Alan

any single phenomenon, like there's a bird on the camera that it can really things that you don't think about can happen.

Also like lens flare and again fog or some specific pattern of clouds.

And then you take your model to another location and maybe there's snow.

And when you train in California in these parts, there's never the models has never seen snow.

So there's a lot of custom things that can go wrong.

And there's a long tail of data that you need to collect for it to be really accurate.

So I'd say that's an interesting one.

Of course, there's many more areas in which we've worked.

So there's work that we've done in forecasting.

How can a retailer forecast how many items they need to buy so that they don't run out of stock next week?

And there's a lot of complexities in that kind of scenarios.

But yeah, I don't know if there's a single most difficult model.

But this is something worth mentioning, for sure.

Business is thriving.

So we're having, I mean, we've been in this space for 15 years and that's every company under the sun right now says they do AI and they're all like mostly users of ChatGPT and similar APIs like Chennai APIs.

but we have developed like a very fine understanding of how really machine learning works from the fundamentals.

And we've done that all over the years.

So we have like hundreds of different use cases.

And yeah, right now we're working for many different industries on the airline business.

We're doing models from like optimization of contingency fuel.