YouSaid · the spoken record

Peter Levine

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23
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2018-06-08
most recent
2018-06-08
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1
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  1. “What framework and what rules would you go and look at as CIOs on where you might optimize things based on people doing expert work in your environment? And I will bet you, if you start just thinking about this, because I went through this exact exercise, you will realize that every function within your company has the opportunity to be data-driven, has the opportunity to be iterative and cognitive based on the work that we're all doing to try to optimize things. And once you start thinking about this, then it becomes reality. And so I'll leave you with that. And next year we can revisit this. I guarantee you it will start to proliferate through the industry in the same way that some of the other things are.”

    2018-06-08 · a16z Podcast · a16z Podcast: The End (and Beginning) of Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  2. “But it starts a new thing. What has been interesting is when you start out with these, like when I start to talk about this stuff, literally everyone looks at me because I've been through this now like I'm crazy. Like, are you NUTS programming is going to be around forever and that? And as I start to think about it in my own mind and put some concrete examples and bring things together, it actually starts to make sense even to me. I mean, I thought about this. I couldn't really describe it now, you know, kind of over time you get better at sort of thinking about the examples and that. So what I would leave for all of you is what does it mean in your organization to utilize data? I mean, I gave the Salesforce example. That's a very real example. So where else can we model the experts in your environment? Where can we take those kind of that data? And then how do we provide”

    2018-06-08 · a16z Podcast · a16z Podcast: The End (and Beginning) of Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  3. “I mean, in some ways it's already happening. There are companies out there who look at Salesforce productivity, looking at the most productive salespeople in an organization, learn what they do, modify that, and then go give that information to so where everyone gets assisted by this new technology, a lot of that stuff is starting to happen. We may not think about it as the data economy or this change in programming, but it is starting to happen as we have these new models where we can process massive amounts of information and to where the outcomes really become, I'd say, digital assistance to humans to actually make them better, whether it's the football player, the auto mechanic, the accountant, the lawyer, or the salesperson. Each of those can be better based on observing the experts in that field. And I would argue it's starting to happen. And sure.”

    2018-06-08 · a16z Podcast · a16z Podcast: The End (and Beginning) of Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  4. “Yeah, that definitely resonates with me. I've seen a lot of history pizza itself, but the time scale is always what The most different to me. Free software really started in the 80s. GitHub came out in 2007. And for me, GitHub was very much influenced by the open source movement, but I think a lot of people, open source didn't become part of their vocabulary until maybe later, 30 years after free software. So with data, do you see a similar timeline?”

    2018-06-08 · a16z Podcast · a16z Podcast: The End (and Beginning) of Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  5. “Purview of each individual, and we will choose how we want to go dispense it. And I think in certain cases our data and what we produce will become valuable to consumers and there'll be a market for data. And rather than all our data going to centralized companies that are hidden inside of organizations, we all will have control over our data. And I think to have a market and to have economics around that data is really interesting. So I think that's kind of the way it takes.”

    2018-06-08 · a16z Podcast · a16z Podcast: The End (and Beginning) of Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  6. “Yes, I think we do. You know, there's this phrase out there, data is a new oil, right? And I have this vision that we all become our own oil well. And we are going to dispense data. And there are now ways where people can get paid for producing data, right? So instead of contributing my data to some centralized place, I can actually monetize that data, my data, to the extent that I want to, or I can contribute it. Examples might be if I have a camera on the front of my car and I'm going through streets and I'm recording visual information, I can choose to maybe offer that to some service that's going to make maps better. But maybe I get paid for that. Or if I have, let's say, our talk here, if somebody finds it valuable, maybe we get paid for it, right? And so I think there will be a lot of cases where data becomes”

    2018-06-08 · a16z Podcast · a16z Podcast: The End (and Beginning) of Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  7. “People in the 80s where you were hanging out, they were really into free software. Before a lot of us, I think, realized that there's something real there. It's not just about hippies. It's about there's a practical value. Do you feel like data's in a similar spot? It's our valuable asset. There's intrinsic value into keeping data secret. We once felt that about code. I don't know if I think that data being open is going to be something that works, but I think that a lot of people once felt that about code. Do you think that we're going to want to make data more open?”

    2018-06-08 · a16z Podcast · a16z Podcast: The End (and Beginning) of Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  8. “So then, I guess part of that is one of the things that we first talked about ever when we met was that you worked on x11, the X window systems. The Unix windowing system, X Windows. I've used that for a long time. It came out of the 80s. One of the big first, in my opinion, successful free software projects that brought sort of this idea of open source and free software to consumers. And it wasn't the best, but it was there and it was an option and it was great. So I think that is all to say that there was once a period of time where everyone believed that code's intrinsic data was in being kept private and there was value in code. And if I had this piece of code and you didn't, I had something that was worth something. And maybe you were in a position where while the industry felt that way, some of the hippies that you're not wearing sandals today, but some of the hippies you either went to class with or you were sure.”

