The following is a conversation with Daphne Koller, a professor of computer science at Stanford University, a cofounder of Coursera with Andrew Ng, and founder and CEO of Incitro, a company at the intersection of machine learning and biomedicine. We're now in the exciting early days of using the data driven methods of machine learning to help discover and develop new drugs and treatments at scale. Daphne and Incitro are leading the way on this with breakthroughs that may ripple through all fields of medicine, including ones most critical for helping with the current coronavirus pandemic. |||||||| HIDDEN IN PREVIEW MODE ||||||| Stay strong, we're in this together, we'll beat this thing. |||||||| HIDDEN IN PREVIEW MODE ||||||| I hope that works for you and doesn't hurt the listening experience. |||||||| HIDDEN IN PREVIEW MODE ||||||| Since Cash App allows you to send and receive money digitally, peer to peer, and security in all digital transactions is very important, let me mention the PCI data security standard that Cash App is compliant with. |||||||| HIDDEN IN PREVIEW MODE ||||||| And after five years in August, 2016, wrote a blog post saying that you're stepping away and wrote, quote, it is time for me to turn to another critical challenge, the development of machine learning and its applications to improving human health. |||||||| HIDDEN IN PREVIEW MODE ||||||| That being said, curing disease is very hard because oftentimes by the time you discover the disease, a lot of damage has already been done. |||||||| HIDDEN IN PREVIEW MODE ||||||| We've been able to provide treatment for an increasingly large number, but the number of things that you could actually define to be cures is actually not that large. So I think that there's a lot of work that would need to happen before one could legitimately say that we have cured even a reasonable number, far less all diseases. |||||||| HIDDEN IN PREVIEW MODE ||||||| Would Alzheimer's and schizophrenia and type two diabetes fall closer to zero or to the 80? I think Alzheimer's is probably closer to zero than to 80. |||||||| HIDDEN IN PREVIEW MODE ||||||| They're almost certainly a heterogeneous collection of mechanisms that manifest in clinically similar ways. |||||||| HIDDEN IN PREVIEW MODE ||||||| Now, in schizophrenia, I would say we're almost certainly closer to zero than to anything else. |||||||| HIDDEN IN PREVIEW MODE ||||||| That's not to say that they're identical. |||||||| HIDDEN IN PREVIEW MODE ||||||| Okay. |||||||| HIDDEN IN PREVIEW MODE ||||||| Some of those have to do with DNA damage that accumulates as cells divide where the repair mechanisms don't fully correct for those. |||||||| HIDDEN IN PREVIEW MODE ||||||| It's a learning, it's a kind of learning mechanism. |||||||| HIDDEN IN PREVIEW MODE ||||||| So I think a wonderful aspiration would be if we could all live to the biblical 120 maybe in perfect health. |||||||| HIDDEN IN PREVIEW MODE ||||||| I think that's up for debate but I think an increased health span is a really worthy goal. |||||||| HIDDEN IN PREVIEW MODE ||||||| There's been dribs and drabs and some interesting machine learning that has been applied, I would say machine learning slash data science, but the last few years are starting to change that. |||||||| HIDDEN IN PREVIEW MODE ||||||| But what we are doing in Citro is actually flipping that around and saying, here's this incredible repertoire of methods that bioengineers, cell biologists have come up with, let's see if we can put them together in brand new ways with the goal of creating data sets that machine learning can really be applied on productively to create powerful predictive models that can help us address fundamental problems in human health. So really focus to get, make data the primary focus and the primary goal and find, use the mechanisms of biology and chemistry to create the kinds of data set that could allow machine learning to benefit the most. |||||||| HIDDEN IN PREVIEW MODE ||||||| So how do you create those data sets so as to drive the ability to generate predictive models which subsequently help improve human health? So before we dive into the details of that, let me take a step back and ask when and where was your interest in human health born? Are there moments, events, perhaps if I may ask, tragedies in your own life that catalyzes passion or was it the broader desire to help humankind? So I would say it's a bit of both. |||||||| HIDDEN IN PREVIEW MODE ||||||| The data sets at the time on the biology side were much more interesting, both from a technical and also from an aspirational perspective. |||||||| HIDDEN IN PREVIEW MODE ||||||| And I said, would that be helpful? Would that change treatment? He said, no, there's only prednisone. That's the only thing we can give him.

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