[ocdtrekkie]

It's not just going to be about straight miles driven, it's about the technology being focused on and what's possible with it. Both Tesla and comma.ai are focusing primarily on what the car can see and do with it's own sensors... Google's cars are only functional on roads excessively mapped far above the normal Google Maps level. Google's existing strategy for self-driving cars isn't practical at a national level because of that extensive mapping requirement, and it possibly never will be. (Google's cars may have driven x number of million miles, but it's all the same very small number of roads.) And while prices drop as technology develops, bear in mind that in addition to all of that, Google's sensor platform is the most expensive out there.

Additionally, I've read some really interesting articles about research other car manufacturers have done. For instance, Google has never tested in bad weather, but Ford has been working on self-driving cars that work in snow. And while Google just assumes the humans are meant to be 'along for the ride', Volkswagon did some really good UI work, in terms of figuring out how to make the car's actions predictable, and hence, less scary. (Essentially, the car indicated to the driver what it was about to do before it executed a maneuver.)

Google is really good at capitalizing on their self-driving car project for marketing purposes, but it's extremely unlikely it'll ever be a market leader.

[petra]

>> Google's existing strategy for self-driving cars isn't practical at a national level because of that extensive mapping requirement, and it possibly never will be.

>> Google's sensor platform is the most expensive out there.

>> Google has never tested in bad weather

What about a self-driving cars as a service ? they can be the first to start a very profitable service that is limited in area and in weather even thought the sensors are more expensive(and they can claim "we aren't cutting corners like everybody else!")

And that could be a great place to be in, strategically.

[Fricken]

A few years ago I was 100% gung-ho about Robotaxis, and I went through a mild depression last winter when I gave way to mounting evidence that it's a really hard problem and the 'it's 30 years out' naysayers are probably correct. It just sucks being wrong.

Google's Koala cars are functional under only the most idyllic, constrained and carefully monitored conditions. There's a huge laundry list of unsolved, and unknown problems between what Google has demonstrated so far and where they need to be technology-wise to run a robust, reliable, profit generating service at the scale needed to cover their R&D.

The casual thought experimenter generally fails to recognize the frequency with which they utilize higher level reasoning when driving that's well beyond the limits of the current state of the art in AI. Nobody has the slightest idea of how to solve this, let alone dig into all the as-of-yet not understood logistical problems inherent in commercializing the technology, an unexplored realm rife with any number of unknown unknowns.

The real world is a very messy place. Unlike Google, Uber is eyeballs deep in the messiness of the real world, so they're probably better poised, though a lot can change in 5 or 10 years. The competitive playing field has been so dramatically altered in the past 2 or 3 years that the days when Google was the only company anyone took seriously feels like ancient history.

With regards to the sensors, my bet is that by the time AI's capacity to reason is where it needs to be, the sensors and software needed to see and interpret the dynamic driving environment will be dirt cheap. Probably all you'll need is cameras, their cost keeps going down and the state of the art in image processing is progressing and will continue to progress.

[ocdtrekkie]

Sure, they could definitely do similarly to what Uber just announced, in a small scope area like the Bay Area suburbs. But that's not likely to be a high margin product, certainly not something Google would want to hang onto long term. It's far smarter to be selling software licenses or cloud access to millions of units built by other car manufacturers and operated by individuals or other companies at scale, that's where the money is.

But you also have to realize that you'll also highlight the weaknesses of the technology. People may not be able to easily specify to the car where they'd like to disembark. What if people want to be taken just outside the service area? Uber is including a human with their self-driving project for now, which doesn't save them (or you) any money.

Google learned from Glass that a small number of users and a lot of public attention and hype about a product can quickly eviscerate it. The technology was good, but people without hands-on experience misunderstood it, and a couple small incidents became national news. A small rollout can just as easily kill your project as kick it off.

[petra]

Even if Google decides to sell access to other companies, at scale, they can still say: "our service only works in summer , in that list of expanding areas". And of course if they sell access on a per-trip-basis, it's almost as if they own the service themselves.

>> What if people want to be taken just outside the service area?

Google is currently trying to be the comparison search engine for people who want to order rides - via their Google Maps. If they sucsseed, they'll just fit you with the right service according the limitations of the self-driving car ,etc.

And regarding Google Glass - IDK. Even Uber is marketed on a city-by-city basis,

[jfoster]

Tesla is either already mapping roads through the sensors on their cars, or is only one software update away from doing so. Their mapping data will be a lot fresher than Google's.

[ocdtrekkie]

This is true but mostly irrelevant, because mapping data is the least valuable self-driving data. Google focuses on it because Google has it already. Google Maps is one of the things Google has that few else have, so it's obvious for them to build their technology on it... nobody else can copy them.

But if you have the most cars collecting the freshest data, you still have to bear in mind, the car collecting that data, is currently relying on the old data. Which means your cars can't trust the map data. And the reality is, with how much things in the real world change, your map data will never be trustworthy. You can have it, but you can't rely on it.

Which is a better self-driving car? The car that can look at a cloud-based 3D map of every object in the entire town, assuming it's current, and decide on a route? Or the car that can ping Google Maps, get told "turn left on Main, right on Washington" then entirely from it's live surroundings, decide how to drive?

[obmelvin]

Tesla cars don't have enough sensors to capture great data. It will require a lot more than a software update for then to record data on par with googles quality

[jfoster]

They claim autopilot uses "cameras, radar, ultrasonic sensors and data."

I think even just the cameras alone would be valuable. It seems a Tesla has a better idea of what's going on around it than a human would, so these sensors should be at least close to sufficient for training an autonomous driving agent.

[kllrnohj]

> Google's cars are only functional on roads excessively mapped far above the normal Google Maps level.

Since this is a core part of your argument, I'm gonna go ahead and [citation needed]

I've not heard anything of the sort and I've seen Google's cars on all sorts of roads. Plenty of their talks have been about the cars detecting anomalous situations and reacting appropriately, as well.

[ocdtrekkie]

There's no reason to believe they've exceeded this limitation: http://www.slate.com/articles/technology/technology/2014/10/...