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  1. #1
    WHT-BR Top Member
    Data de Ingresso
    Dec 2010

    [EN] Marc Andreessen: "timing is the hard part"

    Zach Ullman
    May 23, 2017

    Transcript: A16z’s Marc Andreessen with Axios’ Dan Primack
    30 min read

    At the recent a16z Tech Policy Summit, Axios’ Dan Primack interviewed a16z’s Marc Andreessen. The podcast is available here, and the transcript I typed up is available below.



    So there’s been two narratives on the tech industry and on tech change over the last decade. One narrative has been sort of continuous in years one through nine over the last decade which is tech is dead, tech is over, tech is dumb, tech is stupid, tech is a bubble, it’ll crash any minute. Silicon Valley is just a bunch of kids running around raising too much money and blowing it. Producing a bunch of photo sharing apps and like the golden days of innovation are over and like all this stuff is a bunch of hot air and it doesn’t manner. In the last 12 months, it’s flash cut from that to, tech is overwhelmingly impacting the world and the economy, tech is having way too dramatic of an impact, tech is becoming way too important, tech is fundamentally affecting the economy, changing jobs, destroying jobs, robots, AI, the Terminator. It’s all of a sudden come crashing down. So how do you reconcile these two diametrically opposed views — it’s worthless or it’s infinitely powerful?


    The narrative has switched that 12 months ago from stupid to evil in one with nothing in the middle.


    The way to reconcile the stupid versus evil position, the way to reconcile it is they are both true. They are true in different sectors.


    My point is: we are really mad about the sectors in which tech is having a big impact and then we are also very mad for the completely opposite reason, the sectors where tech is not having a big impact.


    So TVs are going to cost $10 and healthcare is going to cost $1 million. This is where this is all headed.

    I grew up in rural Wisconsin. If you saw the photos of Marc Zuckerberg on the farm a few days ago learning how to milk a cow, it was not from where I grew up.


    So I grew up in the rural Midwest, specifically rural Midwest 1970s and 1980s. This was at a point where agriculture was in severe distress and had been through a 200 year process of transformation, and there was all kinds of chaos happening in agriculture but lots of farmers, and actually manufacturing was in distress. We had light manufacturing where I grew up, but we were right next door to Michigan which had the onslaught from the Japanese and the German automakers in the seventies and eighties. We felt all this really acutely. This is the world that I grew up in. Again though what I would say is I think it’s a coastal conceit that the problem is these idiots can’t keep up with the change. I don’t think that’s the problem. At least that was not the problem I experienced when I was there. The problem was, it was not a question of the rate of change, it was a question of whether the opportunities existed. It’s hard to put yourself in this frame of mind if you didn’t grow up in a place like this but it’s not that people work their entire lives in the Midwest doing the really brutal, rigorous work of farming.


    Most folks in those jobs don’t want their kids to spend the rest of their lives working. They are just like any other parent. They want a better life for their kids, and the question is not so much what happens to that job, the question is what’s the opportunity? Where are things going to go in the future?

    AI has this long history. AI is no a new topic. AI has been a new topic continuously since the 1940s. The concept was first invented in 1942 or 1943 by Alan Turing and his colleagues, and there’s been wave after wave after wave of AI. If you go back and read all of this stuff from when it happened, you have wave after wave after wave of AI hype and then disappointment, and in fact, there was a huge AI bubble in the eighties where there was tons of AI companies that made all these promises — expert systems, some of you may remember. Medical diagnosis that could be transformed into all these things, and then it crashed so hard that the entire field almost got completely written off in the following 20 years. The thing that does seem to be different is, it is working. In the way that AI actually works, it is working now. The drone stuff, we are going to be able to do autonomous drones which I think is a very good thing. We are going to be able to do self-driving cars, but the idea that AI is sort of this magic pixie dust that we sprinkle on anything and all the programmers go away — it’s just science fiction. If anything, what’s actually going to happen is the programmers are going to be higher paid because they are going to be higher productivity.

    I actually have reached the point where I think that all of the ideas in tech and all of the ideas in Silicon Valley are good ideas.


    So timing is the hard part. We have all these people with all these incredible ideas, and many of them are happening. Then there is going to be a whole generation of founders this time just like there were last time and the time before that where they actually have the right idea. They get the timing wrong. The startups can’t survive long enough. When you start a company, it basically starts a five year fuse. If the idea doesn’t hit critical mass sort of in society with the customers in the first five years, you basically lose the company, and then somebody else picks it up and runs with it. That is probably the single biggest thing that tortures us. I bring it up because so much of the dialogue when people comment on tech, so much is around good idea versus bad idea which I think is actually not the main question.


