The Nobel Prize committee is an achievement of the highest order, awarding physicists, chemists, physiologists, medical practitioners, writers, pacifists and economists perhaps the greatest honor in their respective fields. In this week’s Five-Minute Friday, Jon Krohn discusses how two AI pioneers came to win prizes in chemistry and physics.
This year’s Nobel Prize committee awarded its prize in chemistry to Demis Hassabis and David Baker, and its prize in physics to Geoffrey Hinton and John Hopfield. Hassabis and Hinton will be known names to the data science and AI community, with the latter more popularly known as the “godfather of AI”-turned AI skeptic. Sir Demis Hassabis was awarded the Nobel in chemistry for his contributions to AlphaFold, the Google DeepMind AI system that has surpassed human capacity for predicting protein structures, marking a huge leap forward in understanding and treating genetic diseases, among others.
We might not immediately connect Geoffrey Hinton with the field of physics. And yet his contributions, together with physicist John Hopfield, engage with biophysics, where Hinton helped devise techniques that enabled artificial neural networks to become deep neural networks, carrying out deep learning techniques.
These appointments show exactly how much of an impact AI has been making worldwide for the general benefit of humanity and keep us hopeful for the future.
ITEMS MENTIONED IN THIS PODCAST:
- Turing Award
- “Godfathers of AI’ honored with Turing Award, the Nobel Prize of computing”
- “Nobel winner Geoffrey Hinton is the ‘godfather of AI’. Here’s an offer he shouldn’t refuse…”
- “Demis Hassabis: from video game designer to Nobel prize winner”
- AlphaFold
- SDS 748: The Five Levels of AGI
- SDS 820: OpenAI’s o1 “Strawberry” Models
DID YOU ENJOY THE PODCAST?
- Do you have strong feelings about who wins the Nobel prize each year, or do you feel other awards grab your attention more?
- Download The Transcript
Podcast Transcript
(00:05):
This is Episode #830 on the A.I. Nobel Prizes.
(00:19):
Welcome back to The Super Data Science Podcast. I’m your host, Jon Krohn. Let’s start off with two Apple Podcast reviews that came in recently. They’re both five-star reviews Thank you very much. The first is from Jonathan Bown, who is a very frequent listener of the show. He’s won actually lots of books in our book giveaways this year. And yeah, he’s a Staff MLOps Engineer at Western Governors University in Utah. He had a pretty clever review on Apple Podcast.
Welcome back to The Super Data Science Podcast. I’m your host, Jon Krohn. Let’s start off with two Apple Podcast reviews that came in recently. They’re both five-star reviews Thank you very much. The first is from Jonathan Bown, who is a very frequent listener of the show. He’s won actually lots of books in our book giveaways this year. And yeah, he’s a Staff MLOps Engineer at Western Governors University in Utah. He had a pretty clever review on Apple Podcast.
(00:49):
He says, “Correlation is not causation, but my career in data science, now MLOps, took off around the time I found this show two years ago.” Since then, it’s been a consistent treasure trove of relevant resources from tools to courses to great books that he can check out, and yeah, that he frequently also wins. He had some nice things to say about me as a host as well, especially all the opportunities to engage with the show from guest questions that I provide on LinkedIn. I make LinkedIn posts that you can interact with and you can ask questions of the guests that we have coming up on the show. And of course also the book giveaways that I’ve mentioned now a couple of times. So thanks for that Apple podcast review, Jon.
He says, “Correlation is not causation, but my career in data science, now MLOps, took off around the time I found this show two years ago.” Since then, it’s been a consistent treasure trove of relevant resources from tools to courses to great books that he can check out, and yeah, that he frequently also wins. He had some nice things to say about me as a host as well, especially all the opportunities to engage with the show from guest questions that I provide on LinkedIn. I make LinkedIn posts that you can interact with and you can ask questions of the guests that we have coming up on the show. And of course also the book giveaways that I’ve mentioned now a couple of times. So thanks for that Apple podcast review, Jon.
(01:31):
Our second review, also a five-star Apple podcast review. I don’t know what this person’s real name is. Their handle on Apple podcasts is iamkarp, karp there with a K. So maybe it’s Andrej Karpathy. Whoever it is, iamkarp says, “I’ve been a fan of Jon Krohn for maybe a decade.” They say that they own many of my Udemy courses, which they say are excellent, very kind of you to say that, iamkarp. And yeah, many of the episodes of this podcast, apparently, according to iamkarp, must be heard for people interested in machine learning, data science, and AI. Thanks to both of you, Jon Bown, and iamkarp for those reviews.
