BIG IDEAS BY NEW ECONOMIES
00:31:46 · Richard Socher
And then again, there are jobs that I think are going to be immune to AI in entertainment. You know, I think entertainment like people could see AI do all the sports and Probably I could come up with some crazy mechanism to just shoot a soccer ball faster than the speed of sound into some goal a mile away, but it's not going to be that interesting. People are going to want to see other people doing sports and perfecting their craft in that way. So entertainment, sports, travel, all these things will continue to exist. Luxury stuff will continue to exist. And then even in SaaS and in software, there would be pockets that were somewhat immune to AI. Any software that has a marketplace or some other kind of network effect is very hard to vibe code into existence. Sure, you can vibe code like an Instagram app, but then it's just you and a couple of your friends on it, not a billion other people. And then you have brands and data modes that will continue to exist. So I'll pause there and I could talk about hours and how different jobs will be impacted and what hourly workers can do in different industries and how to think about it.
00:33:02 · Ollie Forsyth
[00:33:02] S1: And just like so much of this is about convenience, right? You know, in this kind of ecosystem, we talk to all these people every day. You know, if you look at just like an SF with Waymos now, you know, you no longer need the driver behind the car. This is going to be replicated to the You know, farmers don't want to spend hours cutting their crops, sitting behind a tractor. You can have machines do Where do you see the biggest opportunities for superintelligence outside of research to make It's made the lives of us consumers just so much more enjoyable and convenient.
00:33:40 · Richard Socher
[00:33:40] S0: Okay, So in terms of enjoyable and convenience, I think the trick to predict the future is to look at wealthy people again and just see what the goods and services are that they have access to that are bottlenecked on intelligence and hence are going to be accessible for everyone. I think a personal assistant is I've mentioned for the last few years when asked this question and we're now seeing it. I think Muse is becoming like a personal assistant. I think there'll be many others. There are lots of startups that are working on that and I think DOTS or DOT. You'll see more and more trolls Coactive assistants, those eventually will be connected to robots and then people will come home to a clean apartment. It's going to take a while. Everything in hardware is slower and wetware is even slower. But I think life will be more enjoyable once everyone can afford a personal assistant. And then you're right. The interesting bit with self-driving is, and this is like Tough to describe or explain too, but not every objective improvement for humanity is always good for jobs. There are a lot of jobs that are dependent on people having accidents. There are the people who tow away the broken There are the people in the emergency room working from all the traffic deaths and maimings and injuries and so on. There are the injury lawyers who then can help and try to sue someone over a fender bender. There are the car mechanics shops. I mean, there's so many jobs that depend on people hurting themselves in traffic and with cars that they might hate AI again. But most people should agree that it's better if there are fewer accidents and fewer teenagers dying and so on in cars. So I think the future is complicated and it requires a lot of foresight. And then in many cases, different... I guess stakeholders collaborating as the job landscape changes.
00:35:35 · Ollie Forsyth, Richard Socher
[00:35:35] S1: You just mentioned MUSE and DOTS. Meta hasn't really changed in five, ten years from a grand scheme of things. Do you think if Meta didn't release MUSE or some form of agent, do you think it would still be relevant? What do you think about that kind of opportunity? [00:35:56] S0: I mean, you have to give it to a meta, I guess, like, sure, people use Facebook less than less now, but they use Instagram a ton, right? Like, so there are, like, they, and WhatsApp, people use WhatsApp a lot. So there are, you know, they, they stay extremely relevant through some of those acquisitions. And, but then Muse was developed in-house, so that's, that's been really impressive too. And, yeah. [00:36:20] S1: When we're looking at so many opportunities with founders, if it's building new agents or you look at what all these AI models are doing, I kind of feel sorry for a lot of these early-stage founders. They want to build a note-taking tool app or an agent that MuseNow does and one of these large companies with massive distribution can copy them overnight. What is the role these large companies have in creating technologies, but also allowing these amazing founders, which we both speak to on a daily basis, very early stage founders, to actually go and create the thing that they want to do and have a chance of also becoming the next metas and open AIs?
00:37:00 · Richard Socher
[00:37:00] S0: Yeah, I wish I had a perfect answer for all industries and all software and stuff for that. But I don't think, I mean, these big companies are going to try to maximize their profits. That's their goal. And it is easier now to build something, but it's also easier to copy whatever someone's built. And now with decompiling, even other software that was compiled, like Photoshop and people used to buy, can just be decompiled, re-implemented by an AI and then boom. All the features are there and you have a much cheaper free version of it. In a weird way, I think China has shown the future there because in China, labor has been so cheap for so long that China never developed a deep SaaS ecosystem. If you are going to spend a couple million dollars on a software, you just hire a couple people for like 10,000 bucks a year and have them re-implement that software. Now the US kind of catches up to China where it's so cheap to build things, not because we have more people and they're getting paid less, but because they were so expensive, we have now AI that builds it. And there's a lot of things where that can be true for manufacturing, too. It was too expensive to do in the U .S., so a lot of manufacturing moved overseas. Now with robots it might become cheap enough to then come back to the US and you know I mean In some ways international trade is a force for peace but its also good I guess To be able to manufacture things everywhere You want them to So I don't know if I have Like Perfect answer for every startup and how they need to react to this. But I think generally, again, network effects, brand, marketing, and data modes are continuing to be powerful. And then there's also a funny mode that I would call the mode of boring. Like maybe I don't know, maybe. I need to come up with a better name, but like the boredom moat where People at Anthropic are not that excited about automating taxes. It doesn't feel like, oh, we got one step closer to AGI because we automated taxes, right? It feels cool when you can say, oh, I proved this theorem and it's unproven for a decade or longer. But it doesn't seem that cool to be like, oh, in Alabama, you're like, this income tax, blah, blah, blah. We found this reward hack niche where it's just like, solve this zero tax problem better. And so my hunch is that kind of...
00:39:31 · Richard Socher, Ollie Forsyth
The boringness of certain industries are a mo2. There's not enough people want to get into that. So that is another way to get away from these really large model companies. And then I think in some ways, if you can build in a niche that is kind of standard startup stuff, you find a niche that is too small for people to care about, but then somehow you're able to grow very quickly from that niche such that it's hard for other companies to catch up. And I think that's what is still possible in lots of different pockets of software. [00:40:06] S1: From a Geo standpoint, I feel the U .S. has always been far ahead in what AI can accomplish. Now we're obviously seeing a lot happening in China and a few other countries. When you compare China and the US together, we're going to probably get some hate in the comments, but this is okay. Who do you think is going to win in this AI race, China or the US?