This week, the Nobel Prizes in Physics and Chemistry were awarded to the inventors of technologies that are intimately linked to our work at STFC. Read on to find out more.
John J. Hopfield and Geoffrey E. Hinton received the 2024 Nobel Prize in Physics “for foundational discoveries and inventions that enable machine learning with artificial neural networks.”
Without machine learning, many of the enormous, rich datasets generated by modern science would be totally impenetrable: from analysing particle collisions in the Large Hadron Collider to surveying distant galaxies. Many of our facilities use machine learning to reduce the vast manual effort required to classify and analyse data from experiments.
We also play a key role in helping to embed machine learning and related technologies into research and innovation.
The STFC Hartree Centre helps businesses and organisations make the most of AI, supercomputing and more.
Meanwhile, the STFC Scientific Computing Department provides training, support and resources to the research community through programmes like CoSeC UKRI , and their Scientific Machine Learning Group provides expertise on a range of national and international projects.
Yesterday’s Nobel Prize in Chemistry was jointly awarded to David Baker ‘for computational protein design’ and Demis Hassabis and John M. Jumper ‘for protein structure prediction’ through their AI model AlphaFold2.
For decades, figuring out how proteins folded required sophisticated experimental techniques backed up by major software projects. These included CCP4, a UK community-based software suite led by CoSeC.
When AlphaFold2 was presented in 2020, it was able to accurately predict the structure of virtually all 200 million known proteins.
Dr Martin Wynn , STFC Scientific Computing’s Computational Biology Theme Leader, describes its impact:
“AlphaFold has had an incredible effect on research activities in the biomedical sciences over the last few years. The AI model that has been developed builds on the collective effort of the structural biology community over several decades, an effort to which STFC has made an essential contribution via large scale user facilities such as the SRS and Diamond, and community software projects such as CCP4 and CCP-EM.
“We are now in a new era of structural biology in which, with the ready availability of predicted structures, scientists can ask more sophisticated questions about how these structures function and adapt in living organisms.”
Congratulations to the awardees from everyone at STFC!
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