Our second review, also a five-star Apple podcast review. I don’t know what this person’s real name is. Their handle on Apple podcasts is iamkarp, karp there with a K. So maybe it’s Andrej Karpathy. Whoever it is, iamkarp says, “I’ve been a fan of Jon Krohn for maybe a decade.” They say that they own many of my Udemy courses, which they say are excellent, very kind of you to say that, iamkarp. And yeah, many of the episodes of this podcast, apparently, according to iamkarp, must be heard for people interested in machine learning, data science, and AI. Thanks to both of you, Jon Bown, and iamkarp for those reviews.
(02:14):
And thanks to everyone for all the recent ratings and feedback on Apple Podcasts, Spotify and all the other podcasting platforms out there, as well as for likes and comments on our YouTube videos. I think Apple Podcast reviews are especially helpful to us because they allow you, anyone, to leave written feedback if you want to and I keep a close eye on those so, if you leave Apple Podcast reviews, I’ll be sure to read it on air just like the reviews I read today.
And thanks to everyone for all the recent ratings and feedback on Apple Podcasts, Spotify and all the other podcasting platforms out there, as well as for likes and comments on our YouTube videos. I think Apple Podcast reviews are especially helpful to us because they allow you, anyone, to leave written feedback if you want to and I keep a close eye on those so, if you leave Apple Podcast reviews, I’ll be sure to read it on air just like the reviews I read today.
(02:37):
All right, now onto the meat of today’s episode, which might actually end up being close to being a Five-Minute Friday episode which very, very rarely happens. This one’s about the Nobel Prizes because 2024 has turned out to be the year of A.I. at the Nobels, with Demis Hassabis sharing the Chemistry prize and Geoff Hinton sharing the Physics prize. But, isn’t that kind of weird?… Why are they winning in Chemistry and Physics?
All right, now onto the meat of today’s episode, which might actually end up being close to being a Five-Minute Friday episode which very, very rarely happens. This one’s about the Nobel Prizes because 2024 has turned out to be the year of A.I. at the Nobels, with Demis Hassabis sharing the Chemistry prize and Geoff Hinton sharing the Physics prize. But, isn’t that kind of weird?… Why are they winning in Chemistry and Physics?
(03:08):
Well, I’ll explain. So the Nobel Prizes, these are widely considered to be the most prestigious award you can win in fields the Nobel Prizes cover. The Nobel Prizes are administered by the Nobel Foundation in Sweden in the following six fields: The first one is Physics, the second is Chemistry, the third is Physiology or Medicine, the forth is Literature, the fifth is Peace, and the sixth is Economics. The first five, so Physics, Chemistry, Physiology, Medicine, Literature and Peace, those five have been awarded since 1901, thanks to the will of dynamite inventor Alfred Nobel, who’s obviously the namesake of the Nobel prizes. The sixth prize, the Economics prize, was established almost 70 years later, in 1969 by Sweden’s central bank.
Well, I’ll explain. So the Nobel Prizes, these are widely considered to be the most prestigious award you can win in fields the Nobel Prizes cover. The Nobel Prizes are administered by the Nobel Foundation in Sweden in the following six fields: The first one is Physics, the second is Chemistry, the third is Physiology or Medicine, the forth is Literature, the fifth is Peace, and the sixth is Economics. The first five, so Physics, Chemistry, Physiology, Medicine, Literature and Peace, those five have been awarded since 1901, thanks to the will of dynamite inventor Alfred Nobel, who’s obviously the namesake of the Nobel prizes. The sixth prize, the Economics prize, was established almost 70 years later, in 1969 by Sweden’s central bank.
(04:03):
Regardless of the field, Nobel laureates are those who have “conferred the greatest benefit to humankind.” And, in the past year, the Nobel Foundation — like no doubt many of you listeners out there — has noticed that A.I. has been making a tremendously positive impact on humankind. There are of course negatives and risks too, as Geoff Hinton himself has pointed out a fair bit lately. But you know on this show we do focus a lot on the positive and yeah, I suspect a lot of our listeners are thinking about the positive impact of AI as well, just like evidently the Nobel Foundation.
Regardless of the field, Nobel laureates are those who have “conferred the greatest benefit to humankind.” And, in the past year, the Nobel Foundation — like no doubt many of you listeners out there — has noticed that A.I. has been making a tremendously positive impact on humankind. There are of course negatives and risks too, as Geoff Hinton himself has pointed out a fair bit lately. But you know on this show we do focus a lot on the positive and yeah, I suspect a lot of our listeners are thinking about the positive impact of AI as well, just like evidently the Nobel Foundation.
