I thought the same thing - it smacks of desperation at the moment, any tiny win is exaggerated .
It’s not hard to see why, with the emergence (ha) of OpenAI, Midjourney and all of this generative modelling, what has DeepMind done? I imagine the execs at Google are asking them some very probing questions on their mediocre performance over the last 5 years.
Deepmind has done quite an enormous amount actually, but it's been in academia not in the commercial product sphere.
Just because something is not on a little web page available to average Joe's does not mean there isn't value in it.
For example, Deepmind's work towards estimating quantum properties of materials via density functional theory may not be the best toy for your grandma to play around with, but it certainly does move academia way further ahead of where it once was.
I run atomictessellator.com and have been working on many different implementations of density functional theory for the last 10 years, as well as working closely with professors at Stanford university and Oxford university of using advanced, non-static geometry data structure for density functional theory for multiple years, this is a subject I know a LOT about, so I’m glad you brought it up.
Deep minds work on Density functional theory was complete rubbish, and everyone in computational chemistry knows it. They simply modelled static geometry and overfit their data, we wanted this methodology to work, computing DFT is expensive, and we did multiple months of rigorous work and the reality of the situation is that a bunch of machine learning engineers with a glancing amount of chemistry knowledge, made approximations that were way too naive, and announced it as a huge success in their typical fashion.
What they then count on is people not having enough knowledge of DFT / Quantum property prediction to query their work and make claims like “it certainly does move academia way further ahead” - which is total rubbish. In what way? Why aren’t these models being used in ab initio simulators now? The answer to that is simple: they are not revolutionary, in fact they are not even useful.
Yes, people often mention the number scientific citations that mention AlphaFold as "proof" of its value. Unfortunately, padding researcher CVs is not a net positive for humanity, and so "moving academia further ahead" (by what metric?) is not necessarily a desirable or worthwhile goal if your definition of "ahead" is sufficiently warped as such. Perhaps, one day, the first real human being will be helped by medicine that couldn't have been found/created without AlphaFold. Unless a scientific endeavor is actually useful to humanity, who cares if it "moves ahead"?
They solved an open challenge problem, Protein Structure Prediction, with AlphaFold, which has been nothing short of revolutionary in the structural biology and biochemistry fields. I do scientific research in these fields and the capabilities AlphaFold provides are used now everywhere.
Yes, many research papers have been written, and many CVs have added lines which include the word "AlphaFold". But has the human condition been improved one iota from the "discovery"? Has anything real actually happened? Not at all. Only "maybes" and "possibilities" after more than 5 years of work. "Revolutionary" at padding researcher CVs indeed.
Man, with al respect why your “hate” with the good guys working at DeepMind? Everybody loves and respect Demis Hassabis, he is truly a genius. He really wants the best for the world/humanity and that takes a ton of time, so let’s wait and see.
It’s not hard to see why, with the emergence (ha) of OpenAI, Midjourney and all of this generative modelling, what has DeepMind done? I imagine the execs at Google are asking them some very probing questions on their mediocre performance over the last 5 years.