I kind of dove into that problem much more deeply, of “What really is the best interface for getting domain knowledge from an expert into a model.” Those are themes that I explored for multiple years, that along with my co-founders I ended up being with led us to Snorkel, and then Snorkel AI now. So I think that’s the broader idea, that it was really appealing to me all along the way, that had me coming to machine learning. It felt a little bit more like “Your job’s just to translate from one language to another.” But the cool thing about machine learning or AI in general I think is that you get more a sense, in the right setup, of “If you can tell me what’s good, then I can find it.” There’s better synergy between the human and the computer, where now I can show you what I want, even if I don’t know how to get there, and you can get there, where “you” here is the computer, of course. Very much like describe exactly what you want done, step by step.
I think historically, that’s very imperative code. I’d say from the very beginning one of the ideas that drew me in was there should be this different interface for getting things done, for transferring information from an expert into a program that can now do work for you. And I thought it was so cool that even after I lost my MATLAB during the school year, I had to go back to high school - this was after my junior year I used Excel, and I had a separate tab for each generation of the genetic algorithm, and I tried to recreate it there, because I was still, of course, a lousy programmer, but just thought the ideas were so neat. But there was a lucky break for me - there was an internship program for high school students near Wright-Patterson Air Force Base in Ohio where I grew up… So I was on a project, using MATLAB of course, the lingua franca of mechanical engineers not the Python of machine learning engineers, but… Yeah, so the task that I was assigned to was using genetic algorithms to design better airfoils, so some non-gradient-based optimization.
You know, this maybe just shows how thick I am it actually goes all the way back to high school that I had my first dabbling in machine learning, and loved it, and didn’t realize then that I should have just embraced it wholeheartedly from the get-go.
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