All right, let's do some Q&A. We'll start on the left side here. Go for it.
Sammy: Hi, my name is Sammy, and I just want to personally thank you for helping me get a 100 in my theory of knowledge course. Would not have been able to do it without you. No shame. Quick question for you. You know, with your recent partnership with Nvidia to ship AI models across Europe, there's been talks about Perplexity being installed on all Samsung phones or pre-installed. And that could lift your valuation towards 14 billion, according to sources like Bloomberg. It's a heavy responsibility being the default search engine for you know the mainstream population. What do you think are the most important factors at Perplexity to prevent hallucinations or incorrect data from you know being given to the masses?
Thank you so much. Thank you. Hallucinations is something we really care about. We're building benchmarks internally to keep up to date with that. The only way there is to keep building a better search index, keep capturing better snippets of all the web pages, and then like these models like are getting fast enough that you can have them reason multi-step for every query without incurring too much cost, and so that's another way to reduce hallucinations.
Question about Google's strategy: I want to ask you about like the innovator's dilemma. So, if you were in Sundar's shoes or in like the Google co-founder's shoes, like what would you do and how would you kind of come up with maybe changing their business model even if it's a worse model? So, if you were running Google competing against yourself, what would you do?
I think I don't envy that job at all. Nobody in the world wants that job. It's a very difficult job. Would you sacrifice the business model in order to get like a new get the next product or would you ship it as a separate product? Like if you're Google, would you just build a separate thing that is the Perplexity competitor and sacrifice the distribution advantage that you have in the short run?
Yeah, I don't like genuinely I don't know. I think I can say all what I want, but they have more data on like what their users are doing, and there are a lot of people in the world who hate AI by the way, so I think just throwing AI down people's throats on such a you know massive distribution area is not easy. What I would do, I definitely don't know, and I don't want to be in that position also by the way. If ads are part of every AI answer, you're going to hate it too, and so it's good that there are alternatives like us.
Akshad: Hey Arvin, my name is Akshad. So in a recent interview with Nikhil Kamath, he asked you for an internship at Perplexity. So I was just wondering how that arrangement is going.
He came to the office. He spent a couple of days. I mean he hasn't posted about it. So I'll let him post about it. But we did spend time with him. It was not a proper internship, but we did speak to him for a while.
Question about foundation model consolidation: I want to start by saying thank you very much for your very candid answers. I really appreciated that. So a lot of startups they find some like cool application of foundation models and then they'll like build something off of that, but then if it does gain traction, then the foundation models will consolidate that into their own infrastructure. And Perplexity sort of has that issue too with like a lot of LLMs adding search like ChatGPT, Gemini, companies like Cohere. So I was just wondering like how would you approach something like that? Would you try to pivot, just get better at what you do, or?
I think I would say pick something you want to like be known for? Yes, there are other people integrating search, but we still want to be the fastest and most accurate, and obviously I cannot just say that and then stop like we need to figure out a new strategy too and build new products that don't exist yet. So our browser will be that bet for us, and browser and search are not two distinctive products. They're actually like the browser is a natural graduation step from search, just like how Google graduated from Google search to Chrome, and Chrome is the main reason they got billions of daily queries from hundreds of millions.
So when Google IPOed, they had no browser, and they had like maybe a 100 million queries. Now you know like it's like 10 billion or something. So the browser is an important part of that, and then so that's why we are making a massive bet on that, and agents can only be built with a browser. I'm very like convinced about that vision that if you want to have a mobile agent that you can actually build and implement without being restricted by whatever OS rules that Apple or Google sets in terms of not being able to call third party apps.
Expecting every mobile app to have MCP servers and then like connecting all their data to your thing is not going to be that straightforward. Like nobody wants to be disintermediated by an AI that quickly. So the browser will be a great way to build all these things.
Question about failure and motivation: So as a lot of us here have done, we've tried, we've failed at our startups. You know, some of us have been more successful than others. Some like me have failed. When you're in that moment failing over and over again, what do you tell yourself as CEO or as an entrepreneur to win, to teach yourself to win? What do I tell myself when I feel like I might fail? Yeah. Or when you're in that very specific moment of failing where you feel like everything's crashing down on you or this feature isn't working or this bug has popped up, how do you get through that and what do you think your biggest motivational factor is in that realm? Or maybe like at the beginning before it started to take off, what gave you the hope to keep working on it versus just go back to OpenAI and get your job?
