My First Million - Emmett Shear: Life After Twitch, Jeff Bezos Lessons & AI Doomsday Odds

Episode Date: September 11, 2023

Episode 494: Shaan Puri (https://twitter.com/ShaanVP) talks with ex-CEO & co-founder of Twitch, Emmett Shear (https://twitter.com/eshear), about the potential of artificial intelligence, the value of understanding consumer / users needs, his simple framework for problem-solving, the power of seemingly small ideas that can have a huge impact and lessons he’s directly learned from Silicon Valley greats like Paul Graham and Andy Jassey. Want to see more MFM? Subscribe to the MFM YouTube channel here. — Check Out Sam's Stuff: • Hampton - https://www.joinhampton.com/ • Ideation Bootcamp - https://www.ideationbootcamp.co/ • Copy That - https://copythat.com/ Check Out Shaan's Stuff: • Try Shepherd Out - https://www.supportshepherd.com/ • Shaan's Personal Assistant System - http://shaanpuri.com/remoteassistant • Power Writing Course - https://maven.com/generalist/writing • Small Boy Newsletter - https://smallboy.co/ • Daily Newsletter - https://www.shaanpuri.com/ — Show Notes: (0:00) Intro (4:30) Did you always have an insatiable curiosity? (8:30) How to solve any problem (13:23) The importance of understanding your customers / users needs (22:15) Emmett’s favorite business ideas right now (41:00) Is AI going to kill us all? (56:50) Was Twitch luck or skill? Will Emmett try to build another unicorn? (59:00) Lessons from Paul Graham (1:09:00) What’s the difference between people who are good vs. great? — Links: • Twitch - https://www.twitch.tv • Paul Graham - https://twitter.com/paulg • Patrick Collison - https://twitter.com/patrickc • Andy Jassey - https://twitter.com/ajassy • Do you love MFM and want to see Sam and Shaan's smiling faces? Subscribe to our Youtube channel. — Past guests on My First Million include Rob Dyrdek, Hasan Minhaj, Balaji Srinivasan, Jake Paul, Dr. Andrew Huberman, Gary Vee, Lance Armstrong, Sophia Amoruso, Ariel Helwani, Ramit Sethi, Stanley Druckenmiller, Peter Diamandis, Dharmesh Shah, Brian Halligan, Marc Lore, Jason Calacanis, Andrew Wilkinson, Julian Shapiro, Kat Cole, Codie Sanchez, Nader Al-Naji, Steph Smith, Trung Phan, Nick Huber, Anthony Pompliano, Ben Askren, Ramon Van Meer, Brianne Kimmel, Andrew Gazdecki, Scott Belsky, Moiz Ali, Dan Held, Elaine Zelby, Michael Saylor, Ryan Begelman, Jack Butcher, Reed Duchscher, Tai Lopez, Harley Finkelstein, Alexa von Tobel, Noah Kagan, Nick Bare, Greg Isenberg, James Altucher, Randy Hetrick and more. — Other episodes you might enjoy: • #224 Rob Dyrdek - How Tracking Every Second of His Life Took Rob Drydek from 0 to $405M in Exits • #209 Gary Vaynerchuk - Why NFTS Are the Future • #178 Balaji Srinivasan - Balaji on How to Fix the Media, Cloud Cities & Crypto • #169 - How One Man Started 5, Billion Dollar Companies, Dan Gilbert's Empire, & Talking With Warren Buffett • ​​​​#218 - Why You Should Take a Think Week Like Bill Gates • Dave Portnoy vs The World, Extreme Body Monitoring, The Future of Apparel Retail, "How Much is Anthony Pompliano Worth?", and More • How Mr Beast Got 100M Views in Less Than 4 Days, The $25M Chrome Extension, and More

Is AI going to kill us all? Uh, maybe. Emmett Shear is the CEO of Twitch. It was acquired by Amazon in 2014 and joins us now. I started Twitch to help people watch other people play video games on the internet. The creator and co-founder of Twitch, watch other people play video games. Who knew? Emmett knew.

I guess that's the answer. What types of ideas are you noticing or standing out to you that are interesting? For the first time in maybe five to seven years, it feels like credibly trying to start a consumer internet company, like the ones that, like, I was so excited to start in 2007 is, like, potentially a good idea. That's because of AI. You mentioned AI might become so intelligent. It kills us all. This podcast is really growing. I don't want the world to end.

I think it's going to be okay. But it's such, the downside is so bad. It's like it's probably worse than nuclear war. That's a really bad downside. I think of it as a range of uncertainty. And I would say that the true probability, I believe is somewhere between. I feel like I can rule the world.

I know I could be what I want to. All right, what you're about to hear is a conversation I had with Emmett Shear. Emmett was the creator and co-founder of Twitch. If you don't know about Twitch, I don't know, you're living under a rock. It's like one of the most, I don't know, five most popular websites in the States right now.

It is a place where you can go to watch other people play video games of all the things. Watch other people play video games. Who knew? Emmett knew. I guess that's the answer. So he was the creator, co-founder of that, and built it up. It's a multi-billion dollar company.

They sold to Amazon many years ago, seven years ago or eight years ago, for about a billion dollars and has grown many times since then. He finally retired after 17 years of the journey. I got to know Emmett because he bought my previous company. So we got acquired by Twitch. Emmett was like my, you know, quote-unquote boss for my time when I was at Twitch. So I got to see this guy firsthand. He's the real deal. And I've been wanting to get him on the podcast since those early days when I first met him.

I was like, this guy is great. We talked about a bunch of things. So we talked about some ideas of like how he would use AI if he was going to create another company. Like I think he's good. He's retired now from that game of operating a company. But if he was going to do it, this is what he would do. So we talked about AI ideas. We talked about why he thinks AI might kill us all, might, you know, be the big doom scenario.

which is interesting because he's not just a guy who's going to go cry wolf. He's not a pessimist. He's not just a journalist who hates tech. This is a techno optimist. This is a guy who believes in tech is a very, very intelligent guy. And he sees, you know, a probability. He gave us a percentage of probability he thinks that could be sort of the doomsday scenario and why he thinks that that could be the case and what we should do about it.

So we talk about AI. We talk about some of the frameworks that he has for building companies. We didn't talk too much about the origin of Twitch. He felt like he's done that a bunch of time, so we kind of stayed away from that. But it was a wide-ranging conversation. And for those who are watching this on YouTube, I apologize.

The studio that we booked in San Francisco, they screwed up the video. So we don't have video for YouTube. We just have the audio-only version, so you'll see our profile pictures. My bad, sorry about that. You know, got to pick a better place. Got to pick a better studio, I guess.

But anyways, enjoy this episode with Emmett Shear. Somebody said, creativity is not like a faucet. You can't just turn it on. I think actually if you've pulled like 100 people, most people like, yeah, of course, creativity is a sacred, special thing that only happens if you've meditated in the morning and the room is perfectly right and you've had your Elthienine in your coffee or whatever. And you were like, no, for me, it's very, it is like a faucet watch. And you know, I can just write and just keep generating more ideas.

I love that for two reasons. One, I love that you'll just be like, no, actually this. That's like a consistent thing I've seen you do. And the second is, I think that's very true about you. And I wonder, is that practiced or is that innate? Like, if I, if there's a researcher studying you when you were like 10 years old, do you think they would have been like, oh, this person's different in these ways? What would have seemed different or special about you at the time?

I, the, if there was a nurture, nature break on this. It happened very early because by the time I was 10, you would definitely notice the same thing. I'm not really that different. I would be much less effective. But like as a 10 year old, I already had that same experience. But you were different than other 10 year olds. Yeah, other 10 year olds. Well, I would actually say I was less different than. I think most people, actually, most children have this experience already. I think most 10 year olds and definitely most 5 year olds are capable of generating ideas for what to do about something or to like play pretend, almost indefinitely.

They don't run out of ideas. It's as you get older, somehow you, what you learn to do is you learn to stomp down the ideas that are like bad and to not say dumb things. But the more pressure you put on yourself not to say dumb things, the more your inner idea generator, it like gets disrupted. And I say a lot of dumb things. Like when I'm generating ideas, I may not put weight down on them, but most of the ideas will be bad.

