 Welcome back to the AI for Good Global Summit here in Geneva on day two. Now, Microsoft has a big presence here, and I'm now joined by Jennifer Marsman, and you are the principal software engineer. So, with that in mind, what's your initiative you're bringing to this AI for Good talk here? Well, I'm here in the context of AI for Earth. And AI for Earth is a grant program that was announced in December of 2017 by Brad Smith, Microsoft's president, where Microsoft publicly committed $50 million U.S. over a five-year time period to anyone doing data science or machine learning work in the areas of agriculture, water, climate change, or biodiversity. And this is a great conference for us because obviously the sustainability development goals align very strongly to the things that we care about, and we believe that artificial intelligence can make a real impact in these areas. Tell me how, because we've been hearing this for a while now. Absolutely. So there's a lot of different ways you can make an impact. One example is in the field of agriculture. So we're using precision agriculture and machine learning to basically be able to take data from sensors in a field, and couple that with aerial imagery from drones flying overhead, and with that be able to create machine learning maps of the impact on a forest. So moisture levels, for example, you can use things like visual similarity for, you know, two patches maybe darker in different areas because they've both been freshly watered, and you can use that to extrapolate and figure out that they're both freshly watered. And things that are similar in space will also be similar. There's examples in the field of agriculture. There's examples in the field of conservation. We've seen grant recipients working on poaching of elephants and being able to detect in real time the presence of poachers and work to help prevent that. We've seen another grant recipient, WildMe, who is working on recognizing individual animals within a species. So being able to take, not only realize, you know, zebra, not a zebra, but rather this is a specific zebra 5709, and then with that be able to roughly estimate population densities, track migration patterns, things like that. Microsoft is a for-profit company, of course. So why are you doing this part? Well, I believe that AI can really make an impact in terms of how we can solve these big challenges. And I think everyone helps where they can. And in Microsoft's case, the things that we can bring to the table are access to a cloud. So we have this amazing cloud, Microsoft Azure, which we can give people access to. And a lot of times, the people who are working to solve these problems, non-profits and startups and such, are the people that don't have the funding necessarily to do that. So we don't want anyone to not be able to be effective due to lack of funding. So we're providing access to the cloud. We're providing expertise in education in the field of AI, which we've had decades of experience in. And then the other thing is that I think it does help us as a for-profit business. For AI, for Earth especially, we're dealing with planetary-scale data. When you think about some of these things where we're using satellite imagery, so that's great for our cloud, right? Because we're running these things on Azure. So if it works, fabulous, we're making an impact in a very tangible way. If it doesn't work, great. We know where Azure is falling short on planetary-scale data, and we can fix it and make it better. So by the end of this conference, at the end of this week, what would you like to come away with in terms of AI? Well, there's a number of things I'd like to accomplish at this conference. First of all, I do want to spread awareness of the AI for Earth grant program to all of the amazing people that are here. I've already had so many great conversations with the folks here. And I think the very worst thing is when a pot of money goes on spent, right? So awareness that the AI for Earth grant program exists, along with its sister initiatives, AI for accessibility, and AI for humanitarian action. Together, these three programs comprise the AI for good program. And then I'm also looking for, you know, what are some cool machine learning problems that we can help solve? I personally have a passion for machine learning, so if we can find interesting problems to solve and help brainstorm sessions with folks to help how we can best make an impact with AI, that is worthwhile for me. Okay. Well, that was Jennifer Mosman from Microsoft. Thanks very much for your time. Thank you, Chris.