Artificial Intelligence was once the realm of science fiction. But over the last several years, advances in machine learning and deep neural networks have moved us closer to a reality where computers can learn and solve problems independently, the way a human does. From art and music to medicine and politics, the potential applications of AI are nearly endless, and the technology just keeps getting better.




This week on How I Built This Lab, Guy talks with one of the leaders in the field of AI development, Sam Altman. Sam talks about his journey from Stanford dropout and teenage entrepreneur to president of the legendary startup incubator Y Combinator and co-founder of the nonprofit OpenAI. Plus, Sam shares his hopes and fears for the future of AI and how his company is working to ensure it ultimately benefits all of humanity.

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Hello, and welcome to how I built this lab.

So artificial intelligence is getting really good, really fast.

For many years, most of us assumed AI was gonna replace jobs in manufacturing in the service sector.

But what's actually happening is that machine learning devices are becoming much more adept at generating things we often associate with human creativity you might have seen that piece of digital art that recently won a competition in Colorado.

Art work completely drawn by a piece of software.

AI software is getting really good at composing original music, even writing newspaper articles.

And it means that in the not too distant future, machines might be able to diagnose diseases or answer any questions we have or maybe even solve some of the world's biggest problems.

1 of the pioneers in AI technology is a nonprofit company called OpenAI.

It was co founded by Sam Altman in 20 15.

Sam is the former president of the legendary tech incubator Y Combinator, the accelerator program that helped launch Airbnb Stripe, Coinbase, DoorDash and so many others.

Today, Sam's on a mission to make artificial intelligence work in a way that has the maximum benefit for the maximum number of people.

Open AI has made headlines with some pretty impressive AI tools, including GPT 3, It's a language generator that's written op eds and scientific research papers.

And also Dolly, which is an algorithm that can generate incredibly realistic images from any written description.

But of course, there are lots of open questions about what happens if we can no longer control how this technology is used, which we will hear about.

Louis area obsessed with computers from a pretty early age.

I was a nerdy kid that's true but also like that they're just the power of this idea that we were all gonna be connected to each other, which I would say was evident by

That but, like, I was just like, this is, like, more important and more exciting and and more fun than everything else going on, and this is just this is what I wanna do.

From what I gather, like, a big a big kind of moment for you was getting that that your first Mac too.

And how did you use that computer as you play games on?

I used AOL, which was sort of what I thought was the Internet at the time and then -- Yeah.

pulled up after that figured out there was an actual Internet out there which was was was even cooler.

I read, like, most of the encyclopedia on the CD ROM.

What were you programming in like, basic or in

You know, like, very little stuff, like print out all the prime numbers, like, make a little interactive text game, stuff like that.

It was just like the thrill of getting to make anything.

The excitement of, like, watching somebody else use something you made.

Actually still is, but but especially as as a little kid.

And and so you described yourself as a computer nerd in high school, but Was it clear in your mind that this was what you were going to do?

Or were your parents like, hey, you know, you're really good at math and science.

You maybe should go to med school or something like that.

They they they never they never, like, pushed me to do something I didn't wanna do.

There was there was, you know, gentle suggestions of science or whatever else, but, like, it was very clear to me from a very young age and I'm thankful for this because I I know it doesn't happen to everybody that, like, computers were my thing.

What wasn't about computers as a teenager that you remember feeling so passionate about.

I mean, was it was it a community of other people that you connected with locally or even beyond or you lived in Saint Louis?

I also was into, like, Ham Radio as a kid.

And the 1 thing that I noticed across both of them was the fact that you could, like, A, there was interesting engineering and science problems and technology to figure out.

There's like the fun of using a computer at all.

Especially back then when, like, they didn't work that often and you had to, like, upgrade parts of them yourselves.

That's just like a cool puzzle and technology is interesting.

But definitely 1 thing that I felt across both of them is this ability to connect with anyone around the world instantaneously, which was incredibly appealing to me.

The ability to sort of, like, learn anything, talk to anyone.

Was was just, like and still it's, like, pretty magical.

I think we've we've all just now accepted that as standard.

But if you rewind the clock like 30 years, things were very different.

I mean, I think the computer revolution is as big of a deal as the the other great technological revolutions of the past, as big as the agricultural and industrial revolution.

