 In the AI world, data is so important and yet people have concerns, privacy concerns. How do we strike the balance there? Data is definitely, it's going to be very exciting that we'll be able to preserve privacy and still learn a lot from the data, you know, like which crop should you plant? If we get all the data from the farmers without their means so we don't invade their privacy but giving better farmer advice or seeing here in India, you know, the top 10% of teachers are so good and saying, okay, what are they doing and how do we spread that to the other people or even if there's some new nutrition approach, you know, sometimes it works and sometimes not. And so because you have the medical record, the ability to kind of track and say, okay, this is working very well or this isn't, you know, we can be a lot smarter without threatening individual privacy. I'm going to give it a two-fold one, we need to train the common man for quality data. We need to have quality in our data, we need clarity. Second, the data owner should know what he's asking for from me, what work he's asking for. If he wants to make an agreement with him, he should allow it. And first, he should be priority research. Research data should not be too important or research will be too expensive. And the research institute should also be sure that I'm using your data, it's for the same purpose, it's for global good, for the common man's good. So I believe that no person in the world will be disarming. I think it's interesting that some of these digital systems create efficiency by getting rid of the middleman and you know that's super beneficial. I think it's interesting that some of these digital systems create efficiency by getting rid of the middleman and you know that's super beneficial.