45분 만에 700억 투자받은 창업자가 말하는 AI의 진짜 미래 | Radical AI, Joseph F. Krause

AI is so incredible. This technology is

going to change the world. What I don't

understand is why everyone is picking

lowhanging fruit and solving small

problems. We saw a bunch of AI companies

in software or you know normal SASbased

[music]

businesses. Why is no one using AI to

cure cancer? We are trying to disrupt

the process that is 150 years old with

some of the biggest companies today in

materials. We want to reinvent the way

[music] we do the scientific process. We

don't struggle with driving one, two or

[music] 5% improvements in a current

system. What is incredibly challenging

is novel discovery. The most important

areas are the most challenging. I think

those are the things people should work

on because if you succeed, you will

fundamentally reshape human trajectory.

Every single person that we hire into

radical AI, we ask the same [music]

question. If you are looking for a job,

this is not the place for you. You're

incredibly intelligent. You can go get

employed [music] other places. If you

are looking for a mission, then you

should come work here.

My name is Joseph Krauss. I'm the

co-founder and CEO of Radical AI. At

Radical AI, we are building artificial

general intelligence [music] for

scientific discovery starting in

material science. The material discovery

process is challenging today. Processes

in materials just take an incredibly

long time, [music] typically 10 plus

years. Our AI agents will index millions

of scientific [music] publications and

learn what a field has done already. And

so this process can happen at an

incredible speed in the comparison

[music] to a human scientist about 370

times the speed we operate as a human

scientist today.

I just always was taught and really

wanted to be like my dad in pursuing

something that I knew I was the best in

the world at and that I truly love to

do. My father, he always instilled that

not just about being happy about what

you're doing, but much more engaged in

what you're doing. Find the thing that

you can be better at anyone else in the

world in. Where can I make an impact?

That for me has always been this guiding

light into what I want to do and how I

want to do it. And so when I was an

undergraduate, I actually bumped into

someone who was serving part-time in the

National Guard. I really wanted to go to

a military academy in the United States.

They're incredibly prestigious. You have

the opportunity to serve the country. So

I thought that this would be for me. And

[music] the US National Guard is a

reserve component both of the Army and

the Air Force. You pretty much go to

drill one weekend a month and then you

do two weeks in the summer of training

to actually make sure you're up to code

with your military training. and if you

ever get deployed down range. I was

like, well, this is amazing. I can

continue to study, but I can also serve

in the military in my free time is the

way I looked at it. So, I enlisted in

the military my junior year of college.

Basic training is an amazing experience,

right? Because you're with a bunch of

people you've never met in your life.

Meeting people from so many different

walks of life. I met people from New

York, Pennsylvania, Georgia, Maine, and

the East Coast through to the Midwestern

or or or western states all the way

through to California coming from San

Diego or Silicon Valley. And everyone

was there for the same mission. They

were there for the same goal of building

a stronger military to protect and

defend the freedoms that America likes

to propagate throughout the world. that

was not only inspirational but was the

first time I was forced to remove myself

from the equation and put the mission of

the team which was the battery that I

was serving in before yourself and that

was an incredibly insightful lesson and

so went away to basic training and then

came back and finished my senior year

and then went away to training again

before starting graduate school at Rice.

So for Rice there were one specific

reasons. I had went to this

undergraduate research symposium which I

presented my work on and I won that

symposium and in winning the symposium

the best presentation I got to sit with

a bunch of both graduate students and

professors inside the program and ask

them about their research and what they

were working on and there was a

concurrent theme through that. They were

all working on problems that could have

a big impact, actual things that they

were trying to transition at one point

or another. I interviewed at a lot of

graduate programs when I was thinking

about where to go to school, and none

had felt as strong as I did when I met

the faculty and students at Rice and

this kind of focus on the future and

what they were trying to build. So, I

was doing them concurrently in graduate

school and in the military at the same

time. But I didn't know what I wanted to

do after [music] graduate school. I

didn't know if I wanted to be a

professional scientist. I had thought

about fields like law, patent law. So in

graduate school, I did this deep dive in

understanding where could I make an

impact.

While I was serving in the National

Guard, I was also not together a

scientist at the Army Research Lab. It

is this corporate research lab that the

US Army has a bunch of scientists

working in to try to push novel research

up to higher technology readiness levels

or or make that science more

approachable for the army. We used to

have these commanders who would come

through and tour the facility. We would

have to tell them why the work we were

doing was relevant to the army and their

relevance was not the same relevance to

us. They were thinking about future

conflict about how to bolster the force

or make it stronger. We were thinking

around electrons and and hydrogen atoms

and thinking about making new novel 2D

materials for different technologies.

