Machine Learning Street Talk · Friday, September 11, 2026
The discussion touched upon the idea that AI by itself can be meaningless, emphasizing its potential lies in enabling broader scientific progress through interaction with the wider ecosystem. The speaker, with a background in theoretical physics, shared insights from their time at DeepMind and their work on large language models.
“And presumably you think that AI is the most important thing in the next five years, just generally? No, I wouldn't say that. I think that AI by itself, in some senses, is meaningless. Really, it's what, how can AI enable in interaction with the wider ecosystem? Um, and that for us, we're most interested in in broader scientific progress.”
“So I joined DeepMind, um, in 2017, really animated by that question: how do you build an agent that can itself make discoveries? Um, and I started by working at, on that, on that in the context of reinforcement learning, particularly multi-agent reinforcement learning.”