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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
more excited to have you here.
>> Thank you.
>> Now to get started figured I
would turn to perplexity to help
me craft my questions.
So let's take a look at what
it said.
So to get started,
I figured I would put this prompt
into perplexity, and I asked,
I'm interviewing Aravind for
a one hour interview
at Stanford with an audience of
business school students.
What questions should I ask him?
[LAUGH] now.
>> Hopefully,
they're not too difficult.
>> [LAUGH] >> You probably missed
that in the prompt.
>> You you might have
yourself to blame for that one.
[LAUGH] so perplexity did
give me a very detailed response.
But in summary, it suggested that
we talk about, first,
your personal backstory second,
the early days at perplexity.
Third, the company today, and
fourth, various leadership lessons.
How does that sound?
>> Sounds good?
>> [LAUGH] I thought that sounded
like a pretty good outline, but
I figured we could get just
a little more personal.
So, I thought I would test out my
follow-up prompting skills, and
I asked perplexity.
What is something about Aravind
that the audience may not know?
What is the funniest thing about
him?
What are some questions that I can
ask him to inject humor into
this conversation?
>> [LAUGH] >> Very direct [LAUGH]
what are some rapid-fire questions
I can ask you at the end of the
interview, so stay tuned for that.
And finally,
is perplexity ever wrong?
>> More than you think.
>> [LAUGH] >> So this generated
some more interesting insights than
my initial prompt, including,
here's the very detailed list,
but I'll just hit on a few of them.
First, I learned that you love
cricket.
Second, I discovered that you
actually taught yourself to program
after missing getting into computer
science at IT address by only 0.01
points.
And lastly, I learned about your
connection to Sundar Pichai,
the CEO of Google,
who grew up in the same hometown in
Chennai, India.
Now, perplexity actually suggested
that I watch this video of you and
Sundar from Chennai.
So I figured that this might be
a very good place for us to start.
I'll spare you the video.
But Aravind,
is there something in the water in
Chennai that's led to so
many successful tech entrepreneurs?
>> Well, I think,
it's interesting more than, I'm
sure lot of people in India there's
so many cities which are producing
great people.
And so
one thing that I would say is very
common is this sort of culture
of really trying to excel and do
your best at what you meant to do.
And the sort of like real emphasis
on education is very much present
in Chennai and
many other cities of course, but
in at least in my circles,
people valued being scholarly and
well-read even more than being
rich.
You kind of got respected a lot for
it and I think that translates to
like going above and beyond.
And not just read what's meant for
your exam to do well in your exam,
but really try to go deep into
what you're trying to learn.
And I think that's sort of common
in many people who come from there
and excel in Silicon Valley or
other parts of the US.
I feel that it's a very common
trait.
And obviously,
this cricket thing is there.
And one thing China is known for
is they call the cricket nerds
they really obsess about all
the statistics back before google
or crick info, or
all these sites existed.
We could still recite all the stats
of every player and obsess about
things like what's the run rate,
what's the average.
And you learn basic statistics
before even it start formally to
you that it's not just important to
score a lot of runs in
one game, but
you've got to be pretty consistent.
And so I think that's kind
of common, I would say, for
people from Chennai.
>> So knowledge over wealth and
attend cricket games.
>> Yeah. >> So, it'll take
away from that one.
Now you left India to pursue your
PhD in computer
science at UC Berkeley,
not Stanford, unfortunately.
>> [LAUGH] >> I didn't get in
here that's the truth.
>> [LAUGH] >> Well,
we have you here today.
We couldn't be back here.
But how have your academic roots
shaped your approach to building
Perplexity?
>> Yeah, it's actually pretty core.
Perplexity started off with
citations right after every answer.
This is obviously like real.
I'm not just making it up.
When I first went to Berkeley and
I thought PhD is an amazing thing.
You watch movies, Stephen Hawking,
where you just knock on
your advisor's door,
this is the idea for my thesis.
I really romanticize how that's how
it's going to be.
But it's not quite as,
like easy as that.
You have to, kind of earn your way
to coming up with your first score
original idea.
So institutions like Berkeley or
Stanford, they're kind of like
amazing because they give the new
student sort of like a framework to
get there instead of just leaving
them completely unsupervised.
And so when I first went to
the lab, I was asked to kind of
help a senior student by work on
their idea and try to actually make
it really work, and write a paper.
You learn the process, and
then you kind of get from there.
So after I wrote a paper or two,
they told me this concept
of citations.
And so that matters is not
necessarily you getting a paper
accepted.
It's that other people have to cite
and build on it.
That's how you build your academic
currency in the community.
And I was okay, that's cool but
my paper seems too complicated.
So there's always this trade-off
between writing very complicated
like very creative ideas that might
get the reviewers to accept your
paper, but for someone else
to build on it like, if it's too
complicated nobody cares.