But we've kind of just lived through it so recently that we don't talk about it as historic as it's gonna turn out to be.

So when you set up to to I know you studied Stanford and you studied computer science.

You were very focused on entering this field.

And and presumably, you know, when you get to college, your thought is, eventually, go work for 1 of these big companies.

I I picked Stanford because it was the best computer science program.

I mean, it turned out to be like a wonderful place in a lot of other ways, but that was what I wanted to study.

And my dream job after school was to work at Google.

While you were while you're Stanford, you you basically had a business idea and and you dropped out -- Yeah.

-- presumably with the intention of coming back.

Absolutely with the intention of going back.

1 thing that's very cool about Stanford is they they let you stop out and return sort of no questions asked very easily.

But the idea was, hey, on your cell phone because people had cell phones at that point, you could see where your friends were all at the same time on on a map?

And also, you know, meet new people near you find, like, interesting places to go or events to go to.

And and so the idea was that, like because I'm trying to go back to 2005, and and I know I had I definitely had the Nokia at that time.

At Palm Treo was, like, the height of coolness in 2000.

But most you know, the great great majority of the world had, like, a Nokia or something.

But there were all of these like little mobile app stores.

There's something called J2ME at the time where you could, like, make a little mobile app on on a flip phone or whatever.

It wasn't a very compelling experience, but it was sort of the idea was like as people lived more mobile lives, knowing everything in the context of the location would be super powerful.

We turned out to be mostly wrong about that, by the way.

I I think it didn't really work for a bunch of reasons.

But 1 of them that is still somewhat surprising to me is even as the world has gotten very mobile, most people are sort of still at home or work all the time and there's just like far less spontaneity than it felt like to like a 20 year old or whatever I was at the time.

I mean, it's interesting because on the 1 hand, I think most people wouldn't wanna do that with other people.

But what they do do is they post on social media all the time.

So we do know where people are all the time.

I'm not giving away the plot here by saying that looped ultimately did not sort of become what you you envisioned, but that timeline.

It did it did bring you into this world that would become a really big part of your life y combinator.

You were in the sort of inaugural class of y combinator.

Paul Graham famously 1 of the main co founders.

I guess you met him and and he liked the idea.

I so I was, like, you know, interested in this idea playing around with it.

A guy that lived in my freshman dorm, a name Blake Cross.

Posted something, I believe, on Facebook, but memory could be wrong there now, that there was this new thing and it was called the summer founders program at the time and, you know, people should check it out.

The deadline was like the next day or something.

So I immediately applied with my cofounders, and they invited us out to interview.

That was the first, like, meeting the wise the 4YC founders, Paul Jessica Trevor and Robert.

That was, like, the first time I felt, like, alright, I have, like, finally found the kind of people I wanna be around.

I didn't really know about the startup thing, you know, you I heard about it as like a kid during the dot com boom, but I wasn't really paying attention.

I had met a few VCs on campus, but I could like tell, I didn't like them.

But I met the I was like, wow, these are my people and everything they say resonates.

And even the other founders that met their interviewing, that was this immediate click for me if like, this is awesome.

Like, were you actually writing the the the software.

Then I got pretty busy with other things.

I think a lot of people assume they're gonna keep coding, but

My job ended up being like a huge amount of business development.

I spent a lot of the time on airplanes flying around to the mobile carriers that our partners, but it's I I was not able to code for very long.

So you're basically this is a 19 year kid.

At 1 point, you'd raised money at a valuation of a hundred and 75000000 dollars.

You'd raise almost 40000000 dollars First of all, how did you learn how to become that person you had to become?

To, you know, to be in charge of a company with 40000000 dollars in in capital?

Like, I I think this is something that is still underappreciated about y combinator.

People are capable of learning at a very fast rate.

And 1 of the things that PG says that has always really resonated with me is you can get tough really fast.

And that's sort of like 1 of the skills that is important for young founders.

But if you jump into the deep end, and you are like surrounded by supportive thoughtful advisors.

It was like interesting to me at the time how quickly I could learn, And 1 of the most fun things about running YC later was helping other people learn very quickly.

And just to clarify, when you say PG, you mean, of course, Paul Graham, 1 of the founders of y combinator.

And I think this is 1 of the things that y c still just like people on the outside don't see it.

