Breaking The Bottlenecks: Rus And Stoica Discuss AI Optimization

One of the best talks at our recent Imagination in Action event, The Next Endeavor, was a talk between Daniela Rus, who needs no introduction here, and Ion Stoica, a UC Berkeley Professor and co-founder of companies Databricks and Anyscale.

First, a little background. The Next Endeavor happened September 14–15 at Google Bay View in Mountain View, California, and was put on by IIA, in collaboration with Stanford HAI. (Disclaimer: I am a main organizer of this event.) The conference was well-attended and key speakers shared a lot of insights about where humanity is at with technology today.

As for Rus, even though she’s familiar to most of my regular readers, I’ll note that she runs the MIT CSAIL (Computer Science and Artificial Intelligence) Lab, and works on liquid AI models, which I am also involved in. So Rus is a friend and colleague of mine, and I enjoyed introducing this segment, and then listening to these two experts hold forth on AI.

Rus asked Stoica questions about what remains in the way of our computers handling the agentic age with confidence.

Building the Future

A lot of the discussion had to do with infrastructure, and the best ways to handle change.

“Sometimes it’s not obvious what is going to change, and why things are going to be hard,” Stoica noted, adding that many key innovations including algorithmic evolutions are driven from the system side. “Training and inference are so expensive, and are growing still exponentially at this stage, that efficiency … is so important, and in order to gain the efficiency, you almost need to innovate at every layer of the stack.”

Big Challenges

“I think that one thing you need to pay attention to is memory,” Stoica said. “Why memory? Because it’s still true today, that to store one bit of information, you still need one transistor. There’s not much you can do here, right? You can make the transistor smaller, but you still have this one-to-one mapping.”