    There is not a lot of historical evidence that either the inventor of the new technology or anybody else can anticipate the effects very well. My favorite story, there are lots of example of this is, Thomas Edison invented the phonograph, and like literally they didn’t quite know what it was going to be for, and they made a list of the use cases and applications. One thing is music was not on the list. It was just viewed as why would you do that? Why would you listen to music in your home? And then the other was Edison’s personal number one thing which he thought was a slam dunk for market adoption was of course listening to religious sermons. So being a God fearing Christian white male in that area, you would come home at night, you would take off your black bowtie, you would sit back, and you would listen to religious sermons for two hours, and that would be the killer use case. And of course he therefore thought it would be an instrument of great moral purpose because it would make everybody a lot more ethical.


    When bicycles were invented, there was a moral panic. People freaked out. Bicycles were the first mechanism that allowed unmarried young women to easily get to the next village. Seriously. Young women would buy a bicycle and they would get on and they would go to the next village. This freaked out the moral authorities at the the time so much that the popular magazines at the time created a concept and popularized it that they called “bicycle face.” Bicycle face is if you were an unmarried young woman, and you rode a bicycle, your face would permanently lock into because of the exertion, and you would never be able to find a husband and get married. I swear to god this is a real thing.

    The open discourse is drying up. The private discourse is probably getting more interesting because people are talking in private about the things they don’t feel like they can comfortably talk about in public. This is always one of the things you wonder, is if you suppress speech in the public sphere how much of it just happens in the private sphere, and how much does it actually mutate and possible get worse in the areas that you care about in the private sphere? Some people think this is the big part of the Trump phenomenon — the concept of the shy conservative or the Trump supporter who won’t admit it.

    By the way for example, I will tell you this, I know of exactly two Trump supporters in Silicon Valley. Two.

    So I know of two of a tech community of hundreds of thousands of people, and so I guarantee there are Trump supporters in Silicon Valley who feel like they can’t say so. What does it do to somebody when they feel like they literally cannot express themselves? That’s just such an unhealthy place to get to, and I do really worry that is the place we are getting to.
    Última edição por 5ms; 30-05-2017 às 12:55.

  2. #2
    WHT-BR Top Member
    Data de Ingresso
    Dec 2010

    Invention and Timing


    In a lot of ways, the key to what we do as investors is timing. I think the ideas are often obvious. I think actually the ideas are often tried many times in a row before they ultimately work.

    Take pen computing. When I got to the Valley all the VCs had just gotten their heads handed to them on pen computing, including Apple with the Newton. The Newton in 1989 and the iPad in 2009 are essentially the same product just 20 years later, with 20 years of advances in software and hardware, but the same basic product.

    A lot of very smart people though the Newton was going to be it. They thought the time was right in 1989, and a lot of people were super-skeptical as a result in 2009 when it came around again. But the idea was obvious.

    In fact, Apple took a Newton TV commercial from 1989, it was sort of an inside joke at Apple, and re-shot it frame for frame, word for word for an iPad commercial 20 years later. It’s the same thing. You knew the tablet was coming, people knew the smartphone was coming for a very long time. AI (artificial intelligence) people knew machine learning was going to take hold, social networking research has been going on for decades. In my own work, the web drew on 30 years of work in interactive computing, hypertext and online libraries.

    I think most of the big breakthroughs in the next 20 years already exist, they are already running in labs. You watch that all evolve, you watch people try and fail to commercialize it and fail. And you try to zero-in on a few things:

    – When is the really right time for this thing to happen?

    – When has the technology really reached the point where it actually works?

    – And there is a sociological component, which is, when is the world ready for the new idea?

    – And the psychological component, what will the reaction of customer No. 1 actually be? Either, “Wow, this is great!” or “I thought this would work, but I am actually going to throw this in my closet.” Like everyone did with the Newton.

    – There is the people question of course, who is going to be the person and the team that are going to catalyze the company and bring the idea into the form of a commercial product?

    And again, using these signals, this data, you try and figure out the timing, which is the key to the success or failure of almost all this stuff.

    I am firmly convinced that invention in something that happens over long periods of time, by lots of very smart people, playing each others’ ideas against each other. I think there are very few eureka moments, very few genuinely new ideas.

    It’s the process of combination of lots and lots of smart people working the field over a very long period of time. And then it catalyzes, and that is where the magic is, and where the most fun part of this is. That magic moment when it all comes together.

    And the great thing about being in the venture capital is, if it fails, we’ll try the same thing five years later. Almost certainly with new people, because the previous people will be too traumatized to try it again.

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