AlphaFold developers win $3M breakthrough prize
nature.com
nature.com
What is important about their discovery is that we now know for certain that a judicious combination of expensive-to-obtain structure information, and easy-to-obtain protein sequence relationships can be used to build a generalized protein structure predictor (it can predict structures with no prior example of a fold, although there are limits)... and you don't have solve the general folding problem to do it. You do not need to know the path, to get to the destination!
Many of us in the field expected this to be true but there wasn't any really good example to point to that was widely accepted by the community. And in the ~year or so since this was demonstrated, the community has already found a wide range of uses for this that have validated the structure predictions and demonstrated their utility- using open codes and models.
AlphaFold doesn't solve folding. It makes metaheuristic guesses without writing a bunch of quantum chemistry, statistical physics, thermodyanamics, and topology maths / algorithms.
I don't mean to downplay AlphaFold, but we haven't solved protein folding yet. This press is really getting ahead of itself.
You won't have a perfect answer unless you want to predict its shape in a vacuum, which wouldn't be very useful either way. Having it "close enough" is already extremely useful. There are definitely edge cases where it gets it wrong, but there are always edge cases in ML. More data = better results with the same architecture.
Tons of things that won Nobel prizes weren't 100% accurate, it's not a prize for solving science, rather a prize for advancing science.
My wife is a neurobiologist and the impact of this advance is groundbreaking for her work.
Many engineers will say it doesn't code. It just regurgitates and remixes the data it was trained on. It just makes "meta-heuristic guesses."
But anyone taking an honest and objective view of it can see that Copilot does add value. It's no substitute for a real, human, engineer, but it clearly adds value.
I don't think AlphaFold would get to this level of funding, resource commitment, etc. if it was adding 0 value.
Being a domain expert, I'm curious what value, if any, you think a large transformer model could add to the domain of protein folding. Is it really zero value, in your view?
They didn't say that it added zero value, that's entirely you. They said that it doesn't solve the problem on its' own, which is true.
GitHub ripping off everyone’s code to build copilot has caused a small (not as big as it should have been imho) exodus of open source projects to Gitlab and others.
I still don’t see how it’s a good idea to import unknown code with unknown licenses into your project, but apparently if copilot does it it’s okay.
> Author Pamela McCorduck writes: "It's part of the history of the field of artificial intelligence that every time somebody figured out how to make a computer do something—play good checkers, solve simple but relatively informal problems—there was a chorus of critics to say, 'that's not thinking'." Researcher Rodney Brooks complains: "Every time we figure out a piece of it, it stops being magical; we say, 'Oh, that's just a computation.'"
Solving physics isn't a soft thing like making pretty art.
I'm firmly in the "AI/ML will eat the world" camp, but the praises being foisted upon AlphaFold are borderline damaging to the real field and its practice.
You can't throw AlphaFold at pharmaceutical problems and call it a day. This press feels like a "mission accomplished" victory lap when it's very clear we're only just getting started.
I personally know several people that do research that have unlocked new possibilities through this tool. My wife is a neuroscientist and she's used this tool a few times for reasons that are above my head (even with a Msc in Microbiology). This type of work used to take a PhD student 4 years or more to do a single relatively simple protein. Getting answers within a few seconds is revolutionary.
https://www.chemistryworld.com/opinion/why-alphafold-wont-re...
It does make sense though, seeing as the scientific awards are generally awarded based on actual breakthroughs, whereas the political ones are, let's say, fuzzier.
It's a bit more complicated than that. The committees for Physics and Chemistry (and Economics) are colocated at the Royal Swedish Academy of Sciences. Medicine is elsewhere, as is Literature. Physics, Chemistry, Medicine, and Literature work together for final approval. Peace is completely on its own.
Funny things is how the general scientific community (including nature) defines 'impact'. I somehow still strangley trust the Nobel committee to take a different approach here. Was curious and found this interesting collection of references: https://www.researchgate.net/project/Enacting-Excellency-Awa... .
"We confirm extensive promiscuity, but find that the average area under the receiver operating characteristic curve (auROC) is 0.48, indicating weak model performance."
Derek Lowe had a post about this earlier this month [1] (which includes important qualifications I failed to omit).
[1] "Benchmarking AlphaFold-enabled molecular docking predictions for antibiotic discovery", Molecular Systems Biology 2022 18:e11081 https://doi.org/10.15252/msb.202211081
[2] "Not AlphaFold's Fault", September 7 2022, https://www.science.org/content/blog-post/not-alphafold-s-fa...
What would be more interesting is if we did a whole bunch of crystal or cryo-EM structures far from what we've previously determined and demonstrate whether alphafold could make out-of-class predictions for them.
By contrast, the breakthrough prize in physics was awarded to the entire event horizon telescope collaboration for their image of the supermassive black hole.
I would have assumed that the prize for alphafold would also been awarded to the whole team.
Kind of how most medical advancements come out of the US, which makes up only <4.25% of world population.
I know orgs dont scale like that and there are hits to productivity with orgs getting less lean but still.
The article mentions:
> So far, the data have been harnessed to tackle problems ranging from antibiotic resistance to crop resilience.
Is any of them is about to be used in our daily life and solve a major problem?
How do you know it's not being useful in research already? Biology is a slow field, you won't see papers mentioning it for months if not years. If I know one person team that uses it, there must be plenty.
Problem is, our major problems are mostly social. Biologists will sell you the story that this is a breakthrough that will empower us to improve crop yield and solve world hunger. But we all know we could already have solved it. Turns out the US rather spend billions to build another aircraft carrier instead of develop Africa's farm machinery industry. It is sad. But it is the world.
I wonder if relying on a tool that doesn't 100% accurately represent reality could have a negative effect on future research
It could be argued that this is the case of every scientific tool ever used.
Honestly the only field that has a P value that comes close to 100% is physics. Even medicine which is far more rigorous than most fields fails quite often in phase 3 trials after having vetted it in phase 2.
- for the first time, there isn't mountains and mountains of trolling in an Alphafold thread and the comments are _very_ quiet
- the only reason why is a new account tried doing the trolling
- comment is instadead without any manual flagging
- but, people are afraid to post given the one try in 3 hours is dead
One might research, work hard and solve a problem that might change the course of development of a major field and win a recognition by $3M while someone which fills few numbers on a lottery ticket may earn 1-2 folds more.
I wish the system would give this kind of efforts and stories a bigger exposure, recognition and compensation.
Edit: The idea was about the prize amount, not those specific people. It wasn't the best choice, but the idea was that even as a statement, prizes for scientific achievements should be higher so they will be an extreme to all people to recognize and strive for. I guess one could find a better analogy than what I had in mind.
$3M isn't enough in our days to recognize remarkable work in my opinion. Yes, one of them made a lot of money, but is it true for all the past winners of this prize?
I can say something about the effect I want to achieve with the money: recognition and publicity. So the amount of money should make them on front page of many news papers and such. Now from data it might interesting to get the right amount.
I just want the people who make such achievements to be recognized by younger generation.
I think we should celebrate scientific achievements as a community. Because the failures are as important as the successes. We shouldn't idolize individuals imho. That is toxic.
https://www.mic.com/articles/79039/the-untold-story-of-alice...
And let's not talk about the Sacklers
If anything, the lesson is that if you care about making lots of money from your research (not everybody does), start a company. And it's easier for academics to start companies today than in any other era.
My point was that such a prize should be backed with more money. Even for the sake of a statement what we consider to be important.
So the emphasize was about the enormous ratio between the two and not about lottery being wrong (Moreover it pays for itself).