Did Demis Hassabis Truly Deserve the Nobel Prize?
“Winning the Nobel Prize is the honour of a lifetime and the realisation of a lifelong dream – it still hasn’t really sunk in yet,” said the co-founder of DeepMind, Demis Hassabis, who, along with his team, cracked the 50-year-old challenge of protein structure prediction with AlphaFold 2. “With AlphaFold 2 we cracked the grand challenge of protein structure prediction – predicting the 3D structure of a protein purely from its amino acid sequence,” said Hassabis. He added that the open-access database of over 200 million protein structures has empowered more than 2 million researchers, advancing critical work in enzyme design, disease understanding, and drug discovery. As AI continues to shape the future of therapies and scientific discovery, with teams like Isomorphic Labs driving AI-led innovations, the question arises—does AlphaFold’s monumental achievement justify its Nobel recognition, and does it set a precedent for AI-powered breakthroughs in global scientific accolades? According to Heiner Linke, Chair of the Nobel Committee for Chemistry, “One of the discoveries being recognised this year concerns the construction of spectacular proteins. The other is about fulfilling a 50-year-old dream of predicting protein structures from their amino acid sequences. Both of these discoveries open up vast possibilities.” In December 2020, when AlphaFold 2’s success in predicting protein structures was announced, there was no doubt that this breakthrough had Nobel Prize potential. At the time, experts recognised the colossal impact of solving a decades-old challenge in protein science. Following this, the 2023 Breakthrough Prize was awarded to Demis Hassabis, John Jumper, and the DeepMind team, finally leading to the Nobel Prize in 2024​. It goes without saying that the Nobel Committee recognised​ that such a discovery not only solved age-old scientific challenges but also made the borders of AI and natural sciences porous. It redefines what’s possible in biology and chemistry through the intelligent use of AI, enabling research and innovation across multiple fields. Deserves Every Nobel There Is Founded by Hassabis in 2021, Isomorphic Labs—a sister company of Google DeepMind—is looking to revolutionise drug discovery with AI, potentially building a multi-$100 billion business by accelerating research and improving clinical trial success. “AI-designed drugs would probably be available in the next couple of years,” he said. “I hope to achieve both (commercial success and societal benefits) with Isomorphic and build a multi-100 billion dollar business. I think it has that potential,” said Hassabis without delving into the specific timeline. In May 2024, Google DeepMind released AlphaFold 3, a game changing protein folding model that predicts with 50% better accuracy. “Well, if you ask me the number one thing AI can do for humanity, it will be to solve hundreds of terrible diseases. I can’t imagine a better use case for AI. So that’s partly the motivation behind Isomorphic and AlphaFold and all the work we do in sciences,” said Hassabis. He believes that “revolutionising the drug discovery process to make it ten times faster” and more efficient and increasing the likelihood of passing clinical trials through better property prediction offers plenty of commercial value. Predicts 200 Mn Protein Structures Last month, Google DeepMind, in collaboration with Isomorphic Labs, predicted over 200 million protein structures using AlphaFold. It achieved this by training the model with nearly 100,000 known proteins, driving significant breakthroughs in drug discovery by targeting previously intractable biomedical challenges. The model can predict the 3D structure of proteins with incredible accuracy, aiming to design drugs that target specific proteins, unlocking treatments for diseases that were previously untreatable. Recently, Google DeepMind also launched AlphaProteo, an AI system that generates novel proteins designed to bind to specific target molecules poised to significantly advance research in drug design, disease understanding and other health applications.DeepMind is not the only active player in the market, ESMFold, Meta’s protein-folding model, has also predicted about 772 million protein structures. This is only the beginning.
Does AlphaFold’s monumental achievement justify Nobel recognition and set a precedent for AI-powered breakthroughs in global scientific accolades?
Does AlphaFold’s monumental achievement justify Nobel recognition and set a precedent for AI-powered breakthroughs in global scientific accolades?
["AlphaFold", "demis hassabis", "Nobel prize"]
["Go", "AlphaFold", "API", "programming_languages:R", "AI", "demis hassabis", "innovation", "programming_languages:Go", "Nobel prize", "Aim", "R"]
["AI", "Aim", "R", "Go", "API", "innovation", "programming_languages:R", "programming_languages:Go"]
Shalini is a senior tech journalist, exploring the latest advancements in AI. When she's not reporting on the latest innovations, you can find her immersed in her next literary adventure.