Bill Gates produces an occasional interview podcast called Unconfuse Me. I listened to Episode 5 today with AI computer scientist Yejin Choi.
Few people are better at explaining the science of artificial intelligence than Yejin Choi. She’s a computer science professor at the University of Washington, senior research director at the Allen Institute for AI, and the recipient of a MacArthur Fellowship. I thought her recent TED talk was terrific, and I was thrilled to talk to her about how you train a large language model, why it’s so hard for robots to pick tools out of a box, and why universities must play a key role in the future of AI research.
My takeaway from the conversation was the thought that tools like ChatGPT continue to grow larger. But this makes the science of the query very important. After reviewing some other technologies, Choi posits that what will really progress into useful tools would be reducing the scope. Instead of trying to be all things to all people, what about working on special purpose AI models—say maybe a math tutor.
I thought immediately about my conversations with recently retired Mike Brooks and the ML technology deep within AspenTech. And that is not the only place within process control software where you will find machine learning (ML, which is an AI technology) working for us.
Forget hand-wringing about the future like our journalist friends like to publish. Try thinking making AI useful.