I actually think the opposite, which is that there are going to be many more software engineers than even the rosiest current predictions, and that software engineers will take over these other jobs: legal, marketing, accounting.
What we do know is that the actual Elon Musk that we have to live with on this here timeline was flagrantly incompetent in government, contrary to Noah's previous predictions.
if you look at the nuclear industry outside of Valor, it's mostly a modeling and simulation uh industry. Like when you think of a nuclear company, right, there's like nuclear companies out there that everyone knows the name of. And you kind of look under the cover. It's actually a modeling and simulation company, right? They produce um very very precise what we call paper reactors which have really good predictions of how a theoretical thing might behave.
And if you look at Ricardo's predictions, they're actually right. If you look at all those jobs that made money in Ricardo's time, they got automated. So, if I was David Ricardo and I woke up and somebody told me all those jobs did get automated. And you ask me David Ricardo, like what do you think the prime age employment rate is in 2026? I think he would be surprised if you told him it was the highest it's ever been other than 2000.
I go to myself, "Well, yeah, but what do you mean by code?" Because that kind of implies nobody's writing anything. Well, we're at least doing some prompting. We're having some interaction with the genie. What's that going to be if it's not some form of code in some way? I think the nature of what code is is going to be quite possibly for a very radically different. But I think there is still a need to produce it and be able to interact with it in some way.
I think the trillions of dollars a year market, maybe all of the national security implications and the safety implications that I wrote about in adolescence of technology can happen without it, but I I I also think we, and I imagine others, are working on it. And I think there's a good chance that that, you know, that we get there within the next year or two.
So like they don't have enough intelligence. They're not multimodal enough. They can't do computer use and all this kind of stuff. And they don't do a lot of things. You know, they don't have continual learning. You can't just tell them something and they'll remember it. And they're just cognitively lacking. And it's just not working. And I just think that it will take about a decade to work through all of those issues.
He takes a very proto-rationalist, practical approach to this, that I very much appreciate, complete with yearly predictions. The writing is consistently enjoyable and clear.
Until we develop better ways to bridge this gap - aligning what analysts understand with what is formally forecast - we'll continue to see the same pattern: reality consistently outperforming conservative predictions.
I'm usually reluctant to make predictions about technology, but I feel fairly confident about this one: in a couple decades there won't be many people who can write.
I’ve read this book three times since 1999, and gifted it many times to others. It’s changed the way I look at buildings. I read it again now because I’m building a new house. Its main idea is that all buildings are predictions, and all predictions are wrong, so design to make them easy to change. I think of it metaphorically in life: assuming my predictions about what I want will probably be w…
Despite these advances, contemporary physical and evolutionary-history-based approaches produce predictions that are far short of experimental accuracy in the majority of cases in which a close homologue has not been solved experimentally and this has limited their utility for many biological applications.
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