AI has been a gamechanger for biochemists like Baker. Seeing what DeepMind was able to do with AlphaFold made it clear that deep learning was going to be a powerful tool for their work. "There's just all these problems that were really hard before that we are now having much more success with thanks to generative AI methods. We can do much more complicated things," Baker says. Baker is already busy at work.

Roboticists believe that, using new AI techniques, they can unlock more capable robots that can move freely through unfamiliar environments and tackle challenges they've never seen before. But something is standing in the way: lack of access to the types of data used to train robots so they can interact with the physical world. It's far harder to come by than the data used to train the most advanced AI models, and that scarcity is one of the main things currently holding progress in robotics back. As a result, leading companies and labs are in fierce competition to find new and better ways to gather the data they need. It's led them down strange paths, like using robotic arms to flip pancakes for hours on end.