View From The Top with Aravind Srinivas, Cofounder and CEO of Perplexity

[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]

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