If you walk into a tropical forest, you will essentially miss 90% of the animals are there. They hear things and smell things way before any of us can. They are aware of us much more than we are of them. With camatrops and other passive sensors, we now have technologies that collect information no matter what. We can put them in a very large area and then they will snap a picture of an animal going by. And the amount of information that you can get from them is incredible. The report that came out from the biodiversity convention's scientific body was the first official UN report on the state of biological diversity of planet. And of course it's not surprising that it's very alarming. You know, there have been five times in the history of life on Earth when there have been mass extinctions. The premise of that UN report is that we are on the very verge of a six extinction. Some of the things going on right now are exactly the preludes that will lead to such a calamitous loss of biological diversity. Maybe 10 to 20% of all life on Earth. And it's time for us to wake up and do something about it. When threats like the forestation are accelerating and evolving quickly, we just don't have enough time to wait for data to come in. In one place that we were setting camatrops, we left the cameras for one month and we get almost 150,000 pictures. And this is like the bottleneck that we have. We improve the system to collect the data, but we are quite slow in processing and analyzing this information. The second barrier that we identify with camatrop data is that the data is siloed. And it's very difficult to have like a big picture of what all this data is telling you if it's all in different places. Well, life insights is a response to these barriers. Wildlife insights is a cloud-based AI-enabled platform that allows many different organizations to upload, store, manage, and share their data and derive meaningful insights from that data. The hope is that it's going to drastically speed the process of getting the data from in the field on the camera to up in the Google Cloud and open for analysis and mapping. The first priority for the AI models is being able to distinguish if there is an animal in an image or if there's just a blank background with no animal in it. This is a nightmare for people who are doing photos of a plane. There are hundreds of photos where there's nothing. Here's the first white one, here's the second white one. Here's the water. It's incredible. The second task is to do species classification and allow a researcher to filter through millions and millions of images and say, show me all the greater bamboo lemurs or whatever species of their interest. We have a map of the species that we can see in the areas of each species. We know if the species has been effective or not, but it's a good idea to have a good idea. If we have good data about what's happening to wildlife, this will provide a guide for policymakers. It's basically illuminating the path. I think we're just at the beginning of being able to understand how we can use this very powerful tool. The ability to have our finger on the pulse of these wild places and then being able to translate that very quickly into advances in conservation and for a more sustainable future. That's where we want to go. If we build wildlife insights and becomes a huge collection of camatrop data that never gets used for anything, we had utterly failed. Change is what we're after.