and the Boundless TAM of Information Alex questions why fewer generative AI startups are breaking through given the hype, citing Character AI's apparent lack of usage. Srinivas politely corrects the host's framing, explaining the demographics and use cases of Character AI versus utility products.5:08–10:07 · Guest teaching 6/10 Google's Innovator Dilemma and Business Model Constraints Alex asks about Google's internal culture and talent issues. Srinivas delivers a detailed breakdown of the Innovator's Dilemma, explaining how changing the ten-blue-links model directly threatens Google's CPC/CPM business model and stock valuation.10:07–12:17 · Guest teaching 3/10 The Silicon Valley AI Talent War and Tech Layoffs Alex asks about recruiting from Google amidst layoffs. Srinivas shares an anecdote about a 4x counteroffer and speculates on how Google handles high-compensation layoffs.12:18–16:37 · Guest teaching 5/10 Redefining Search into Conversational Problem Solving Alex prompts Srinivas to define what makes conversational search different from traditional search. Srinivas explains how modern search acts like an advisor rather than ten competing salespeople.16:41–22:40 · Guest teaching 4/10 Navigational Search, Answer Engines, and Wikipedia Integration Alex pushes back on the total addressable market and whether Perplexity can replace Google completely or just coexist with it. Srinivas articulates the spectrum between navigational search engines and answer engines.22:40–26:07 · Guest teaching 7/10 Levelling the Playing Field: Model Intelligence Over Raw User Data Alex highlights Google's massive user data advantage. Srinivas directly reframes the premise, arguing that LLMs drastically reduce the need for raw user data and equalize competition against incumbents.26:09–30:12 · Guest teaching 4/10 Content Attribution, Publisher Relations, and Real-Time Information Alex draws on his experience as a publisher to question publisher relations, content attribution, and site crawling rights. Srinivas outlines Perplexity's academic citation model and acknowledges publisher monetization remains an open question.30:13–35:14 · Guest teaching 5/10 Rethinking Digital Advertising, E-Commerce, and User Alignment Alex cites Google ad revenue figures and challenges the intrusion of ads into conversational AI. Srinivas responds with a vision of transactional conversion and commerce assistance.35:15–42:42 · Guest teaching 5/10 Securing Backing from Jeff Bezos and the Memo Process Alex inquires about fundraising from Jeff Bezos and the upcoming model landscape from OpenAI, Anthropic, and Meta. Srinivas breaks down expected AI capability milestones such as multimodality, reliability, and reasoning.42:43–43:04 · Guest teaching 0/10 Podcast Conclusion and Where to Find Perplexity Standard brief podcast outro wrapping up the episode and sharing Perplexity's web address.0:40–5:08 · Guest disagreement 2/10 Startup Adoption Barriers and the Boundless TAM of Information Alex questions why fewer generative AI startups are breaking through given the hype, citing Character AI's apparent lack of usage. Srinivas politely corrects the host's framing, explaining the demographics and use cases of Character AI versus utility products.5:08–10:07 · Guest disagreement 2/10 Google's Innovator Dilemma and Business Model Constraints Alex asks about Google's internal culture and talent issues. Srinivas delivers a detailed breakdown of the Innovator's Dilemma, explaining how changing the ten-blue-links model directly threatens Google's CPC/CPM business model and stock valuation.10:07–12:17 · Guest disagreement 1/10 The Silicon Valley AI Talent War and Tech Layoffs Alex asks about recruiting from Google amidst layoffs. Srinivas shares an anecdote about a 4x counteroffer and speculates on how Google handles high-compensation layoffs.12:18–16:37 · Guest disagreement 1/10 Redefining Search into Conversational Problem Solving Alex prompts Srinivas to define what makes conversational search different from traditional search. Srinivas explains how modern search acts like an advisor rather than ten competing salespeople.16:41–22:40 · Guest disagreement 2/10 Navigational Search, Answer Engines, and Wikipedia Integration Alex pushes back on the total addressable market and whether Perplexity can replace Google completely or just coexist with it. Srinivas articulates the spectrum between navigational search engines and answer engines.22:40–26:07 · Guest disagreement 3/10 Levelling the Playing Field: Model Intelligence Over Raw User Data Alex highlights Google's massive user data advantage. Srinivas directly reframes the premise, arguing that LLMs drastically reduce the need for raw user data and equalize competition against incumbents.26:09–30:12 · Guest disagreement 2/10 Content Attribution, Publisher Relations, and Real-Time Information Alex draws on his experience as a publisher to question publisher relations, content attribution, and site crawling rights. Srinivas outlines Perplexity's academic citation model and acknowledges publisher monetization remains an open question.30:13–35:14 · Guest disagreement 2/10 Rethinking Digital Advertising, E-Commerce, and User Alignment Alex cites Google ad revenue figures and challenges the intrusion of ads into conversational AI. Srinivas responds with a vision of transactional conversion and commerce assistance.35:15–42:42 · Guest disagreement 2/10 Securing Backing from Jeff Bezos and the Memo Process Alex inquires about fundraising from Jeff Bezos and the upcoming model landscape from OpenAI, Anthropic, and Meta. Srinivas breaks down expected AI capability milestones such as multimodality, reliability, and reasoning.42:43–43:04 · Guest disagreement 0/10 Podcast Conclusion and Where to Find Perplexity Standard brief podcast outro wrapping up the episode and sharing Perplexity's web address.0:40–5:08 · Alex pushing back 3/10 Startup Adoption Barriers and the Boundless TAM of Information Alex questions why fewer generative AI startups are breaking through given the hype, citing Character AI's apparent lack of usage. Srinivas politely corrects the host's framing, explaining the demographics and use cases of Character AI versus utility products.5:08–10:07 · Alex pushing back 2/10 Google's Innovator Dilemma and Business Model Constraints Alex asks about Google's internal culture and talent issues. Srinivas delivers a detailed breakdown of the Innovator's Dilemma, explaining how changing the ten-blue-links model directly threatens Google's CPC/CPM business model and stock valuation.10:07–12:17 · Alex pushing back 2/10 The Silicon Valley AI Talent War and Tech Layoffs Alex asks about recruiting from Google amidst layoffs. Srinivas shares an anecdote about a 4x counteroffer and speculates on how Google handles high-compensation layoffs.12:18–16:37 · Alex pushing back 2/10 Redefining Search into Conversational Problem Solving Alex prompts Srinivas to define what makes conversational search different from traditional search. Srinivas explains how modern search acts like an advisor rather than ten competing salespeople.16:41–22:40 · Alex pushing back 4/10 Navigational Search, Answer Engines, and Wikipedia Integration Alex pushes back on the total addressable market and whether Perplexity can replace Google completely or just coexist with it. Srinivas articulates the spectrum between navigational search engines and answer engines.22:40–26:07 · Alex pushing back 3/10 Levelling the Playing Field: Model Intelligence Over Raw User Data Alex highlights Google's massive user data advantage. Srinivas directly reframes the premise, arguing that LLMs drastically reduce the need for raw user data and equalize competition against incumbents.26:09–30:12 · Alex pushing back 5/10 Content Attribution, Publisher Relations, and Real-Time Information Alex draws on his experience as a publisher to question publisher relations, content attribution, and site crawling rights. Srinivas outlines Perplexity's academic citation model and acknowledges publisher monetization remains an open question.30:13–35:14 · Alex pushing back 4/10 Rethinking Digital Advertising, E-Commerce, and User Alignment Alex cites Google ad revenue figures and challenges the intrusion of ads into conversational AI. Srinivas responds with a vision of transactional conversion and commerce assistance.35:15–42:42 · Alex pushing back 3/10 Securing Backing from Jeff Bezos and the Memo Process Alex inquires about fundraising from Jeff Bezos and the upcoming model landscape from OpenAI, Anthropic, and Meta. Srinivas breaks down expected AI capability milestones such as multimodality, reliability, and reasoning.42:43–43:04 · Alex pushing back 0/10 Podcast Conclusion and Where to Find Perplexity Standard brief podcast outro wrapping up the episode and sharing Perplexity's web address.

