I'm Arvind Srinivas. I'm the co-founder and CEO of perplexity
AI. Perplexity is a conversational and search engine that aims to deliver answers
to you, to whatever questions you may ask. We are trying to revolutionize
how people consume information online. Instead of getting ten blue links, they
can just ask questions in natural language and just get it answered instantly. And we launch the product
on December 7th, 2022. We have like about 10 million
monthly active users at this point. It's basically grown thousand X
over a period of one year. So I grew up in India,
studied in one of the IIT's there, and I was really into algorithms
programing ever since the beginning. A friend of mine told me about a machine
learning contest, which I didn't even know what machine learning was, what? All they told me was, hey, there's
this data set and you can figure out a way to predict the output given the input. And it was fun. And I won the contest
and I didn't spend a lot of time on it, and it came more naturally. So I decided to go deeper into it. And I went and did my PhD in Berkeley
on AI and deep learning. I worked at OpenAI in 2018 summer
as a research intern. I thought I was good, okay,
I did really well in India. I came to Berkeley. I'm like, definitely one
of the top AI PhD students. And then I went to OpenAI
and I felt like really bad because people were so much better than me. It was a big reality check that, okay,
I could improve a lot more in programing. I could improve a lot more
in first principles. Thinking my clarity of thoughts. After an internship at OpenAI in 2018,
that was when GPT 1 was published. We realized that there is this new form
of learning using all the internet data and learning from it, and I figured
that was going to be more important. So I told my advisor
that this is the right thing to do. We should go work on this. And he was actually like pretty
open minded and said, okay, you know what? Like I'm not a specialist here,
but let's try. I mean, if this is the next thing,
the best way to learn a new topic is to force yourself to teach it to others. So we spent a lot of time holidays,
weekends, just learning and coding and just understanding all these things. And we did this for two years. All that helped me find a new research
topic, which is how to combine generative AI and RL together,
which is what results in these amazing technologies like ChatGPT. ChatGPT is not just predicting
the next word on the internet. It's doing that and then making sure that
you know how to communicate with humans. I'd always been interested
in entrepreneurship because I've been in the Bay area. I watched this TV show, Silicon Valley,
which is pretty real, but never really found an example of an academic turned
entrepreneur that I really resonated with. It was all like undergrad dropouts. At one point, I was in the library
in the late nights reading books, and then I stumbled upon this book,
wrote the story of Larry and Sergey in the book How Google Works. Larry had written the foreword. In it, I had only two
career pathways for myself. It was either to be a professor
or an entrepreneur, and the reason is that no other career pathway
would let me execute on my own vision. I would have to be working
on someone else's vision. I wouldn't be able to bring out what
the ideas I have in my head into reality. Artificial intelligence
would be the ultimate version of Google. So we had the ultimate search engine. It would understand everything on the web,
it would understand exactly what you wanted,
and it would give you the right thing. Yeah. Perplexity is the world's
first conversational answer engine. What does that mean? Earlier, we were used to entering
something like keywords or a bunch of phrases,
and Google gives you ten blue links and you open each of them and start reading. Perplexity is trying to build a future
where you don't have to do this. You can just come and ask a question,
just like how you would ask a friend, and that AI replies to you
with the answer, but not just the answer. Every sentence that it says
also has a corresponding reference, or we call it a citation. This is all coming
from our academic background. Like my co-founder, Dennis and I are PhDs. We figured that we would use this
principle that everything in a paper that you write in academia, you have to back it
up with reference from some other paper. And that's how perplexity works. It's almost like how a journalist essay
is written or research paper is written. Often you're curious about something,
but you don't exactly know what you want. Even so, how can I help you
if you don't know what you want? People are not expert, prompt engineers
they're never going to be. Don't blame the user
for not having a good prompt. Blame the AI for not being able to expand
or help them expand themselves to a good prompt. That's why we built this thing
called copilot on our side, where as you ask a question, copilot will last. Clarifying questions on your prompt is
basically getting expanded interactively. This is similar to talking
to a friend like, hey, you know what? I'm figuring out which school to go to. I was like, oh, okay, cool.
What are you actually interested in? Are you interested in like,
English majors? So you're interested in computer science? And then I think I might be interested
in both English and computer science. Okay. Yeah. You know what?