So I think like you want that sweet
spot of like very simple ideas that
will get cited, but also will get
accepted in a conference.
I had to learn the Hard way.
And once I learned that,
I kind of obsessed about citations.
And, I also learned that was
the core inspiration for the Google
search engine of how academic
citation graph to like marrying
that idea to the web hyperlinks.
So that sort of also came into
perplexity because we asked
the question, okay, what if an AI
always responded like an academic?
When you write a paper,
every sentence you write in
an academic paper needs to have
a corresponding citation to it, or
else it's kind of coming across
like an opinion.
It needs to be something like
a source of truth from some other
peer-reviewed paper in the past or
some experimental
To result in your own paper.
And we thought, okay,
what if we do that for AI,
where every sentence in the answer,
needs to come from some source in
the web that has some amount of
domain authority or trust score.
And if we can bake that into
the prompt, it's like inbuilt,
then that sort of creates a very
unique product experience, and
that's actually how my academic
roots help me in perplexity.
>> Now I know perplexity is
academic focus feature has been
a key driver of adoption here at
Stanford, and lets you cite only
academic journals.
>> Yeah. >> In your research, so
very helpful for
all of us who are studying today.
Now at perplexity, you're very
focused that's on improving access
to information and you're building
the world's first answer engine.
Why is democratizing access to
knowledge so important to you.
>> Because I love using it myself.
Like I said right,
I came from a culture where being
knowledgeable was very valued.
There is even this quote from
Charlie Munger where the best thing
you can do for
another human being is
to help them learn and know more.
And it's almost like a moral duty
for all of us to seek wisdom and
become perpetual learning machines,
because nothing else can help
us keep upgrading ourselves.
You can probably focus on wealth
and your net worth.
You can try to use that as a metric
for your progress in life, but
at some point, like it taps out,
it stops motivating you if you
reach a certain threshold.
On the other hand,
there is no end to knowledge.
That's why in perplexity,
the tagline is where knowledge
begins, because there's actually
truly no end to knowledge and
you can only keep getting better.
So there's one metric ultimately
that we can converge to view
ourselves as making progress
on that, it's just understanding
the world better.
So if that is so
core to the human nature, it's
essential all of us have access to
the tools that help us get
there in the most accessible way.
And we are trying to do our best to
do that and
obviously the more premium services
are behind paywalls.
But as these AI models
are getting cheaper and smarter,
more efficient, more distilled into
smaller versions.
It's going to be possible to create
a version that's just widely
accessible for all and helps them
basically ask any question they
wanted and get an instant answer
>> Where knowledge begins.
>> Yeah, exactly.
>> I love that.
Now I want to go back to
the genesis of perplexity.
To tackle such a big problem,
you needed a great team.
So what qualities did you look for
and how did you build your initial
founding team?
>> Yeah, I was lucky enough to know
one of my co-founders
Dennis during my PhD days.
This is also where the academic
background helps you a lot,
you learn people who are very
motivated and deep thinkers.
And so we wrote the same paper,
literally the same idea,
a day apart and so that's how we
got to know each other.
And he spent some time as
a visiting student in my lab.
And we used to brainstorm ideas
on what we could do together, but
nothing really came out of it.
One quality, I would say,
you look for
your founding team is, obviously,
people with complimentary skills.
You don't want to be as good as
them in what they excel at.
Ideally, they should
be a lot better.
And also, you don't want to step on
their toes when they do that.
And in our case,
it's kind of Dennis and
Johnny were my core founding team.
And I would say Johnny was world
number one at competitive
programming, he represented
the United States at the IOI.
And those who are aware of
competitive programming, there
used to be this guy called Turis.
And only one guy has beaten him in
the IOI ever, and that was Johnny.
So that sort of prodigy who can
not just write amazing code, but
has the problem solving skills
to instantly solve hard problems
quickly.
And the sort of AI depth and
background and
software engineering background
that Dennis had combined together
allowed me to take bold risks.
And try to set up the sort of
very overarching mission of trying
to build a completely new search
experience.
Otherwise it's impossible forget
about trying to do this, right?
So and then over time, you try to
hire more and more people who can
bring in new skills.
Obviously, none of the three of us
have front end programming skills,
so we hired someone really good at
the full stack experience.
And we hired someone really good at
writing CUDA kernels, it keeps on
becoming an incremental additive as
well as multiplicative force.
And I think that that sort of
effect is necessary when there's
a lot of people, it's not I think
there's a mental model of vector
sum of all the people.
But I actually think if you want to
create even truly great company,
there needs to be some kind of this
Lollapalooza effect,
there's factors that become
multiplicative in nature.
And one example I can give is our
design team was very well known
too, but none of the founding team
had that design quality.
So we went and hired someone
specifically for that, where that
person actually wanted to build
a product like this, but he did not
have the AI background or depth.
