Why companies are becoming a series of loops | Anish Acharya (a16z)

00:36:15 · Lenny RachitskyPlay from here

[00:36:15] S0: I want to come back to the whole space of consumer and AI and things like that, but I want to follow this thread a little bit more about just the optimism around where things might go. There's a lot of fear and worry about the future with AI and just generally. Mark Andreessen when he came on the pod had this really interesting take that AI came just in time to save us, because population is declining, productivity's going down, there's all this war, climate change and all these things, and we would be in big trouble if AI wasn't here to fill that gap. Talk about just your bigger picture perspective on why you think maybe people are underestimating the positive and optimism around AI.

00:36:58 · Anish AcharyaPlay from here

[00:36:58] S1: One, I think it's a potential for it to be a sort of emotional spiritual interface on which we can get leverage and explore aspects of ourselves that have been really buried. If you look at the kind of effect of the industrial revolution, it's that there are these scale advantages which are insurmountable. And as much as obviously I'm very pro-capitalism and I love the economy that we live in, I think that centralization, it sort of discourages the individual in some ways and it maybe detracts from their identity. So, I think one of the really magical things is this is a technology that really amplifies our identity, our agency, it kind of unbundles skill from desire. For example, if you want to make music, you can make music now. You don't have to know how to play the piano. If you want to be a programmer and make software, you can make software now. So it really amplifies our individuality, it allows us to explore aspects of our lives that we were never able to explore before. And just in terms of the nuts and bolts, we have been in this sort of morass of 2% GDP growth. Who said that we have to be there? Why can't we be 10 or 15 or 20%? And this is a technology with which not only can we dramatically drive productivity, we can dramatically drive ambition. Maybe this is a caricature, but the 1950s and 1960s we believed that we could do anything. We were coming out of World War II where the entire economy, the entire world mobilized in a way that we didn't think was possible. And one of my theories, Lenny, is that when the stakes are high we are awesome. When the stakes are low we are at our absolute worst. And in a lot of ways, I think the world we lived in five years ago felt like a low stakes world, which is why we collectively had a lot of these side projects as a society which weren't necessarily productive or making any of us happier. And now you've got, it's not just Elon doing everything he's doing, but I think everybody feels like they're climbing the ambition ladder. You ship your bad ideas so you can discover your good ideas. And if you want to build software, great. If you want to build a bridge, you don't have to be a civil architect to know how to do that anymore.

00:38:55 · Anish Acharya, Lenny RachitskyPlay from here

So, I really think that we have the makings of a sort of dramatically happier, more fulfilled, more productive society, and yet we're here talking about permanent underclass. [00:39:05] S0: I love all of that, that all feels so right. It's so hard to really believe that. But if you actually look at how things have gone so far with the rise of AI, unemployment's down, people are making a lot of money. Obviously a lot of people are struggling, there's a lot of downsides, data centers causing problems for people, things like that. A lot of issues, but it feels like as an economy and as a country feels like things are going well so far. They just almost cured some kind of cancer the other day.

00:39:05 · Lenny Rachitsky, Anish AcharyaPlay from here

[00:39:05] S0: I love all of that, that all feels so right. It's so hard to really believe that. But if you actually look at how things have gone so far with the rise of AI, unemployment's down, people are making a lot of money. Obviously a lot of people are struggling, there's a lot of downsides, data centers causing problems for people, things like that. A lot of issues, but it feels like as an economy and as a country feels like things are going well so far. They just almost cured some kind of cancer the other day. [00:39:33] S1: Yeah, you're right. Moderna just did. I mean, the fact that Dario can write a blog post and say, "What happens when we cure every disease?" And then we debate it as a serious topic, what world are we living in here? I also think that we're collectively worried always, these abstractions, the world, the average worker, the middle manager, the person who lives in the vicinity of a data center, these are abstractions, but our actual lives seem like they're getting more fulfilled, we're more capable, we're more empowered. So, I think that's also something that the revealed preferences tend to show how people are experiencing it individually, and the stated preferences tend to show how people are sort of observing it or believe it's playing out societally. If you ask people if they want a data center in their neighborhood, most will say no, but if you ask them if they use ChatGPT today, most people will say yes. So, that's kind of the dissonance.

00:39:33 · Anish Acharya, Lenny RachitskyPlay from here

[00:39:33] S1: Yeah, you're right. Moderna just did. I mean, the fact that Dario can write a blog post and say, "What happens when we cure every disease?" And then we debate it as a serious topic, what world are we living in here? I also think that we're collectively worried always, these abstractions, the world, the average worker, the middle manager, the person who lives in the vicinity of a data center, these are abstractions, but our actual lives seem like they're getting more fulfilled, we're more capable, we're more empowered. So, I think that's also something that the revealed preferences tend to show how people are experiencing it individually, and the stated preferences tend to show how people are sort of observing it or believe it's playing out societally. If you ask people if they want a data center in their neighborhood, most will say no, but if you ask them if they use ChatGPT today, most people will say yes. So, that's kind of the dissonance. [00:40:26] S0: The obvious issue is just the PR around AI has not been great. There's a lot of fearmongering. Thoughts on that, what's going on there? Do you think that'll change?

00:40:34 · Anish AcharyaPlay from here

[00:40:34] S1: The most important thing that we can do with AI to change the kind of conversation around it is make important things cheap. There's two things that are extraordinarily important in America that have only gotten more expensive, healthcare and education. If you look at healthcare, 45% is administrative. So, if you take a lot of that administrative burden out, you can actually see deflationary healthcare costs, also things like curing every disease. That sounds awesome. GLP-1s, also obviously not an AI thing but I think is a reason to be optimistic about deflationary health costs. And then, education as well. I think education now has the strongest form of competition, sort of traditional education that it's had in 200 years. And I think it's going to be very, very good to kind of unbundle learning from institutions. And also by the way, status from credentials. You don't need a Harvard degree, you just need to get, and that's pretty cool. I mean, without commenting on OpenAI specifically, I think that maybe I'm a little skeptical on some of these things where I think the aura that Anthropic got from having a model that was too dangerous to release was extraordinary. And maybe they had a GPU shortage. Now, maybe the capabilities were more advanced than they actually wanted. Maybe they actually wanted to keep that proprietary model internal to extend their own lead. So, I think there's a lot of sort of confounding factors that would cause you to pull back a little bit. Look, I do take the points about offensive cyber seriously, which is we should harden all of our systems before we make them trivial to penetrate. But I think the sort of concept of the model that's too dangerous to release, it kind of conflates marketing, inference capacity, and then also economic considerations like do you want to externalize your competitive advantage or use it to make yourself better?