(04:39):
Skimming the list of six prizes above, again, Physics, Chemistry, Physiology/Medicine, Literature, Peace, Economics, there is no Nobel Prize directly related to computing, the most prestigious award by the way, in computer science is called the Turing Award, named after Alan Turing. And that was actually jointly awarded to Geoff Hinton who won the Nobel Prize this year in physics. And Geoff Hinton, when he won that Turing Award in 2018, that was for deep learning. And he was awarded jointly alongside Yann LeCun and Yoshua Bengio. Three names, Geoff Hinton, Yann LeCun and Yoshua Bengio that anyone who’s been around in AI for a while are, yeah, no doubt familiar with for a huge amount of critical early innovation in deep learning. But anyway, despite there not being a Nobel Prize directly related to computing, that did not stop the Nobel Prize committee from finding a way to recognize the achievements of those behind world-transforming artificial intelligence.
Skimming the list of six prizes above, again, Physics, Chemistry, Physiology/Medicine, Literature, Peace, Economics, there is no Nobel Prize directly related to computing, the most prestigious award by the way, in computer science is called the Turing Award, named after Alan Turing. And that was actually jointly awarded to Geoff Hinton who won the Nobel Prize this year in physics. And Geoff Hinton, when he won that Turing Award in 2018, that was for deep learning. And he was awarded jointly alongside Yann LeCun and Yoshua Bengio. Three names, Geoff Hinton, Yann LeCun and Yoshua Bengio that anyone who’s been around in AI for a while are, yeah, no doubt familiar with for a huge amount of critical early innovation in deep learning. But anyway, despite there not being a Nobel Prize directly related to computing, that did not stop the Nobel Prize committee from finding a way to recognize the achievements of those behind world-transforming artificial intelligence.
(05:41):
So let’s start with talking about Geoff Hinton and his physics award. The justification for awarding Hinton, who is a cognitive and computer scientist, who’s now Professor Emeritus at the University of Toronto, and until recently he also led the Google Brain team based in Toronto, so the justification for awarding him with a Nobel Prize in Physics is provided by Hinton sharing it with John Hopfield. John Hopfield is an American physicist and emeritus professor at Princeton. A portion of Hopfield’s work is classified as something called “biophysics”, including his work on the development of artificial neural networks (ANNs), which are inspired by the physiology, and I guess the biophysics??, of biological brain cells.
So let’s start with talking about Geoff Hinton and his physics award. The justification for awarding Hinton, who is a cognitive and computer scientist, who’s now Professor Emeritus at the University of Toronto, and until recently he also led the Google Brain team based in Toronto, so the justification for awarding him with a Nobel Prize in Physics is provided by Hinton sharing it with John Hopfield. John Hopfield is an American physicist and emeritus professor at Princeton. A portion of Hopfield’s work is classified as something called “biophysics”, including his work on the development of artificial neural networks (ANNs), which are inspired by the physiology, and I guess the biophysics??, of biological brain cells.
(06:29):
Hinton was pivotal in devising techniques for making artificial neural networks “deeper”, that is, having more layers of processing, and that earned artificial neural networks, the moniker “deep neural networks”, once they became deep like that, because they carry out “deep learning” and Hinton has been recognized now with this “godfather of A.I.” name that lots of people call him by these days. Today, deep learning underlies essentially all of the cutting-edge A.I. capabilities, including things like the near-magical “reasoning” capabilities of state-of-the-art Large Language Models like OpenAI’s o1, which we did talk about recently in episode 820.
Hinton was pivotal in devising techniques for making artificial neural networks “deeper”, that is, having more layers of processing, and that earned artificial neural networks, the moniker “deep neural networks”, once they became deep like that, because they carry out “deep learning” and Hinton has been recognized now with this “godfather of A.I.” name that lots of people call him by these days. Today, deep learning underlies essentially all of the cutting-edge A.I. capabilities, including things like the near-magical “reasoning” capabilities of state-of-the-art Large Language Models like OpenAI’s o1, which we did talk about recently in episode 820.
(07:14):
All right, so Geoff Hinton, the justification for awarding him with the physics Nobel Prize, is related to seems like mostly John Hopfield’s earlier work that sometimes gets classified as biophysics on the artificial neural networks that Geoff Hinton made deep, so maybe a little bit tenuous, and some people have been ribbing the Nobel Prizes for making this connection. For me personally, I think it’s pretty cool. It’s great to see someone like Geoff Hinton, whom I admire so much, being awarded with a Nobel Prize. And so, thanks Nobel Prize committee for finding a way to make that work.
All right, so Geoff Hinton, the justification for awarding him with the physics Nobel Prize, is related to seems like mostly John Hopfield’s earlier work that sometimes gets classified as biophysics on the artificial neural networks that Geoff Hinton made deep, so maybe a little bit tenuous, and some people have been ribbing the Nobel Prizes for making this connection. For me personally, I think it’s pretty cool. It’s great to see someone like Geoff Hinton, whom I admire so much, being awarded with a Nobel Prize. And so, thanks Nobel Prize committee for finding a way to make that work.
