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世界中の人々や組織は、非常に有用なデータを絶えず生成しています。それを活用して問題を解決する方法を見つける必要があると思います。The challenge has been a lot of these data sets are very fragmented. Most of society's complex challenges don't get solved with a single data source. So this fragmentation gets in the way of being able to use the world's information to actually make a big difference to everybody everywhere. Google's mission is to organize and make easily accessible all kinds of information. We're doing it now for public data. We have gathered, standardized and processed data from tens of thousands of tables from hundreds of reliable global sources and pulled it into one easily understandable view. This is the fun part. Now comes AI and natural language processing. Most people don't think in terms of scatter plots or variables of interest or data points or triplets. They think in terms of the question they want to ask of data. Now imagine if you could just simply ask the question in ordinary English. And then you get back these graphs that help get you insights and that let you explore more deeply in sensible ways. That ability to make data accessible and intelligent, pragmatic, practical at the organization level makes data commons, I think, an essential tool for organizations as they're doing their work. Generative AI now powers some of the most important functionality in data commons. With large language models, you can ask your questions and start getting answers. Imagine, for example, I'm a climate NGO and I'm trying to understand how access to electricity has changed across countries in Africa. I'd search for it on data commons. From these charts, we see that Kenya, Somalia and Ghana have had some of the greatest increases in access to electricity. I wonder what the impact of this on their greenhouse gas emissions has been. From these charts, we can see that Ghana's greenhouse gas emissions have gone up substantially more than that of Kenya. These observations are the beginning of a journey for us to better understand how we could increase access to things like electricity without proportionately increasing greenhouse gas emissions. When it comes to actually taking action out of the insights from this data, it's going to take people on the ground. We also have to think about this responsibly. So that's why doing this together and thinking about partnerships, collaborations, I think is so, so important. It's these people who have deep domain knowledge, who know what the right questions to ask are, who know what the right solutions to build are. At TechSoup, we've been working globally to connect nonprofits to technology for over 30 years. Data is at the heart of what organizations need to be able to make change. So we began working with food banks and food pantries across the United States and Google's data commons to build our own instance of data commons that pulled together the data points and variables that would be most interesting to these kinds of organizations. One of the big complaints we often hear about small organizations is they don't take risks. And it's hard to take risks if you don't have data because they're operating in the known world, right? The world that they see in their data, which becomes self-reinforcing. Data Commons は、組織がその世界にアクセスできるようにします。つまり、盲目的にリスクを負う必要はありません。I would not have ever guessed I would see this in my lifetime and it's so exciting to be at a time and this is actually possible. Organizations know the questions they want to ask of data. They have the knowledge that gets at the answers that will be meaningful to them. Data commons democratizes that. So you just go in and type the question you actually have. That is absolutely game-changing.