The AlphaFold paper has countless authors, many researchers and company resources underlying it. Hassabis’ contribution is management of resources and entrepreneurship, not the actual science. There are hundreds of thousands of scientists out there doing deep technical work, and they aren’t recognized.
I think we might be the end of it, as the emphasis shifts to commercialization and product development.
These AI demonstrations require so many GPUs, specialized hardware and data that nobody has but the biggest players. Moreover, they are engineering work, not really scientistic (putting together a lot of hacks and tweaks). Meanwhile, the person who led the transformer paper (a key ingredient in LLMs) hasn’t been recognized.
This will incentivize scientists to focus on management of other researchers who will manage other researchers who will produce the technical inventions. The same issue arises with citations and indices, and the general reward structure in academia.
The signal these AI events convey to me: You better focus on practical stuff, and you better move on in the management ladder.
The Nobel prize cannot go to a team so they have to pick individuals. This is true for many (most?) nobel prize awards. Consider for example the discovery of gravity waves - the team that built and operated LIGO was huge, but they have to pick. This has commonly been the case since the inception of the prizes - the professor gets the prize, the PhD students and postdocs don't usually. Not saying this is right, but it's the way it is.
For gravitational waves discovery, Nobel prize went to the designers of the LIGO which was done long before we actually built it. The example that will fit more your idea would be Carlo Rubbia who got the award in 1984 for leading the CERN team who discovered the W and Z bosons. He did not have any contributions than leading the experiment that did it [1]. It is not like he designed or proposed the way we used to detect them. And the Nobel prize for higgs discovery went to theorists who proposed and predict it not the experimental physicists (thousands) who discovered it in 2012.
So can we expect that Sam Altman will be honored with Nobel prize 2025? After all physics prize went to AI researchers this year, and chemistry prize went to an organizational head.
The Nobel prize's prestige comes from its history, not from the size of the monetary award.
For an example, the Millennium Technology Prize is awarded every two years and the prize money is slightly higher than the Nobel prize (1M EUR vs 0.94M EUR). The achievements it's been awarded for tend to be much more practical, immediate and understandable than the Nobel prize achievements. The next one should be awarded in a couple of weeks.
And when that happens, it'll get 1/10th the publicity a Nobel prize gets, because the Nobel prize is older than any living human and has been accumulating prestige all that time, while the Millennium prize is only 20 years old.
You're really conflating things. Altman is no Hassabis.
Just because there is a ton of hype from OpenAI doesn't detract from what DeepMind has done. AlphaGo anybody?
Are we really already forgetting what a monumental problem protein folding was, decades of research, and AlphaFold came in and revolutionized it overnight.
We are pretty jaded these days when miracles are happening all the time and people are like "yeah, but he's just a manager 'now', what have they done for me in the last few days".
I am missing context here and would love to know more.
Say I know about ATP Synthase and how the proteins/molecules involved there interact to make a sort of motor.
How does AlphaFold help us understand that or more complicated systems?
Are proteins quite often dispersed and unique, finding each other to interact with? Or like ATP Synthase are they more of a specific blueprint which tends to arrange in the same way but in different forms?
In other words:
Situation 1) Are there many ATP synthase type situations we find too complex to understand - regular patterns and regular co-occurences of proteins but we don't understand them?
Situation 2) Or is most of the use of Protein situational and one-off? We see proteins only once or twice, very complicated ones, yet they do useful things?
I struggle to situate the problem of Unknown proteins without knowing which of the above two is true (and why?)
The Nobel prize isn't awarded for a paper. Even if (and that's a large if) all of these contributed equally to the results in the paper, some obviously did more than others to prepare the ground for that study.
I did raise an eyebrow at it too, but I doubt his contribution was entirely “management of resources”.
I think one must also give him the credit for the vision, risk taking and drive to apply the resources at his disposal, and RL, to these particular problems.
Without that push this research would never have been done, but there may have been many fungible people willing to iron out the details (and, to be fair, contribute some important ideas along the way).
I’m not a proponent of the “great man” theory of history, but based on the above I can see that this could be fair (although I have no way of telling if internally this is actually how it played out).
Agree. Hassabis is more than a manager. He did start DeepMind with just a few people and was a big part of the brains behind it.
Now that it has grown he might be doing more management. But the groundwork that went into AlphaFold was built on all the earlier Alphaxxx things they have built, and he contributed.
It isn't like other big tech managers that just got some new thing dumped in their lap. He did start off building this.
> The AlphaFold paper has countless authors, many researchers and company resources underlying it. Hassabis’ contribution is management of resources and entrepreneurship, not the actual science.
That's usually how you get a Nobel prize in science. You become an accomplished scientist, and eventually you lead a big lab/department/project and with a massive massiv you work on projects where there are big discoveries. These discoveries aren't possible to attribute to individuals. If you look back through history and try to find how many "Boss professor leading massive team/project" vs. how many "Einstein type making big discovery in their own head" I think you'll find that the former is a lot more common.
> This will incentivize scientists to focus on management of other researchers who will manage other researchers who will produce the technical inventions.
I don't think the Nobel prize is a large driver of science. It's a celebration and a way to put a spotlight on something and someone. But I doubt many people choose careers or projects based on "this might get us the prize..."
> You become an accomplished scientist, and eventually you lead a big lab/department/project and with a massive massiv you work on projects where there are big discoveries.
That's a very recent thing. Up to the 90s, the Nobel committee refused to even recognize it. They just started to award those prizes at the 21 century, and on most fields they never became the majority.
> These AI demonstrations require so many GPUs, specialized hardware and data that nobody has but the biggest players. Moreover, they are engineering work, not really scientistic
The Nobel prize is aimed at the general public. It has a kind of late 19th century progressive humanistic ethos. It's science outreach. This way, at least once a year, the everyday layperson hears about scientific discoveries.
The Nobel isn't a vehicle to recognize hundreds of thousands of deeply technical scientific researchers. How could it be? They have to pick a symbolic figurehead to represent a breakthrough.
They could also simply give it to "DeepMind" similar to how they give the peace prize to orgs sometimes, or how the Time Person of the Year is sometimes something abstract as well (like the cutesy "You" of 2006). But it would be silly. Just deal with it, we can't "recognize" hundreds of thousands, and we want to see a personal face, not a logo of a company getting the award. That's how we are, better learn to deal with it.
> The Nobel prize is aimed at the general public...
Which is okay. The Nobel prize is okay.
> This way, at least once a year, the everyday layperson hears about scientific discoveries.
Spot on.
The problem we have is that the everyday layperson hears very little about scientific discoveries. The scientists themselves, one in a million of them, can get a Nobel prize. The rest, if they are lucky, get a somewhat okay salary. Sometimes better than that of a software engineer. Almost always worse working hours.
But I suppose it's all for the best. Imagine a world where a good scientist, one that knows everything about biology and protein folding, gets to avoid cancer and even aging, while the everyday layperson can only go to the doctor...
I think we might be the end of it, as the emphasis shifts to commercialization and product development.
These AI demonstrations require so many GPUs, specialized hardware and data that nobody has but the biggest players. Moreover, they are engineering work, not really scientistic (putting together a lot of hacks and tweaks). Meanwhile, the person who led the transformer paper (a key ingredient in LLMs) hasn’t been recognized.
This will incentivize scientists to focus on management of other researchers who will manage other researchers who will produce the technical inventions. The same issue arises with citations and indices, and the general reward structure in academia.
The signal these AI events convey to me: You better focus on practical stuff, and you better move on in the management ladder.