He used to work at Cora,
where humans came and
answered questions.
So when we gave him the platform
to use this AI to be able to answer
questions like his imagination
skills came in and
created something that's completely
like multiplicative.
And that's kind of how I
generally try to scale up the team.
>> Find the people who
multiplicate you.
>> Yeah, exactly.
>> Yeah, so less than a year later
you're in the middle of raising
your series a financing round.
When you find out that one of
your key competitors Open AI
has just launched their own search
competitor.
So when you heard the news,
how did you respond and what gave
you the confidence that there was
still room for perplexity?
>> So you're asking me about
my Series A.
>> The Series A and the news that
open AI has a search competitor.
>> Yeah, actually just this
correction there, at that time open
AI wasn't launching search.
It was actually Microsoft was
going to launch Bing and this is
almost like a Silicon Valley story,
the TV show kind of story where we
were at the office of NEA.
And we hand shook on a set of terms
there and
then I went to Blue Bottle paddle
to hear a new app with Dennis and
we're just chilling.
Okay, finally it's done.
And then the Verge publishes a
story of Bing releasing on Monday,
and screenshots were already
leaked because of some A/B tests.
And in venture funding, there's
this period called due diligence,
like 30 days.
In fact, another VC would also
offer us a term sheet.
After seeing that,
they increased the diligence from
30 days to 45 days.
And I was okay,
this doesn't seem quite right.
Maybe I was trying to back out here
and then the NEA also calls me on
Saturday morning.
Hey, do you have time for
a phone call on Saturday morning?
I was okay,
maybe they just going to say,
they want to back out,
but they actually said,
look, we believe in you.
We saw the Microsoft thing,
don't worry about it.
You figure out a way, So we're not
going to back out of the deal,
you keep going.
So that gave us a lot of
confidence, and
I felt like that was very crucial,
because I've heard lots of stories
of how you get term sheets and
actually don't get the funding, but
Dave, we're true believers.
>> Luckily your investors had
your back.
And as the underdog, you must have
needed to get creative several
times when fundraising, and you
have been very successful at it.
You have attracted Jeff Bezos from
Amazon, Yann LeCun, the godfather
of AI, and even Nvidia.
So how did you assemble
such a great group of investors and
what war stories can you tell us?
>> Well, here,
this is a funny story.
Dennis was at NYU, so
he kind of already knew Yann, but
obviously, Yann is a celebrity,
it's so hard to reach him.
So Yann was on a vacation in France
for a long time and we just heard
he came back to the NYU Campus.
So we were already in New York at
the time, so we just basically
camped in front of his office for
multiple hours.
>> [LAUGH] >> And he went for
lunch, and he was like, yeah,
you guys are waiting.
Okay, fine, I'll come back.
And then we finally got half
an hour with him, and we built
this search over Twitter demo,
where all we had to do is let him
search over his own tweets and
who's replying to him and
how many followers does he have?
All those kind of interesting
questions everybody has for
themselves, and he allowed it.
And he's like, okay, fine,
I want to invest,
he just made the decision like ten
minutes of using the product.
Same thing happened with
other investors, like Karpathy,
he's a celebrity here.
He asked for
a deck and I just sent him the link
to directly try the product.
And same thing with Jeff Dean, all
these people were just impressed
by just using the product.
So the main takeaway here is,
there's this thing called
a circle of competence.
If you're not good at making decks,
don't try to do it, right?
>> [LAUGH] >> And
I wasn't good at it, so instead,
just make sure there is a link that
they can actually use or
try instantly and
make sure it works.
Because there are some people who
do that and
the moment you just click on it,
it just crashes or it doesn't work.
That's not a good experience.
But if it works,
I think it communicates a lot more
than having a deck because,
number one, most people don't have
the time they're on their phones.
They're not on their computers
reading every small part
of the deck you optimize for.
The other thing is,
if you're not good at it like me,
then don't try to do it.
And by the way,
I haven't really done decks much,
even for our Series A,
it was very minimal.
Series B, no decks, C, D, I just
write memos or notion documents.
I actually try not to do
it because I'm just not good at it.
Even a lot of successful decks from
the past, like Airbnb, LinkedIn,
Facebook, and you see all that and
you're just even more confused how
to make one.
because they're all so
different, and you don't know
which one to copy or like how to be
original, it's very confusing.
So I just never tried to do it.
>> [LAUGH] So
play to your strengths instead of
being a copycat.
>> Yeah.
>> It's like a lesson,
you have a lot of perspective
entrepreneurs in the audience, and
so I think this is a good reminder
that it takes great determination
and hard work, and
that that can really pay off >> Or
you don't have to be really good at
many things that people may, like,
if you can be founder, CEO and not
know how to make that, it's fine.
