A highlight from Cade Metz on Genius Makers

Eye On A.I.
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Automatic TRANSCRIPT

I thought i'd start by having you introduce yourself. Tell us what your background is. How you came to write the book. I know that a lot of the experiences began well before your tenure at the times and then i have some questions. Obviously we can talk from there. My name is kate mets. I'm a correspondent. Ed tech reporter with the new york times based in san francisco bureau. Just because this is where all the tech is here. I live in berkeley and commute across the bay to the bureau when i'm not traveling around the bay area or various other places and this is my first book and it very much dove tails with my beat over the past few years since i joined the times a as people call it has become central to my be if not a very large part of the beat and so glut of what i have done what the times has kind of woven into the book and has worked out. Well as far as i'm concerned that these you wrote for the register. I believe then for wired you appeared in the alpha go documentary so you've been intimately involved with this world longer than almost any journalists out there i think. Can you talk a little bit about how you initially got involved with machine learning in particular deep learning well. It happened when i was with wire before. I was a senior writer with wired magazine. Also based in san francisco. And i ran a team that covered what you might call the tech and this became one of our core themes i was at wired as deep learning as they call it started to take off and the way we really worked was to find where the industry is really changing and cover that really well and this is one of those areas where the change was enormous and in many ways unexpected and rapid and so with other quarters. I was the editor of the section. It wired with other reports like bob macmillan at the wall street journal yellow hernandez. Who's now at the journal as well. We really started to cover this area. And they have actually both left wired. And then as i joined the times it was part of my pitch at the time this area in particular needed to be covered covered. Well i think a lot of people misunderstand what is needs to be covered and this deep learning space and we can discuss. That is where the change really was a lot of hype around and there's a lot of frankly nonsense that gets thrown around about ai of the layperson understands what that term means because gets applied to everything. But there's this real change that has happened over. The past ten years deserve being covered. It wired certainly deserve being covered at the times is and will continue to affect people's lives and it deserved to book a you and i talked about this years ago that so many of the people dry being. This change are so interesting and the narrative the very real narrative behind this beat that i covered time needed to be covered in a different way. You know i tell everybody this is a book about a i. But it's really about the people and i feel that if the reader can understand who these people are and can understand the story of these people that they will understand the technology so much and that's one of the things i appreciated about the ball coming. I've read terry sunau skis deep learning revolution. I've read pedro domingo's the master algorithm. Which you you mentioned in the book and they're very much in the science and you manage talking about the science. In a way that lay people can understand avoiding getting into the weeds. I found the the stories fascinating partly. Because i met a lot of the people and didn't know all these stories behind them the initial anecdote of geoff hinton selling his shell company to google. I isn't it just so amazing to the point where you know you wonder if it's real but it let me tell you every fact that is absolutely real an astounding story and the details psych. Like him sleeping on the floor of between two crazier between two bed between two bells. The harrah's hotel. In lake tahoe. One of my first questions is the title genius makers. I wasn't sure whether you meant people like geoff. Hinton and yama in the day were making machines that are in effect. Geniuses you were talking about organizations like jeff facebook and google who are bringing people into this world or if you were talking about the algorithms some cells. What was in your mind right. I bet you hit it that it has many different meanings right. Who were the geniuses. Who were the makers is it. Is it the machines that are genius or is it the people you know it is it. Ironic is not. I think it means a lot of things and it's going to mean a lot of things to many different people. Meaning the the people who read the book and the reason we eventually settled in at title though is is that it does show you. It's about the builders right the builders and the makers of the technology. What i kept telling myself at my darkest moments when i thought. Why did i take on this. Enormous project is it ever going to work. What i kept telling myself was. If i can just show people what. Jeff hinton is like in the book will be a success and the data plaza the whole book in that. It's about these people who are interesting in so many different ways. And if i can just show the world who they are and what they are like and what they had done and the idea kind of bounce around in their head than the book work and so

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