
14 segments available
John Jumper on June 16, 2025 at AI Startup School in San Francisco. John Jumper is a physicist-turned-computational biologist who led DeepMind’s AlphaFold team—and earned the 2024 Nobel Prize in Chemistry for solving protein folding, a decades-old scientific challenge. In this talk, he shares how a deep learning breakthrough at CASP14 turned into AlphaFold 1 and then AlphaFold 2, delivering atomic accuracy predictions and revolutionizing biology. He explains the scientific puzzle behind protein folding, the key algorithmic breakthroughs, and the impact of making millions of protein structures accessible to researchers worldwide. Apply to Y Combinator: https://ycombinator.com/apply Work at a startup: https://workatastartup.com Chapters: 00:00 - Personal Background 01:26 - Transition to Computational Biology 02:01 - Journey into Machine Learning 02:59 - Joining Google DeepMind 03:47 - AlphaFold and Its Impact 04:54 - The Complexity of Cells and Proteins 07:44 - Challenges in Protein Structure Determination 10:28 - Building the AlphaFold AI System 11:29 - The Importance of Research in AI 13:28 - AlphaFold's Breakthrough and Public Data 18:09 - Making AlphaFold Accessible 21:20 - Real-World Applications and Success Stories 22:33 - Engineering New Proteins with AlphaFold 25:23 - Future of AI in Structural Biology
"This is something of a nice change. I've given a lot of scientific talks and no one claps and cheers when I come on. Not normally even when I come on. It's really exciting. It's really wonderful to be..."
"didn't start a startup. That would have been very on point for this event, but I uh dropped out and I ended up working at a company that was doing computational biology. How do we get computers to say..."
"Then I really kind of became a biologist and a machine learner. Actually a machine learner because I left that job and I went back to grad school in biohysics and chemistry and uh I no longer had acce..."
"after this I joined uh Google DeepMind and really joining a company that wanted to say how are we going to take these powerful technologies and all kind of these ideas and we they were becoming very v..."
"guiding principle for me has that when we do this work that ultimately we are building tools that will enable scientists to make discoveries. And what I think is really heartening about the work we've..."
"I'll start with the world's shortest biology lesson. The cell is complex. Um, for people who have only studied biology in high school or in college, you might have this idea that the cell is a couple ..."
"Now scientists have through an incredible amount of cleverness figured out the structure of lots of proteins and it remains to this day exceptionally difficult. Right? You shouldn't imagine this as I ..."
"We wanted to build an AI system. In fact, we didn't even care if it was an AI system. That's one of the nice things about uh working in AI for science is you don't care how you solve it. If it ended u..."
"and I feel like we tell too many stories about the first two and not enough about the third. In data, we had 200,000 protein structures. Everyone has the same data. In terms of compute, this isn't LLM..."
"Alphafold 2 is the system that is quite famous, the one that uh was quite a large improvement. AlphaFold one was the best in the world. But someone did uh the Alcesi lab did a very uh careful experime..."
"available and we thought it was and we did a lot of assessment but we decided that it was very important to make it available in two ways. One is that we open source the code and we actually open sour..."
"darnest things. They will use tools in ways you didn't know were possible. The tweet on the left from Yoshaka Morowaki came out two days after our code was available. We had predicted the structure of..."
"built. One application that really uh I thought was really important is that people have started to learn how to use it to engineer big proteins or to use it in part of and I want to tell this story f..."
"of this. And I like to think that our work made the whole field of what's called structural biology, biology that deals with structures, you know, five or 10% faster. But the amount to which that matt..."