The Future of AI May Be in Orbit: Inside Little Place Labs’ Space-Tech Strategy

We're here with Bosco Lai, CEO and co-founder of Little Place Labs. Thank you so much for being here, Bosco. Thanks for having me. Yeah, this is such an interesting time to talk about space, right? There's so much going on in space. Tell us a little bit about the company and why you wanted to found it and why you thought right now was the right time. Yeah, so my name is Bosco. I'm the co-founder and CEO of Little Place Labs. What we do is we run AI applications on an orchestrated network of satellites and sensors. So we run software on different types of sensors and the process and compute. to really collapse and reduce the time latency of insights and information getting back to the end users. And thinking about all of this technology kind of coming together, you're using a lot of this technology now in space, right? So talk to us a little bit about this space component and why this is so important up in space. Yeah, because a lot of use cases, especially on the time sensitive side, requires monitoring from space and space data. But again, like we need that information very quickly. And so what we have seen in the space industry is there's more sensors that is being put up in orbit. There's more compute that is being put up in orbit and the compute is more powerful than even a few years ago. That allow us to run a lot more efficiently and more powerful and complex AI application. to open up to a lot more use cases, both on the national security side and on the commercial side. This is the best time to do this. Yeah, and thinking about that, we talked about the national security side, so obviously working with the government on that, and then you also have the commercial side. So talk to us about how your business kind of manages doing both of those things, dealing with customers in the government and also on the commercial side. Yeah, so when we started the company, we made a decision to focus on the government first. Because there is a lot of, you know, funding opportunity and early stage contracting opportunity for us to learn more and really get up, you know, the speed of development and R&D at the beginning stage. And the time is critical, right? The mission on the government side, when we talk about latency, when we talk about accuracy, that is not a good to have, it's a must have. So that's where we focus on it. But now that we are at a stage as a company where we have done, you know, in orbit demonstration mission multiple times, we are more mature. Then we start to open up ourselves to, you know, on the commercial side. There is a lot of opportunities on the commercial side that we can crack with the infrastructure in space and with the AI applications that we can build. Yeah, and thinking about these kind of two sides of the business here, what have been your biggest challenges when it comes to both of them? Because I could imagine that the challenges might be a little bit different when you're dealing with the government versus when you're dealing with kind of private customers. Yeah, with the government, I think we need to go through a lot of conversations to really get to the right people because government is big, right? There is operation, budget, program manager. So you really need to spend the time to have conversations and peel the onion a little bit to really understand what is the problem, how we're going to solve it, how do we remove all the friction, the reasons to say no. So that takes us some time. I think equivalently on the commercial side, when we talk about some of the bigger industry or more traditional industry, like construction, mining, farming, agriculture, those are the bigger industry where they are more tend to gravitate around the existing tools. And so there's also a lot of education that we have to go through, right? What can space and satellite data do for you? What low-latency insights that we provide can do for them, and how do they actually absorb that into the workflow without making too many changes? Again, removing conflict from the customer and really pinpointing what they need and do it again and again and again to build trust. Yeah, doing it again and again and again is so important as you're talking about. Also really speaks to this question of scale, right? How do you really scale, especially when you're looking at these two different sides here, how do you really scale and get to the next level? Yeah, so we are a software-first company, so we focus on building an AI application and the whole workflow that is agnostic to different satellites and different sensors. So, again, that allows us to not just be bound to our own satellites or to our own constellation, but we can actually work on every satellite that goes up that has the right compute and the right sensor. And in time, every company, let's say, you know, there's a new company that is putting up a new type of sensor, collecting new type of data modality, we can ride on that. So our network becomes... you know that much bigger every year with our software applications and the combination of those two it's going to open up a lot of use cases. Yeah I mean thinking about all of those new use cases and again all of the different companies parts of the government you could be working with What do you think is next as you look to not only the end of this year but into next year and the year after, what are you really looking to do and really grow this into? Yeah, so if you're following space and compute orbital data center computing space is a This is a really, really hot topic. I think what we are seeing in terms of running traditional LLMs and those kind of workflows in orbital data centers, it's still going to be, let's say, three, five or even more years away. But if you're talking about GPUs and good enough compute that can run really good workflows and AI models, it's already now. So what we are looking forward and really excited about is how do we expand our offering? How do we put more complex applications on board? as we trend up the curve in terms of compute and sensors in the company, in the industry itself. I would say, you know, even rewind back a few years ago when we first ran our first mission in space, we were running on a very simple CPU. And then fast forward two years, we were running on a spacecraft that has multiple GPUs. So just imagine what can that be in a year's time, in two years time, and better compute, better power, more satellites, better data. And you kind of stitch it all up with AI application. That's going to open up a lot of use cases. Yeah, I mean, it's so exciting to think about where all of this could go, where space is going in general. It's amazing. Thank you so much, Bosco Li, CEO and co-founder of Little Place Labs. Thank you for being here today. Thanks for having me.