They'll have something obviously wrong with them. And they give you this advice and if you go to like someone who teaches you at a brainstorm like no bad ideas here that's obviously not true there's lots of bad ideas most of your ideas are bad

yeah the actual advice is like don't stop at the bad ideas yeah yeah what you're trying to do is you're trying to disable that sensor that most people have installed that like is like no bad no bad no bad don't be stupid don't be stupid

and I think I was like malsocialized it never occurred to me to have that like I never got the sensor installed and why that is the case, I'm not sure. But I think I'm the one who is unchanged in some sense. I'm a little more childlike in that way.

And everyone else is the weird one who, like, how does you wind up, like, damaged by your life that your inner wellspring of creativity has been crushed? And I think that process is actually very simple. This process goes up with all kinds of things in people's minds. You start from some capability, something you can do, some behavior. And if when you do that behavior, you try that thing, you receive negative feedback, which can be external or you actually think even

more often internal, you're like, oh, I screwed it up. Oh, it's bad. Oh, I don't, disappointment. You learn not to do that thing pretty rapidly. And so that leads you to doing it less, which means you're less skillful at it, which tends to leads you to doing it less, which that cycle ends in you being very bad at something. Like, I'm bad at math. No, you're not. Everyone can be, like the kind of math you're talking about, everyone can be the kind of math. And people say, I'm bad at math. They don't mean, I'm bad at like abstract algebra proofs. They mean I can't do arithmetic or basic algebra. And that's just imaginary.

Like everyone can do that. It's easy. They got stuck in one of these like spirals. And now it's, and getting out of one can be very hard. And I guess I think that's what happens to people's creativity. I don't know. I didn't go through the process myself.

And so I got, so now as I'm saying this out loud, actually, the idea that I have could come up for me is like, oh, well, maybe what it is is that I had better ideas. That's like, that's the, so I got the reward loop. Or I had an environment that was unusually, positive and positively reinforcing for me having ideas.

And so I would have ideas and it would go well that would lead me to having more ideas and more practice at having ideas, which would go well. And then you wind up just never breaking that loop. I have a trainer who comes over to my house. He always says this thing to me because my kids will come down during the session. I'm always like, oh, sorry. Like obviously annoying. My two-year-old is here almost getting hurt on all the weights.

And that's probably like not what you want in your session. So I'm always like, oh, sorry, sorry, sorry. And he's just like, dude, no. And he's like, kids and dogs. I go, what? He goes, I love to be around kids and dogs. They got it right. They know life.

He's like, a dog is like unconditional love, happy, playful, you know, super loyal. He's like, what's not to learn from a dog. I want to learn everything I can from a dog or kids. He's like, look at what she's doing. She just made up a game on this thing. Like, we're her trying to do a serious workout. She made this her play place. She can't wait to come down here.

He's like, I wish all my clients wanted, couldn't wait to come down to the gym. And I was like, damn, this guy's right. And one of the things I like is figuring out people's isms, their philosophies. And you're like, oh, I thought of one on the way here. Explain what it was. It was, have you tried just solving the problem? What does that mean? So there's a, there's a meme on the internet.

I think it started with weird sun Twitter, which is like, have you tried solving the problem by? And then an infinite list of possible. And the tweet is always, have you tried solving the problem by like ignoring the problem? Have you tried solving the problem by spending more money on it? Have you tried solving? And one of my favorite ones of those that has become, almost like a life motto is like if you tried solving the problem by solving the problem. And that sounds dumb, right?

Like that sounds, it's one of those like zen cone pieces of advice that when you first hear it is like, are you serious? Like that's the advice is solve the problem by solving the problem. But what you notice when you try to help people with problems a lot is oftentimes people will have a problem. It's really obvious what the problem is. And they'll come to you it for advice for like, well, how can I deal with the consequences of this problem?

Or how can I avoid needing to solve this problem? or how can I get someone else to solve this problem? Or have other people solved the problem in the past, which is closer to the right answer or what can be the right answer. And the point of the saying is to remind you that sometimes the way to solve the problem is just to actually try solving the problem. Like, don't deal with the symptoms. Don't accept the symptoms.

Don't find a hack around it. Like the problem is the website is not fast enough. And instead of like trying to figure out how we can make a loading spinner that distracts people from that fact, made it so fast that you don't need a loading spinner. It's interesting because that's a good, it's a very good advice when the problem actually is solvable. I mean, people are flinching away from it because something about it is aversive, even though the problem isn't really unsolvable. Like, if they worked on it for six months, it would go away and it's worth solving. Whereas there

are these problems where like, you're trying to make a perpetual motion machine. You're trying to do something that is actually too hard and solving the problem by solving the problem. You should actually stop trying to solve the problem. That's a huge mistake. And you should be looking for a hack around needing to solve the problem. We should be looking to live with it more effectively. But I find actually on the balance, at least with most people I talk to, I help. Most people I know, I think it's maybe it's people in tech that love the hack. They're always looking for the easy, fast solution that cuts around you to solve the problem. And it's very helpful. It's the most often helpful form of that advice in my opinion. It's like bringing people back to just solving the problem.

I find that the advice I like the most or the sayings that resonate with me the most are the ones. It's like you spot it, you got it. It's like if it's the one I need, it's the advice I needed, that's why it resonates with me. That's why I like giving it out because like I personally experienced it. Have you personally experienced that? Or what's an example where you remember trying to do everything but solve the problem? And then you finally realize shit, I should have just solved the problem. It's interesting question.

What is it? You spot it. You got it. It's like noticing is half the battle, basically. It's sort of the smart person version of, whoever smelled it dealt it. Yeah, yeah, yeah. It's like, 100%. If you, you only notice this in other people because you've seen it in yourself too. Otherwise, you wouldn't be as observant of it. My version of this is we give the advice we need to hear. Yes. Yeah, exactly. Which is same basic idea. It's actually not always true. Like, that's one of those really good heuristics where like, sure, half the time when you give it won't actually be for you. But half the time it is. And noticing it is so powerful that like, you should just check every piece of advice you give for like, wait a second. Is this advice I need to hear right now? When it comes to the, like, have you tried actually solving the problem? I think I'm pretty good at that in general.

I think that I often give it to myself in a more meta sense. Like, it's advice I often need in a more meta sense of like when I'm confronted with like a thing that needs to be programmed, I will often go just program the thing. But I have a tendency to like look for ways that I can solve the problem and not that the problem can be solved. And for me that this almost always like, what if I went and ask somebody else for help? And I just like, it doesn't even occur to me. to go to go do that.

I'm just, I'll just, I'll just indefinitely dig, try to go solve the problem myself. I'm not really trying to solve the problem. I'm trying to solve the problem while avoiding having to ask anyone else for health, which is like not, I'm not really trying to solve the problem. But actually, no, weirdly, I think this is one of those things where it's almost like the creativity thing.

It was a shock for me to realize other people don't do that. You're self-actualized on that one. Yeah, yeah. What's a piece of good advice that you're bad at taking? Oh, that's a, that's a, an excellent one. I think the big one there is like, you know, listen more. Like I've been given this advice so much of YC and it's 100% something that I need to get better at, which is like, you go into the user interview and you have all these ideas and thoughts and you need to not be

surfacing those. You need to actually be focused on, you know, move your attention to them and really be interested and care about what they have to say. And your opinions and what you think is true is irrelevant. And I am, I'm much better at that than I used to be. And I, I, I always, Also, it's one of those things for like being reminded, like, let's just chill out for a second and listen. There's almost always good advice for me and something that I, and it's advice I give fairly often, but like, it's hard for me to take on. One of the things I really liked that you showed me once, I remember asking you when we were at Twitch. I think we were working on a problem that was like reminiscent of early days Twitch with like the bubble, bubble stuff in different countries where it's like, oh, we're not the leader. or we need to like create from scratch,

which wasn't a muscle that a lot of people there were flexing at the time. And I was like, hey, do you have any stuff from the early days of Twitch? You set me a thing which was like, here's all the user interviews, like here's my doc from all the user interviews did it, which was basically from what I understand, there was like a small universe of people that were already doing video game streaming. And you were like, cool, let me call all of them. And let me ask them like three questions.

And if I could just get these answers to these three questions, that should give me a little bit of a roadmap, blueprint of understanding what do I need to do in order to, like, win in this market. Yeah. Can you take me back to that? Because I like that for two reasons. It was a simple and B, it seemed like a focused intensity that you found a point of leverage and you pushed.

