Great blogpost by Ruiqi (and other GDM ex-colleagues), clearly explaining the the connection between flow matching and diffusion models. Super happy they took the time to explain this topic, there's confusion on this topic, I think many will find this quite valuable!
To be clear, bitemark evidence is junk science. There has never been any scientific research to support the idea that bites on human skin can be matched to the teeth of one person, to the exclusion of everyone else.
Take Eroom’s Law: the number of new drugs approved per dollar of R&D has fallen for decades, even as our scientific tools have grown vastly more powerful, the exact opposite of what the existence of more raw capability would predict.
I think anytime a new technology comes along, especially one that's as transformative as GenAI, you go through a storming phase before you go through the forming phase of things. And I think we are in the middle of that right now.
And then I also think um you know right now for matching it's like everything's done at literally the last minute. It's like someone dies, an organ comes available and like you're just kind of calling around trying to find like what patient is available to get this organ and you don't have that much time to make the optimal match, right?
By contrast, AI is increasingly matching the general cognitive profile of humans, which means it will also be good at the new jobs that would ordinarily be created in response to the old ones being automated.
I've worked a lot of companies right but I'm wrong all the time and I think consumer behavior can be very fickle and especially when you work at a company you become a power user naturally. So sometimes you you may forget like what the actual user experience is for a brand new user.
But then I think that there’s a confusion that dead stars, these very, very massive stars that die, are synonymous with the phenomenon of black hole. And it’s really not the case. Black holes are more general and more fundamental than just the death state of a star.
And then you can go to chemical system. I don’t think that’s good either. I think there’s a confusion because life emerges in chemistry that life is chemical. I don’t think life is chemical. I think life emerges in chemistry because chemistry is the first thing the universe builds where it cannot exhaust all the possibilities, because the combinatorial space of chemistry is too large.
The cost to discover and develop a drug today is orders of magnitude higher than in the 1950s. Despite this, the probability that a drug entering clinical trials will eventually reach the market has hardly improved in the intervening years.
Whether one does find a good spouse or not depends more on one's orientation towards actually building relationships, and whether they can identify non-trivial traits in a partner that would contribute to that.
Here we show that scaling up language models greatly improves task-agnostic, few-shot performance, sometimes even reaching competitiveness with prior state-of-the-art fine-tuning approaches.
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