There's this assumption that, like, oh, if you get into YC, you're gold plated.

You have this, like, you know, stamp of approval.

But why see does so much that no other program as far as I know has figured out about how to get people up with the learning curve really quickly?

That it's it's a very big deal and it was super important to me personally.

And I think to many of y c's biggest successes, it's been super important.

And the difference that you can make there is huge.

So so this was your life, looped was your life, apps with support from Y Combinator for several years, but ultimately, it just didn't it didn't take off.

It was acquired for, I think, for about 43000000 dollars.

It was acquired for, like, about what we raised.

So the later investors didn't make much money.

You you earned a little bit, actually, more than a little bit.

You know, think about 5000000 dollars from that sale.

I earned some, but, you know, on like, this is another thing that is just sort of I trying to think about.

I made, like, orders of magnitude more money from angel investments that I made

that I spent no time on the other thing I poured my life into.

But after that happened, you were in 20 14, you were named president of y combinator.

Already by that point why combinator had kind of become this sort of legendary incubator.

Tamela, we're about sort of taking on that role.

Did it feel scary, you know, to be because again, you were still pretty young leading this thing that that had gained this kind of massive reputation?

You know, it it it this may be some sort of, like, weird flaw of mine.

Like, it took PG a while to convince me because I really wanted to do another startup.

I wanted to, like, prove myself I was, yeah, 28 or something at the time, I didn't feel ready to, like, go retire and do a career adventure, which is really how I thought of it.

I didn't, like, have a ton of respect for the career path.

And so there was like some sense in which it was an admission of defeat about, you know, I just I can't run a company, so I'm gonna go do the easy job or I'm gonna go do the retirement job or something.

And it took me a long time to get comfortable with the idea of doing it.

But I can't overstate how much of the time and how much now still I love why I see.

Feel incredible gratitude towards it personally.

Also think it's just this incredibly good force in the world.

And as I I thought about the things that I wanted to do, I I had this list from when I was like a college student of what I wanted to work on.

I I realized I couldn't start all of those companies.

I also really was interested in pushing more investment in hard tech, deep tech, whatever you wanna call it, which I didn't think that was much of happening at the time.

Because at the time, why she was focused mainly on, like, software.

And you wanted you wanted them to focus more on things like nuclear energy, self driving cars, like like actual physical things that you use?

Not necessarily physical things, but I would just say like hard to technology.

Like, there's a thing about Silicon Valley, which is it had not been that well geared towards the time and capital intensive science projects.

So I wanted to do that, and I kind of was just like thinking about, you know, I had like basically taken a year off.

It had been really fun I had, like, learned a lot about everything.

I had read, like, many, many dozens of textbooks.

And there was, like, all of this stuff that I wanted to do.

In some sense, yes, BNAVC is like an admission of failure.

But in some other sense, what an incredible plot you know, I could, like, do whatever I wanted here.

So you became president of y combinator and lots of YC companies have been on how I built this in the past is is, I think, you know, including Stripe and Airbnb and Reddit and coinbase and and lots of others.

And I think maybe like a year end to that job you co founder this nonprofit.

So so I studied AI as an undergrad, which was like dark times.

then in 20 12, deep neural network started to work.

And not only did they start to work, it appeared that the more compute throughout them, the better they got.

Are you talking about, like, Watson and these these kinds of neural networks?

The 1 that really kicked it off, I think, for the field, certainly for me, personally, was the ImageNet result.

This is the identifying images based on descriptions.

You type in the computer horse eating an apple or whatever, and it it it could find them very quickly.

It it was more like you'd showed an image and it would correctly say this is a horse eating an apple?

Or at the time it would just be more like this is a horse.

It it came out in my kind of like year off I was just learning about things and I looked at it with great interest, you know, but kind of like it was 1 of many things that I spent time on that year.

But I kept watching it and kept paying attention.

And certainly like of all of the hard tech dreams, AGI is the top of the list

And just to clarify, Sam, when you talk about AGI, artificial general intelligence, you're distinguishing that from very narrow specific types of artificial intelligence?

So, you know, we already have made good progress with narrow AI that can categorize images or or some 1 task like that.

But for me, AGI is a system that can learn and self improve and create and reason about new information like a human does.

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HIBT Lab! OpenAI: Sam Altman