>> [LAUGH] You have a lot of
consultants here who all we do is
make slide decks.
>> [LAUGH] >> [LAUGH] So, maybe we
have the opposite skill set.
We're a good team,
if you put the two together.
Now, at Perplexity you're building
an answer engine, but
you don't own the content and
you don't own the models.
So what is your technical moat, and
why is the Perplexity approach
better than direct vertical
integration?
>> She's politely asking me why
you're just the rapper, so tell us.
>> [LAUGH] >> Those are your
words, not mine.
[LAUGH] >> But
yeah, this is kind of, actually I
would be, one year ago, the whole
community was pretty divided on
which startups to invest in, or
which kind of startups to build.
Should these companies be training
their own models, or
should they be using APIs?
And we had a conviction that,
number one, models are going to get
increasingly commoditized,
and if you do want to be one of
those players that build it,
like our provider of the models.
You need to have an insane amount
of funding and you need to be a
company that is losing billions of
dollars a year and it's still fine.
And we were not in a position to be
and we didn't want to be either, so
we decided to use other people's
models and shape them to be really
good for a end-to-end consumer
experience of searching.
And we felt like there was a lot to
do outside the model there.
And I think that bet ended
up being right in the sense,
there are a lot of companies that
were trying to build their models
who no longer exist.
And I think that was a clear proof
point that you either raise $10
billion or
you don't do this thing at all.
You do something else.
And for us, we were working on
giving answers to people.
And if the answer to this question,
for giving accurate answers to
everybody, do you need to build
your own foundation models?
The answer to that question is
an absolute yes, yes,
we shouldn't be doing this thing
without raising 10 billion.
But I felt like if
open-source makes progress and
models keep getting cheaper,
the cost of these APIs is going
down 2x every four months.
So assume that trend continues for
another year or two, we are at
least going to ride the wave of
a 10 to 100x reduction in the cost
for the same intelligence.
And the level of intelligence and
reasoning is also going up.
And open source is keeping a check
on these closed source models and
bringing the price down.
It's a perfect time to be
an application company using these
models and post training them to be
good at summarization, referencing,
formatting.
Custom UIs for these so
many different verticals, finance,
sports, reasoning,
all these kind of charts.
There's so many things to do
outside the model that we felt like
it was just completely worth it to
build a differentiated business.
And at the end,
most successful businesses
are rappers of some form, right?
Like, before they existed,
something else was the more
valuable thing, and
then something comes on top.
There's even a thing of,
Coca-Cola wouldn't have
really worked if the refrigeration
technology did not exist, right?
But Coca-Cola is extremely valuable
direct to consumer product.
And so, you can always create
something that's some magic
formula, the right packaging,
that works with the foundational
technology.
But in the hands of the consumer
provides immense value to them that
it's totally worth building.
And so, that's what we want to be.
>> What should you build yourself
and when can you leverage things
that already exist.
>> Yeah.
>> It's a great strategy.
Now, you've been openly
critical of Google's over-reliance
on advertising.
And yet, just this past
week Perplexity announced that it
was also introducing advertising
[LAUGH] for the very first time.
So what is your monetization
strategy, and how big of a role
will ads play in the future?
Future.
>> Yeah, so perplexities ads
are different from Google's ads.
Google's ad the problem is the same
ad unit is whatever is the answer
unit is also the ad unit there in
the sense Google gives you a bunch
of links as for most queries.
And that is also the unit an
advertiser can influence by paying.
So that way, when you're looking
for relevant answers information,
and if the ordering of the links
was manipulated with ads,
it frustrates you.
If we can avoid the trap and pick
an ad unit that's lower margins,
lower Profits, yet allows us to be
true to our users and
still make money.
It's a reasonably better, or
like you say,
I would say a much better sweet
spot than what Google went for.
And we said, okay, there is an
answer that should be unbiased and
truthful to whatever you ask for.
But after the answer,
there are a bunch of questions
that we suggest you to ask next.
You don't have to literally ask
that, but at least it influences
you on what you want to ask next.
And let's say a shot like having
a shopping related query of,
like I'm looking for running shoes,
and this is exactly what I want.
And these are the brands I like,
and it gives you an answer,
the follow-up question that we
could suggest there is some shoe
brand that tries to get your
attention there.
Which could be what makes Adidas
better than Nike for tennis or
something like that, right?
That's a question they might have
picked because your first question
was probably, I'm looking for
shoes for playing tennis.
That's a very
high intent question compared
to just an ad word of a shoe.
But we're not making a particular
brand appear one in front of
the other on the original answer,
but we could still get your
attention on the brand as
a follow up question.
You can choose to ignore it too.
So that is an ad unit that we
are experimenting with, and
we're working with a few brands who
are willing to try it out.
First of all, the major concern is,
right now for brands,
they're afraid how the answer can
come out to be, because they don't
really control the answer.