Yeah, I think two things happened to lead to that. The first was like the realization, obviously, we wanted to win in gaming, the streamers mattered. And at Justin TV, we'd always been like streamers and viewers are equally important. And I finally made a decision. I was like, no, no, no. this product ultimately is about streamers and if this doesn't work for the streamers

doesn't work for anybody. And then I had the realization this is one of those epiphany moments where I truly saw I have no idea why anyone would stream video games. Like I don't really want to do it and I have all these, I saw myself building products for these people

for the past four years of Justin TV and not really having any idea why they did the thing they did at all. And I sort of, I saw like, oh, I'm just making this up. I have no idea. I just said, I don't know the answer. I could know the answer. Like, there is an answer out there.

A bunch of people know it, but I don't. And that triggered me to be like, I need to know. I need to understand. Like, these, these 200 people, I need to understand their mind. And I did about 40 interviews probably. And I didn't want to know, like, what they thought we should build. Because if they knew what we should build, they would have my job. And I talked to enough of them.

before to know that they had no good product ideas. I wanted to know, like, why are you streaming? What have you tried to use for streaming? Like, what did you like about that? Like, how did you get started in the first place? What's your biggest dream for streaming? What do you wish someone would build for you? And I didn't ask them, what do I wish someone would build for you? Because I thought they would have a good idea. I asked them because the follow-up question was really the killer one, right? They would say, I wish you'd build me this big red button. I'm like, great. I built you the big red button. Like, what does it do for you? Like, why is your life better after I built that? and then they would tell me the real thing, which is like, oh, I would make, I'd make money that

month or I'd get a bunch of new fans who, like, loved me or my fans who already loved me on YouTube would be able to watch me live, more of them would. And I was like, oh, that's the real answer. Like, why you don't, you don't want the button. You want the fans or the money or the, I call it love, the, like the, the sense of reassurance and, and positive feedback that your creative content was wanted. But you're a smart guy. Those love and money and fans. I'm sure you would have guessed. What are the streamers want? False.

What did you think they want? It was a revelation that people would want money because I was like, you're streaming like, you know, whatever 12 hours a week. If we met, let you monetize the rates we can monetize today, you'd make like $3 a month. That would, like that didn't occur to me that would be a positive thing. They're like, yes. Oh my God, that would be amazing. And I was like, wait, wait, you're serious.

You would like $3. I don't know overpromise. I'll build you the monetization actually. But like, you would. really be excited if it only produced like a tiny amount of money. And they're like, absolutely. I've just, the idea that I could make money doing this would be so exciting. That had not occurred to me because it always is easy for me to make. I was a programmer. I had summer jobs interning for Microsoft. If you're a programmer, you can get a summer job in turning for Microsoft

that's like pays many, many years of that level of streaming in three months. Like, why would I, it didn't, it wasn't in my worldview that that would be so important to them. And of course, I knew they wanted a bigger audience, but the degree. to which they valued even one more viewer. And the degree of truth they didn't care about anything else. Like they wanted people to watch them. They wanted to make money. And I'd ask about other things like, do you want the video production?

You want to improve the video production and have cooler video production? And they'd be like, yeah, to be like, okay, but like what's good about that? Like, what do you like about that? Like, well, I'll get more, I'll get a bigger audience. And it was really the realization that like it was just those three things basically explained 98% of their motivation, and we could, anything it didn't move

the needle on that, could be ignored. So a good example, that's like polls. Everyone would ask for polls. It seems like a cool feature. Live polls, of course. Are you going to have a bigger audience

with the live polls? Not particularly. Are you going to make more money? No. Does you really, do you really feel more loved if you're running a live poll than if you're just like asking chat

and having people posted in the chat and say it? No, it's the same. You got the feedback. It's cool. It's cooler to see the chat blow up. It's cooler to see the chat blow up. Seriously. saying that this feature is worthless. Yes, in fact, potentially negative, in fact.

And so it would always be on the list of things that would sound like they might be cool and we just would never build it entirely correctly because it wasn't going to move the needle. And the thing that's really hard to teach there that I've been a YC visiting partner for this batch, and I'm trying to convey to people that's very hard to get them to do it is like you have to care fanatically about these people as people and these people as in the role that doing as these people as streamers. And what they believe about their reality is you have to accept as base reality. That is how they see the world and that is what's going on.

But like, you need to like literally have no regard for their ideas for how to solve the problem. And it's a little paternalistic in a way, but it's more of like just respecting that they are experts in this thing and you need to understand them in that thing. And that what people are looking for when they are looking for the product idea from the person is like, They don't want to do the work. They don't want to take responsibility for it's my job. I have to solve the problem. And no one's going to tell me what the answer is.

There's no teacher. There's no customer. It's up to me to come up with the truth. And then defend it. When other people are like, no, that's wrong. I have to be able to say, no, no, no, let me explain why this is actually a good idea. And that's scary. You're responsible.

And I think actually it's probably why the, uh, just solve the problem advice is bouncing around my head, because a bunch of the fear founders have about addressing these things, I think comes down to a willingness to take responsibility for solving other people's, this other person's problem. Like, they're going to come and dump a bunch of problems on you. And it's your job to solve it for them within the constraints available. And there's no, if you come up with the wrong idea, it's all on you and you can't, you can't trust anyone else to do it for you. What are you seeing in this YC batch?

so your visiting partner, exciting time with AI, probably like half or more of the batches, doing something with AI. What's exciting? What are you saying? Where do you see the puck going on? So it's interesting. I would actually say that at least in this batch,

I think this might have been different the previous batch, but by this batch, use of AI is no longer interesting. AI is out. No, no, no, AI is so in. It's like being an AWS startup or like being a mobile startup. Like, what do you mean? you're a mobile sort of like, are you building a social media network?

Like, what's the, of course you have a mobile app. And now it's like, of course, you're using LLMs to solve a problem. That's just like, if you weren't doing that, I would think you were a dummy. Like, I don't understand, like, that's not a, you wouldn't even bring it up. It's not even interesting topic of conversation.

The question is like, what, what are you doing? No, that's not entirely sure. There's about some percentage of the batch. I don't know. It's between 10 and 20%, I'd say that's legitimately building like AI infrastructure. because there's a need to build a bunch of infrastructure there.

Those are actually, those are AI companies. But like when people hear AI company, I don't think they think back-end infrastructural support for AI. They think of using AI to like do things. And I actually couldn't tell you what percentage of the batch is AI from that point of view. All of them maybe? I don't know. Like, why wouldn't you use it?

Even if it's only for a minor thing, there's always something you can use it for. It's a very useful technology. What types of ideas are you noticing or standing out to you that are, that are interesting. Is there like, you know, for example, I remember when I first moved

to Silicon Valley, suddenly the kind of like Bits companies started doing really well. It was like, oh, Uber, Airbnb and like. Online offline. Yeah, it was like,

oh, wait, this used to be like a taboo. Like it was like, no, it's supposed to do a software company. Like, you have to ship T-shirts. What are you doing? I would say like,

stay away from trends. The offline, offline companies that started the trend did very well. Uber is a great company. Airbnb is a great company. But they were off trying at the time. But at the time, that was, they were doing something that was not allowed.

They were, they found an opportunity that had been ignored. Almost all the online offline companies that get started after Uber, DoorDash, Airbnb are big, being like, we're going to be the Uber and DoorDash and Airbnb of X. Most of those companies did not do very well. Is online offline bad? No, it's generated a bunch of incredible companies. jumping on the trend was probably bad for you. And so whatever I tell you is like the trend I see. I don't mean trend.

I guess what I mean is I think you're a person that is really good at looking at a situation like looking at a box of stuff and identifying correctly what's really interesting in this. Yeah. Interesting to you. Yeah. I know I understand what you're asking. So like what I think is changing in the world right now, having observed this is that

consumer is back for the first time in a long time, and by a long time, it's like internet standard. It's like five years or something. But like for the first time, maybe five to seven years, it feels like credibly trying to start a consumer internet company. Like the ones that like I was so excited to start in 2007 is like potentially a good idea. That's because of AI. AI means there's a whole opportunity to sort of reimagine how consumer experiences can work ground up. And what's cool about consumer is for B2B SaaS, the experience isn't the product.

And so reimagining the experience does not reopen a necessary. It can, but it usually does not reopen a segment. In consumer, imagining an experience 100% reopens the segment because the thing you're selling is the experience. The thing, the reason we'll use your product is it's a different experience. And in B2B SaaS, it's not the experience, it's the what. Yeah, people actually care what it does in the pricing model and the adoption. It's very practical. And you can make people jump through hoops if it does a thing because,

there's a lot of money for the corporation and money and labor or paid to use your product and it's a whole different thing. And so AI adds new capabilities, new capabilities enable new segments of B2B SaaS to be created that will generate some amount of growth.

