 us minutes to do this introduction. So a couple announcements before we start for McLean faculty and fellows and those who will be coming to Case Conference at three, it's going to be an H300 today. If you don't know how to get to H300, ask Micah Paraska, he can lead us. Next week there is no noon conference for the ASBH meeting, which many people will be attending. The following week on 10-18, Dr. Will Parker will be presenting on crisis standards of care preparing for the next pandemic. So I urge you to come. That'll be an outstanding talk. So we have a real treat today. We have the benefit of having Dr. Jim Weinstein as our speaker. I'm going to say a few words about Jim and I am really just scratching the surface in terms of his accomplishments and accolades, but I want to give you a sense of how fortunate we are to have him join us. Jim joined Microsoft in July of 2018 as Senior Vice President for Microsoft Health, leading strategy and innovation. Today he leads Health Access and Health Equity globally for Microsoft. Jim is the immediate past Chief Executive Officer and President of Dartmouth Health. Prior to being CEO and President, he was president of the Dartmouth Physician Group and was the inaugural director of the Dartmouth Institute, home of the Dartmouth Atlas. He created the first value-based population health operating model locally and nationally grounded in the quadruple aim and he created a joint venture with Harvard Pilgrim to create a provider payer health plan for Northern New England. Jim has had... prescription for error broken out of their system, was published in February of 2016, and he's a contributor to the latest of AI that I strongly recommend, particularly in others' home AI revolution, medicine tax, or the beyond. So it's really a pleasure for me to talk with him. He was a speaker for us I think in 2008 at the center, but it's a pleasure. Great. Thank you. So great to be with you. I'm not sure if we can get rid of the echo sign, but I'll try not to echo, which may not be possible. Anyhow, there's a lot to talk about and what I wanted to start out with is because the world is kind of confusing right now. And for young people, you must think we're kind of in a crazy chaotic state. I think we've been in that crazy chaotic state for my whole life. And just to give some history, Microsoft was founded about 50 years ago. The first computer came out 50 years ago. Brezhnev and Carter were fighting. Inflation was at 14 percent or some crazy number. That was my first home mortgage was 14 percent. So don't complain about five or seven. We had a stagnant economy. There was the Iranian revolution. The hostage crisis and the Soviets in not in Ukraine in Afghanistan. So things haven't changed much. And unfortunately, unfortunately, that's going to be part of my talk because if this works, maybe it doesn't work. So now it's hooked up to this. Sorry. I'm going to take this off. Okay. Life. Anyhow, let's see what happened. I don't know what button you push. And I guess I have to echo. I'm just going to talk. Okay. Work in machine learning for imaging of the hydronephrosis. So two questions. One is, are we right to say it's artificial intelligence or augmented intelligence? That's one question I have. You don't like either. Okay. Actionable intelligence. Okay. Okay. Okay. That's great because what I'm thinking is this is all human being created and the machine is helping us to put it together in a clever way. And that's where the common people are thinking artificial means something. So what do you think about that? Because that's where it's a huge confusion coming on about artificial or augmented. Thank you. And second question is in the food chain of this whole process, where does the machine learning fits in or is it scope for chart GP 10 for every problem? It is machine learning. And if you think about looking at pictures and say, you know, draw a cat. So I could ask GP T to draw. We've done this access to draw a unicorn. GP T three, you know, I had pieces all over the place that looked like Play-Doh. But when you ask GP T four with some plugins, it actually kind of looked like a unicorn. But machine learning is looking at lots of images or text and learning from that, which creates AI. So most of AI is machine learning. And, you know, the closed test C L O Z E that really is predicting the next word. And that's how these things theoretically work. But I kind of like the outcome razor. I think the reflex, you know, think jumps. Oh, I know what happened there. I went to this international neuron. I can't figure out this, you know, huge trillion dollar parameter or trillion parameter stuff. But it happens so fast. It's like a reflex to me. So yeah. Other questions? Yeah, I had a question. I think, you know, I think we can all see the importance in terms of the ethics of AI with regard to regulation. But what do you think about the commercialization of AI? I mean, most of the development seems to be seen as a commercial opportunity by a lot of companies around the world. In recent history of medicine, almost every new technology comes with a large price tag and ends up increasing the total cost of care. That's already, as everybody knows, somewhat unsustainable in the US. How is AI going to be commercialized? How do we make sure that this actually helps the system rather than helping entrench commercial interests that are developing it now? I think I understood your question. Not totally so. Just tell me if I got it right. You're asking how this gets commercialized and what's up and down side of that. Basically, fair. Yeah, I'm a capitalist. I think people who want to do wonderful things should do what you've reimbursed for them, but not at the expense of others. Okay, so what I'm trying to do in my job is leading global equity for Microsoft and access is to make sure we move the whole curve to the right, not just some people. And my fear, as I said in the beginning with this technology, we're just going to create another lane, more resources will be spent, and we won't change those maps that I've been doing for 40 years now. That's a failure. And so I'm saying the same things at Microsoft. And so I'm hoping that like Uplift AI 211 will be free and that any money made will go back to the systems or communities that actually used it to help support those things. So that's my motivation. Does Microsoft deserve to make a profit? Absolutely, because it can make things like this possible for everybody. What's the right profit? I'm not the person to judge that. I am going to speak out on behalf of everybody to move that curve to the right. But I can't affect decisions to stockholders. But you in this room working with me can affect what happens. And don't be angry if somebody makes a lot of money. Some of these people should. This is miraculous. But let's make sure that it benefits everybody.