No brand is influencing the answer,
they're only able to pick
the question.
So it first takes courage for
some brands come and experiment
this style, the ROI is not exactly
clear, because it's not necessarily
driving a lot of traffic to you.
So it's
still very early days for us.
But what we are very,
very clear on is not trying
to influence the accuracy and
truthfulness of the answer.
Because once we do that, then we're
going to end up in the same path
as Google, where people
are frustrated with the answer.
>> So when I type
my initial prompt, for example, for
this interview,
I will never see an ad response?
>> Exactly, yeah.
>> Okay, reassuring to hear.
Now, perplexity is obviously
innovating very quickly,
and yet this pace of innovation has
attracted some controversy.
So News Corp, the parent company of
the Wall Street Journal, has sued
you for copyright infringement.
The New York Times has also issued
a cease and desist order for
inappropriate content use.
How are you handling these recent
challenges, and what is your vision
for ethical AI development?
>> Yeah, so here's what we believe,
and we've said this on our blog
post to, no one has a copyright or
ownership over truth or facts.
This is true in the world of
journalism too.
If there is an article,
for example,
right now in our interview,
you reference is that the New York
Times is zero perplexity.
Now, that was reported by somebody
else, but
you're using that in our interview.
Now, can someone claim ownership
over that and disallow you from
saying that particular thing,
no, right?
So truth is supposed to be
distributed widely, right?
So the specific expression of
truth, the specific way in which
something is written that has
some copyright angle there, and
that's actually the core
OpenAI New York Times scenario.
But what we are doing is,
we are referencing truth that
already exists in these outlets and
summarizing and synthesizing it for
the user in the context of a search
experience.
So people need to differentiate
the use of AI that trains on
proprietary content, versus AI's
that just use them as sources and
give answers and there's no actual
training happening.
So we made that very clear in our
response and we've also made it
clear that we can only survive and
keep getting better as a product if
there is an open and
thriving ecosystem of journalism.
Because we do need real time
information to be created every
single day, and if there's not the
right financial incentive for them
to do that, then it's not good.
So what we did is It's, okay,
we're going to make revenue through
ads, and we're going to share
that ad revenue with publishers.
And that way, you enter into this
publisher program that we came up
with, which is not exactly paying
you money just to license your data
for a certain period of time.
And then once we've absorbed it,
we don't want to create that sort
of a short-term model.
A long-term model,
is as we scale and
usage as we scale as a business and
revenue.
We want to share that revenue with
you on a query level basis.
So it's very clear, this is
more inspired by how Spotify shares
revenue and fortune time.
Der Spiegel have all signed up
to be part of it,
WordPress signed up part of it.
And we are also going to announce
more partners in the coming weeks.
So, we are very confident that that
program will soon resonate with
everybody in the journalism
community.
And we also made grants to
Northwestern University to kind of
do more research on how tools like
ours can help journalists write
better, because all journalists do
fact checks, and we are an amazing
tool for doing fact checks.
So I'm very confident that this
current period of turbulence will
go away, and a year or
two from now we'll have a system
that helps both these different set
of people to flourish together Just
to follow up on that.
So earlier today we talked about
perplexities, academic roots and
the importance of citations.
>> Yeah. >> So given that,
how do you handle these journalist
allegations of plagiarism in
particular?
>> Yeah, so exactly, so that when
you want to go deeper into
the definition of plagiarism, it's
if you don't attribute the source.
That's a core part of it, and
when you're always attributing
the source, it's very hard to say
you're plagiarizing content, and
also you're not exactly
reproducing things, as sure,
AI are unreliable at times.
And there are times when they're
word overlap of more than three or
four words.
And you can argue to what extent
that is exact reproduction was
just trying to synthesize.
But what we are trying to say is we
are trying our level best to
summarize, synthesize from diverse
sources, and make sure to give
credit to all the original sources.
And that way,
to our best can control these AIs.
We are doing our best to make sure
that the credit attribution
part is clear.
>> I like the Spotify analogy,
it's such a rapidly changing.
>> Yeah exactly, so
if we make an ad revenue where
you're a source, we're going to
share that revenue with you.
Who would ever share ad revenue?
Google, because they gave you
the traffic, but they made the ad
revenue on their platforms.
And the only way for
you to monetize the traffic
that you get is to put pop-ups and
ads on your site through another
product of theirs called AdSense.
And so that is what frustrates many
users who come directly to read on
many Journalist sites because
there's a lot of ads on the site,
and they have to close a lot
of pop ups.
And so this system
of just referring traffic and
making you monetize with more
ads is not sustainable, right?
You need to create something that
the user really wants.
And we're also offering our APIs so
that they can build AI native
products and
chat bots on their websites.
So if people want to just come
there and ask questions about only
articles that they've written.
