Consider it this fashion, he says. Finding a protein’s structure might previously have cost $100,000 within the lab: “If we were only 100 thousand dollars away from doing a thing, it could already be done.”
At the identical time, researchers are in search of ways to do as much as they will with this technology, says Jumper: “We’re attempting to work out how you can make structure prediction a good greater a part of the issue, because we have now a pleasant big hammer to hit it with.”
In other words, they need to make every thing into nails? “Yeah, let’s make things into nails,” he says. “How can we make this thing that we made 1,000,000 times faster an even bigger a part of our process?”
What’s next?
Jumper’s next act? He desires to fuse the deep but narrow power of AlphaFold with the broad sweep of LLMs.
“We now have machines that may read science. They will do some scientific reasoning,” he says. “And we will construct amazing, superhuman systems for protein structure prediction. How do you get these two technologies to work together?”
That makes me consider a system called AlphaEvolve, which is being built by one other team at Google DeepMind. AlphaEvolve uses an LLM to generate possible solutions to an issue and a second model to ascertain them, filtering out the trash. Researchers have already used AlphaEvolve to make a handful of practical discoveries in math and computer science.
Is that what Jumper has in mind? “I won’t say an excessive amount of on methods, but I’ll be shocked if we don’t see increasingly LLM impact on science,” he says. “I feel that’s the exciting open query that I’ll say almost nothing about. That is all speculation, in fact.”
Jumper was 39 when he won his Nobel Prize. What’s next for him?
“It worries me,” he says. “I imagine I’m the youngest chemistry laureate in 75 years.”
He adds: “I’m on the midpoint of my profession, roughly. I assume my approach to that is to attempt to do smaller things, little ideas that you just keep pulling on. The following thing I announce doesn’t should be, you realize, my second shot at a Nobel. I feel that’s the trap.”