(07:50):
On the other hand, the justification for awarding *Sir* Demis Hassabis, who is a founder of one of the world’s leading A.I. labs DeepMind; today called Google DeepMind, because acquisition by Google some years ago now, Demis Hassabis, him getting the Nobel Prize in chemistry is more straightforward. The Chemistry prizes are frequently awarded for biological well, at least biochemical breakthroughs and Hassabis, with co-laureate John Jumper led development of AlphaFold, a Google DeepMind A.I. system that far exceeds human capacities at predicting protein structure, with tremendous biological research and healthcare implications.
On the other hand, the justification for awarding *Sir* Demis Hassabis, who is a founder of one of the world’s leading A.I. labs DeepMind; today called Google DeepMind, because acquisition by Google some years ago now, Demis Hassabis, him getting the Nobel Prize in chemistry is more straightforward. The Chemistry prizes are frequently awarded for biological well, at least biochemical breakthroughs and Hassabis, with co-laureate John Jumper led development of AlphaFold, a Google DeepMind A.I. system that far exceeds human capacities at predicting protein structure, with tremendous biological research and healthcare implications.
(08:33):
In Episode #748 of this show, I did episode on the levels of Artificial General Intelligence (AGI), and I cite in that episode that the superhuman capabilities of AlphaFold, Demis Hassabis’ innovation are one of the existing examples of an Artificial Super Intelligence (ASI) that we have already today, the key point being that today ASI systems are very narrow in their capabilities. It should, conservatively, be at least a few years before ASI overtakes the capabilities of all humans on all cognitive tasks unleashing the singularity. Hopefully we have at least a little bit of time before that happens to prepare.
In Episode #748 of this show, I did episode on the levels of Artificial General Intelligence (AGI), and I cite in that episode that the superhuman capabilities of AlphaFold, Demis Hassabis’ innovation are one of the existing examples of an Artificial Super Intelligence (ASI) that we have already today, the key point being that today ASI systems are very narrow in their capabilities. It should, conservatively, be at least a few years before ASI overtakes the capabilities of all humans on all cognitive tasks unleashing the singularity. Hopefully we have at least a little bit of time before that happens to prepare.
(09:20):
So yeah, so that’s the main points of today’s episode. We just wanted to have a discussion on these Nobel Prizes, one by Geoff Hinton and Demis Hassabis in Physics and Chemistry. And now, yeah, hopefully, you learned a bit about the Nobel Prizes as well as their innovations related to A.I. and how the Nobel Prize Committee is justifying A.I. being awarded with Nobel Prizes in Physics and Chemistry.
So yeah, so that’s the main points of today’s episode. We just wanted to have a discussion on these Nobel Prizes, one by Geoff Hinton and Demis Hassabis in Physics and Chemistry. And now, yeah, hopefully, you learned a bit about the Nobel Prizes as well as their innovations related to A.I. and how the Nobel Prize Committee is justifying A.I. being awarded with Nobel Prizes in Physics and Chemistry.
(09:51):
All right, that’s it for today’s episode. If you enjoyed today’s episode or know someone who might, consider sharing this episode with them, leave a review of the show on your favorite podcasting platform, tag me in a LinkedIn or Twitter post with your thoughts, for example, do you think it’s weird that AI breakthroughs are leading to Nobel prizes in fields like Physics and Chemistry? Do you think this might be the beginning of a trend? So wherever you post those thoughts on LinkedIn or Twitter, I’ll read those and where appropriate, I’ll respond as well. And in addition to those ways of interacting with the show, if you aren’t already be sure to subscribe to the show. Most importantly, though, we just hope you’ll keep on listening. Until next time, keep on rockin’ it out there and I’m looking forward to enjoying another round of the Super Data Science podcast with you very soon.
All right, that’s it for today’s episode. If you enjoyed today’s episode or know someone who might, consider sharing this episode with them, leave a review of the show on your favorite podcasting platform, tag me in a LinkedIn or Twitter post with your thoughts, for example, do you think it’s weird that AI breakthroughs are leading to Nobel prizes in fields like Physics and Chemistry? Do you think this might be the beginning of a trend? So wherever you post those thoughts on LinkedIn or Twitter, I’ll read those and where appropriate, I’ll respond as well. And in addition to those ways of interacting with the show, if you aren’t already be sure to subscribe to the show. Most importantly, though, we just hope you’ll keep on listening. Until next time, keep on rockin’ it out there and I’m looking forward to enjoying another round of the Super Data Science podcast with you very soon.
