The end of the beginning

I gave this presentation at a16z’s annual tech conference last week.

Close to three quarters of all the adults on earth now have a smartphone, and most of the rest will get one in the next few years. However, the use of this connectivity is still only just beginning. Ecommerce is still only a small fraction of retail spending, and many other areas that will be transformed by software and the internet in the next decade or two have barely been touched. Global retail is perhaps $25 trillion dollars, after all.

Meanwhile, as companies address more and more of this with software and the internet, they do it in new ways. We began with models that presumed low internet penetration, low speeds, little consumer readiness and little capital. Now all of those are inverted. So, we used to do apartment listings and now Opendoor will buy your home; we used to do restaurant reviews and now you can get a hot meal delivered to your door. Tech is building different kinds of businesses, and so will take different shares of that opportunity, but more importantly change what those industries look like. Tesla isn’t interesting because of what it does to gasoline, but because of what it does to the car. Netflix changes TV, but so does Twitch.

Finally, as we think about the next decade or two, we have some new fundamental building blocks. The internet began as an open, ‘permissionless’, decentralized network, but then we got (and indeed needed) new centralised networks on top, and so we’ve spent a lot of the past decade talking about search and social. Machine learning and crypto give new and often decentralized, permissionless fundamental layers for looking at meaning, intent and preference, and for attaching value to those.

 

Tesla, software and disruption

When Nokia people looked at the first iPhone, they saw a not-great phone with some cool features that they were going to build too, being produced at a small fraction of the volumes they were selling. They shrugged. “No 3G, and just look at the camera!”

When many car company people look at a Tesla, they see a not-great car with some cool features that they’re going to build too, being produced at a small fraction of the volumes they’re selling. “Look at the fit and finish, and the panel gaps, and the tent!”

The Nokia people were terribly, terribly wrong. Are the car people wrong?

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Ways to think about machine learning

We're now four or five years into the current explosion of machine learning, and pretty much everyone has heard of it, and every big company is working on projects around ‘AI’. We know this is a Next Big Thing. I don't think, though, that we yet have a settled sense of quite what machine learning means - what it will mean for tech companies or for companies in the broader economy, how to think structurally about what new things it could enable, and what important problems it might actually be able to solve.

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