Nordic Life Science 1
60 “I’ve always thought if we could build AI in t
he right way, it could be the ultimate tool to help scientists, help us explore the universe around us.” convolution approach was abandoned, and instead a transformer architecture was used, with the essential attention mechanism for learning which parts of the input are more important for the objective of network. The network is also of the end-to-end type, where atomic coordinates are directly produced as output rather than contact information, which had to be post-processed separately in AF1. “The AF2 can be viewed as the first real scientific breakthrough of AI,” stated the Royal Swedish Academy of Sciences after the announcement. “AI will make science faster” Hassabis and Jumper had succeeded in solving the protein structure prediction problem for monomeric proteins to within a backbone accuracy of about 1 Å, and since 2020 more than two million people from 190 countries have used their program. The AF2 source code was also made public, which was a decisive contributor to its impact as it could be extensively tested and validated. “It is a key demonstration that AI will make science faster and ultimately help to understand disease and develop therapeutics. This is the work of an exceptional team at Google DeepMind [Google acquired DeepMind in 2014] and this award recognizes their amazing work,” stated John Jumper after receiving the news that he had won the Nobel Prize. Captivated by chess and the universe Demis Hassabis, born in 1976 in London, was captivated by chess really early on in life and at the age of 13 he reached Master status. In interviews and on X he has emphasized the importance of chess and playing games for his career and his life. It got him thinking about thinking and also provided him with money to buy his first computer. In his teens he also started working as a programmer and successful games developer. He later found Elixir Studios, producing games for Microsoft and Vivendi Universal, and contributed to many bestselling games. He then studied cognitive neuroscience at University College London, completing his PhD in 2009, and pursued postdoc work at Harvard and MIT. He used what he learned about the brain to develop better neural networks for AI and in 2010 he co-founded DeepMind with the modest goal of “solving the problem of intelligence”. “The reason I’ve worked on AI my whole life is that I’m passionate about science and finding out knowledge, and I’ve always thought if we could build AI in the right way, it could be the ultimate tool to help scientists, help us explore the universe around us,” he said in an interview with Adam Smith, chief scientific officer, Nobel Prize Outreach, right after the announcement. John Jumper, born in 1985 in Little Rock, Arkansas, USA, is the youngest awardee of the Nobel Prize in Chemistry in 70 years. He received his PhD in theoretical chemistry from the University of Chicago in 2017 and his thesis examined how to apply machine learning techniques to the study of protein dynamics. He subsequently worked as a postdoctoral researcher before moving to Google DeepMind. Jumper’s fascination with the universe was what made him start studying physics and mathematics according to the Royal Swedish Academy of Sciences. “You know, we need computation to solve the problems of biology. And I just love that it’s starting to work, and I can’t believe we’re getting recognition this fast for it,” he stated to Adam Smith after the announcement. NLS Illustration of Demis Hassabis and John Jumper THE NOBEL PRIZE // CHEMISTRY ILLUSTRATION NIKLAS ELMEHED/NOBEL PRIZE OUTREACH