speaking balance: gold is Alex, purple is the guest (3 minute bins)

0:00 · Alex 63.7% · guest 36.3%0:00 · Alex 63.7% · guest 36.3%3:00 · Alex 26.6% · guest 73.4%3:00 · Alex 26.6% · guest 73.4%6:00 · Alex 0.2% · guest 99.8%6:00 · Alex 0.2% · guest 99.8%9:00 · Alex 17.6% · guest 82.4%9:00 · Alex 17.6% · guest 82.4%12:00 · Alex 29.6% · guest 70.4%12:00 · Alex 29.6% · guest 70.4%15:00 · Alex 23.8% · guest 76.2%15:00 · Alex 23.8% · guest 76.2%18:00 · Alex 19% · guest 81%18:00 · Alex 19% · guest 81%21:00 · Alex 28.7% · guest 71.3%21:00 · Alex 28.7% · guest 71.3%24:00 · Alex 28.4% · guest 71.6%24:00 · Alex 28.4% · guest 71.6%27:00 · Alex 28.4% · guest 71.6%27:00 · Alex 28.4% · guest 71.6%30:00 · Alex 37.3% · guest 62.7%30:00 · Alex 37.3% · guest 62.7%33:00 · Alex 18.3% · guest 81.7%33:00 · Alex 18.3% · guest 81.7%36:00 · Alex 21.6% · guest 78.4%36:00 · Alex 21.6% · guest 78.4%39:00 · Alex 6.1% · guest 93.9%39:00 · Alex 6.1% · guest 93.9%42:00 · Alex 31.6% · guest 68.4%42:00 · Alex 31.6% · guest 68.4%
Sharpest disagreement ▶ 23:16 Dismissing incumbent data moat

Srinivas dismisses the host's premise that Google's data volume is an insurmountable moat, explaining that modern generative models only require a fraction of that data.

