Hacker News

points by fraywing 11 hours ago | 0 comments

To me, all signs point to US over investment in hardware capacity to support the "frontier" when in reality the next major breakthroughs are likely radical optimizations that end in increased consumer training and inference efficiency.

I'm not sure how that, combined with open models inching up on frontier intelligence, is compatible with these massive AI IPO valuations?

It seems like closed model AI demand has a lot of contingencies that are ultimately fragile and possibly short sighted.

[–] uptrails 11 hours ago

The article is about a guy leaving Microsoft and the disbanding of an internal team called "AI Frontiers".

[–] fraywing 11 hours ago

Yeah, I'm speaking to "scaling vs research" and where investment is going. Which is relevant to the article. Accelerating scale requires demand, closed frontier demand is what I'm questioning.

[–] joe_the_user 11 hours ago

And gp's comment is relevant to the particular problems the guy (John Langford) cites in his comment about leaving. IE, that research first winds being only about scaling and then winds-up ignored because "just scale" can be an easier answer.

[–] senordevnyc 9 hours ago

Do you think humanity is just going to run out of problems that need the smartest intelligence?

If so, then yeah, increasing efficiency 100x means we hit that point much faster.

If not, then it just means we make improvements 100x faster.

[–] kylestanfield 9 hours ago

Everyone wants radically more efficient AI. That doesn’t mean it’s coming any time soon. And when models are twice as efficient, guess what happens next. We try making one twice as big for the same cost.