Now to something that a lot of people are talking about this afternoon and that is using artificial intelligence in the fight against the coronavirus. Let's talk more about it this afternoon with Arter Qulian. He is a machine learning expert and data scientist in Los Angeles. Thank you so much for joining us this afternoon. Talk a little bit about how technology is helping in this fight. Thanks for having me. So we're a global distributed international group of volunteers that is primarily focused on building AI and machine learning tools to help research community better understand where to focus their efforts. So we're working with a giant data set of scientific papers and trying to extract the most relevant information for researchers to focus on. So what type of information are you in fact looking at? So we're actually working with the White House back challenge. They presented a list of 10 questions that research community is learning requesting to learn and we're primarily focusing on four of those 10 tasks which are what are the risk factors of COVID-19? How geography affects virality? What do we know about transmission and incubation? And what do we know about vaccines and treatments? And how do you think you'll go about being able to answer those questions? So we're building a tool kind of a more comprehensive search engine for this specific problem. We're not trying to produce any insights or make any claims that there is some cure. We're simply building a tool for research community to connect the dots much faster with a you know limited resources that they have right now. So a great analysis. And that really is important. I'm sorry I didn't mean to interrupt but that is important getting that information together quickly. Correct and the great analogy is hammers. It's a tool. It doesn't instruct you how to swing or where to hit the nail but when you do use hammer to hit a nail it's a game changer. And that's exactly what we're trying to provide to research community right now. And that you know timing is extremely important right now. Yeah we're all looking for that game changer. I talked to me though about some of the challenges that you face in trying to do this. Yeah absolutely. And until today the biggest challenge was computational resources and thanks to Google and Amazon today they provided a lot of free credits for us in terms of the cloud computing because some of these machine learning algorithms take a lot of computational power and time to run and that's why like as volunteers we're not able to commit personally for you know thousands of dollars to run these models. The other problem is you know cross-discipline communication because we have virologists epidemiologists, toxicologists and we're trying to bridge the communication between them and machine learning engineers. And as you can imagine that's very very hard. Yeah I can't imagine well thank you again for what you're doing and and we're all looking forward to as I mentioned that game changer appreciate your time thank you. Thanks. Alright it was a great