Hello and welcome to Eye on AI. In this edition…Amazon taps AI for easier package delivery; Anthropic cuts batch processing costs in half; and advertisers temper their excitement about AI.
AI is making a splash at the Nobel Prizes this week. AI pioneers John Hopfield and Geoffrey Hinton won the 2024 prize for physics for their machine learning breakthroughs that led to today’s AI boom. Then yesterday, Demis Hassabis and John Jumper of Google DeepMind, along with David Baker, a professor of biochemistry at The University of Washington, were awarded the prize in chemistry for discovering techniques for predicting and designing novel proteins that could transform how therapeutic drugs are made.
A 50-year dream
Heiner Linke, chair of the Nobel Committee for chemistry, said in a press release that the researchers taking home the chemistry award “fulfill[ed] a 50-year-old dream.” That dream was really the vision of a previous Nobel Laureate, chemist Christian Anfinsen, who back in 1973 postulated that it would be possible to predict the shape of a protein based solely on knowing its DNA sequence. A corollary of this idea was that it would be possible to manipulate DNA to design proteins, which are the building blocks and engines of life, with specific functions, since it is mostly a protein’s shape that determines what it does.
Progress on achieving this dream began in 2003 when Baker used the 20 different amino acids found in proteins to design new proteins unlike any other. Then Hassabis and Jumper made a stunning breakthrough in 2020 with their machine learning model AlphaFold2, which enabled them to predict the structure of virtually all the 200 million proteins that researchers have identified. The model has since been used by more than two million people from 190 countries, according to the press release.
The award is a full-circle moment for Hassabis, who began his AI pursuits by teaching computers to master games like Go but always dreamed bigger. Even more so, it represents the best of what AI can offer humanity.
From a distant vision to the top prize in science
More than a decade ago, Hassabis was looking toward a future where AI models would make monumental scientific breakthroughs. In 2014, when his AI lab DeepMind was still largely focused on teaching machines to play games and just shortly after selling to Google, Hassabis told MIT Technology Review about his vision for “AI Scientists.”
“But Hassabis sounds more excited when he talks about going beyond just tweaking the algorithms behind today’s products,” reads the article, following his mentions of how AI could be used to refine YouTube’s recommendations or improve the company’s search. “He dreams of creating ‘AI scientists’ that could do things like generate and test new hypotheses about disease in the lab.”
DeepMind began working on protein folding in 2016, and by 2018, was winning awards for the first version of AlphaFold. The company followed up with AlphaFold 2 two years later, and in July 2022, announced it had successfully predicted virtually all known proteins. Earlier this year, operating now as Google DeepMind, the research lab unveiled AlphaFold 3, which it says can predict the interactions of proteins with DNA, RNA, and various other molecules and provides significant accuracy improvements over the previous model.
Overall, it’s an amazing feat for Hassabis—as well as a clear showing of how rapidly AI is being developed and improving. Ten years ago, this was all just a vision. This week, the breakthrough is real, its impacts are being felt around the world, and it’s just been awarded the top prize in science.
AI's most positive impact
While the use of AI models in many industries is contentious—with some business executives doubting the value of today’s AI software to deliver a financial return—AI’s impact in scientific discovery is already starting to come to fruition, as breakthroughs like AlphaFold make clear. I’m often asked what positive impact AI can have on humanity or what I think is the most exciting way AI is being used. Scientific research and medical breakthroughs is always my answer.
This summer, an AI model developed by Cambridge scientists showed an 82% accuracy in predicting the progression of Alzheimer’s disease, outperforming clinical tests. Several AI-discovered drugs have advanced into Phase I and Phase II tests, including just last week with a cancer treatment from Recursion.
AI’s success in fields like drug discovery and medicine is in no way guaranteed or free from issues like bias, but it’s an obviously worthy pursuit with some early accomplishments worth celebrating.
And with that, here’s more AI news.
Sage Lazzaro
sage.lazzaro@consultant.fortune.com
sagelazzaro.com
This story was originally featured on Fortune.com
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