“We’ve given incentives to a lot of faculty to create a lot of new courses throughout the College of Engineering for AI and ML for what matters to their field. For instance, if you’re an electrical engineer, there’s a lot of hardware to it, you know you have a model for that. How do you make the model smaller so that you can put it in hardware? That’s one very tangible question that the students would ask. But if they’re, say, mechanical engineers, they might use it differently. Maybe for them what generative AI could do is help them generate 3D models, think about structures that they would not think about naturally. And you can decline that model. The Makerspace is a massive tool. But how the tool is used is really a function of the specific domain. The goal, of course, is for Makerspace to be available beyond engineering.
“It’s already being used by our College of Computing, and we’re hoping that our co colleagues in, say, the College of Business will see the value, because they haven’t used AI yet — perhaps for financial models, predicting whether to sell or buy a stock. I think the sky is a limit. There’s no one use of AI through Makerspace. It’s an infrastructure that provides the tools. And then these tools find declinations in all different areas of expertise.”
Why is it important to have this technology at the school for students to learn about AI? “The way we’ve come to articulate this is as follows: We’re not deliverers in doomsday scenarios, where AI is going to generate terminators that are going to eradicate humanity. Okay, that’s not how we’re thinking about it.