And so there was this disconnect [music]

between leadership at the army and the

scientific perspective that we were

driving. And there was this day where I

had to actually explain why what we were

doing in the lab could eventually impact

future of warfare or future technology

that the army would want to use. And

that's when I realized that that is

exactly what I wanted to do. I wanted to

transition from this fundamental area of

research driving our understanding of

science to actually commercialize

science. Science that could actually go

into products and make a difference. And

that was where things started to come

together that the only way to really do

this is to actually push technology in

[music] a novel way in which case

startups are the best in my opinion the

best place to do that today. Okay. I

know one day I want to build a company,

but I have no idea how to build it. And

so I said, let me find entrepreneurs and

investors who have built a company in

the past and now are investing in the

companies of of the future. And so I

looked up a bunch of venture

capitalists, entrepreneurs, and really

wanted to be in New York. Actually, I I

tailored my search to New York and I

bumped into Kevin Ryan. Kevin Ryan is a

prolific entrepreneur in New York City.

He built and ran Doubleclick before

taking that company public. And then he

came out of that and started Ali Corp,

which is both an incubation studio as

well as an earlystage investment firm.

And when I talked to Kevin, I had told

him, if you're not investing in

materials, you're not going to invest in

the future. And he said, "That's a big

that's a big bet. Why don't you come

prove that out?" And so I took a leave

of absence. I moved to New York a week

later, and I had a six-month internship

to see if this was the field for me, if

this was the career for me. Kevin had

taught me early part of my career that

you have to have a bias to action

[music] and just get things done.

Strategy can be effective but most of

the time will also lead to a dead end

with no action involved. The best

entrepreneurs have an immense [music]

bias to action. They just get things

done and in doing so watch the results

unfold in front of them as they do that

and then they continue to [music] go to

go through their process. Startups are

already hard enough and the way to make

them easier is to do more than anyone in

your space will do with more information

than anyone in your space has with a

thesis [music] that no one else has been

able to come up with. That is truly what

can drive good value. And I think a bias

to action is the most important lesson

I've learned from him.

One of my other co-founders and I were

both investors at at Ali Corp. And Jorge

was looking into AI technology as every

good investor was, but really at a

fundamental level. He was reading the

publications coming out on novel

architectures and novel approaches to

machine learning and really what the

impact of the technology was. And he

came over to me one day. We sat next to

each other in the office and said, you

know, AI is so incredible. I am actually

convinced this technology is going to

change the world. What I don't

understand is why everyone is picking

lowhanging fruit and solving small

problems. Why is no one using AI to cure

cancer was the question he asked me. And

and I said, well, I don't know about

curing cancer, but that's a really good

opportunity. And so we spent the next

month and a half reading hundreds of

research papers on all the different

fields that we think AI could be put

into. And finally it dawned on me that

well material science problems with

fragmentation, slowmoving ability, you

know, lack of progress over short

timelines. This might be a great area

for AI to be implemented in. And so we

took another deep dive and we read every

publication we could find at the

intersection of material science, AI and

as we found out robotics and that led us

to our third co-founder Herd Cedar who

had built an autonomous scientific lab

at Lawrence Berkeley National Lab and

together with him us three really saw

and came up with this vision for where

science is going to go where AI and

autonomy are going to build a new

paradigm of scientific [music]

discovery. driving us from a

human-driven to an AI and autonomydriven

process. And we were all aligned that

whether we started Radical AI or not,

this is the way science was going to go

and it had to be us who were going to

build this company. And so all three of

us agreed and that was the formation

story for Radical AI. The most important

areas are the most challenging. I think

those are the things people should work

on. I think if you look at technology

today, we don't struggle with what we

call optimization problems at Radical

AI, driving one, two, or 5% improvements

in a current system. We're actually

quite good at that. What is incredibly

challenging is novel discovery. And

that's where most hard problems lie. And

when us three wanted to form the company

and we're going to build radical AI, we

had this opinion that if you want to

impact the most important industries in

the world, automotive and aerospace,

manufacturing and defense, climate

energy, semiconductors, all of them are

a direct result from materials R&D. But

these processes and materials just take

an incredibly long time, typically 10

plus years, [music] and an exorbitant

amount of cost to go from a novel

discovery to a scale material system.

And this was the exact place [music]

that we could make a massive impact. We

think AI and autonomy [music] are going

to drive change in the process and in

doing so can actually unlock and remove

materials as our biggest barrier to some

of our most important industries. And I

think if you are aligned on that

mission, then the problems that you want

to solve are naturally going to be hard

because if you succeed, you will

fundamentally reshape human trajectory.

And that is an incredibly impactful

thing to be able to do and also

incredibly important to the future of

the world.

We're going to leave Ali Corp and we're

going to raise money of course to start

the company and Ali Corp as I mentioned

likes to incubate companies and we were

incubating this company inside the Ali

Corp umbrella. So we knew Kevin had told

us they are going to put some money in

in this incubation setting and then

we'll roll out from there. And we knew

we needed a lot of capital. Material

science is a hard business to build in

and we are building a full stack

solution which requires a lot of

capital. So we knew we wanted to raise a

fairly large preede round. And so we

went to Kevin and said, "Look, we're

going to we're going to start this

company." Put together a whole 100page

pitch deck on why we think the

opportunity is now, where the technology

is today, why interdisiplinary approach

is incredibly important to solving the

problem. The reason AI is so impactful

in this space is its ability to index

[music]

information. The best example that we

always like to give is Alph Go. It was

this AI that was built by the Google

team and it played the best player in

the world, a game of Go. And the best

part of the story is this infamous move

it makes where everyone watching thinks

the AI makes a mistake and in reality it

has indexed so many games of go. It made

a move the human brain has never thought

of before. And when we take that to

science, all of our limitations in

science come from the human brain. How

many papers can we read? How many things

can we simulate? How [music] many

experiments can we run? And then how do

we tie all those together to make a new

hypothesis on what we want to build? But

if you bring AI and autonomy to the

center of that, you unlock this indexing

problem that a human scientist feels.

