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.
Uber is now offering a service to retailers so that they can have customers picked up and ferried to stores to make purchases. At the same time it is also reaching out to restaurants and telling them what other meals they can produce which are in demand from takeout customers at its UberEats service.
These might be two services offered by the same company but they are also a further iteration on the evolution of the declining cost of providing transportation services model which Uber disintermediated when it launched ride sharing.
The bigger question for the company is how will it keep up if it is not the first company to develop driverless vehicles.
This article from Sciencemag.org on the impact autonomous vehicles have on traffic fluidity may be of interest. Here is a section:
The results were impressive. In the figure eight scenario, replacing just one of the 14 “human”-driven cars with a self-driving car doubled the average car speed, the researchers reported last month at the Conference on Robot Learning in Zurich, Switzerland. In the merge scenarios, replacing 10% of the regular cars with self-driving cars also increased overall traffic flow, in some cases doubling the average car speed. The self-driving cars sped up traffic in part by keeping a buffer between themselves and the cars in front of them, forcing them to brake less often. Giving the algorithm control over traffic lights in a Manhattan-style traffic grid increased the number of cars passing through by 7%.
The tested algorithms leave plenty of room for improvement, says study author Eugene Vinitsky, an AI researcher at the University of California (UC), Berkeley. That’s why his team is making its programs public. “If anyone has a brilliant solution or algorithm, you can use this framework to test [new ideas],” says Meng Wang, a transportation engineer at Delft University of Technology in the Netherlands who’s done related work.Back to top