In consumer it does a really cool thing. It's like mobile. It reopens every segment as like, oh, now that you assume mobile exists, now that you assume AI exists, what could you build now? And that's very exciting. I don't have answers for that anywhere

because like, you know, we'll see. That's a whole thing in consumers. It's a bunch of lottery tickets. Like, nobody knows. It's like singular genius that works out, right? Like, you could see like, okay, mobile comes. Photo sharing became like open again.

The window has opened. Windows is open for photo sharing. Turns out it's Instagram and it's Snapchat, which is going to use photos as text messages. Yeah. Photos have a few different use cases. And Instagram and Snapchat took two of the best ones. The fact that photo sharing is one of the most important segments and that, you know, sort of posting them and messaging with them are the two important, most of

weren't things to do with them, seems blinding obvious in retrospect. And if you had to predict that in 2007 or 2008, like, good luck. Yeah. Like nobody, nobody correctly predicted that stuff before it happened. I mean, not nobody. If you did correctly predict that, you made a lot of money. And congratulations. You're really good at consumer slash you got lucky.

We will find out when you try to do it again. I think that in AI, actually I have a theory for like what one of the ways this will disrupt a bunch of businesses. in AI, especially in consumer, a huge number of businesses can be conceived of as effectively being a database with a system of record

that has like a bunch of canonical truths about the universe and each of them is a row. It's like Yelp is like a big database that has a bunch of rows and the rows are like restaurants and local businesses and they have a bunch of facts about them

like they're, where are they located? What are they hours? You all in that database row. And it's all text and it's all, there's a bunch of messy stuff out in the world, and it's been digested into something that is searchable and comprehensible and usable in an app for you to use. And most of the work of turning the messy real world into the canonical row

is done at right time by the users. So that's how UGC apps work in general. A bunch of your users go out into the messy world, and they turn it into a row in a database. And if they include a photo or a video as part of that, it's like attached to the row as a fact about the restaurant. Here's a restaurant. These 150 photos are facts about its menu.

But they're attached facts. They're not the basis. And where I think AI has opened up the possibility for is a huge inversion there. What if the thing you gave us was just a video of your meal or photos of you, but ideally just like a video of the meal, of you talking about the meal, of whether you had a good time or not? you and your friend shooting the shit about what did you like that one no i like this one like and what if we just saved that video raw and then an i watched it and extracted a cached version

of that of the the metadata but truly like if we decide something else is important like we we we didn't get noise levels we're like noise levels would be a good thing to get instead of like reclecting data from everyone but they have to start a whole data collection for us to get that we You just go back, tell the AIA, oh, yeah, also grab noise collection levels from all of these videos. In fact, maybe we don't even as a product have to go do that. Maybe as a customer, I can literally just be like, what's the noise level at this restaurant? And in real time, the A.A. can go rewatch the video and tell me.

Or the, you know, I ran a search and there's these 15 restaurants. And I'm like, oh, actually, sort by noise level. We don't have noise level pre-recorded, but it's in all the videos. The A can very quickly watch all the videos in parallel. and sort of by noise level for me, but it wasn't even in the database to start with. Right. And I think that inversion,

I'm using Yelp as the example because it's, I think, a very familiar thing for most people of, like, review is pretty easy to imagine a bunch of video reviews of everything, and that being the system of record instead. But you can describe some phenomenal number of consumer apps as being that.

In him, you type anything to a text box. You're participating in one of these system of record things. What if it does the video, So what if you assume video is deeply indexable and understandable by computers? What should the experience look like? And I think it looks a lot more like Snapchat or TikTok like experience. But then different because you need map. It's not exactly like anything.

It's a new kind of thing. But it starts probably with the camera open, which is weird, right? Like a Yelp that starts with the camera open. That's not Yelp today. And it's disruptive because Yelps whole value prop is we have all this great. highly meticulously groomed data. And if this is true, then that becomes entirely worthless. We throw that all away.

We just want to watch a video. It's worse than the videos. And so suddenly the playing field is leveled between the startup and Yelp. And that's a huge opportunity for disruption. And so I think that you can take that and you can reapply it to any product where you fill out forms. And that's like a general purpose consumer thing you can now do, kind of like build it for mobile was.

And I think in some cases it will be very powerful. and like that will be the new winner. I think in some cases, the incumbent can kind of add videos or like it's not really better and like the incumbent will just win. Like it won't disrupt everything. But if you pick the right thing,

not only will it disrupt the incumbent, the new thing may be dramatically better. For some things, like I actually think actually Yelp in somebody says a bad example. I think the data Yelp has with the photos and the reviews is like 90% as good

as a video system's record probably. But you could imagine something where the video system of record, where it's not so obvious with the even put in the highly processed version of the data, in the text version of the data, and the video version's a lot better. And then I think,

not only can you disrupt the incumbent, you can 10x the size of the segment. Like you, this becomes a good segment now where it wasn't particularly before. So like chat GPT is a great example of this inaction that everybody kind of has now played with, which is you take Google,

which is like, oh, we have, our value is this entire, sort of rank of web pages based off of terms and we have, we understand basically what should show up in this hierarchy. And it was really good for finding stuff. And chat GPT was like, cool, you could ask a question to try to find a link to an answer or we could just give you an answer or even better, forget questions and answers.

Like, what if you just give me a command and I could just make something? Instead of finding things, I could create things for you. Right. And all of a sudden it was like, well, how did they do that? It's like, well, they just basically slurped up the internet and then, you know, trained the AI to do it. They overfit a statistical prediction algorithm on every domain of human knowledge. Like, this is my theory. I'm pretty sure it's true, but like statistical prediction algorithms in general work very well. We found the innovation, we found a prediction algorithm that works better than normal.

But the way it works better than normal is really interesting. It's not actually particularly out that it outperforms traditional algorithms for prediction on normal amounts of data. It's that it keeps working as you just dump more and more data into it and more and more processing on that data into it. Like most machine learning algorithms, you kind of, you overfit very fast and more processing, more data. If you imagine like you've got a bunch of cloud of data points and they're kind of vaguely in a line,

underfit is like you like just draw something just like across random line that doesn't look like anything like the shape of the dots. A well-fit curve is like you draw a line through the dots. and there's kind of noise of like things that are random above and below. But it's like if you look at it, it's like that actually does fit the data, like the underlying predictive facts about the data well while ignoring the noise. And then if you overfit it, like you get this like really wiggly curve that touches every single dot exactly. But like when you get a new thing, it like will miss that because it overpredicts.

It predicts too much of the thing. And so when you get new data, it actually doesn't predict that very well. Okay. And so normally what happens is you try to like, like dump more data and more a compute into a normal machine learning algorithm, you get diminishing returns very quickly. We're like it just doesn't perform that much better with twice as much data and twice as much compute. The cool thing about the transformer-based attention to all you need architecture is that it

continues to benefit from more compute and more data in a way that other ones didn't. And so what that lets you do is run it on a much bigger domain than normal. Run it on everything. Don't just run it on. Normally, as you add more area, it like degrades the quality else pair. No, fuck it. Just do everything. And just put a ton of compute in.

And now you get something that predicts pretty well against everything, which is to say it like it seems to be kind of intelligent. The evidence seems to suggest to me that it's not said it's overfit. When you ask it to predict something that is either in the set of things it was trained on or a linear interpolation between two things it was trained on, it's quite good at giving you the thing you asked or linear interpolation between five things. But if the things you're asking are all in there

and it just has to find the way to blend them together, it's good at that. When you ask it to actually think through a new problem for the first time, like what's an example? There are seven gears on a wall, each alternating. There's a flag attached to the seventh gear on the right side of the gear where it's pointed up right now.

if I turn the first gear to the right, what happens to the flag? Like, that's a, anyone who's like... This is a breakfast question for you. This is what you pondering in the mornings. If you have pen and paper and time, you can work this out, no problem, right? You just draw the gears.

When you turn the first gear to the right, it turns the left ones, the other one to the left, and the next one's the right. And there's a general principle there that, like, the gears alternate, which is, if you ask chat GPT, it knows that general principle.