Hardest push from Alex ▶ 29:44 Host pushes publisher survival concerns

Alex challenges Srinivas's assertion that citation and awareness are sufficient, arguing directly that publishers cannot survive without actual web traffic and page views.

Biggest teaching moment ▶ 23:33 Explaining the LLM paradigm shift

Srinivas explains to the host how next-word prediction on generic web text replaced traditional historical click-data moats.

Alex holds their own ▶ 31:01 Host cites Google ad earnings statistics

Alex cites specific financial figures regarding Google's incremental ad growth and Madison and Wall research to pressure Srinivas on search monetization.

the scores for every segment, with the reasoning behind each
ChapterTopicAlex as informed peerGuest teachingGuest disagreementAlex pushing backWhy
Startup Adoption Barriers and the Boundless TAM of Information 4523 Alex questions why fewer generative AI startups are breaking through given the hype, citing Character AI's apparent lack of usage. Srinivas politely corrects the host's framing, explaining the demographics and use cases of Character AI versus utility products.
Google's Innovator Dilemma and Business Model Constraints 4622 Alex asks about Google's internal culture and talent issues. Srinivas delivers a detailed breakdown of the Innovator's Dilemma, explaining how changing the ten-blue-links model directly threatens Google's CPC/CPM business model and stock valuation.
The Silicon Valley AI Talent War and Tech Layoffs 3312 Alex asks about recruiting from Google amidst layoffs. Srinivas shares an anecdote about a 4x counteroffer and speculates on how Google handles high-compensation layoffs.
Redefining Search into Conversational Problem Solving 4512 Alex prompts Srinivas to define what makes conversational search different from traditional search. Srinivas explains how modern search acts like an advisor rather than ten competing salespeople.
Navigational Search, Answer Engines, and Wikipedia Integration 5424 Alex pushes back on the total addressable market and whether Perplexity can replace Google completely or just coexist with it. Srinivas articulates the spectrum between navigational search engines and answer engines.
Levelling the Playing Field: Model Intelligence Over Raw User Data 3733 Alex highlights Google's massive user data advantage. Srinivas directly reframes the premise, arguing that LLMs drastically reduce the need for raw user data and equalize competition against incumbents.
Content Attribution, Publisher Relations, and Real-Time Information 6425 Alex draws on his experience as a publisher to question publisher relations, content attribution, and site crawling rights. Srinivas outlines Perplexity's academic citation model and acknowledges publisher monetization remains an open question.
Rethinking Digital Advertising, E-Commerce, and User Alignment 5524 Alex cites Google ad revenue figures and challenges the intrusion of ads into conversational AI. Srinivas responds with a vision of transactional conversion and commerce assistance.
Securing Backing from Jeff Bezos and the Memo Process 4523 Alex inquires about fundraising from Jeff Bezos and the upcoming model landscape from OpenAI, Anthropic, and Meta. Srinivas breaks down expected AI capability milestones such as multimodality, reliability, and reasoning.
Podcast Conclusion and Where to Find Perplexity 1000 Standard brief podcast outro wrapping up the episode and sharing Perplexity's web address.

Statements from this episode (18)

