Connor Zwick, Co-Founder and CEO of AI-powered language tutor Speak, discusses how the group is fine-tuning models that can bridge the complexities of learning new languages on its platform.

San Francisco

The CEO of Speak, an AI-driven language learning platform, discussed the company's focus on markets like South Korea and Japan, where there is significant demand for English learning. Over 10 percent of the Korean population has tried the product, which aims to replicate the benefits of human tutoring at a lower cost and with greater accessibility.

Despite technological advances, the CEO noted that AI models are not yet perfectly reliable and require ongoing fine-tuning to address cultural nuances and ensure trustworthiness. While AI can surpass tutors in some areas, human interaction remains valuable, and complete accuracy is unlikely to be achieved. The company continues to invest in improving its application layer to make AI-powered language learning more effective and user-friendly.

AI-powered language learning models need fine-tuning: Speak CEO

So what has been really the reception to your service in South Korea and perhaps some of the things that you can actually do to make the service a little bit better and more tailored to cultures like South Korea and Japan. Yeah I mean there's so much here. So I think first of all we really focused on those markets to begin with because we thought there was a huge demand for learning English. And I think just stepping out stepping back for a second if we think about the problem we're trying to solve here. You know I said there's two billion people on the planet trying to learn a language. That's a majority of people in both Japan and Korea that that are interested in learning languages. And today we've had over 10 percent of the entire Korean population try and use our product already. And so I think there's like an incredibly wide amount of demand. But the way that we're going to tap that demand is by offering a structurally better product. Right. Historically the only real solutions that worked were tutors but tutors were expensive and uncomfortable and inconvenient. So the real thing that we're offering is we're using AI to build the best parts of that tutoring experience but make it available to anyone who wants it at a fraction of the cost. And ultimately I think when you can have that sort of technological disruption you can actually grow the market and make it really large. And so that's really the thing that we're providing. I think I know you're very familiar with the South Korean market and I think one classic hallmark just to give one vignette of what we're able to offer. One of the biggest things that's resonated for our product is the fact that a lot of South Koreans are taught to to fear making mistakes because of the primary education systems focus on being correct. And a huge part of our marketing efforts and a big part of the resonance of our product is the fact that it's OK to make mistakes with speak. It's not a real tutor. There's nothing to be embarrassed about. You can really try to speak the language with none of that fear. And I think we're trying to change that narrative. And it's something that I think is one of the favorite parts about the app and why people are finding it to be so much more effective than everything they've tried before. And on this cultural nuances and earlier you touched on the pros and cons of a human tutor. So how close are we really to having an A.I. tutor that really grasps all these human nuances and complexities especially when it comes to Asian languages. Yeah great question. I mean I would say that we have almost all of the technological breakthroughs today to make that possible. And now it's our job. And this is the thing that we're fervently trying to do to continue to actually build that application layer logic to actually make it better than a human tutor in many ways. At the end of the day we're not trying to replace human tutors right. But the fact of the matter is there's only one tutor for every 100 people that wants a tutor and that's an imbalance. So it's really about making that quality accessible to anyone who wants it. And you know in many cases we we find that the you know we find that the average consumer likes to use our product but they still like to use tutors as well. And in some ways we're better than tutors already today. And in other ways you know we're never going to be better than tutors. For example that you know manifesting that kind of discomfort that comes with looking at another human in the eyes and making mistakes. You know that's something that people will still want to do this for for a long time. Right. And you've previously talked about you know the difference between 90 percent accuracy and ninety nine point nine percent accuracy is actually crucial. And I definitely feel that when I use a tutors for languages. So what do you think is preventing AI now from achieving that full or nearly full accuracy. Is it a matter of having access to the language resources or is it about how AI is still comprehending the complexities of languages. Yeah that's a really important point that I think a lot of people don't really have an understanding of how these models work. You know in many ways we've already passed the Turing test. Right. Like you know five years ago if you described what what we have today people would say oh we've we've created artificial general intelligence. You know the world's going to be different forever. But that's that's not happening. The world kind of looks the same as it did a year ago or two years ago. And I think it's mostly because the models are still not perfectly reliable. And so for us as a as an application layer that's that's like one of the biggest challenges. And that's where we need to build our own engineering excellence and fine tune the models and build a bunch of product experience around it to make it still really valuable and useful and trustworthy for the end user. And there's a million things that we're doing. And that's the heart. That's one of the hard parts of the job. And I think that that's going to continue to get better over time. But there's always going to be error. And if you think about it we make mistakes all the time as humans. We misspeak without without thinking about it. We might confidently answer a question and we might be wrong. So I don't think it's realistic to expect it to ever get to 100 percent accuracy either.

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