I think if I look back over the last 10+ years, there are a bunch of different moments that come to mind—things that really left an impression on me and changed the way I think about AI.

Obviously, in 2012, there was the AlexNet paper, and even just doing image recognition with these deep neural networks was really, really cool. Then AlphaGo was another big moment. But for me personally, I was up close and personal with AI in 2015. My co-founder and I were doing our own independent AI research, trying to learn as much as possible—reading all the papers, implementing things. We scraped a bunch of YouTube data as a side project.

We put all the data into the model, not really knowing what to expect. On the first training run, we came back a few hours later and tested it. We had built a model that was better than the state of the art in accent detection—classifying what accent someone was speaking with.

For us, it was about how to integrate deep learning into the language learning experience. The first few years of Speak were focused on building really good speaking experiences. It was actually really obvious because, before us, language learning apps didn’t really have speaking components. If they did, they didn’t have models that could robustly understand someone speaking with an accent.