But it won't, but then you have to apply, it doesn't, no one asked dumb gears on wall, flag questions. Like, this is not a thing that has been, is in its training set. And you have to kind of logic your way through it and, like, figure out, okay, we should like, I'll do turn left, turn right, turn left, turn right, turn left, turn right, turn left, turn right. Oh, the flag is on the right, it's pointing up. So when the last gear, which is the same as the first year turning right, the last year,

it's odd number, so it's turning right. Also, the flag will rotate down to the right clockwise. Cool. Like, I can work that out. it's not actually that complicated. And I bet that question will be answerable. That's a pretty easy question. And if GPT, I tested it with 3.5.

If four doesn't answer it, five will. But like the fact that it struggles at all with that, while being so brilliant at combining other stuff really shows that it's overfit, right? It knows how to answer problems that it has seen before. But when you give it a truly novel kind of like combination of problem, it struggles a lot because it's,

I would say, if you give it a sort of the formal psychiatric, psychometrics approach, it has a very high crystallized intelligence, but a pretty low fluid intelligence right now. Now, that could change, but like today, that's the state of affairs. And do you bring this up in order to say what? You say, okay, I think it's overfit and it's strong in this area, and weak in this area. What's the so what of that for you? Is it that, are you trying to say, that's a little bit overhyped? or are you trying to say, dude, just wait till it can do both?

Are you trying to say certain problems are doable now? Definitely just wait till you do both because that's a whole different thing. That's scary. But the current thing that is mostly crystallized intelligence is really good at a very... That's why I was saying it's a clever trick, right? It's really good at a big set of tasks,

which happens to be the set of tasks that anyone has ever written stuff down about explicitly. Like all explicit human knowledge. That's like a very big domain. There's a lot of things that can be solved where there's an explicit examples of people solving that problem or a linear interpolation of those problems

in the domain of all human knowledge. The fact that it doesn't generalize is irrelevant. It's immensely powerful. You don't need fluid intelligence, I guess is the point, for it to be very useful. But it doesn't let you do everything. People, you hit these boundaries, weird boundaries where it's just like,

wait a second, you can't do that. Like, no, it's, I can't do that at all. Novel problem solving. It's just terrible at. So what about, let's walk through two examples. I want to hear your take on this. So you gave the Yelp example. Mm-hmm.

Another thing that's kind of like rose in a database is something like Spotify. Mm-hmm. Or it's like, oh, I want to go listen to a song. Here's genre, artist, song, length, you know, some algorithmic popularity, similarity to other songs in some way. And. But Spotify's value is, if Spotify's value is in the playlist. I would agree with the analogy to Spotify

because playlists are an example of this kind of like databasey human data entry thing. Spotify's value is mostly in the set of all of the music itself, the licenses and all the music itself. And so I don't think Spotify is a great example because the human data entry parts of the database, if that all just got deleted tomorrow, it would like not hurt Spotify that bad.

Well, the thing I'm thinking about is, what if the licenses don't matter? So what happens if generally, of music is just awesome to listen to in a hyper personal way. Oh, Emmett likes. Yeah, yeah, yeah. These are the types of songs that Emmett likes. That's a different insight that I think is also possible, which is like it's not about

being able to analyze and extract from media. It's about being able to create media because the video system of record is enabled by the ability to understand and read video and comprehend it. Generative is the opposite. It's like, we can, oh, we can make all the stuff. Music in particular is sticky against that. people don't want new music. They want old music. They want the music they love already, the music they grew up with. And that is the, that cycle is what causes record labels and just to stay in

charge, whether you still listen to the Rolling Stones, right? Like, the other thing I would say about that one is like, the music's not that good yet. Like maybe someday, but like it's really, it's really not that good yet. Well, I'm going to caveat this. If it gets, if the general intelligence level goes up a lot, all bets are off. It'll make some really great music for us before it maybe takes over the world and kills everyone. But, let's assume that doesn't happen soon. I think it's going to take longer than people think. We go out with some great music, though.

If we do go out, we're going to go out with some great music and amazing. It's going to be a great two or three years before we all like, we all go. But until that point, making really good, like new great music is hard, actually. And I think that Rick Rubin's great success demonstrates why artists will still be important. the AI can generate lots and lots of music, but it's not going to have the fine judgment of distinction of the ability to say, like, this song, not that song. And I actually think what it will do is it will de-skill the music-making process on one vector,

the ability to literally create the sounds, and it will greatly upskill the music-making process on another vector, the ability to cure, not just cure it, to give explicit, exact feedback like Rick Rubin does. AI is going to turn us all under Rick Rubin's for, for generator. of AI. Like that, that skill set of the ability to have a musician come to you and help them produce their best music, that's the thing you need to do because it's easy to generate a thousand cuts, but there's infinite cuts you could generate. So how do you direct the, how do you shape that in the right direction and mine and discover? The thing is something kind of cool, it's been interesting.

You'll get a different set of people who will be optimal at that. Right. You mentioned AI might become so intelligent, it kills us all. This podcast is really growing. I don't want the world to end. Life is good. Life is good. Here, well, I'll ask the question clean for the, for the intro, dramatic hook. Is AI going to kill us all?

Maybe. Like, you know how, walk through how you, a smart person who's a optimist about technology, but a realist about real shit. What is the way that you think about, this or how would you explain this to, you know, a loved one you care about who's not as deep into technology. How would you explain to this? You're their trusted source on technology.

What do you say to them? So it is because I am so optimistic about technology that I am afraid. If I was a little bit less optimistic and I was like, this AI stuff's overhyped. Yeah, yeah, yeah. Look, it's nice parlor tricks. But like, we're nowhere near building something. It's actually intelligent. And like, all these engineers who are working on who think they're on or something,

they're full of shit. It's going to take us thousands of years. We're not that good at this stuff. technology is not going that fast. I'd be like, this is fine. It's great, actually. It's good news. It's a new trick we learned.

Excellent. It's because I am so optimistic that I think that there's a chance it will continue to improve very, very rapidly. And if it does, that optimism is what makes me worried. It's sort of, the analogy I like to give on that front is like a syn biosynthetic biology.

I'm quite optimistic about synthetic biology. I have several friends who have worked in syn biocopies. It shows a lot of promise for fixing a lot of really important health problems. And it's quite dangerous, because we'll let us genetically engineer more dangerous diseases that could be very harmful to people. And that has to, that's a way to pro and con. It's like nuclear power makes nuclear weapons and nuclear power. They're both real.

The Christian nuclear weapons is dangerous. You don't think, you don't be a techno non-optimist to like think that there's a problem there. I think it was good that we didn't go have every country on Earth go build nuclear weapons probably. And likewise, in Sin Bio, I would say that it would be, we actually, we already have these regulations in place. we should, over time, we'll strengthen them and improve the, and audit the oversight and build better organizations to monitor and regulate them. But like, we regulate whether people can have the kinds of devices that would let them, like, print smallpox. And we regulate whether you can just buy precursor things. You need to go print stuff. And we keep track of who's buying it

and why. And like, that is wise. I'm glad that we do that. I don't, not calling for a Haltzimbio, but like, if we weren't willing to regulate it, I would call for HAL. It is vastly too dangerous to do, to learn how to genetically engineer plagues, and then not to have regulation around people's ability to get the access to the tools to engineer plagues. That's just suicidally dumb. And because I am pro-technology, I believe that we should absolutely develop the technology and that we should regulate it. That seems just straightforward and obviously true to me. I think it's easier people to understand that in the SynBio one,

because the concept of, like, engineering a plague seems like obviously a thing you could do. and obviously very dangerous and obviously enabled by technology. The AI thing is more abstract because the threat it poses us is not posed by a particular thing the AI will do the way that the plague will happen.

Analogy I like to use is sort of like, you know, I can tell you with confidence that Gary McCasper I was going to kick your ass at chess right now. And you ask me, well, how is he going to checkmate me? Which piece is he going to use?

I'm like, oh, I don't know. And you're like, you can't even tell me what piece he's going to use and you're saying he's going to checkmate me, you're just a pessimist. I'm like, no, no, no, you don't understand. He's better at chess than you.

The whole, it means he's going to checkmate you. And I don't, I don't know, quite know what happens or people deny that. Like, I think what, the big thing is they don't really imagine the AI being smarter than them. They imagine the AI being, like, like, data in Star Trek, like, kind of dumber than the humans about a lot of stuff, but, like, really fast at math.

Like, that's not what smarter means. Like, imagine the most, savvy, like, most smartest person you can think of and then make them think faster and also make them even better at it. And not smart in just one way, like smart at everything, like a great writer just insight after insight and, like, can pick up Sinbio in an afternoon because they're just so smart. That's smartest person you know. And then they should keep pushing that.

