Perplexity AI CEO's plan to take on Google
Inside Google’s frenzy to catch up with OpenAI
OpenAI CEO about building a consumer tech company
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Perplexity AI CEO's plan to take on Google
Perplexity has a plan to take on Google in online search, including more products for corporate customers. Several years ago, Aravind Srinivas was a recent Ph.D. student interning at Google’s AI lab, DeepMind. Today, he’s the chief executive officer of a top AI startup that’s trying to loosen his former employer’s grip on the search market. Perplexity AI, founded in 2022, gained an early cult following from power users who appreciated the AI chatbot’s focus on surfacing compelling real-time information in response to queries and including citations for sources.
Perplexity has been expanding its research options for businesses, including with a product that allows customers to search company files. Srinivas told me to imagine a world where Perplexity serves as a central hub for more sophisticated and affordable AI tools that can shop, book hotels, provide valuable data and generally act as a “personal assistant” for all users. “Then we’ll be a very valuable company because ours will be the only thing that can package it all end-to-end for the user, without the user having to worry about which AI model to use or which data to use,” he said.
A lot of people were using Perplexity at work. Perplexity actually kind of initially catered more to the research and knowledge worker audience because it was able to answer a lot of questions that you would need during your work time. When you only have 500 million queries a month, you want the value of those queries to be very high so that the company is attractive enough and can monetize those searches early on. And once they use it at work, it’s very easy for them to also go back home and use it for their personal life questions. We are still the most feature-complete product and the cheapest and most efficient to use. We provide today $20-a-month Deep Research. That’s thanks to open source. There’s no other reason.
In general, what happens in Silicon Valley companies is that once you get to a certain stage — $5 billion, $10 billion market caps — you don’t exactly know how to go from there to the $100 billion market caps. It’s very difficult. Big Tech tries to crush you by offering the same products, copying everything you did, pixel to pixel, bundling it. You’re unable to fight all that and get distribution....
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Inside Google’s frenzy to catch up with OpenAI
The search giant should’ve been first to the chatbot revolution. It wasn’t. So it punched back with late nights, layoffs—and lowering some guardrails. A hundred days that was how long Google was giving Sissie Hsiao. A hundred days to build a ChatGPT rival. Hsiao had seen her share of corporate crises—but nothing like the code red that had been brewing in the days since OpenAI, a small research lab, released its public experiment in artificial intelligence.
Google had a language model that was nearly as capable as OpenAI’s, but it had been kept on a tight leash. Wall Street was uneasy. More than six years earlier, CEO Sundar Pichai had promised to prepare for an “AI-first world” in which “an intelligent assistant” would replace “the very concept of the ‘device.’” Soon after, eight of Google’s own researchers had invented transformer-based architecture, the literal “T” in ChatGPT. What did Google have to show for it? Disappointing ad sales. A trail of resignations among the transformers inventors. A product called Assistant—the one Hsiao managed—that wasn’t used for much beyond setting a timer or playing music.
Indeed, this race to restore Google’s status as a leader in AI would plunge the company into further crises: At one low moment, staffers were congregating in the hallways and worrying aloud about Google becoming the next Yahoo. This is the story, being told with detailed recollections from several executives for the first time, of those turbulent two years and the trade-offs required along the way. To build the new ChatGPT rival, codenamed Bard, former employees say Hsiao plucked about 100 people from teams across Google. Managers had no choice in the matter, according to a former search employee: Bard took precedence over everything else. Hsiao says she prioritized big-picture thinkers with the technical skills and emotional intelligence. They nearly maxed out electricity usage at some of the company’s data centers, risking equipment burnout, and rapidly designed new tools to more safely handle ever-increasing power demand. When flags were thrown up to delay Bard’s launch, they were overruled. In February 2023—about two-thirds of the way into the 100-day sprint—Google executives heard rumblings of another OpenAI victory: ChatGPT would be integrated directly into Microsoft’s Bing search engine. Once again, the “AI-first” company was behind on AI. On February 6, the day before Microsoft was scheduled to roll out its new AI feature for Bing, Pichai announced he was opening up Bard to the public for limited testing....
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OpenAI CEO about building a consumer tech company
What was your motivation for doing OpenAI at a personal level? The Sam Altman reason.
SA: I believed before then, I believed then I believe now, that if we could figure out how to build AGI and if we could figure out how to make it a net good force in the world, it would be one of the most exciting, interesting, impactful, positive things anybody could ever do.
Scratch all those itches that were still unscratched.
SA: Yeah. But it’s just like, I don’t know. It’s gone better than I could have hoped for, but it has been the most interesting and amazing cool thing to work on.
Maybe the most consequential year for OpenAI — well, I mean there’s going to be a lot of consequential years here — but from a business strategy nerd perspective, my sort of corner of the Internet — was 2019, I think. You released GPT-2. You don’t open source the model immediately and you create a for-profit structure, raise money from Microsoft. Both of these were in some senses violation of the original OpenAI vision, but I guess I struggle because I’m talking to you, not like OpenAI as a whole, to see any way in which these were incompatible with your vision, they were just things that needed to be done to achieve this amazing thing. Is that a fair characterization?
SA: First of all, I think they’re pretty different. Like the GPT-2 release, there were some people who were just very concerned about, you know, probably the model was totally safe, but we didn’t know we wanted to get — we did have this new and powerful thing, we wanted society to come along with us.
Now in retrospect, I totally regret some of the language we used and I get why people are like, “Ah man, this was like hype and fear-mongering and whatever”, it was truly not the intention. The people who made those decisions had I think great intentions at the time, but I can see now how it got misconstrued.
The fundraising — yeah, that one was like, “Hey, it turns out we really need to scale, we’ve figured out scaling laws and you know, we’ve got to figure out a structure that’ll let us do this”.
SA: Why be a nonprofit?
Yeah. Why be a nonprofit and all the problems that come with that?
SA: Because we thought we were going to be a research lab. We literally had no idea we were ever going to become a company. Like the plan was to put out research papers. But there was no product, there was no plan for a product, there was no revenue, there was no business model, there were no plan for those things. One thing that has always served me well in life is just stumble your way in the dark until you find the light and we were stumbling in the dark for a long time and then we found the thing that worked.
Right. But isn’t this thing kind of like a millstone around the company’s neck now? If you could do it over again, would you have done it differently?
SA: Yeah. If I knew everything I knew now, of course. Of course we would have set it up differently, but we didn’t know everything we knew now and I think the price of being on the forefront of innovation is you make a lot of dumb mistakes because you’re so deep in the fog of war.
So Dario(CEO of Anthropic) and Kevin Weil, I think, have both said or in various aspects that 99% of code authorship will be automated by sort of end of the year, a very fast timeframe. What do you think that fraction is today? When do you think we’ll pass 50% or have we already?
SA: I think in many companies, it’s probably past 50% now. But the big thing I think will come with agentic coding, which no one’s doing for real yet.
What’s the hangup there?
SA: Oh, we just need a little longer.
Is it a product problem or is it a model problem?
SA: Model problem.
Should you still be hiring software engineers? I think you have a lot of job listings.
SA: I mean, my basic assumption is that each software engineer will just do much, much more for a while. And then at some point, yeah, maybe we do need less software engineers.....