    2018-06-08 · a16z Podcast · a16z Podcast: The End (and Beginning) of Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  9. “So that's an example of kind of taking correlated data and using that through a machine that I believe will start to really move us again from this notion of intent, find something to this notion of using data to find correlations that actually we may not have been looking for. I mean, to some people, the fake news is real news. So that's a little more arbitrary. But certainly the input of data, I believe, is going to be a super big deal.”

    2018-06-08 · a16z Podcast · a16z Podcast: The End (and Beginning) of Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  10. “Between the lights not working and the maintenance schedule for the light itself. That was something that the human, in your sense, right, terrible at finding things that we don't know that we're not looking for because you don't know, but a computer through looking at data and looking at patterns actually helped to determine in that situation a new thing that the human wasn't looking for to begin with. And that's where I would argue that code breaks down. Code will say the number of times that the current code, if light goes on, counter goes up by one, right? But if you're not looking at a maintenance schedule there or whatever, how would you ever know to look at a maintenance schedule?”

    2018-06-08 · a16z Podcast · a16z Podcast: The End (and Beginning) of Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  11. “And so let me parse the question on a couple of ways. When we know what we're looking for, we're actually very good at that. I can write a query and say, look for all numbers greater than 10. When you know what you're looking for, we're actually very good at that. What we're not good at is looking for things that we don't know that we're not looking for, right? And so I think what's going to happen, and we're already starting to see this, is systems in the future will actually help us see data in ways that we can't see it right now. So let me give you an example, a real example. There's a company that collect data off a traffic signal and to see how many red and green lights that occur in a traffic environment and the flow of traffic. That's the input. So that, I would argue, we could code that. But the system actually uncovered the fact that there's a correlation”

    2018-06-08 · a16z Podcast · a16z Podcast: The End (and Beginning) of Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  12. “Don't people just suck at interpreting data? So I think about fake news. I think about the lies that we all see going through the internet. And I think about programming. Like if we're trying to get a billion developers, don't we feel like people in general, including myself, are bad at data, but okay at telling people and machines what we want?”

    2018-06-08 · a16z Podcast · a16z Podcast: The End (and Beginning) of Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  13. “You know, I think that data science will become the new academic approach in computer science. There will be less coding and more about data science, new algorithms for data science, new approaches to understand the world around us. So we can call this software 2.0, which is moving from code to data. And I think many people will need to literally upgrade their skill sets to know much more about data than they will about code, in my opinion.”

    2018-06-08 · a16z Podcast · a16z Podcast: The End (and Beginning) of Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  14. “So then, for the current open source developers, people that today spend their time fixing bugs, sort of trying to make this piece of software better, not because they're making money off of it, because they want to become a developer who has this name. What does this do for them? Does this make them become data scientists, the current crop of open source developers, or do they now partner more with data scientists in the future?”

    2018-06-08 · a16z Podcast · a16z Podcast: The End (and Beginning) of Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  15. “So, I mean, imagine your dad is fixing some part of the car and that has been done by someone else. And imagine if somebody else has optimized effectively, has created the exact precise user manual for how to fix a particular part of the car. Imagine if your dad now was wearing goggles and it looked at what he was doing and the system was helping him to do a better job in fixing certain parts of the car. You take the experts who are the programmers in their field and they then push that knowledge off to everyone else and maybe your dad's an expert in certain parts of this and he can participate in it. It's the open source of data, right? Everyone's manipulating this to get better solutions.”

    2018-06-08 · a16z Podcast · a16z Podcast: The End (and Beginning) of Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  16. “A transmission. Well, I can wear goggles and I can record it, and I have the best expert going and fixing a transmission, and that person would then go back to that data. And of course, we need the right tools. So what are the tools for us to go manipulate this data? It won't be a spreadsheet. It will be some visual interface where I, as an auto mechanic, can go in and modify the output of what the system is doing. And in effect, we create a set of expert rules based on what the human does and then imagine that we go roll out those rules to everyone else who has to go fix transmissions or become a salesperson or a lawyer or an accountant or football coaches. And in my mind, by using data and having folks optimize the data, they actually become the next generation of programmers. They're not trained as programmers. They won't even know what a program really is. They're all manipulating data in the context.”

