Benedict Evans raises a number of good points and asks a bunch of good questions about the “steps to autonomy” in his recent blog post.
Right now we’re all talking about autonomous vehicles in terms of their level of autonomy – namely 1 through 5. L1 is some degree of autonomy, but in almost all situations, you still need a human driver. L5 is no human driver needed, ever.
But as Evans points out, the level of autonomy depends on the place, and it is unlikely – at least initially – that L4 or L5 will mean L4 or L5 in all environments. Here is an excerpt from his post:
It naturally follows that we will have vehicles that will reliably reach a given level of autonomous capability in some (‘easy’) places before they can do it everywhere. These will have huge safety and economic benefits, so we’ll deploy them - we won’t wait and do nothing at all until we have a perfect L5 car that can drive itself around anywhere from Kathmandu to South Boston. And so, if we call a car even L4, we have to say, well, where are we talking about? We might mean ‘most of this country’. But more probably, it will be L4 in one neighborhood, L3 in another and only L2 in a third - and a car might encounter all three of those on one journey. Put your route into the map and it will tell you if today is an L5 day or not.
Benedict Evans raises a number of good points and asks a bunch of good questions about the “steps to autonomy” in his recent blog post.
Right now we’re all talking about autonomous vehicles in terms of their level of autonomy – namely 1 through 5. L1 is some degree of autonomy, but in almost all situations, you still need a human driver. L5 is no human driver needed, ever.
But as Evans points out, the level of autonomy depends on the place, and it is unlikely – at least initially – that L4 or L5 will mean L4 or L5 in all environments. Here is an excerpt from his post:
It naturally follows that we will have vehicles that will reliably reach a given level of autonomous capability in some (‘easy’) places before they can do it everywhere. These will have huge safety and economic benefits, so we’ll deploy them - we won’t wait and do nothing at all until we have a perfect L5 car that can drive itself around anywhere from Kathmandu to South Boston. And so, if we call a car even L4, we have to say, well, where are we talking about? We might mean ‘most of this country’. But more probably, it will be L4 in one neighborhood, L3 in another and only L2 in a third - and a car might encounter all three of those on one journey. Put your route into the map and it will tell you if today is an L5 day or not.
Thinking about the Gartner Hype Cycle, there’s often (always?) a “peak of inflated expectations”, as well as a chasm that new technologies need to cross as they are being adopted.
Benedict’s article reminded me that we’re probably coming off that peak with autonomous vehicles and about to enter the so-called “trough of disillusionment.”
Autonomous vehicles represent a monumental shift in mobility, which will in turn impact our cities. That’s going to seem like an insurmountable challenge – until it doesn’t.
Below is a keynote talk by Benedict Evans about what’s going on in tech today and what may happen in the next ten years. It covers: the growth of mobile; S-curves; Google / Apple / Facebook / Amazon (who knew Amazon had so many employees?); machine learning; autonomous vehicles/impact to cities; mixed reality; crypto-currencies; and so on.
For those of you interested in crypto-currencies – and that appears to be everyone these days – it’s interesting to hear how Evans describes their current position at the beginning of the curve: “The tech works, but what’s the use case?” This is not to say the potential isn’t huge. It is. Automated trust. Distributed and programmable money. But the future is still unclear.
Thinking about the Gartner Hype Cycle, there’s often (always?) a “peak of inflated expectations”, as well as a chasm that new technologies need to cross as they are being adopted.
Benedict’s article reminded me that we’re probably coming off that peak with autonomous vehicles and about to enter the so-called “trough of disillusionment.”
Autonomous vehicles represent a monumental shift in mobility, which will in turn impact our cities. That’s going to seem like an insurmountable challenge – until it doesn’t.
Below is a keynote talk by Benedict Evans about what’s going on in tech today and what may happen in the next ten years. It covers: the growth of mobile; S-curves; Google / Apple / Facebook / Amazon (who knew Amazon had so many employees?); machine learning; autonomous vehicles/impact to cities; mixed reality; crypto-currencies; and so on.
For those of you interested in crypto-currencies – and that appears to be everyone these days – it’s interesting to hear how Evans describes their current position at the beginning of the curve: “The tech works, but what’s the use case?” This is not to say the potential isn’t huge. It is. Automated trust. Distributed and programmable money. But the future is still unclear.
The argument I was trying to make was that the hardware, similar to smartphones today, will likely become a commodity. More of the value will end up flowing to the firms that control the software.
To begin with, it seems pretty clear that the hardware and sensors for autonomy - and, probably, for electric - will be commodities. There is plenty of science and engineering in these (and a lot more work to do), just as there is in, say, LCD screens, but there is no reason why you have to use one rather than another just because everyone else is. There are strong manufacturing scale effects, but no network effect. [My link, not his.]
And here’s his conclusion:
So, the network effects - the winner-takes-all effects - are in data: in driving data and in maps.
That said, it is still early days for autonomous vehicles. Who knows if these network effects will end up being highly defensible or weak. There are still lots of assumptions and questions at this stage.
From a city building perspective, one of the major concerns with autonomous vehicles is that they could tempt us back to car-centric city planning. That would be a shame.
The argument I was trying to make was that the hardware, similar to smartphones today, will likely become a commodity. More of the value will end up flowing to the firms that control the software.
To begin with, it seems pretty clear that the hardware and sensors for autonomy - and, probably, for electric - will be commodities. There is plenty of science and engineering in these (and a lot more work to do), just as there is in, say, LCD screens, but there is no reason why you have to use one rather than another just because everyone else is. There are strong manufacturing scale effects, but no network effect. [My link, not his.]
And here’s his conclusion:
So, the network effects - the winner-takes-all effects - are in data: in driving data and in maps.
That said, it is still early days for autonomous vehicles. Who knows if these network effects will end up being highly defensible or weak. There are still lots of assumptions and questions at this stage.
From a city building perspective, one of the major concerns with autonomous vehicles is that they could tempt us back to car-centric city planning. That would be a shame.
