‘AlphaFold is Just 4 Years Old—Very Young to be a Nobel Prize Material’
A historic moment for AI and humanity—unlike anything seen before. This year’s Nobel Prize in Chemistry was recently awarded to Demis Hassabis, CEO and co-founder of Google DeepMind, and John M. Jumper for their contributions to protein structure prediction through the AI system AlphaFold, alongside David Baker, professor at the University of Washington, receiving the other half for computational protein design. Interestingly, AlphaFold is one of the youngest innovations to make it to the Nobel Prize. “AlphaFold is 4 years old, very young to be a Nobel prize material,” said the presenter at the award ceremony in Stockholm, while announcing Hassabis’s name. The Royal Swedish Academy of Sciences recognized AlphaFold for its impact on structural biology. The AI system predicts the 3D structure of proteins from their amino acid sequences. Since its public release in 2021, AlphaFold has predicted nearly all known protein structures, created a database of over 200 million structures, and is used by more than 2 million researchers across 190 countries. Honoured and proud to be at the @NobelPrize ceremony today with some of the key members of the AlphaFold team where our @GoogleDeepMind colleagues @demishassabis and John Jumper will be co-awarded the Nobel Prize in Chemistry. pic.twitter.com/tCMDQdqK6Z— Pushmeet Kohli (@pushmeet) December 10, 2024 “The Nobel Prize ceremony was an ethereal & profound experience. An amazing event dedicated to celebrating the ingenuity of the human mind filled with many inspirational & moving highlights: My dear colleagues Demis Hassabis and John receiving their Medals for Alphafold,” said Pushmeet Kohli, VP of Research at Google Deepmind. Geoffrey Hinton Knew It—All Along! Geoffrey Hinton, known as the “Godfather of AI,” was also awarded the Nobel Prize in Physics alongside John Hopfield, and already knew that they were going to win the Nobel Prize for their work in building the ‘Boltzmann Machine.’ Hinton also recalled the early days of neural network research. “When Terry came up with this theory for Boltzmann machines, we were completely convinced that must be how the brain works. We decided we were going to get the Nobel Prize in Physiology or Medicine,” he shared, confidently. Hinton, whose work on neural networks in the 1980s laid the foundation for modern AI, reflected on the broader potential of artificial intelligence during his acceptance speech. “This new form of AI excels at modelling human intuition rather than human reasoning, and it will enable us to create highly intelligent and knowledgeable assistants who will increase productivity in almost all industries,” he said. Hinton suggested that insights from sleep could inspire new approaches to neural network training.“Unlearning during sleep may hold the key to making neural networks more biologically plausible. Once we understand how the brain truly learns, it will inspire a new generation of AI architectures,” he said. He added, “The idea of using sleep to do unlearning in neural networks is biologically plausible and could unlock better ways to train AI.” Nobel Prize for Plagiarism? Jürgen Schmidhuber, director of the AI Initiative at KAUST, alleged that the recognition is based on uncredited work. Schmidhuber claimed that Hinton and Hopfield’s contributions drew heavily on earlier research without proper acknowledgement. “This is a Nobel Prize for plagiarism,” Schmidhuber wrote on LinkedIn. He asserted that methodologies developed by Alexey Ivakhnenko in Ukraine and Shun’ichi Amari in Japan during the 1960s and 1970s formed the foundation of the laureates’ work. “They republished methodologies developed in Ukraine and Japan without citing the original papers. Even in later surveys, they didn’t credit the original inventors,” Schmidhuber added, suggesting the omission might have been deliberate. Schmidhuber Effect: This is not the first time Schmidhuber has made accusations. Previously, he accused Meta chief AI scientist Yann LeCun of rehashing old ideas and presenting them without credit, saying, “We must stop crediting the wrong people for inventions made by others.”
Since its public release in 2021, AlphaFold has predicted nearly all known protein structures, created a database of over 200 million structures, and is used by more than 2 million researchers across 190 countries.
This year’s Nobel Prize in Chemistry was recently awarded to Demis Hassabis, CEO and co-founder of Google DeepMind, and John M. Jumper for their contributions to protein structure prediction through the AI system AlphaFold, alongside David Baker, professor at the University of Washington, receiving the other half for computational protein design.
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Siddharth is a media graduate who loves to explore tech through journalism and putting forward ideas worth pondering about in the era of artificial intelligence.