We're offering our APIs for
free to these people, and
we're also offering our tools for
free to all the people who work at
a particular journalist outlet.
So that way, we can create a system
that is economically pretty
lucrative for them.
>> It's an interesting
future ahead.
So if we take a step back now and
we think about the biggest
technology companies of all time,
in almost every case, these
are category creating companies,
Uber, Facebook, Airbnb, Salesforce.
So a decade from now if we look
back on this moment in time.
What is the history defining
company that you are building?
>> I would say if we can help
people get answers to all their
questions and
get help for all their tasks we'll
be in that league for sure.
And we're getting pretty close to
being a reliable answer machine.
I know you asked the question,
is Perplexity ever wrong?
I'm telling you,
there are a lot of mistakes we
still make on a daily basis.
But zoom out and think,
if models keep getting better and
our coverage of the web
is getting better.
The mistakes are going to
be whatever is one in a 10 or
one in 100 is going to,
be reduced to one in 1001 or
10,000 the order of magnitude
improvement is going to come.
So if we are a reliable answer
machine to everybody and
widely accessible, and
not just give you answers, but
help you accomplish tasks.
To make transactions, buy things,
book things,
book flights, get the best deals,
and make your life more productive,
give you back all more time.
I think we are going to be a pretty
industry-defined product in
a company.
>> It's exciting, we hope to see
you there a few years from now.
Now, there's so much more we
could talk about when it comes to
Perplexity, but I wanted to save
a few minutes to talk about you and
your leadership style.
So in just two years,
you've progressed from a scrappy
founder, to CEO, to the leader of
a $9 billion AI company.
What does your leadership journey
look like across all of these
different stages?
>> Yeah,
I tried my best to keep upgrading.
And I'm still not the most
seasoned, polished CEO.
But I would say there's an extreme
bias for
action that I try to bring in and
try to encourage everybody else in
the company to adopt.
And I think that's what's helping
us continue to be fast, even when
you've gotten to about 100 people.
A founder that I really admire told
me, once you get to 100 people,
you're guaranteed to move slow.
And I was very determined to prove
him wrong.
So, so far, so good.
But at some point, definitely,
we're going to hit the problems of
scale and how to move fast.
So I'm determined to solve that
problem and if whatever final
solution I come up with, I hope
it's helpful for other people too.
And the other thing I would say is
giving people who haven't
necessarily become experts at
one thing the opportunity to go do
something they're not yet
proven for.
Is something I've done a lot,
you don't have to hire the former
head of growth at Instagram to be
the head of growth or
head of product Perplexity.
That's a trap that a lot of people
fall into.
It's, if I want the best person for
doing AB tests,
I'm going to get the person who did
it at the previous best consumer
company and hire them here.
I have not fallen into this trap.
I've actually tried to hire people
with some chips on their shoulders
who are very talented, but
they have not had their first
major hit yet.
Chips on shoulders,
put chips in your pockets.
So not my original quote, so
I don't remember who said this, but
it's pretty cool.
So that's something that I wish
more people did the sort of
experimentation, putting someone
in the waters and letting them
figure out how to swim.
Rather than hiring the most,
well known expert at that topic.
Main reason is that most people
are unable to push themselves for
the second success in general,
I've seen that.
And I think, it's very hard to be
extremely motivated to do grueling
hours when you've already had big
success in your life.
So that's one way I've tried to be
different and bias for action,
trying to do things on my own,
to understand what it is.
And I use the product
quite a lot myself,
pretty much it's like at least 10
queries a day is my average.
But there are some users who do
it more than me, so I'm very happy,
and I think that helps me to make
the right decisions.
If at some point you stop using
your own product that the company's
building, it's very easy to lose
touch with reality.
And you're just making decisions
based on what other people tell
you, and it's very essential
that you're as close as possible
to the source of truth.
So when people complain on social
platforms like Twitter or
this thing's not working,
that thing's not working,
I love doing customer support.
I think we have people
who do customer support too.
I'm not trying to
say they're not needed, but
it really helps you to understand
what the customer frustration is,
the user frustration is.
And be that sort of a user
yourself, complain about your own
product to your engineers,
your product managers say,
this should be fast.
You don't have to, sort of just
be doing whiteboarding and
strategy all the time.
You can actually just sit for
hours and
hours using your own product, and
you can make better decisions.
>> How we stay scrappy at scale?
>> Yeah.
>> It's a great one to stick with.
So before we open it up to
audience Q and A,
I have one final question that
we're asking all of our speakers
this year at view from the top,
our theme is leaving your mark.
So Aravind, how would you like to
be remembered?
>> I would love for myself and
Perplexity, to be known as helping
make the world smarter.
If people who use Perplexity feel
smarter after using it because they
learn something new,
they slept wiser than when they go
to bed, then they woke up.
