Late to this post, but my impression was that later models would be more efficient per task? Wouldn't they save compute released fable 5, maybe capping the effort, if it is actually a better model?
Lol I feel like no one has any attention span here. Tech shit is expensive in the beginning when it's new. It gets cheaper with time. This is a tech forum, don't we know this? Of course people overreact in both directions on both sides of the issue. It's a very fast technology, wait for things to settle before making grand declarations.
I mean, didn't we give the government and the public long enough to prove they could provide abundant, cheap nuclear? They were so closed in the 60/70s and have since failed miserably and everyone has suffered for it. Cheap, abundant energy is good for humanity. If a private company accelerates it, I'm here for it.
Yes, I'm also for solar, and wind, and geothermal, and nat gas, and way out there fusion. It's hard to exaggerate how much cheap, abundant, reliable energy helps civilization.
That's the permit/approval for the pilot/test, right? There are about a million approvals they need to get through. Are they using the DoE fast tracking method?
Most mathematicians don't take pride in their results having no applications. That's just not true. Maybe some quirky pure logicians or something. But otherwise 90%+* of mathematicians I know would be at least satisfied if not thrilled for their work to be used by others.
Wouldn't that just accelerate collapse? How much do you trust the outputs of the llm to provide trustworthy and valuable new information? I mean I understand distillation works. But that's much more structured and thoughtful than my sessions at least.
More predictive power is always a good goal, full stop. This is orthogonal to whether the model producing prediction helps with "understanding" directly. Predictability encodes understanding in a strict information theoretic sense, regardless of our ability as humans to access that understanding.
Per frontier token. You're not calculating the cost of a fixed quality asset here. Old hw running non-frontier models will be very valuable. In fact, we have two direct examples: older server gpus actually appreciating and the very obvious fact that not everyone always use MAX FULL EFFORT BEST MODEL no matter what.
Yeah. It's called brain drain. Talent has options. It weighs pros and cons. When the relative attraction of a country and thus institutions within it drops, they choose to go there less.
To be clear, I would still choose to do my PhD in the US. But this is a marginal effect, people weigh many factors. If you think, for example, you're going to be constantly worried about visa issues, you may just choose Europe or China over the US.