Yale might be a good option for you. Like, that's how you talk
to a friend, right? We want that experience
to come to a search engine, to that human intelligence needed
to do that is being done by an AI now. And we think this is the future
of how people are going to interact with information on the internet. We launched the product
on December 7th, 2022, our first day, I think we saw around 2000 3000 queries. Now we serve more than
3 to 4 million queries a day. It's basically grown thousand X
over a period of one year. Growth so far has been that somebody says
ChatGPT doesn't work for this particular thing, or like Bard sucks at this thing. And then like, people just tweet,
oh, look at this perplexity thing. It just gets it. Look at this thing. This is how we maintain the quality of
the answer comes down to improving every single component here a component of like,
does it have spammy sites or does it have like high quality sites? How good are you at writing that amazing,
concise summary without hallucination? We are playing the orchestra here. These are all like individual musicians
and any one musician failing will make the result fail. That's why this is a hard thing to build. That's why this is not something where,
oh, because you're a startup, you're going to lose. Because even for a big company,
playing the orchestra is hard. Of course, if you have more money,
you can hire better musicians and like you play a better orchestra over time. But that's still
the part of orchestrating. But the user doesn't care
where it goes wrong in any of these. For the user, they read an answer
and they're like, oh, this is good. Or like, this is not good, right? So that's why this particular product
is super hard to build. And that's why, like, we are so focused
on improving every aspect of this. This is a really hard problem. And we believe it can be solved over time
as we gather more data from users as improve our own like stacks in each of
these components, your experience is going to keep getting better. So the Pro plan is priced at $20 a month. It's the exact same pricing
as ChatGPT plus, I'll tell you why. So we use OpenAI's GPT four. If we priced it lower than chat GPT plus,
people would come and pay for it, but not necessarily for what we're
probably because we subsidized GPT 4 and gave it to the user. And subsidy in any industry
has product market fit. But then do you have product market fit
as a company because you're subsidizing something everybody wants,
which is GPT 4, or do you have product market fit for your core offering, which
is combining LLM and search together? And it's very important for you to not
conflate something with something else. So we decided, okay, we'll price it at the
same price and then see how many people are still paying for our product, because
they realize that we are the best provider of search and algorithms together. Either they have to cancel
GPT subscription, come here, or they have to pay for both. Just like how you pay
for both Netflix and HBO. That's why we decided to do this, and we
are super happy that that worked, because that means what if a user comes and pays
for us, communicates to us one thing, which is they value that you are providing
the best service of this one particular thing, that they want the highest quality. Yeah, the best strategy for startups
is to focus on very few things, like literally even one thing,
because there's not much time. As a startup, you're supposed
to move fast, and as a startup you have very few shots at failure. You're also supposed to ship high quality
things so that the user trusts you. So physically impossible
for you to do many things. We're still a small team,
around 30 people. When you have fewer people,
you can only do fewer things. So therefore you spend a lot of time
thinking about what to do. And once you've decided, you just do it. There is a quote I really like
from the Airbnb founder that you have to earn the right to ship
a new feature from your user, because the user wants already a bunch of things. Your job is to actually go and do
that for them, and once they are happy, you're like, hey, give me new features
when you're doing pretty well. That's when you got to go
and ship new features. We have this mentality in the company
that don't immediately say yes to every single obvious idea
that you can do, try to really think about what the user wants and how does it work
in the context of our mission, which is to make the world's most knowledge
centric company ultimate knowledge app And once we have strategized that well,
we would just focus on execution. We wouldn't get distracted. And once it's shipped and it's in a good
enough state, we would finish the project and move on to the next thing. And then it becomes
like a repeatable workflow. And it's also the culture you want to set. Like you tell people,
okay, I'll do it tomorrow. Why can't you do it today?
Just ask that question. Don't tell them to do no, no,
no, you do it today because just ask can we do it today? And if they have a solid explanation for
why it cannot be done today, then fair. But maybe they didn't even consider they
thought okay, they could do it tomorrow. So not in a way
where it comes across as toxic, but more like trying to push them towards urgency. Hey look, we are a startup.
We need to execute. Like if we don't,
all our potential just decays. If you have a rolling ball and you do
nothing, it will automatically stop. But if you have a rolling ball and you
keep kicking it, it'll go even faster. Something is complex
because there's a lot of information. Then force your brain to say, okay,
this is a lot, but what is the one most important thing? What is the second most important thing?
Usually there's not more than two. Let's say there's like one thing
that has two choices. And there are like three things
that are eight choices. Now your brain is not able
to process eight choices at once. It's usually has 3 or 4 at best. So your job is actually to figure out
what is that two choices. In fact, there is like a advice
from Reid Hoffman that says, in life, whenever you're going to make decisions,
people usually do pros and cons where they write down the pros,
they write down the cons and then see which has more, and they pick that option. But that's like the wrong way of doing
things, because that way you're weighing everything equally important,
where things are not equally important. Usually some things are way more important
than others, so you've got to be able to take something and pick the most important
thing out of it and focus on that. Usually it works. Reformulate the problem better,
and so the complex problem becomes much simpler and then iterate. Look, I'm not saying
I'm really good at this today. I can still improve and so can everybody.
So believe in the improvement process. Don't believe in like being perfect.
And we all learn. We all make mistakes and it's fine. So I've given this advice
in other interviews I want to continue to say this not just for consistency. I really believe in it. When you are starting a company,
do what you really love because the world is not something that's static,
it changes dynamically really fast. I would say what you love doesn't
usually change, so start with that. The mission is not about making money. That said, the mission requires money
and therefore we will make money in order to like serve the mission. The metric should never be like oh,
by X year or X month. I'm going to increase the valuation by
alpha times X. It should be really focused on okay, I should make the product better. I should have more users. I should have a higher quality product,
more accuracy. A lot of people, when they wake up,
they feel like going back to bed. They feel like want to sleep
1 or 2 more hours more, and nothing's really going to change. For me, it's the opposite. I'm like waking up sooner than I wanted
to, sleeping later than I wanted to. When the day ends, I always feel like
there's more stuff I could have done, so that's actually a privilege. I also feel stress,
but the opposite wouldn't make me feel any fulfillment, honestly. So it's very fulfilling. It's definitely a privilege
and I want to keep going this way.
