ility to customize applications). There is also revenue generated from buying extra machine learning reports, and eventually we’ll be selling anonymized agricultural data sets via our partners Ocean Protocol and their data marketplace. Another revenue stream is farmers buying things like extra IoT sensors for their farms and having to buy those sensors with DMTR tokens. As we onboard more and more farms, communities, and regions of countries this will all add up over time. Keep in mind we are contracted with 22 million farms + to use our platforms. This doesn’t mean they are implemented or that all 22 million + farms will take our platforms but the governments we are working with want our platforms to be with as many of their farms as possible. It’s a very exciting time for us. Dimitra有很多收入来源。 首先，我们的 "Connected Farmer"平台、"Connected Coffee "平台、"Livestock Guru "平台和最近的 "Deforestation "平台的授权所产生的收入。Dimitra还从客户要求的定制化构建或功能中获得收入（我们的平台有开箱即用的版本，也有可能做定制化应用程序）。 还有来自购买额外的机器学习报告的收入，最终我们将通过我们的合作伙伴海洋协议和他们的数据市场出售匿名的农业数据集。 另一个收入来源是农民为他们的农场购买额外的物联网传感器等东西，并且必须用DMTR代币购买这些传感器。 随着我们加入越来越多的农场、社区和国家地区，随着时间的推移，这些都会增加。 请记住，我们与2200万个农场签订了合同，以使用我们的平台。 这并不意味着他们已经实施或所有2200万+农场都会使用我们的平台，但与我们合作的政府希望我们的平台与他们尽可能多的农场合作。 这对我们来说是一个非常令人兴奋的时刻。 Q10 主持人：据我们所知Dimitra也运用了很多AI和机器学习的技术，能给我们具体说说Dimitra是如何运用AI和ML的吗？您是怎么看待最近的AI技术的革新和发展的？ As far as we know, Dimitra has been utilizing a lot of AI and Machine Learning Technology too, can you tell us more about it? And How are you viewing the latest development of the AI technology? Jon Trask：This is a great question - thank you for this great question and first please take a look at our new AI focussed DMTR logo: We love the logo and hope you do too :) Artificial intelligence is certainly a hot topic these days and it is used in many areas of our applications. Here are three examples of how Dimitra uses AI and machine learning: Deforestation - we assess satellite images to differentiate between trees, crops, forested areas and clear cut areas. Machine learning is trained to understand the difference between what is on the ground. Some land looks the same from a satellite and we need to train the AI to understand texture, color, reflectivity, etc.. and understand what it is actually seeing. Crop performance - we use spectral analysis and radar based analysis from the satellite to provide us readings on the ground. This data is combined with weather, planting, soil data, known agronomy parameters and a combination of statistical analysis and artificial intelligence is used to make recommendations to maximize the performance of each crop. These models are built for each crop and each combination of soil, terrain, weather, irrigation and known soil data. Machine learning is used to compare data sets across the world and align those recommendations based on regional differences. Animal productivity - many environmental, management and hereditary factors affect the performance of cow. Machine learning combined with statistical analysis helps analyze and provide probabilities of what traits may be passed on, how mating one animal to another produces a prediction of performance. Mom donates 50% of her genes, Dad donates 50% of his genes. Nutrition, weather, water, disease, temperature, care, stress all play a factor. We group the animals based on conditions to make these predictions. Here is a great feature about our work in AI that CIO review did last year and featured us as one of the top 20 AI companies to watch in the future 这是一个很好的问题--谢谢你的这个好问题，首先请看一下我们新的以人工智能为重点的DMTR标志。 我们喜欢这个标志，希望你也喜欢。人工智能无疑是这些天的一个热门话题，它被用于我们应用的许多领域。 这里有三个例子说明Dimitra如何使用人工智能和机器学习。 Deforestation--我们评估卫星图像，以区分树木、农作物、林区和空旷地带。 机器学习被训练来理解地面上的东西之间的区别。 有些土地从卫星上看是一样的，我们需要训练人工智能来理解纹理、颜色、反射率等，并理解它实际看到的东西。 作物性能--我们使用来自卫星的光谱分析和基于雷达的分析，为我们提供地面上的读数。 这些数据与天气、种植、土壤数据、已知的农艺参数相结合，并结合统计分析和人工智能来提出建议，以使每种作物的性能最大化。 这些模型是为每种作物以及土壤、地形、天气、灌溉和已知土壤数据的每种组合建立的。 机器学习被用来比较世界各地的数据集，并根据地区差异调整这些建议。 动物生产力--许多环境、管理和遗传因素影响着奶牛的表现。 机器学习与统计分析相结合，有助于分析并提供哪些性状可能会被传递的概率，一个动物与另一个动物交配如何产生性能的预测。 妈妈捐出了她50%的基因，爸爸捐出了他50%的基因。 营养、天气、水、疾病、温度、护理、压力都是一个因素。 我们根据条件对动物进行分组，以进行这些预测。 这里有一个关于我们在人工智能方面工作的伟大专题，CIO review去年做了这个专题，并把我们作为未来值得关注的20家人工智能公司之一 Q11 主持人：作为第一个或许是唯一一个区块链农业项目，Dimitra的愿景是什么？这里面有些什么故事吗？ As the first farm and probably the only project that is solving agricultural issues, what is your vision and what’s the story behind it? Jon Trask：I realized many years ago while working on international supply chain projects and when I was contracted to build an identity system for an African nation that there was a huge need and opportunity in developing nations for agtech and that the people who needed agtech the most did not have it. That’s where Dimitra started and as we spoke to more and more governments around the world on their agricultural pain points and what they wanted to achieve we started building Dimitra’s platforms and what you see today is the culmination of all of that feedback. As new use cases emerge such as Dimitra DEFI loans for farmers, and Dimitra DEFI insurance for farmers we will keep building. Thank you for having me here today and I hope this was informative for your community. 多年前，我在从事国际供应链项目时意识到，当我受雇为一个非洲国家建立一个身份识别系统时，发展中国家对农业技术有巨大的需求和机会，而那些最需要农业技术的人却没有。 这就是Dimitra开始的地方，随着我们与世界各地越来越多的政府讨论他们的农业痛点和他们想要实现的目标，我们开始建立Dimitra的平台，你今天看到的是所有这些反馈的高潮。 随着新的用例的出现，如Dimitra DEFI农民贷款和Dimitra DEFI农民保险，我们将继续建设。 感谢你们今天邀请我来到这里，我希望这对你们的社区来说是有意义的。 感谢Jon Trask来到追风社，祝愿未来的Dimitra更加强大！ 本次 AMA 由追风社、Dimitra联合举办，感谢各位支持、关注，我们下期再见。 来源：金色财经lg...
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