I think it's fair to say that it (where "it" is defined as "DeepMind's contribution to the protein folding problem") hasn't yet given us massive improvements to the human condition. It might, and in fact I think it probably will. But it hasn't yet.
When the biggest criticism of deep mind is it hasn't literally saved the world yet, i think that is pretty telling about how impressive it really is.
That isn't the criticism at all. The criticism is that it hasn't done ANYTHING, and has probably been a net negative since human brainpower and energy costs are being spent on (so far) useless technology for 5 years. It's not that it hasn't saved the world, it's that it's worse than useless.
Lee Sedol retired in 2019 following his 2016 defeat by Alpha Go in a 5 round match. At the start of the match most people were confident an AI could never defeat a top human player at Go. By the end of the match, watching (arguable) world champ Sedol suffer lost game after lost game the story had changed dramatically. Sedol fans were championing his single win against the unstoppable AI. We (hacker news) discussed Le…
This is correct history, but not the point TaupeRanger was trying to make (I believe). I think their assertion is that the release of AlphaGo has actually made human Go players worse at the game, contrasted with chess where most agree that the introduction of Superhuman chess engines has elevated the (human) state of play. But I don't think there is actually much evidence for that. I'm sure the introduction of AlphaG…
I don't think that AlphaGo has made players worse. My point is that there's no evidence that anything USEFUL or IMPORTANT has come from a system that has gotten so much hype (and cost ungodly amounts of money). If players aren't getting better (there's no evidence they are) or are quitting the game after playing, it's simply a net negative, along with DeepMind's other ventures.
That claim is often made, and never substantiated.
It's made here in response to a claim that Go players are made worse by practicing with AlphaGo, which is also unsubstantiated.
Wrong. The claim was never made that players got worse, only that their ratings dropped, which is empirically true. After playing AlphaGo, for example, Ke Jie dropped in the rankings and was quickly taken out of 1st place overall. The overall point though, is that AlphaGo produced nothing of value for humans, since there's also no evidence that players have improved since AlphaGo's creation. Factoring in the immense cost and human brainpower wasted on creating a superhuman perfect-information-game-playing program, and it's easily a net negative for humanity.
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 certain…
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"?
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.
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.
It's made here in response to a claim that Go players are made worse by practicing with AlphaGo, which is also unsubstantiated.
Wrong. The claim was never made that players got worse, only that their ratings dropped, which is empirically true. After playing AlphaGo, for example, Ke Jie dropped in the rankings and was quickly taken out of 1st place overall. The overall point though, is that AlphaGo produced nothing of value for humans, since there's also no evidence that players have improved since AlphaGo's creation. Factoring in the immense…
"there's also no evidence that players have improved since AlphaGo's creation"
Read this for example. The author is Korean pro.
"The upside is that we sometimes see a player who was somewhat past his prime suddenly climb back to the top, having trained with AI more intensely. There are a growing number of young and new pros who demonstrate surprising strength. This change gives hope to all pros who dream to become number one, and also makes competitions more interesting to fans as well." [0]
> proves the point that optimal programs are very inhuman Maybe there should be an AI that produces optimally-readable/understandable programs? That's what I would want if I was adding the output to a codebase.
Optimal routing of delivery vehicles for UPS/Fedex etc is also non-compressible to the drivers, so the planners often intentionally generate suboptimal solutions. A suboptimal implemented solution is a better than an optimal not implemented one.
> Optimal routing of delivery vehicles for UPS/Fedex etc is also non-compressible to the drivers, so the planners often intentionally generate suboptimal solutions.
Really? That's the first time I've heard that (and I've worked on vehicle routing).
Normally, the driver would get the next address they have to visit and would use satnav to work out how to get there. They don't need to "comprehend" the overall route.
This is correct history, but not the point TaupeRanger was trying to make (I believe). I think their assertion is that the release of AlphaGo has actually made human Go players worse at the game, contrasted with chess where most agree that the introduction of Superhuman chess engines has elevated the (human) state of play. But I don't think there is actually much evidence for that. I'm sure the introduction of AlphaG…
I don't think that AlphaGo has made players worse. My point is that there's no evidence that anything USEFUL or IMPORTANT has come from a system that has gotten so much hype (and cost ungodly amounts of money). If players aren't getting better (there's no evidence they are) or are quitting the game after playing, it's simply a net negative, along with DeepMind's other ventures.
Sorry, but this is just incorrect. Go players have gotten stronger over time overall [0][1], and AI discovered many new ideas that all top pros have incorporated into their game-play (idk how to give a source for this, it's just very well known in the Go community that the style of play changed drastically in response to AlphaGo, and absolutely everyone trains with AI these days).