Comment by aerovistae | Hacker News Reader

Comment by aerovistae | Hacker News Reader

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The strategy Musk has clearly been using for a long time now with this is to put as much hardware and software into the field as possible, often even without the customers knowing it's there, and gathering vast amounts of data from it, and gradually forcing it into widespread availability and acceptance, all while letting the system learn and improve itself, which is a necessary step.

He's doing what he does best: forcing a hard change on an established system.

Autonomous driving not allowed? Well, we'll give them "Autopilot"-- make sure to keep your hands on the wheel! Nope, it's not autonomous, it's Autopilot! It just happens to have all the hardware needed to be fully autonomous, and Autopilot will "gradually gain new capabilities." Questionable? Sure. Best way to make an extremely hard industry transition? Almost definitely.

It would be a chicken and egg problem if he didn't do this. Can't test the system extensively beyond the lab without regulations, can't have a system that doesn't meet regulations because it hasn't been tested enough yet. He's just sidestepping this dilemma.

It's an extremely bold commitment on Tesla's part. The available details are a bit ambiguous, but it appears they're putting $8k worth of hardware into every new car though Tesla owners need only pay for it if they want it enabled.

All this in spite of tremendous uncertainty not just with regards to the regulatory environment but to the not yet fully developed capabilities of their own software.

There's no way it's $8k of hardware. The hardware is pretty simple, it's the r+d that's expensive

Someone needs to pay for the R+D before the hardware can exist, so I don't see anything wrong with considering R+D as part of the cost of the hardware (its "worth" if you will). The alternative is only considering the raw materials as part of the cost of building something.

Right, but the parent comment was questioning the widsom of installing the hardware in every car. My point is the pricing model is that people using the software pay for it. The price of putting the hardware in the cars is probably low, and also Tesla probably benefit from the data gathered by that hardware anyway.

Tldr: I suspect Tesla know what they're doing with the pricing of this thing.

>Tesla probably benefit from the data gathered by that hardware anyway.

In a big way. They are using data gathered by the self-driving ready hardware to develop the software that will use it.

Thousands of cars out there collecting data is a huge advantage over groups working with a handful of prototypes.

> Thousands of cars out there collecting data is a huge advantage over groups working with a handful of prototypes.

I'm not sure this is true. At least for Google, it seems like the main bottleneck to progress is engineering time to fix the problems that arise. The problem is not a lack of vehicles driving and finding problems.

I say this because Google has made very little effort to expand their fleet of testing vehicles. The last big expansion, from 28 to 48 vehicles, was in Sept. 2015. Since then they've expanded from 48 to 58, but it doesn't seem to be a priority. [1]

[1] https://docs.google.com/spreadsheets/d/1v0BBTDOXvD8JdhrySFy6...

I think it's just that it isn't an option. The data from 100 cars isnt much more useful than the data from 50. That doesn't mean the data from 10000 cars isn't much more useful than the data from 50.

It just isn't reasonable for Google to build and manage a fleet of that size for a development program. It would cost Google half a billion dollars, but for Tesla it's just a bit of cost they roll into the product.

Depends on the algorithms you are using. In machine learning, bigger data sets can trump better algorithms.

Sure. But having auto-pilot a significant % of the roads in the USA (and norway by the sounds of it) gives tesla an advantage. After all you can't learn from a road you haven't been on.

Teslas approach is different to Google's. Tesla is gathering hi-res location data from both human driven and autopilot driven cars to build an accurate map of every lane of every highway.

It's wrong because the marginal cost of adding another unit to a car has nothing to do with r&d.

In the choice between putting the hardware on all cars vs only on a few prototypes, the R&D is a sunk cost that shouldn't influence the decision and only the pure incremental cost of the hardware matters.

I'm not disagreeing with you. I like the move; I think it's smart.

But saying it's an "autonomous car" because it has the sensors and computers just isn't so. When it gets the software, then it's an "autonomous car."

To use GPs analogy to the iPhone1: If Apple had just shipped the hardware without iOS, it wouldn't have been the iPhone.

That I agree with, yes. But he always stretches the wording. It's his version of advertising, and frankly I prefer it over dancing hamsters.

I don't think the iPhone had iOS 10 ;). Apple is a pretty good analogy for what Tesla's HW/SW plans seems to be. "Reasonable" backwards software support (at least compared to the otherwise "none") while iterating hardware.

The iPhone couldn't cut and paste for a long while. Hell, iirc, there wasn't the App Store until iOS 2 or 3.

> Nope, it's not autonomous, it's Autopilot!

Yeah, well... it's not really autonomous. It's a slightly better cruise control + assisted lane change. In fact the "Autopilot" marketing term makes it sound much more like fully autonomous driving than it actually is.

I think he/she is referring to 2.0 which is fully autonomous.

>> The strategy Musk has clearly been using for a long time now (redacted for brevity)

Elon Musk does what he does best alright: make billions. The rest is just educated guesses at best.

At worse, any attempt to "explain" marketing strategy as some sort of passionate drive to improve the technology, or similar, is just so much cold-reading yourself at for the benefit of a commercial company's bottom line.

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