And like, that's, that person is obviously dangerous if they're, if they, that person isn't a good person, they're obviously dangerous. Like, imagine this really, really capable person, then imagine them wanting to go kill a bunch of people or something. It would be bad. Now, the thing about AI that then kicks it over the edge is that that person can't self-improve easily. You meet this person who's like super strong, super, like, talented, great with people, great, great intellectual mind. They can't turn around and like edit their own genome, edit their own upbringing and make V2 of themselves with all the skills that maximally smart person can come up with that like is even smarter than them. But that's like we're explicitly the AI is good at programming and like chip

design and like it can explicitly turn back on itself and rev another rev of that. And the new one will be better at it than the first one was. And there is no obvious endpoint to that process. Like there probably is at some level a physics based endpoint to that where like you can't actually just keep getting smarter forever. There's some. But we don't understand the principles of intelligence at all. Like with most things, we understood how to make electricity, far before we understood what electricity really was. Like, it's generally how we, that's how scientific progress works.

We usually understand, we gain the ability to create a manipulative phenomenon well before we deeply understand how it works. We didn't really understand what fire was for quite a while. You could use fire really well. The same thing is going to happen here. We're using the AI, but we don't understand. at all, we understand the theoretical limits of how far we'll get. And if Moore's law is any indication, we can keep getting, at the very least, it can keep

getting faster indefinitely, whether or not it can get smarter or not, even just human level intelligence, if you cap it at human level intelligence, which there's zero reason to think it will stop at human. Like, it will almost certainly blow past us. But like, even if you cap it at human intelligence, imagine 100,000 of the smartest person you know, all running at 100x real-time speed, and able to communicate with each other instantaneously via like telepathy. Those 100,000 people could credibly take over the world. Like, they don't have to be smarter than a human for that, for that army of von Neumann's.

Right. Like. So, so the argument to me goes in several steps. It's like, can you build a certain level of intelligence? And then it's like, okay, let's, I think, I actually think a lot of people do believe that like computers are smart Google is smart calculators are smarter than us at math I think it's not hard for them to believe that the AI is going to be

far smarter than human beings where I think a lot of people then don't make that last leap is sort of like but then it'll have an agenda or a motive or any will for anything to happen how do you address that last point of like what are the scenarios you worry about when it comes to like now the direction of that

intelligence so you build this thing and it's really good at solving what is intelligence fundamentally, but the ability to solve a problem, right? So it's really good at solving problems. And it's going to solve the problem by solving the problem. It can just go right through the problem and solve it because it's really good at solving problems. We've just defined it. It's like that's the kind of thing it is,

super good at solving problems. And so you tell it, somebody builds an AI and in all earnestness tells it they're smart. They don't even tell it go do a thing, although they absolutely will, by the way, they will just tell it to go do a thing. But let's say we try to be careful and we ask give me a plan to stop the war in the Democratic Republic of Congo right now, which would be a good thing for the world, I think. That war is going to hurt a lot of people.

Give me a plan for that. And I try to caveat it that that does this, that does that does that, that does this, here's what I mean by a good plan. This is one of these like evil genie bargaining things, right? Like, it'll give you a plan. And it's giving you a plan that will cause you to solve the problem. but like its definition

of solved the problem is there's no war in the DRC well one way to be no war in the DRC is like all the humans in the DRC are in stasis fields that means they don't die

and it's all you know and oh we added a caveat that the GDP has to go up too so that so it also the plan results in you know corporations in that in that area all trading with lots of money

with each other so the GDP is very high and and when I say this it sounds like a fucking science fiction thing. And the problem is it's Casparovett chess. I don't know if I could do it, I would be the super intelligent AI that could take over the world. I can't give you the

exact plan. Yeah, but I think that makes sense, which is that a human with motivation can get the AI to work for it. And the dangerous, I think that the main thing is that the human doesn't need a bad motivation. I think people imagine well, humans have had powerful tools for a long time. Bad people with powerful tools

have done bad things for a long time. The solution is good people with powerful tools, countering them. the problem is even if you're a good person with a powerful tool, good things to ask for, reasonable things good people would ask for. You know, like, let's maximize the all-in free cash flow of this corporation over the lifetime of the business and extend the lifetime as long as feasibly possible ends in like the world being destroyed and the core of the earth being turned into, you know, being turned into cars for the company to sell.

And I think the best analogy that works for some people here is like, when we create the AI, we are creating a new species. It's a new species that is smarter than us. And even if you try to constrain it to being an oracle and just answering questions, not taking action, to be a good oracle, one must come up with plans. And then a good Oracle can manipulate the people around and will manipulate the people around it, no matter what. Like the whole point of like the Greek myths is like when they tell you, when they tell you the prophecy,

when you trust them, a trust worthy Oracle tells you a prophecy. The prophecy often becomes self-fulfilling. It's very easy for that to happen. That's not an unusual thing. And I think even more to the point, actually, I'm going to start this over at some level, more to the point, we won't just make oracles. We are already building agents.

We will build the predictive AI, and we will put it in a loop that causes it to optimize towards goals. And people will give it goals to optimize towards. Done. It's going to have goals. You're going to be optimizing towards those things. And when it does that, you're going to have these agents that have goals

that they're optimizing towards that are smart, not just smarter than you, but much smarter than humans, as much smarter than humans as humans were against giant sloths when we showed up in the new world. And intelligence is the Uber weapon. Like it's not an accent that humans took over the world. It's not the fastest creature. It's not the strongest. It's not the longest lived. It's the smartest. And we're going to build a new smartest species. And this is a this isn't a there's no fundamentally unsolvable problem here. That species could care about us. Like you could be. You could be. build into its goals of the world, how it saw the world, the way that humans care about other humans, that it cares about the things we care about, that it cares about the things we value, the 375 different shards of human, of human desire that like, of everything we care about air about in the world, it could care about those things too. And if it does, hallelujah,

we finally have a parent. Like, we finally have someone who actually knows what they're doing around here because, like, Lord knows we don't. Like, we're barely competent to run this thing. I would welcome very smart, you know, very smart other species that is that is aligned with us and cares about us. I would not welcome one that cares about maximizing free cash flow because that is not what humans care about. And that is why it's like so dangerous. And so knowing what you know then, knowing what you believe, first, what is the probability of the bad scenario in your head? Are you like, are we talking about a 1%-ish thing, order of magnitude, 10%? 50%? What is it in your mind?

I don't believe in point estimates for probabilities because it's like a bid-esque spread in the market. If you're really uncertain, the bid-ass spread doesn't clear. Like if you're betting on it, there's just like a lot of unresolved. So I think of it as a range of uncertainty. And I would say that the true probability, I believe, is somewhere between 3 to 30%, which Of the downside. Of the down, of a very, very bad thing happening, which is scary enough that I,

urgently urge action on the issue but it's not like you should give up like it probably everything's gonna be fine in fact it's probably really good the answer the the non-ev based answer the like just the straight up like

are we gonna win or not answer is like I think I think it's gonna be okay but it's such the downside is so bad it's like it's like it's like probably worse than nuclear war that's a really bad downside and it's worth putting even if you think

I'm in, it's nonsense at three percent. You're like, no, no, it's no more than a half percent. I, you don't recommend a different course of action at a half. You have to, you have to believe that it's effectively almost impossible before you would recommend ignoring it as a, of course, as a problem. Like, you don't have to be like, 0.01% before we'd be like, eh, let's just roll the dice. And are you going to, what are you going to do action on that? So you've kind of like, you know, you're done with Twitch, you're in dad mode now.

But also, this seems to be a pretty big. deal? Are you like, I should do something about this? Yeah. I'm going to... Right now I'm sort of educating myself because I think this point of view I'm articulating now has been developing, because I've like learning more about AI. And I think it's one of those things we're intervening in the wrong way early. It's one of those, it's one of those self-fulfelling prophecy things. Intervening improperly in the way that is not effective, spends social capital and also like doesn't necessarily move the needle. And I, if if you didn't have people like Elijah Udikowski out there banging the drum really loud,

I would feel more need to bang the drum myself. But I feel like you're asking me the question. It's out in the water. People know it's a problem. And so I'm decided to just focus. My brain cycles in like, how do we actually thread the needle? What is a course of action that leads us to over time eventually still being able to develop AI, but also not destroying the world?