I would feel really,
really glad if we accomplish that
because I think that's not easy.
Most consumer products end up
wasting people's times.
There are obviously not going to,
I'm not going to mention which, but
there are some products I
am addicted to.
I use it a lot, but
I don't feel good at the end,
I've wasted so many hours.
And Perplexity is not that,
at least, I don't think it is that
sort of a product that may, even
the discover feed that we have,
people tell me that they
learned something when they scroll
through it.
And I want that to continue to be
the case.
And I also want us to help
people do things.
Not a lot of people can afford to
have a Assistants, executive
assistants, personal assistants.
And I remember in 2018, when I was
an intern at OpenAI, Sam Altman did
this fireside chat with Bill Gates.
And he asked Bill Gates,
what do you think the world would
look like when there is AGI?
And the answer Gates
gave was very interesting.
He said it would basically be like
living my life.
>> [LAUGH] >> Live like
a billionaire, where
if I want to know about a topic,
if I want to learn about a topic,
I don't have to read any book.
I can have people read it for
me and prepare a report for me and
even make a presentation for me.
If I have to get somewhere,
I have a jet, people take care of
all the travel planning, meals.
If I want to work out,
everything is done.
I want the best nutritionist,
I know what to eat.
I don't have to think that
life is so easy.
It's like running life on
cheat code.
Now, I think that sort of
a life can be made more and
more accessible to most people.
If AI can do stuff for you,
truly understand you, help you plan
stuff, help you book stuff,
all the mundane work that you have
to do on the web.
If a tool can sort of increasingly
get better and better at doing it,
I feel like your life will be
like a billionaire, right?
And then the meaning of the word
billionaire also sort of loses
significance over time.
So I think if we can be one such
tool, I'm not saying we want to be
the only tool, but if we can be
the one such tool that helps people
do that, I feel like I would've
made a good mark in the world.
>> If Perplexity can give me
Bill Gates' life,
I will be very happy one day.
[LAUGH] Now, we'd like to open it
up to audience Q&A.
So if you have a question,
please raise your hand and
one of our view from the top mic
runners will come find you.
If you're selected, stand up,
state your question and year, and
ask your question.
>> Aravind, firstly thank you,
and then you're one of the young
leaders we all look up to given
where we are today.
I'm a fan of the book
Atomic Habits.
So in your journey from PhD student
to Perplexity CEO, what is the one
habit or daily habit you had to let
go of and maybe a new one you
learned that helped you
become the leader you are today?
>> So the one habit I let go of,
I'm not sure if I had to,
but I definitely let go of this and
I feel like it helped me,
is waking up late was something I
stopped doing.
So- >> [LAUGH] >> Yeah,
I think it makes me feel like I get
more hours in the day.
And so that also means going to
bed early.
Early to bed, early to rise.
I feel like it helped me severally.
So it's been probably
at least maybe three to four years
since I've woken up later than 8 AM
in the morning.
And it doesn't matter which city or
where, I've always done this.
What was the other other question?
>> The one you learned,
that you had to pick up I
think, yeah, at least trying to get
better at getting three days a week
workouts.
>> [LAUGH] >> And I never used to
work out much before, so.
>> [LAUGH] >> Thank you for
being here, Aravind.
>> Thank you. >> My name is Ravin,
I'm a second year MBA student,
went to IIT Bombay for my dual
degree in electrical engineering.
I think you answered the technical
mode question really well,
but we'd like to hear from you.
What do you think is the biggest
risk or challenge that you feel
the company is facing?
>> Sorry, could you repeat that?
>> What do you think is the biggest
risk or challenge that you feel
the company is facing today?
>> Yeah,
I think it's the same thing I said
earlier, which is, I think every
startup that's tried to scale
somehow ended up moving slower
once they got several hundreds
of people, a thousand people.
Somehow it gets difficult to
do things.
You expect progress to be at least
linear, and the number of people,
you can do more projects.
But it gets very difficult to
simultaneously execute well
without some drop in quality.
And when there is a drop in
quality, users notice that, and
they think you've regressed,
your product has gotten worse.
There's this whole phrase called
enshittification, when you're
trying to scale and scale your
business, scale your users,
product gets worse in quality for
the initial loyalists who allowed
it for the quality.
So that's, in my opinion,
the biggest challenge for us.
>> Hey, I've got to follow up to
Aislinn's question earlier about
the ethical issues that Perplexity
has been facing.
I know that you personally
have experienced a lot of criticism
surrounding some of those issues,
and I imagine that as a leader in
those spaces, you spend a lot
of time thinking about that.
I'm curious how you've approached
ethical issues, whose opinions
you seek out to inform yourself
as you step into bigger and
bigger roles, and
if there's an example where you've
seen yourself change your position
on something really important?
I'm sorry, I'm and I'm an MBA 1.
