Home » Sam Altman: The Winding Path of Progress @ Talks at Google (Full Transcript)

Sam Altman: The Winding Path of Progress @ Talks at Google (Full Transcript)

Sam Altman @Talks at Google


JORGE CUETO (Associate Product Manager – ‎Google): Hi, everyone. Welcome to our Talks at Google event.

I’m going to go through some logistics first. This is a fire side chat style talk. So it will take about 40 minutes to talk through some questions. And then in the last 20 minutes, we’ll open up to the audience to submit questions, both in person here through a mic in the back of the room and also through the Dory at go/ask-sam. And I’d like to thank everyone who has helped out to make this talk possible, including our facilities team and everyone on the PM speaker series organizing team.

So it’s great to have Sam Altman here with us today for Talks at Google. Sam is the President of Y Combinator, which is widely regarded as one of the top startup incubators in Silicon Valley. He went to Stanford and studied computer science and was the founder and CEO of a mobile location-based startup called Loopt, which was funded by YC as part of its first class of startups in 2005 and acquired by a financial services company Green Dot in 2012. In 2014, he was named president of Y Combinator. And since then, he’s worked on a wide range of initiatives from YC Research, which is a non-profit branch of Y Combinator that focuses on doing pure research around moon-shot ideas, like universal basic income.

And he’s also worked on OpenAI, which is a non-profit AI research company looking into finding ways to create safe, friendly artificial intelligence that can actually help all of humanity. And it’s great to have you here.

SAM ALTMAN (President of Y Combinator): Thanks for having me.

JORGE CUETO: So just as I mentioned, you’re involved in a wide range of things from YC to OpenAI. And most recently, you released The United Slate. So I wanted to ask you how you think about prioritizing the projects that you work on.

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SAM ALTMAN: You know, I think optimal time allocation is probably like an AI complete problem. I think if you can get to spending like 1% of your time perfectly, that’s really good. And so I think this idea of figuring out what to focus on and what not to focus on is both really hard and still significantly under-invested in. The frameworks that I have used, the sort of two big frameworks that I’ve used to figure out how to allocate time, one is impact maximization slash regret minimization. So I try to look at those two curves together.

And I try to think about where I can have the biggest net impact on the world, net positive impact on the world. Easy to have a big impact. And then, also, just regret minimization. You know, you get to live once. It’s really important that you do what you want to do and that you spend time with the people you’d like to work with and work on the things that you find personally fulfilling.

And so if I think I’m going to really regret doing something or regret not doing something, even if I think it’s not the best use of my time for a pure sort of net impact on the world, I’m still willing to take that really seriously. And I think that makes me do better at the things I do that do help the world. So you know, the broad things that I’ve learned that I like to do– one is teach people. Another is create economic growth. I really do believe that one of the things that is most fundamentally going wrong right now in the country is that we don’t have enough economic growth.

And the little that we do is not evenly distributed at all. And so I think in a democracy you really want everyone’s lives to get better every year. We’re basically insensitive to the absolute quality of our lives and extremely sensitive to relative differences year over year to our neighbors. And it’s really important that everyone’s life is getting better constantly. And I think economic growth is important in that.

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I think that AI is going to be the most important technological trend of our lifetime. So I spend a lot of my time on that. And you know, I try to think about things on those two strategies. The other framework besides the sort of impact maximization, regret minimization that I found really useful is spend a little bit of effort trying a lot of things, and then relentlessly prune down and focus quickly on the ones that you like and the ones that seem to be working. So in some sense, this is the Y Combinator model of fund a lot of startups with a little bit of money.

And then, you know, most don’t work out, and some work really well. You spend more time and more money on the ones that do. Hey, guys. This is the thing that I’ve tried to apply to my life more generally is this idea that I can try a lot of things with a little bit of effort. It’s very hard to predict exactly what’s going to work and what hasn’t.

But then the hard part about that, the thing that most people don’t do, is you really want to relentlessly focus down on the ones that do work. And the last thing I’ll say about prioritization is the other hack I have learned is if you can get one really great partner with you on every project, that will cover up a lot of the slack. Because if you try to do multiple things at once, crises come at the same times. And that’s really hard if you have to do it all yourself.

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