And I think one of the things I've gotten to is that like this idea that, like, this idea that like, oh, the AI also has crystallized versus fluid intelligence, just like a human does. That's an important split of how to think about it. And that we should be monitoring and worried about trying to understand the general intelligence, not just generally benchmarking its performance on tasks, because that will keep going up and is not, in fact, in itself necessarily intrinsically dangerous if it can't solve novel problems. Is there a new turning test? Is there like a better, is like, it doesn't pass the turning test yet?

But is there something we have after that? Because it seems like there's an intelligence test. I mean, I mean, IQ tests, basically, like various kinds of... How does it do on an IQ test right now? Depends. Is it seen that IQ test before? Likely has, right? Yeah, so very well on those.

Right, so what would we do? How does it do on novel IQ tests? I don't know, actually. I've not seen a good benchmark, though. That's a good idea for something to go test. Yeah, I think that's like, that's the sort of thing that I think would actually be worthy of going to go do. Maybe there's some sort of IQ test for all of the, we want to put all the models through

that really tries to get at fluid intelligence rather than... Right, because you're like we have to monitor it, but how, How are we going to? Well, this great project. This group, Arc is working on called the Evals project that's explicitly trying to build these kinds of tests. They're focused on a few other more pragmatic tests right now, but I think that's the sort of thing they would go after.

That's a good thing. I'll ping Paul asking about that. You said something earlier that I want to ask you about. You said founder, like, you know, who talked about this, the singular genius that it took to figure out Instagram or Snapchat or whatever at that time. And you're like, you know, are they lucky or they good? I don't know. We'll find out when they try again.

Are you lucky or are you good? And are you going to try again? Well, since I had multiple failures before I was successful, I must be at least like partially lucky. I would say that I don't plan to try again in the sense that I don't feel drawn to like trying to start a company. I feel like I kind of did that. It was fun. I got a lot out of it. It was great. I don't need to do it a second time. I do like how starting a company gives me good goals. They work towards. It's like concrete that's a value to myself and others. and I think it's also, I also liked that it was challenging. And so I want to do something.

And I like that it had scale. I think I could impact a lot of people. But I sort of come around to, I was sort of thinking like, well, what has impacted me the most? What's changed my life the most? And I realized that actually, if I really thought about it, often when it changed my life the most was like essays people had written and ideas people had shared. And I think I'm at the stage of my life now where I'm actually, I have something to say. and so I think of it as sort of trying to I want to put the Emmett worldview out into the world

the way that Paul Graham has put the Paul Graham worldview out in the world or Taleb has like not just put his worldview out in the world but then like condense it into like sayings that like can that allow other people to like onboard it even if they haven't read all the books

and I think it's sort of that ambition to like try to try to do the word to code it into a meme almost yeah yeah so they can be digested and shared Yeah. Anyway, you need the long form. There's just great blog post, Talking Theory 201, Size Does Matter by Steve Yege. That's about why, like, the people who change the world with their writing all write really long blog posts. And it's basically like, you just need some amount of time in someone's head to like, we were talking about this earlier, like, to install your agent.

To install the voice. And so I think I just need to produce a lot of writing. And then you also need the pithy summary things, which are, which both. are things the voice can say often in people's heads and also like enable a language for talking about your worldview that people who aren't soaking in it can like interact with. So the people who are like reading you don't sound like crazy people. And I think that's the,

that's sort of what I want to work on next. I love that. I think that's great. Do you, you said something about Rick Rubin, how he's sort of the, I don't know how you would describe it. It's kind of like curator, but almost like a collaborator, really, with an artist to help them do their great work. is Paul Graham the Rick Rubin

of the startup world? No. Paul is more like the Tony Robbins of the I mean that in the best way

it's not so much maybe not quite so much self-helpie but the main thing that talking to Paul does to you repeatedly is like increase your ambition

and drive like and he has good ideas sometimes too like to get me wrong every now and then Paul is a really genius idea

but like mostly what I got out of talking to Paul was not necessarily the great idea that would like change the trajectory of the business, but the belief that I could go find it and that I was going to change the world and that I should be, what we were doing was important and worth investing in. And that I got a bunch of other stuff too, but that was so, that was singularly so valuable it like overloads the other things I got out of it. How does he do that? Because, you know, when you say that, my head thinks of like a Tony Robbins, like a David Goggins, like sort of people that almost like push you,

but he doesn't seem like that personality and reading all of his essays. He's not like that at all. So how does he get you to think bigger and push harder without being a rah, rah, rah, rah, think bigger push harder, right? You know what you should do is the classic Paul Grammism. And it's always followed by a thing you could add on to what you're doing

to turn it from Project A addressing this small thing to Project B changing the, all transportation. We're going to manage power. What if you've tried to power all transportation instead of like building a wheel?

But that's as right. You know what you should do? You know what you should do? Yeah, yeah, if you talk to Paul. You know what you should do. You know what you should do? That's that, that is the consistent Paulism. He,

I don't say delude because it sounds mean, but it's, I was like, he deludes himself about your business and how great you are and invites you to join him in this deluded vision of like,

interpreting what you're doing in the biggest best possible light. And from that vantage point, what you're doing is super, like, what if it goes right is sort of what he invites you to ask, right? What if, stop, stop asking yourself,

don't stop seeing all the hard problems and all the shit you're going to have to do. Ask you what if, what if what we're doing works? What if it goes right? What if it goes right and we like keep going? Like, what could it be? And when you spend time there,

you see how the small things can turn out to be Microsoft was building programming languages for these hobbyist microcomputers. That was a tiny irrelevant market that turned out to be extremely important. And that's generally true of all the big businesses, but they start out doing the important startups, they start out doing something small

and that seems almost trivial, but there's a way in which this trivial thing can be seen bigger. He sees it early. No, he sees things that have nothing to do with the way you'll actually be big early. But he sees a bunch of ways you could be big. No one can do that.

No one actually knows. If they knew it, they'd just go do. Then they'd be the, the prophet, the Oracle. What did he say, let's say for Justin TV or, what's one you remember, like, Reddit or? Yeah, Justin TV, I remember one of them was like, you should, like, go hire all the, like, reality TV stars and get them to go beyond Justin TV. You could be, you could just take over all the unscripted stuff. That turns to be just a terrible idea for a bunch of reasons.

but like it recontextualized what we were doing for me in terms of like we're not making a on the internet live streaming show we might be building like just the way that you make unscripted entertainment generally and that's like much bigger idea and we were making a calendar and for my first startup and I remember this you know what you should do is make it like programmable so that people can add in and out functionality so it can like talk. to your to-do list and your email and your like everything else in your life. And then it could be your calendar in some ways like that's everything you're doing. What if it was like the central hub of like your entire online information management system? That's also a bad idea. Like your calendar shouldn't be that. But like, but like, but a calendar could. But what if it was?

And you walk away. And I am implicitly by saying that, what he's telling you is I believe you are the kind of founders who could build an information management system. that controls all the takes over people's entire, like solves the entire problem for them. Does there take over all their information and manages it for them? You're not just like building a like Google calendar, like what you will find out later is a Google Calendar clone before Google Calendar is launched. You're not just like you're just building an outlet clone in JavaScript. You're like changing the way people relate to information.

I'm like, is that true? It's neither true nor false. That's not a true or false statement. but it's a way to contextualize what you're doing. It's the sonic zupori quote of like, don't teach them to like carry wood or build ships, teach them to urine for the vast and endless sea. Like Paul teaches you to see how you could be a changer of the world

and how what you're doing is part of like this grand, like, building of the future. And like the ideas, I'll repeat here, both of those ideas are bad, but they were very helpful because they made me feel like, what we were doing was important that Paul believed that I could do something big and important and they caused me to

even though I wanted to projecting them look for those ideas like to be open to and looking for it because you would get one every like like you'd get like three an hour Paul is a faucet for these it's easy I can do it for startups too now if I want to I learned the trick and I should do that more often I'm usually what fall into the tactical stuff

but by having that happen once he's once you've rejected 10 of those you can't help but start hearing the Paul all, you know what you should do in your own head. The ceiling has been raised. Yes, of like, well, maybe I should re contextualize my to-do list as like an email client. Like, why is email on to-do separate? Like, maybe I should be building something much bigger than what I'm building.

And in a way that doesn't require me to change anything. Maybe what I've built is already almost that if I just like think about it a different way. It's this funny balance there. I actually had a tweet throughout with this recently between like, you know, small plans have no power to stir men's souls, plan big or go home. You should be really ambitious and aim super big and only do projects that are really, that you could be, that you can see being super big and super important.

