IIt was more than even its most ardent defenders expected. Artificial intelligence was awarded the Nobel Prize this week after demonstrating superhuman abilities and debate over whether this technology is the greatest invention in human history or a surefire route to self-destruction. And then another landed.
First is the Physics Prize. American John Hopfield and British-Canadian Geoffrey Hinton won the award for their fundamental research into artificial neural networks, the computational architecture that underpins modern AI such as ChatGPT. The Chemistry Prize was next presented, with Google DeepMind’s Demis Hassabis and John Jumper winning half each. Their AlphaFold program solved a decades-old scientific challenge by predicting the structures of all life’s proteins.
It is another thing that artificial intelligence has won two Nobel Prizes in the same number of days. Another fact is that both recognized British researchers in fields that had previously been ignored by the Nobel Prize. Hinton and Hassabis were both born in London, but have been separated for nearly 30 years. This watershed moment raises the obvious question of where it all went wrong. And more importantly, won’t it work?
Experts in the field say that Britain’s pedigree in artificial intelligence (a technology that can be loosely defined as a computer system that performs tasks that generally require human intelligence) is based on specific moments or specific decisions. I don’t think so. But key elements have come together to set the stage for what happened in Stockholm this week.
Demis Hassabis won the Nobel Prize in Chemistry for his work on the Alphafold project, which solved a decades-long scientific challenge. Photo: Toby Melville/Reuters
The foundations were formed over many centuries. Thomas Bayes, George Boole, Charles Babbage, Ada Lovelace, and others long before Alan Turing asked, “Can machines think?” Britain was serious about statistics, logic, mathematics, and engineering. I have been working on this. As computers became established as a technology, expertise flourished in a few centers.
“The UK has long been a leader in computing science and AI,” says Dame Muffy Calder, vice-principal and head of science and engineering at the University of Glasgow. “We’ve been leading for years, and I think part of the reason for that is because of the funding environment in the past that allowed so-called discovery-driven research.”
Unlike research that focuses on solving well-defined problems, the research Calder refers to is more speculative. Both AI and quantum technology have benefited from this research after decades of support, Calder said. “That’s the message: You have to keep funding ideas from the beginning,” she said. “Everything can’t be focused on innovation or focused on challenges. Turing machines? When Alan Turing came up with Turing machines, the applications didn’t exist.”
British-Canadian Geoffrey Hinton was co-recipient of the Nobel Prize in Physics for his fundamental research into the artificial neural networks that underpin modern AI. Photo: Johnny Guatto/University of Toronto/Reuters
Among the major early influential groups were the University of Edinburgh, the University of Cambridge and the University of Aston, all of which remain strong today. But the momentum Sahani mentioned has led to further clusters. His unit at UCL is one of them, and its history tells a story of how these nodes attract and drive expertise. The Gatsby Unit was founded by Hinton, who spent most of his career in Toronto after studying at Cambridge and Edinburgh. Mr. Sahani returned to the UK to take up a post at Gatsby, and Mr. Hassabis, who went on to found DeepMind, did postdoctoral research there.
“‘Gatsby’ had an incredible turnout,” Sahani says. Funding from the Gatsby Foundation, a charity founded by supermarket heir David Sainsbury, allows the scientists to avoid the hassle of pursuing teaching and grants, which occupies other academic fields. , I was able to concentrate on my research. “It’s like a chain reaction,” Sahani says. “When you get critical mass and you have people doing exciting things and talking to each other, other people come up and want to be a part of it.”
AI has gone through boom-and-bust cycles for decades, but the machine learning revolution, driven by multi-layer neural networks processing massive data sets on processors built for gaming, is electrifying investors. Invigorated. A surge in funding from companies and countries that can’t risk being left behind has changed the game, with AI research now dominated by primarily American tech companies.
“It’s becoming increasingly difficult to be competitive, not just in universities in other countries, but also in industry,” Sahani says. “The UK doesn’t have the disproportionate presence it had 10 or 15 years ago. It’s not because we’ve gone backwards, it’s because everyone else has invested and caught up a lot.”
Universities cannot hope to compete with the vast computing resources available to Google and other big tech companies, the vast datasets to feed AI models, or the salaries they can offer.
Dame Wendy Hall, professor of computer science at the University of Southampton and member of the UN advisory body on AI, says the UK’s priority must be to protect its “academic heritage” in technology. .
“It is critical that we keep the pedal to the metal on funding for AI research in universities. This is where future generations of AI technology will come from, and we need advanced skills to support the growing AI industry.” she says. “Other countries are very envious. It takes more than 20 years to raise a research star like Hassabis. It doesn’t just fall from a tree.”
Mr Sahani believes the UK’s future competition will be helped by more centers like the Gatsby Unit, where researchers can focus purely on research, and by funders willing to pick and support winners. Mr Calder said that while close links between universities and tech companies were essential for the prosperity of both, the UK should make better use of its sovereign assets such as NHS health data. “We have to look at the resources we have,” she says.
Will there be more Nobel Prize winners? That also affects individuals and the working environment around them. “What stands out about Jeff is his creativity and insatiable curiosity. He pursues all kinds of different problems,” Sahani says. “In Demis’ case, what was evident when he was here was his dynamism. He felt great things were going to be built and he was going to go after it.”
Source: www.theguardian.com