You can read millions of publications,

simulate billions of materials and test

thousands of them, connecting all this

information in real time. And so if you

can do that, the world that we think we

[music] can really build is one that is

what we call inversely designed where we

are no longer making materials and then

looking for a solution to solve. We are

actually taking our hardest problems and

inversely designing material from that.

[music] And human scientists can't do

that today or if they can can do so in

only very very long time frames whereas

AI and autonomy can [music] do that

incredibly fast and incredibly

efficient. What we actually think AI can

do is not [music] replace that scientist

but rather give them the tools and the

capabilities to index across a multitude

of different experimental processes. So

they are spending their time thinking

around what next material to build or

what next problem to solve and not on

going through the monotonous process of

fundamental research. That is really

where we see the impact on AI for

science and how we are building the

future of the scientific process. And to

Kevin's credit he said you're not going

to raise money anywhere else. I I want

to give you all of it. And so he was the

only investor. We raised our preed round

in about 45 minutes uh which was great.

and we were able to get started and

start building and us three started

recruiting from that time on and built

the company that that we have today.

We are incredibly

passionate about the culture that we

build at the company. Every single

person that we hire into Radical AI, we

ask the same question. If you are

looking for a job, this is not the place

for you. You're incredibly intelligent.

You can go get employed other places. If

you are looking for a mission, then you

should come work here. Every person that

comes to Radical AI [music] deeply

deeply believes in the mission that we

are going after. And the way that we

keep that alignment is through culture.

We are never afraid to fail. We actually

know failure is a part of the discovery

and learning process. And so we will

push aggressively, relentlessly to drive

technology to rethink from first

principles and to build a connected

system that can truly discover novel

materials. So we adopted a rule very in

the company. I believe SpaceX started it

called the 51% rule where when you are

at 51% confidence on a decision, you

just make that decision. And the reason

why is you will actually cause more time

and less efficacy across the company by

debating on decisions that you could

otherwise quickly decide on and see what

the result of that decision is going to

be. When it comes to 51% two different

things that we think about first how big

is the decision and second what are the

risks if the decision is wrong and those

two together allow us to actually

identify when we are at 51% or not. Of

course, we do a bunch of research and

have a bunch of conversations and debate

around getting to that confidence

interval of 51%. But when it is a

decision in daytoday, for example, it's

not year defining or or really decade

defining and what we're trying to go

after. Well, then we can have confidence

to make it quickly. And when we think

about what the other side of that

decision is, what is the worst case

scenario that happens that usually

alerts you to you are already at 51% or

you are nowhere near 51%. And that has a

great checkpoint that we ask ourselves

and everyone in the company and

constantly pushing towards uh getting

getting at quick decision-m but

effective decision-m as well. You know,

51% is not about just making decisions

fast for fast sake. 51% is making

decisions that you are already going to

make, just making them earlier and then

dealing with the effect of not always

being 100% correct. Because no matter if

you take a bad decision for 2 weeks or 2

years, there's still a likelihood that

you're not going to be correct. And

because we operate the company that way,

failure is inherent. You will

automatically fail if you come work at

Radical AI in something that you do. We

don't view someone as failing or a

project as failing. We view it as

learning and an opportunity to recreate

the process that we just thought that we

should build. And so for us, I actually

think we go deeper into the essence of

asking why and first principles. And we

don't view things as failure. It is just

normal to try things that don't work,

learn from them, and try again. At

Radical AI, one of my favorite quotes in

the world is, you know, Steve Jobs is

connecting the dots. You can never

connect the dots looking forward. You

can only connect them looking backwards.

This is an exact moment where I didn't

know where this dot was going to lead.

But now when I look back, it was

imperative [music]

that I went through that experience and

lived through the frustrations of

materials research today. You [music]

need dots to be able to connect. And

while you might not know where this dot

is going to make an impact, you never

know where it is going to or how it is

going to impact what comes next. And so

I didn't care that I didn't know what

was coming next. I didn't care if it was

going to work or not. I didn't care if I

was going to be a scientist or not in in

the real retrospect. What I cared about

was continuing to push forward and

searching for the answer. And I think

that's truly how I ended up getting to

the answer. So, I just reminded myself

every day that this will lead to [music]

something. You have to never ever give

up no matter the scenario. We want to

remove materials as the blocker to those

innovations. And that's why we don't

think there's an end to [music] the

company. We think this company will be

100, 200 years old. It will way outlive

myself and and the two co-founders. This

is a company and a technology that when

it succeeds [music]

will truly be able to create a world not

today thought possible.