And yet, life expectancy about two years more than the national average is rather common in rich regions with selective migration, even in European countries with even access to health care, like France and Spain.
I would also note that my sense is that like the place where the misalignment most lives is the place where you're trying to really push the eyes hard and get them to like do work that's really on the cutting edge of what they are capable of
new laws are like code that is pushed live to production without even being read (let alone tested), often in the face of tremendous opposition, affecting millions of citizens, with minimal monitoring to ensure they’re producing the desired results, an extremely slow customer feedback cycle, and few ways to truly opt out.
I think Google has pretty much gone to on-sites at this point, back to the traditional whiteboard format. And they'll let you code on a laptop if you want to, as well, but it's going to be in person. Somebody's going to be watching you code, and you're probably not going to be able to cheat your way through that.
You have to call like seven APIs to get a VM in the cloud. Create a VM, a network, a storage device connected to a VPC and then attach credentials. Like that's not intent based. I want a VM.
So I'm looking at this like guys the fundamentals of this isn't like everything is going to change because of MCP. What the hell? A whole conference guys? This is just API design.
my sense is that these complex traits have not pushed in one direction because there's advantage there's spectrums where there's advantages to both ends of the spectrum
But I think it's highly likely that if natural selection was pushed pushed any of these traits in more in one direction than it is, the mean would move.
But I'm being obviously overly facetious, but if ultimately part of your scaling is how big is the animal versus how big is its brain, that's most of a T-Rex brain. It's a fraction of the size of a chimp brain, and chimps don't weigh seven tons.
because it's not competing against humans for most of those roles, it would be competing against the other labs, right? And so you'd actually see like the cost pushed down to, you know, a mult a small multiple of whatever the marginal production cost of those tokens is.
Industrial policy was heavily criticized and again, if I talk to my Harvard professors, they’ll be very, very, very skeptical about the role of the state, especially in such a major way. But if you look at the Chinese experience, the evidence for success is all there. The cities that have pushed the most on supporting that particular sector ultimately did the best in terms of production, but also in terms of innovation, measured by patents. It’s all in the data.
So that’s why I think this is a thing that I come back to over and over again, is that you will retain information better if you’re constantly pushing yourself to your limit. If you are feeling like you’re coasting, then you’re actually not learning
That’s a theatrical risk. That is a thing that can really take over how people think about this problem. And there’s a big group of very smart, I think very well-meaning AI safety researchers that got super-hung up on this one problem, I’d argue without much progress, but super-hung up on this one problem. I’m actually happy that they do that, because I think we do need to think about this more. But I think it pushed out of the space of discourse a lot of the other very significant AI- related risks.
An enshittification strategy only succeeds if it is pursued in measured amounts. Even the most locked-in user eventually reaches a breaking-point and walks away, or gets pushed.
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