Offering a footgun to consumers which puts other people in danger is a questionable choice.

If you think the name has nothing to do with it, would you also say that if it had the name "Deluxe Cruise Control" people would treat it the same? I'm not so sure about that. Engineers maybe.

[1] Following a number of WTF-type accidents, there is some concern that airplane automation has become too complex for pilots to reason about when it partially fails, but if that is actually the case, it raises the bar for all partial automation, including for cars.

The common meaning has been derived from the technical and is affected by some common misunderstandings, such as:

autopilot flies planes all over the place and hardly ever runs into anything becomes autopilot is very safe and not autopilot doesn't run into anything because in the sky there is not very much to run into.

I guess Tesla should have named it something else, but this kind of mistake is quite easy to make and I would say is the norm if anything.

EDIT: it's a 1-D array of distances, ie, an array of polar coordinates on the 2-D plane. So, it's 2-D data.

If it returns a 2D array then its 'seeing in 3D'.

So I guess that works out.

This is an edge case, and clearly something that requires more training to avoid. The challenge in edge-case learning is to encounter them often enough, or perhaps create them artificially, and then to ensure the learning can be transferred and generalized to all similar situations.

At the very least, as a driver, I'm slightly cautious when I see a car move out of the lane in front. I feel like the solution lies in: (a) separating the signal from the noise in the set of things moving with the ground, and (b) getting the car to 'understand' why other cars change lanes. Sometimes it's so they can avoid obstacles in the road. It almost feels like cars need to have a theory of mind of other cars. I certainly drive with an intuition of driver intentions stuck in my head.

The problem is you can't have a pre-existing bias when working with this kind of technology, you need to be able to adapt to whatever changes that need to be made.

A camera is not a replacement of how our eyes work, how our brain distinguishes between objects and understand from prior experience and can make independent decisions on the fly. But neither does LiDAR, but with LiDAR and good machine learning (ie, Waymo), you can drastically improve the reliability of your autonomous system.

Elon is insisting on a no-LiDAR system at the same time advertising tesla autopilot as an autonomous system and has said multiple times that All Tesla on the road is already equipped with the hardware needed for fully autonomous driving. This is dangerously false.

There is not a single autonomous car out there (at least serious ones that we know of), that has a non-LiDAR system.

Reality Distortion Field is strong with Elon, Unlike Steve Jobs and Apple products, this one will kill people.

I don't think you need lidar.

I'm not saying that vision-only won't take longer, because it will, but I believe it'll probably happen unless the cost of lidar falls a great deal.

Have a look at, for example, "learning to see in the dark" (the CVPR 2018 one), DensePose (the FB research one) to get a sense of how quickly difficult problems are being solved.

Waymo LiDAR is custom made and they cost a lot less than what is available in the market. https://arstechnica.com/cars/2017/01/googles-waymo-invests-i...

I don't think it's a cost, Elon has a personal bias, or maybe he didn't account for the fact that in the not so near future LiDAR cost will go down drastically.

  But the Autopilot has cameras, and therefore it has 3+1D
  data (2D frames, 1D inferred depth from stereo or
  training, 1D time from frame diffs).

I mean _really_ simple - to deploy an airbag, early systems were as simple as checking the accelerometer works at startup, then firing the airbag if the acceleration passes a threshold consistent with a crash.

If your safety system relies on multiple cameras, stereo vision, camera motion tracking, and a neural network, it ain't simple.

That's why IMHO every self-driving car needs LIDAR - you need to be able to detect the firetruck or highway divider in from of you without relying on a million lines of code.

A well written manual can be a teaching lesson about the relevant stuff given by domain experts for regular users. Who'd say No to that?

Legally they were made aware, if you want to change the law do so. But please stop letting user play morons selectively when it turns out they didn’t rtfm. That is on them and should be on them.

In balance: https://www.theverge.com/2018/2/7/16988628/elon-musk-lidar-s...