I just watched the Elon Musk videos on YouTube. No, I'm serious. [Applause] I can tell you which video. There's a video where there's like a third failure in a row and like what do you think? And he's like, "I don't ever give up. I would have to be dead or incapacitated."
So you'd say you're also never going to give up? Yeah, I hope to like stay that way. It's not easy. I think he's done it for way longer, and that's why you all like respect him. But that's you know there are examples of great entrepreneurs who have done this despite all the odds stacked against them. So what do you have to lose? Just keep going. Thank you. Yeah. [Applause]
Question about web sustainability: Yeah, my question is about kind of the sustainability of Perplexity not in terms of the business model but just in terms of the web in general. You know, a lot of studies have come out recently showing that AI search engines like Perplexity drive a lot less traffic to websites. So, I'm curious, what do you think like the web will look like in 5 to 10 years when a lot of these websites, you know, they're not getting as much traffic and so they have to kind of cease their operations and like the web will just be a lot quieter of a place for content creation. How do you think Perplexity fits into that? And what do you think the web will look like in that era?
I think that there are going to be, you know, the web is already pretty long tail, and there's a massive power law. So I feel like the parallel is going to get even more skewed. That is very obvious. There are going to be certain brands that are well-known, and they're going to preserve direct organic visits, but those who are trying to game the SEO system and trying to get traffic, I think they're definitely going to have a harder time.
Question about plagiarism and bias: Hi Rean, good afternoon. Firstly, where do you place the line between summarization and plagiarism in report generation? And how do you avoid IP violations in your product? And secondly, how do you deal with political bias? Bias and political sorry, political bias and personal interest in news articles and other human written sources.
Yeah, I think there are cases where you actually have objective truth, right? Like what was the score in the NBA game? What is the live weather right now in San Francisco? Where you don't want to be wrong ever on those queries, and people know what is true, but you even there you're trusting, right? Like you're trusting some data provider who's tracking the live game, the TV that's showing you the number, or Apple or Google's like acute weather. All these things, so at some point it all relies on trust, and trust is built over time based on being accurate reliably, and so trying to surface the right data from the right people who have earned the right to like be surfaced in AI is how we think about it for accuracy.
Now there are things that don't have one clear accurate answer. I think there the best thing we can do is offer all the perspectives and not really take a clear opinion on like what is right and wrong when there's no clear answer to that question.
Do you measure how accurate you are at that job by user feedback in some way? We don't actually measure it today. We should an eval set should be built for that like questions where there is no one objective answer. The problem with building an automated eval for that type of thing is what is the right answer? It's subjective, right? Like if there are questions about the origins of COVID and there's so many different opinions of that, relying a lot on Wikipedia as a source and you know can say maybe for a human raider you're like okay saying all the things Wikipedia said it's a good answer, but maybe what you want is to say stuff that is not there in Wikipedia, and that relies on like having a much better human evaluators like pool, much smarter people who are supposed to rate these things, and they're not like available for like you scale AI style evaluations. Right. Right.
Question about go-to-market strategy: Okay. I think we have time for one final question. You get it? Awesome. Hi, my name is Angela. Thank you so much for talking to us. I have a question about your go-to-market strategy. You had a great campaign for students. That's how I and assume many college students learn about you guys. But then also you had a collaboration with Costco which is a little bit different audience. So I'm just trying to understand how do you decide which audience you're trying to get?
I think like what one perspective here is trying to get into distributions of users that you don't typically have access to on your traditional marketing channels. You know, there are a lot of people who don't use Twitter or LinkedIn, and they all exist in the world. We just are living in a bubble here. And there are some other businesses that have good access to them, like you know traditional businesses like you could imagine the kind of people who use Costco regularly may not even be using AI on a regular basis, and so if that's the kind of people you're going for, then it makes sense to change your strategy to reach them.
But also remember that it's good to grow with adjacencies like you do want to have some overlapping sets of people who would be the word of mouth carriers as they help you expand to more you know non-overlapping circles. So I think that's how I think about it. Like there should be some overlap, but your distribution should keep evolving over time.
Thank you. All right, Arvin, thanks for joining us. Thank you everybody.