Are you doing 4-way mo Cruz and uber? Yes, so what we've done at scale is built. The data platform for AI, so AI, is really built on top of data, and these algorithms require billions and billions of examples of labeled data to be able to perform in a safe or reliable way.
So what we've done is built a platform that allows these companies to get the data. They need to be able to build these algorithms in a safe and reliable way, and then they use the data to build their self-driving cars.
So what kinds of data? What kinds of algorithms are they building yeah using your software? So one of the big problems in machine learning is perception being able to fully understand the environment around you using machine learning.
So we process a lot of image: data, lidar data or radar data map, data etc. For for some of these companies and then for other companies, we process tax data or tabular data or speech data. Now is the work that you're, doing going to improve the safety of self-driving cars because there's.
A lot of concerns about you know how quickly they can come to market, even if they work some of the time it has to be perfect. Yeah it's. Actually, I think, even further than that are the work we do is critical to building safe autonomous vehicles, for example, because without the data that we're able to provide to these companies, they actually wouldn't even be able to build Algorithms, that could perform in any any manner that is safer, reliable.
So if there are thousands of human beings that are necessary to do this job now in the future, how much of their work can a I really take on, because it certainly seems that there's, always going to need to be some sort of Marriage between humans and technology - you can't eliminate humans altogether yeah.
I definitely agree with that. I think that AI is really about augmenting humans, with technology and and making them more effective and more efficient using technology, and, in particular, I think, for for a lot of the problems that we work on where AI is, plays a really critical role in self-driving or Medical imagery, etc.
You really want to make sure that humans are a part of the process to ensure that these systems are providing very or are performing very safely and reliably. So there are companies that are doing or trying to do what you do.
Uber just bought a company called mighty. Ai Amazon has its own labeling services. You know what differentiates you from the competition and how does the market evolve? I think one view that we really taken is: how do we solve this in the most tech enabled way as possible? So how do we use as much machine learning and technology on our side to make the process as efficient and high quality as possible, and I think that's, a very differentiated view.
Actually many of these other efforts are much more human powered than technology powered. Do you have a view on which company is going to get a self-driving car to the mainstream market the fastest? Unfortunately, I can & # 39.
T really comment on that, but you have a view, but I think it's very exciting that all these all these companies have really incredible technology and it's, getting better and better every single year right.
So they're. We're, really getting closer and closer to solving this. So I have to ask you you're 22 years old. I am yeah. We've, been doing this for what three years three years. How did you? How did you get here at 22, yeah? Well, I was really lucky.
I grew up in in Los Alamos New Mexico, but after high school I was lucky to be able to come out here to the valley to work as a software engineer, and that really exposed me to. I think a lot of these problems where work, AI and machine learning are really core and - and I went back to school for a year and then after that year at school I dropped out and started this company.
So should everyone drop out, I don't, think stopping has something you recommend. You ask me this all the time. I think if you know what you want to do more and more these days, you don't need a degree to be able to accomplish what you need to do.
I think people care a lot more about what what can you accomplish and what? What are your skills