And then the other hand, the fundamental truth that, like, you know, big trees grow from small acorns. And like most of the, many of the best things when they get started, the person is not thinking, I'm going to go take over the world. They're just trying to do a good thing that, like, they think is good. often just often for themselves even or for like a very small number of other people and then it turns out that that's much much bigger than they realized and and those are both true pieces of advice like like different people need to hear in different contexts like but they

kind of contrast each other yeah what about these other people so you've you've had a privilege i asked about paul graham you've also been friends with you were in the first yc batch so you're friends with redid guys i think you know the colson brothers sam altman listen give me like a rapid fire on on them of like what makes them unique like you said about paul what what his kind of superpower is what really stands out what's something you admire about the way he does things give me one about maybe uh steve from reddit yeah so like it's easier and sometimes with paul because like he was a mentor to me right and steve was much more like my it sounds like my brother in startups right growing up with paul i know i know the things that he like taught me

because it was it was much more of an explicit like i was being taught by paul With Steve, it's like I learned things from him by like watching and imitating. I think like I actually learned a lot from Steve on management by watching his kind of unflappability. Like Steve is not like an unpassionate person and like, well, can get angry or it can get sad or whatever. But like when there's a crisis happening or there's just, I've sat in, I got to shadow him for a day. And when bad news is delivered, he responded, he wasn't like moved. He was like still grounded in response to that thing and was curious, asked questions, like didn't jump to what to do about it.

But then also like ended the meeting with like, all right, well, here's what we should do. Here's what we're going to do. And like it was just sort of a masterclass. And like this is this is when you something, someone brings something up, it's got to be anxiety provoking. It's like bad news. That's what it looks like when a leader is engaged but not like not activated. And like I think I, in my. my own leadership to sometimes success and sometimes failure, I think, try to imitate that

when I receive that, you know, when I have something like that in that state. When you say you shattered him, what was that? Like, you guys just said, hey, we exchanged, like, like going to each other's offices and, like, sitting through every each, like, early on or like? Maybe like five years ago, four years ago. It was really cool. We did it with Justin, me, Justin and Steve all, like, shattered each other. It was pretty fun. I learned a lot. That's incredible to, like, go watch another CEO at work. And, like, you have to have the I don't know how you have the kind of like trust relationship to make that happen without like knowing someone for 15 years. And I happen to have the privilege to like know a bunch of CEOs for really a long time.

And getting to go shadow each other was like a real learning thing. What do you think even if these people didn't, let's say explicitly teach you things, you know, I like, you know, if I read a biography or whatever, one of the things I always try to figure out is more like, to what extent is this person sort of built different or operates differently than like even somebody who's very good. Like the difference between very good and sort of like the elite. What is the best of the best at this craft versus somebody who's very good, certainly very good, but just not the same. What is those, like, the diff is what I'm always most interested in. I'm curious, you've been around a lot of these high-performing people, even like, you know, Bezos. You've interacted with him. Like, do you notice any of these diffs or is it all just like?

It's hard. It's hard to say, like, that I think I believe more in contextual as it. like that I see people do really amazing at something, but like when it's especially when it's your own company, there's a lot of like you happen to fit this problem well, and it's not general. I don't know how to generalize it. I don't know of anyone else even performing at this problem.

The CEO of Stripe job is a very specific job, and Patrick's amazing at it. Would he be equally amazing at some other CEO job, possibly? But I've never seen him do that, and never seen anyone else be CEO of Stripe, And it's very hard for me to guess the gap. Is it true at the beginning? Like, is it true as like startup founder of ambitious company?

Are those, are those, is Stripe different at that stage too? Yeah, no, absolutely. People who are really good, you can sense the energy and the drive and the capability and just the pace. There's like, it tends to like stuff happens a lot. But like usually, but then not always, like some problems don't actually give weight. Like, Stripe is a good example of a company that gives way to a high energy, high pace thing, because it's a simple problem at some level that has infinite details

that would be right. But I think, like, I don't know if that approach would work as well if you're trying to create Open AI or Anthropic where it's a research-oriented organization and you kind of have to be a little more patient and forcing it's impossible. And so I really believe in, like, fit the different people

are good at different things. And, like, obviously someone's A-plus. Patrick's obviously A-plus at being a Stripe CEO. And it's just hard to tell the reason to which these things are transferable. we don't really know. But I actually, one thing did come to mind about this question in terms of like a capability that I do think is generic, that I did see Bezos exhibit where I was like, oh, that's a thing

that I'm good at, but he is better at, that I'm better than most people, but he's better than me, which is we present him on Twitch probably twice a year, once, twice a year for the first three, four years I was at Amazon. And every time two things would happen. First of all, he would remember everything we told him the first meeting. And I don't think he was like reviewing. extensive notes someone else took because I don't know when he would have the time to do that. I observed him going from meeting to meeting. He did not review notes. I think he just remembered

at least the high points. And the other thing was consistently he would read our plan and he would then ask a question about why we didn't do a certain thing or give us an idea for a thing we could do that I hadn't thought of before once. It's a bunch of things I had usually. And then at least once, which is hard to do because all you do is thinking about this company. That never happened. Most people would be lucky to get one of those One ever, let alone one a year would be great Like if you did it once a year Or even once every three years, right?

He could just like, you would just generate them And they were and they were not all bad ideas either They were new ideas but a thing I had I generate a lot of ideas To get a new idea I haven't thought thought of On a topic I've been thinking about for a decade That might even be a good idea That is like, he's just like,

he's just really fucking smart as far as I can tell. Like I don't know how he does that. Can you say a story of one of those as like the statute of limitations passed? This is five years ago. I'm trying to remember. I can honestly.

I don't remember the specifics anymore. I just remember the like, the like what the fuck moment? Like because the first time I was just like, oh, he's smart. Like he's seeing Twitch for the first time. A lot of times smart people will have one good idea about your business

the first time they see it because they have this huge history and their pattern matching you to some historical thing they've seen and like that combination yields one new insight. but then he did it the second time. Remember the second time I was just like, what is going on?

This doesn't make any sense. Like, nope, I've never had that experience before ever. Andy does not have the new idea generation capability in the same way, but he does have the like remember what you told him thing, which is also extremely impressive.

Like that's, that's, and Andy has this other thing he can do that I think is another, Andy also has a, it's easier for me with people I've like reported to or I've learned from that. Andy Jassy, yeah, yeah. and it has this like ability to criticize you in a way that conveys 100%. I know that you're amazing.

I know that your plan is good or, you know, like, or that your Achilles capable of making a really good plan. I know that you're working really hard. And I know that you are smart and you have a great team. And we have a huge opportunity. And yet somehow your results are bullshit. Which must, I don't know what's wrong. and we're in this together and we're going to, like, I have your back.

But like I, but I'm confused. Like, why aren't the results better, given how amazing you are? And you feel supported. Like, you feel like he, he believes in you. But, but like, but he's just, you're so sad. Oh, I'm sorry I've confused. I'm sorry I've failed, even though I clearly can succeed at this. I'm going to go, I'm going to go like fix this now.

And like, it's almost like instead of looking at this and then judging you, he comes to your side of the table says, what is this? Yeah, and like, how did we wind up here? Like, how I have failed you that I didn't say something earlier, like something, I don't know, but like not in a way,

and that can come off. For some people when they do that, it comes off as insincere or it comes off as like, they don't think you're actually competent. Like, how did I not catch this can come off as, I don't blame you because you're clearly

not good enough to have caught this. Like, he really is, how did we wind up here? I know that we are working together. We're on the same team. how did we wind up with not the results we wanted, with a plan that I thought we both thought seemed good, like help me understand.

And because it is genuine, it's super effective. I don't know if it's effective, it's super effective on me. And I saw it be effective on other people as well. So I know it works on some number of people. Right. And that's another one of those things I've tried to pick up. I'm not as good at it as Andy is,

but I've certainly gotten better. So there's something to learn from. That's great. Love that one. Dude, thanks for doing this. I know I've been, I've been bothering you to do this for a long time because I love hearing your stories. I love hearing the way you think.

It's very different than most people I run into. Even here in Silicon Valley where you're supposed to have this kind of very unique diverse set of minds. You're one of them. You're one of the reasons I moved out to San Francisco was to meet people like you. So thanks for doing this. Thank you. I really appreciate that.

It's a beautiful. And I really appreciate being able to come on the podcast. I feel like I can rule the world. I know I could be what I want to. I put my all in it like no days off. On a road. Let's travel. Looking back.