 If you walk into a tropical forest, you will essentially miss 90% of the animals that are there. They hear things and smell things way before any of us can. They're aware of us much more than we are of them. This is the biggest animal in the world. It's the biggest animal in the world. It's like a snake for the camera. With camera traps and other passive sensors, we now have technologies that collect information no matter what. You 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 the 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 percent of all life on Earth. And it's time for us to wake up and do something about it. When threads like deforestation 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 set in camera traps, we left the cameras for one month and we get almost 150,000 pictures. And this is like the bottleneck that we have. We improved the system to collect the data, but we are quite slow in processing and analyzing this information. The second barrier that we identify with camera trap 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. Wildlife 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. 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, you know, greater bamboo lemurs or whatever species of their interest. If we have good data about what's happening to wildlife, this will provide a guide for policy makers. 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 make sure that we have the ability 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 camera trap data that never gets used for anything, we had utterly failed. Change is what we're after.