Assertion Contradicted
Srinivas: 50% to 60% of Character.AI Users Are Under 20
“It's more popular among the younger generation, like 50 to 60% of their user base is under the age of 20. Because they're using it to talk to imaginary anime characters and things like that.”
Aravind Srinivas Feb 15, 2024 ▶ 2:18
Opinion
Srinivas: Perplexity's Total Addressable Market Mathematically Has No Upper Bound
“This product has no upper bound, honestly. Because it's upper bounded by the number of people on the planet multiplied by each individual's curiosity and Curiosity has no upper bound either, right? So therefore by mathematically the Tam of perplexity has no up…”
Aravind Srinivas Feb 15, 2024 ▶ 4:45
Opinion
Srinivas: Google Has More Talented People Than Even OpenAI
“I mean, you have to be insane to think you have more talented people than Google. I don't even think OpenAI has that, even though, like, they have a massive concentration of talent density today.”
Aravind Srinivas Feb 15, 2024 ▶ 5:54
Insight
Srinivas: Google Can Easily Build Perplexity But Cannot Deploy It
“It's not that they cannot build a product perplexity. They can very easily do that literally today. Like they probably already have something internally like that, but they cannot roll it out to every Google user.”
Aravind Srinivas Feb 15, 2024 ▶ 7:54
Assertion Not checkable as stated
Srinivas: Google quadrupled an engineer's pay to stop Perplexity recruitment
“There was one amazing candidate that I tried to recruit from Google. This candidate used to work in the, I mean, he still works there, in the Google search team. Like, it's not one of the AI people. And the moment he told them that he's gonna join us, they qua…”
Aravind Srinivas Feb 15, 2024 ▶ 10:13
Opinion
Srinivas: Google has no incentive to save search users' time
“And there is no incentive for Google to save your time in searches, by the way, because the whole point for them is that you spend as much time opening, like, 10 tabs on Chrome the browser they control, and give, give the analytics to all of these independen…”
Aravind Srinivas Feb 15, 2024 ▶ 13:55
Insight
Srinivas: AI search is creating a new conversational query behavior
“There is like a new segment of searches that these products like perplexity or ChatGPT are creating, which is like, you know, making people actually ask well-informed questions because we were not asking questions until now. We were just entering keywords. Lik…”
Aravind Srinivas Feb 15, 2024 ▶ 15:17
Insight
Srinivas: User question formulation is the key bottleneck for AI search
“There's number one skill is number one skill that actually is a bottleneck for these products to really take off is stability to ask good questions.”
Aravind Srinivas Feb 15, 2024 ▶ 20:32
Assertion Open · timeframe Feb 2027
Srinivas: Wikipedia will not build its own GPT
“No, they're not going to build their own GPT. I've spoken to him and he uses our product and he likes our product a lot.”
Aravind Srinivas Feb 15, 2024 ▶ 21:37
Opinion
Srinivas: AI outside Google is now higher quality than Google's internal AI
“So the first time, for the first time, we have had intelligence outside Google, like artificial intelligence outside Google, that's of higher quality than what is inside Google.”
Aravind Srinivas Feb 15, 2024 ▶ 25:09
Insight
Srinivas: Incumbents' data volume advantage has disappeared with generative AI
“So the advantages that the incumbents had in terms of having a large volume of data has gone away. I'm not saying you don't need user data at all. All I'm saying is you need a fraction of what was needed earlier for the first time.”
Aravind Srinivas Feb 15, 2024 ▶ 25:55
Opinion
Srinivas: Perplexity AI summaries constitute fair use of publisher content
“I think that's very fair use of other people's content. We're not stealing it. We're actually, like, just being a middleman between them and the end reader, and we're giving them more visibility, right?”
Aravind Srinivas Feb 15, 2024 ▶ 28:34
Prediction Not checkable as stated
Srinivas: Perplexity link clicks will be more valuable than Google clicks
“Our sense is also that the value of a link click on perplexity will be more than on Google. You know, your pitch has to be a way higher intent to still leave the site and go.”
Aravind Srinivas Feb 15, 2024 ▶ 29:27
Disclosure
Srinivas: Perplexity will not extract all search value like Google did
“We perplexity is not trying to be creating a trillion dollar economy On top of ads or on top of all the searches that we get and trying to take all of it and not give away much to others. Like nobody won, only Google won in the past era where, you know, the te…”
Aravind Srinivas Feb 15, 2024 ▶ 33:04
Assertion Not checkable as stated
Srinivas: Amazon faces Google-like ad conflicts with conversational shopping
“For Amazon to do this hard, obviously, because they do rely on advertising revenue on amazon.com to keep amazon.com profitable, so they have, like, similar problems to Google there”
Aravind Srinivas Feb 15, 2024 ▶ 34:54
Prediction Held up
Srinivas: Anthropic will release a model better than GPT-4 in 2024
“I actually think they will end up creating a model better than GPT-IV this year. Like, it, it's sort of almost guaranteed to happen. So I believe it's going to happen with CLAW-III.”
Aravind Srinivas Feb 15, 2024 ▶ 40:30
Prediction Held up
Srinivas: OpenAI will stay ahead of competitors with GPT-4.5 or GPT-5
“I'm sure there's a GPT 4.5 or five that will stay ahead. So it really is going to be a cat and mouse game there where Anthropics playing catch up and OpenAI is ahead through multimodal capabilities, reasoning capabilities, and things, things like that.”
Aravind Srinivas Feb 15, 2024 ▶ 40:45
Prediction Not checkable as stated
Srinivas: OpenAI's ultimate value will lie in ChatGPT, not model APIs
“I think OpenAI's value will lie in the ChatGPT product itself. The end-to-end product, and they're going to face competition there, too.”
Aravind Srinivas Feb 15, 2024 ▶ 42:03
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