Recent submissions

Comment · 4 days ago
What did you select for data controls?
Comment · 4 days ago
I agree that you can build a facility to put energy on the grid in under a decade, but the probability that it works is going to be tiny, and anyone giving you the billion or so it would take would be disappointed to say the least.

Therefore, most credible folks are talking a 2-3 facility staged approach. And probably 5 years per facility to build, and 5 years per to test.

Also, remember that even with huge cash pools, you have supply chain problems. Some of the nonlinear optics takes a fixed amount of time to fabricate.

Comment · 4 days ago
Respectfully, finding out how scientific computation is used in fusion research is a Google click away. And yes, we can simulate these conditions.

Let's put it this way - a first year graduate student can ignite a fusion target in simulations. It took thousands of scientists the better part of three decades to do that in experiments. I think agents could do the former really efficiently and at scale, but I'm skeptical that agents could do the latter. Oh, and btw, fusion simulations of the kind you're talking are in exa-zettaflop territory ;)

Comment · 4 days ago
I guess I'd say, let's have a swarm of agents build a metro line first and see how well that goes. Obviously, given that we have embodied intelligence (sometimes) that's capable of doing this work, it would be silly of me to say that it's impossible for it to happen in silicon. But given where the SOTA is right now I'm skeptical of this being true in the near future. But hey! If you'd asked me the same question about GPT in 2019 I'd have said I would be skeptical there too. So who knows.
Comment · 5 days ago
I think you should realize that we already do that. In fact, that's one of the reasons computers were invented in the first place! It turns out that science is about unknown unknowns, and by definition simulations can't answer that.

But agents are really useful for doing some of the really boring stuff, like convergence checks or setting up meshes or whatever.

Comment · 5 days ago
Nah I agree with you. Not this century, not this planet. Fusion rockets are really efficient, though ;)

I just find it to be an interesting problem! My hope is it happens before I die. My rule of thumb is anyone who says energy on the grid in < 10 years is a blatant liar.

Comment · 5 days ago
Nah. And I have an enterprise plan, so I'm /relatively/ confident that they aren't going to do that.
Comment · 5 days ago
Hah. Fusion scammers are a dime a dozen. Unlike SaaS apps or finance, though, you can't sweet talk a neutron into existence, so they fizzle out pretty fast. I'm more worried about fusion dying because nobody comes up with a good enough idea than someone stealing my ideas.
Comment · 5 days ago
Enough! I think it's a reasonably fair test of the models. Let's put it this way, I use the same process to resolve problems outside my peak expertise, and I find it works well.

I think the solution is easy enough that any competent colleague would come up with it. Some variant on it has probably even been published (hence why I'm not chomping at the bit to publish). I think it comes down to the models being extremely spiky, and the problems they're trying to solve being easily verifiable in code.

Comment · 5 days ago
I'll give you an example from my field (nuclear fusion). I have a small team working on an idea which I think would really advance the field. Our initial concept paper was published in 2019. Progress on it has been slow because we don't have enough manufacturing capabilities, budget, or time on the facility. Will AI solve that? Don't get me wrong, I'm pretty bullish on AI, and it's been phenomenally useful so far (I definitely feel like a 10x physicist in the last 6 months), but I don't see a swarm of agents putting fusion energy on the grid tomorrow.

Also, fwiw I have a personal test problem I give to every frontier model on release, which is to ask it to final a realatively obvious solution (in hindsight) to a minorly important open problem in my field. I know the answer, but havent gotten around to writing it up yet (it's really not that important). Every frontier model (so far) just regurgitates existing solutions.

Comment · 6 days ago
It's definitely not the first. I'm not convinced it's the second, either. I'm pretty sure if you Google for HOMM3 strategy, there should be enough hits! I guess what I'm trying to say is that you shouldn't give up :)

Also the speed is painful in the extreme. It's definitely not yet at the point where I can just play a game. But maybe if they get Astra on those cerebras chips and get the price down...

Comment · 6 days ago
I mean, it's the pareto principle, right? 80% of the applications require 20% of the intelligence. If I can drop in something without needing to create high quality training data that's good enough, that's great! Skin cancer probably isn't one of those applications.
Comment · 6 days ago
I'm surprised that it's not very good. I'm working on an MCP for a Foss civ 5 reimplementation (unciv) and I find that 5.6 Luna is better than the built in AI, and costs about $2-4/player/game at API prices. I suspect Astra would blow humans out of the water, but I don't have $1k/player/game to spend on that lol
Comment · 7 days ago
People used to complain about back of the napkin posts because they signaled low effort. The same is true about LLM blogs. A back of the napkin blog signals more effort than slop.
Comment · 7 days ago
Main python should move faster on standardizing fixes to its abysmal package distribution scheme, then. Nobody is trying to replace cargo.

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