Catherine Nakalembe

and then adapt basically what would be face detection.

But instead of detecting faces, cats, dogs, et cetera, we modified it to detect maize, beans, cassava.

We covered all of Western Kenya in two weeks with just two teams.

collected over five million images, a lot of them with volunteers, everyday motor taxi drivers, students.

This would allow us to build a more complex model that can learn from all these different examples from all the different contexts.

There was a flood in Kenya in 2024.

It happened really, really rapidly.

And, you know, the entire country was affected pretty much.

I got an email from the Ministry of Agriculture asking to do an assessment using satellite data to look at where floods happened, where were crops and give an estimate of what the total area of cropland that's been affected was.

And then what the ministry does with the information is they make their response programs, which is where do we need to go to provide seeds so people can replant, as an example of an action that was taken.

It's really powerful to be able to do that.

True innovation is not about high-tech systems, but about making the technology fit the problem.

We have to provide really good information to the people who can do something

with it.

If we do this correctly, we can save time, we can save money, we can save livelihoods.

I'm so grateful to be here.

I'm really excited to be in the TED office, but also for the opportunity to sit down and chat with you during Climate Week.

I used to play badminton.

I was going to do sports science.

That's like literally I was called Catherine Badminton when I was in high school.