We need to do something that inflicts pain on nicer, more sympathetic Israelis in Tel Aviv and Haifa, something that makes them want to actually change course and meaningfully alter the situation.
When liability exposure approaches 0—when no one pays the price for unverified failures—verification budgets collapse...Deployers flood the Runaway Risk Zone with unmonitored agents, capturing the gains of automation while socializing catastrophic risks.
Omarchy is not going to adopt a formal Code of Conduct because those turned out to be struggle-session processes in the last turning. But we are going to play nice. We're going to be courteous, professional, and composed in our direct interactions with users, competitors, and even haters. Because that's what's going to pave the path to the win.
LLMs constantly hallucinate and cannot be trusted. I still have to verify and iterate a lot but now I usually focus on architecture and design instead of code style.
I think it is making it more popular. I don't know if it'll make it go mainstream, but it's definitely making it a lot more popular. It's bringing it from maybe like 0.1% to 0.3% which is huge.
I love formal methods, but I think it's a fairly niche tool for most people and I think like property-based testing is in general going to be useful for more people.
I think the case of TLA+ and most, not all, but most formal methods, they shine the most in highly computational domains, where most of the problems are highly technical and not like business embedded.
when you start talking about like most interesting domain problems, you have to pull in so much context that basically even writing what the function is supposed to do becomes a nightmare. The imperative program you write that will get correct 99% of the time is probably good enough to use in almost all cases.
I think a lot of the reason people are skeptical of these is because they've been burned by things like case and UML and all these other miracle solutions that were forced on them by people who wanted them to use it no matter what.
I think the skill nowadays is less about prompt engineering and more about figuring out how do you give Claude a hard task that seems a little bit too hard. And then how do you make it possible for Claude to verify its work along the way? And the verification I think is probably the single most important thing that people do not get right
These developments inform our position that AI systems are now capable of meaningful contributions to formal mathematics, not merely informal problem-solving.
However, these LLM reasoners that generate informal reasoning in natural language are fundamentally limited by the lack of precise, machine-checkable semantics, making their outputs prone to hallucinations [Huang et al., 2025b] and precluding autonomous verification, a prerequisite for tackling open-ended mathematical research.
We argue that the next leap in AI4Math systems requires a decisive shift from predefined problem-solvers to research agents that can address frontier mathematical challenges with rigorous formal mathematical reasoning.
That's a very unique thing that math has that nothing else has where you could press go and then just like just just poor compute at it and like look away for 10 years and then come back and say like what do you have and there's there's going to be something, right?
that's how progress has always been made historically, right? It's not um through centralization. It's through empowering individuals to try things that are somewhat out of the mainstream that other people didn't think were good ideas
To a certain extent, the concerns about cognitive offloading are an example of technological lag, where the mainstream discussion of AI and its impact is still framed in terms of the first-generation chatbots.
But a proof can reason about potentially infinite state spaces. So, it can tell you things about like every possible thing that could possibly happen in the entire universe.
One is that the LLMs are getting increasingly good at writing these proofs. And if we don't have to write the proof by hand as humans, it just becomes feasible to do them in situations where previously it would have not been economical.
But also LLMs increase the need for these formal proofs because, you know, we're live coding a bunch of stuff. If we have to manually review all of that code, then that will become the bottleneck.
And so you just have to first realize that chips exist in China. They manufacture 60% of the world's mainstream chips, maybe more. It's a very large industry for them. They have some of the world's greatest computer scientists.
So certainly one thing that a lot of them seem to be bottlenecked on is now having interesting ideas and in particular having interesting design ideas.
Abraham Lincoln surrounded himself with his opponents, gradually turning them into admirers and influential advisors. Lincoln’s approach to leadership offers lessons for anyone looking to tap into the wisdom of others, with or without formal authority.
The overall workflow is intuitive, especially for those new to formal evaluation processes. The UI guides you through creating datasets, running experiments, and annotating results.
so the mainstream view would say, well, China has cheaper labor, which is no longer true, uh, say compared to Mexico, and it's got lower environmental regulations, uh, which is true, and that it is more businessfriendly, which is absolutely crazy.
He offers a unique form of grounding on political, sports and other issues, and a way of bridging my kinds of ideas into mainstream discourse. I almost never regret reading.
I don’t believe it’s providing a kind of formal explanation of the different positions. It’s just saying which position is better or not that you can intuit as a human being, and then from that, we humans can construct a theory of the matter.
The success of LLMs can thus be seen as vindicating semantic inferentialism against earlier, symbolic approaches to AI that tried and failed to explicate the rules of ordinary language using formal logic.
However, luasec does not perform any certificate verification by default! This makes its out-of-the-box behavior very unsafe, and I have to recommend against using it for anything.
Despite misleading statements by mainstream education economists, college attendance in particular is not a good career investment for most of the population.
And then we end up at the bottom of that with this idea of everyday I wake up and I check my phone and I'm like, oh, it's going to be 60 degrees out. Great. And we start thinking that 60 degrees is more real than hot and cold. That thermodynamics, the whole formal structure of thermodynamics is more real than the basic experience of hot and cold that it came from.
Another manifestation of the lack of sufficiently abstract, formal reasoning in LLMs is the way in which performance often fall apart as problems are made bigger.
So having an independently owned powerful platform is very important for truth, for free speech, for hearing the other side of the story, for counterbalancing the power of the government.
All the evidence is that Hispanics are integrating into the American mainstream more quickly and more effectively than the European immigrant groups that came starting around 1835.
the most likely identifiable scenario by which fertility will rise again is via the growth of currently-small insular high-fertility subgroups like the Amish and Orthodox Jews
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