>> Thank you.
So I think we have a good set of
people in our company.
Actually, for the Publisher program
itself, it's the brainchild of our
chief business officer, Dimitri.
So clearly, one thing that I've
learnt is, just because I'm the CEO
doesn't mean I have to be the one
who solves every problem.
If someone's better than me at
doing some thing,
you should trust instincts there.
One thing I did believe in
is there's a lot you can do by just
engaging and trying to educate
people on the other side of what
you're trying to do.
I'll give you an instance.
Forbes, obviously, was pretty
unhappy with some of our attempts
to do pages and things like that.
But when I actually met the person
who criticized me on Twitter and
explained to him what we are doing,
he at least shook hands and
said, I never understood this is
exactly what you're trying to do.
And so I think there's more
work to be done there.
I haven't met everybody in the
community who's talking about us.
And I think just trying to
perceiving something, right?
When there is even a sign of war or
it's foggy around there, feels
something my bad might happen,
the first thing you got to do
is make a phone call and talk.
So that's what I intend to do.
Hey.
>> Thanks so much for coming here.
>> I'm Varun, MBA 1 student,
computer science from IIT Kanpur.
You're a big inspiration
>> Thank you.
>> I really resonated with
the point where you said that
you're trying to help people find
the answers that looking for.
But then also when you talked about
introducing ads in suggestions,
where you suggest like, why do you
think a Adidas is a better shoe for
sports than Nike or something?
Don't you think that affects
the kind of information or the view
that you're presenting the users?
That might not be the answer
they're looking for.
So don't you
think- >> It's a question, though,
it's not an answer.
It's just a suggested question.
But if you do decide to engage with
that question, the answer to that
question is still unbiased.
It's not something Adidas is
influencing us to write relative to
the other The brand, and
the same way.
So at some point, we would really
understand you quite deeply enough
that even those questions are quite
personalized to you and
not a generic sponsored question
that the brand picks.
And there has been evidence that,
for example, a lot of people feel
like the Instagram
ads are pretty relevant to them,
and a lot of purchases
happen as a result of that.
So, I feel like relevance is
the true answer to making ads work,
and making sure that it's not
interfering with the core value
of the product.
Which is, any question you ask if
the answer to that is un influenced
by ads, and it's always going to
be truthful, the product serves its
value to you.
But if we want to bring such
a quality product, which is almost
never wrong, so you can trust what
it says at scale, the company does
need to figure out some intelligent
sweet spots of monetization too.
>> Thank you so much.
>> I think we have time for
just one more question.
>> Hi, Irwin, I think this might
be a good one to end with.
By the way, I'm Abrar,
I'm an MBA 1, so as the co-founder
of Perplexity, what is the question
that you find the most perplexing?
>> [LAUGH] >> This one.
>> [LAUGH]
[APPLAUSE] >> It's
a great answer.
>> [LAUGH] >> I'm glad you
stopped there.
>> We do have one final tradition
here at beef from the top.
Where I ask you a set of rapid fire
questions, and you respond with
the first thing that comes to mind.
>> Okay.
>> For this one, I use Perplexity
to generate all of these questions.
Should be easy, right?
>> Hopefully.
>> [LAUGH] If you weren't the CEO
of Perplexity,
what would you be doing right now?
>> I'd probably be doing research,
that's what I was doing before.
So, this AI research.
>> You're a cricket enthusiast,
what is your all time favorite
cricket moment?
>> When India won the World Cup in
2011.
>> [APPLAUSE] >> If you could have
dinner with any tech visionary that
are alive, who would it be?
>> Larry Page.
I mean, I'm not saying this,
Steve Jobs or
Larry Page would be my pick.
>> Bring them together,
dinner for two.
[LAUGH] And finally,
what is the strangest search query
you've seen on Perplexity?
>> [LAUGH] >> So
we released Shopping on Monday, and
just looking at some of the otters,
and someone basically bought this
face mask that only has an opening
for the eyes and nothing else.
And so, either they're looking at
it in the context of skiing
somewhere or like biking somewhere
it's really cold, or
they're conducting a heist.
>> [LAUGH] >> A nd we weren't sure
of it, so we actually went into
the query, and the query was, okay,
I'm really trying to bike in this
weather in the coming months.
And I need something that can cover
my face, keep me warm,
let me breathe, but
only as an opening for the eyes.
That was the intent level of the
query, and then we got them some
pretty good answer that they just
bought a product right from there.
>> [LAUGH] >> [LAUGH] Well,
let's hope that the use case was
the former and not the latter.
>> [LAUGH] >> But
that's a great place for
us to wrap up.
So thank you so much, Arvin, for
being here.
It's been a pleasure.
>> [APPLAUSE] >> Thank you.
>> [APPLAUSE]
[MUSIC]
Nikhil Kamath