    2018-06-08 · a16z Podcast · a16z Podcast: The End (and Beginning) of Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  17. “Recognizing it is very complicated to do if then else on facial recognition. So imagine now when we have all the tools to go and do this, imagine that through repetitive looking at football plays, the system actually learns. And it learns what the right movements are and all of that. And then what does the coach do? The coach comes in and optimizes that model to say, you know what, the system got it a little wrong here. The quarterback should move 10 yards back, whatever. the coach in conjunction with the system actually is a programmer because the coach actually informs the data and they become a in my new definition of the world a programmer and you can take this now across any field whether you're a lawyer an accountant a salesperson and we can watch the best behaviors we can watch the best behaviors and best human interactions let's say i'm trying to fix”

    2018-06-08 · a16z Podcast · a16z Podcast: The End (and Beginning) of Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  18. “Compute time has all been based on if then else. If-this, do that, do this, right? And it gets very complicated, but it's all if-then-else. And basically, as a programmer, you have to know what you're asking for. You tell the computer what you want it to do. As opposed to the reverse is I want to look at data and I want to instruct the outcome as opposed to a priori knowing what the input might be. So let me give you an example. A football coach becomes a programmer. And if one had a program, a football game and said quarterback throws the ball to the receiver, if this, then that, and these guys go do this. It's an indeterminate problem. There's too many moving pieces like the program would be very, very complex to just run one play. Just like if you were doing facial recognition or voice”

    2018-06-08 · a16z Podcast · a16z Podcast: The End (and Beginning) of Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  19. “So originally I was thinking about this talk titling it the end of software development, but then maybe a little much. So it's really how do we go from 20 or 30 million developers to a billion developers. So in order to get to a billion developers, I want to change the definition of what a developer and what a programmer is, right? So when we think about certain data as the input into a system, we often think about right now like facial recognition is easier done, better done by a computer than done by a human right now. And I started to think about how data as an input to a system could actually change the world of programming such that everyone becomes a programmer. The reason why I think that programming ends as we currently know it is the declarative languages that we've used since the beginning of time, beginning of”

    2018-06-08 · a16z Podcast · a16z Podcast: The End (and Beginning) of Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  20. “That number. There are way more people who have their fingers in development than the numbers that GitHub can even tell, and it's growing. So the more you can open that up, I think, the better it is for everyone. So anyway, what I want to talk about, though, is not 20 million or 40 million developers. We talk at GitHub a lot about the next 100 million developers. What do we need to do to ensure people in the future can become developers? For me, it's a lot more of how do we lower the barrier to entry? How do we get more people on board? How do we make development this thing that a billion people want to use? I think for Peter he sees it almost, I don't want to put words in his mouth, sees a different route to the next billion developers, and I think you see it more from data than simplifying tools, making tools easier, lowering the barrier to entry.”

    2018-06-08 · a16z Podcast · a16z Podcast: The End (and Beginning) of Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  21. “We think there are 20 million people employed that are writing code, but the idea of what a programmer is someone who writes software in their free time or even professionally that's not counted in a programmer, it's way more than 20 million, it's way more than 40 million. It's growing every day. I think what that means isn't that the reporters are wrong or Gartner is wrong or RedMonk is wrong. I respect those firms a lot. I think really what that means is the term and the sort of definition is evolving and changing. We also see our customers, people that used to use JIRA, people that are in the marketing team that want to update just some copy on a website. They're increasingly moving to something like GitHub. And they're also giving us feature requests specifically for these teams of people that are not the core collaborate ship developer pipeline. So I think the answer to your question is 20 million full-time 40 hour plus developers, but don't”

    2018-06-08 · a16z Podcast · a16z Podcast: The End (and Beginning) of Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  22. “Oriented, consumer focused software developers building things for other software developers. And Peter has helped as a software developer himself me and the company really expand what we're thinking in terms of customers and in terms of our approach to business. So this was an opportunity for us, I feel, to talk about some of the things we agree on in terms of the next 10 years and some of the things we don't agree on. I don't think either of us knows the truth of what's going to happen in 10 years from now, but I think it's somewhere in the middle.”

    2018-06-08 · a16z Podcast · a16z Podcast: The End (and Beginning) of Programming · IDENTIFIED FROM THE TRANSCRIPT · source

  23. “Hi, everyone. Hello. Thank you for joining us today. I'm Chris, by the way. This is Peter. If you're confused about who was who I'm the GitHub person, this is the Andreessen person. But we've actually known each other since 2012. We've been working together for a long time. We're 10 years old. And we first decided to raise investment in 2012 after we were around four years old because we wanted to branch out from our own personal networks of software developers, from programmers. We wanted to get into the world of business. We wanted to really expand GitHub to anyone who is interested in building software. And Dreason has been a huge part of that, but Peter in particular has been there since 2012, since the very first meeting that we had. I say that not to say that Peter is this great guy because he is, but to tell you that he has interviewed me so many times that I'm very excited to interview him for once. So this is a big moment for me. I come from this world of really product”

    2018-06-08 · a16z Podcast · a16z Podcast: The End (and Beginning) of Programming · IDENTIFIED FROM THE TRANSCRIPT · source