Two trailblazing computer scientists have won the 2024 Turing Award for their work in reinforcement learning, a discipline in which machines learn through a reward-based trial-and-error approach that lets them adapt within constrained or dynamic environments.
Andrew G. Barto, a professor emeritus at the University of Massachusetts Amherst; and Richard S. Sutton, a professor at the University of Alberta, developed key algorithms and theories through a seminal series of papers starting in the 1980s. This includes work on a reinforcement technique called temporal difference learning; the duo later published an academic textbook called Reinforcement Learning: An Introduction.
Esteemed mathematician Alan Turing (pictured above), after whom the Turing Award is named, also produced a paper in the 1950s called Computing Machinery and Intelligence that questioned whether computers can think and touched on similar concepts around learning from experience.
In more recent years, reinforcement learning has received more attention after Google Deepmind used the technique to build an AI that defeated the world’s best AlphaGo players. And in the past few months, Chinese AI upstart DeepSeek hit the headlines for its game-changing R1 reasoning model, which leaned heavily on reinforcement learning to create more cost-effective foundation models.
‘Nobel Prize for computing’
The Turing Award, administered by the Association for Computing Machinery (ACM), has often been dubbed the “Nobel Prize for computing.” However, the Nobel Prize itself has been encroaching into the computing realm, particularly around AI; Geoff Hinton and John Hopfield won the Nobel Prize in Physics for their work in foundational AI last year. This was followed shortly after by DeepMind’s Demis Hassabis and John Jumper who were awarded the Nobel Prize in Chemistry for their work on AlphaFold.
“Research areas ranging from cognitive science and psychology to neuroscience inspired the development of reinforcement learning, which has laid the foundations for some of the most important advances in AI and has given us greater insight into how the brain works,” ACM president Yannis Ioannidis said in a press release. “Barto and Sutton’s work is not a stepping stone that we have now moved on from. Reinforcement learning continues to grow and offers great potential for further advances in computing and many other disciplines. It is fitting that we are honoring them with the most prestigious award in our field.”
Other notable AI pioneers to win the Turing Award include Meta’s chief AI scientist Yann LeCun, who was awarded the prize in 2018 alongside Geoff Hinton and Yoshua Bengio for their work on deep neural networks.
Barto and Sutton will share the $1 million cash prize, which was provided with support from Google.
Paul is a senior writer based in London, focused largely (but not exclusively) on the world of UK and European startups. He also writes about other subjects that he’s passionate about, such as the business of open source software. Prior to joining TechCrunch in June 2022, Paul had gained more than a decade’s experience covering consumer and enterprise technologies for The Next Web (now owned by the Financial Times) and VentureBeat. Pitches on: paul.sawers [at] techcrunch.com Secure/anon tip-offs via Signal: PSTC.08 See me on Bluesky: @jambo.bsky.social
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