[LittleTimothy]

I'm surprised this article doesn't mention the elephant in the room. With Musk's influence over the Trump administration it seems overwhelmingly likely that Tesla will achieve Full Self Driving by changing the regulatory framework to allow whatever Tesla currently has to be called (and used as) self-driving. It's that simple. Will your Tesla suddenly become an autonomous vehicle? Well obviously not you cant just change the regulations and hope reality accomodates you.

So what we'll probably end up with is real self driving Waymos all over the place and fake self-driving Teslas that 'self-drive' as long as you're still really driving.

The only real concern I have is whether Musk exploits his position to impact the regulations to push both Waymo and Tesla into a bucket called "self-driving" where they get categorized the same and both still require drivers, essentially using the regulations to knee cap any rival that is ahead of Tesla.

The other side of it is that I think we'd all be very happy if Musk went back to just lying about his electric vehicles.

[jqpabc123]

The real elephant in the room is whether FSD is even possible by using primarily visual input.

Personally, I don't think so.

There are simply too many driving situations where visual input is severely limited. FSD can use all the help it can get.

[jfengel]

Don't you drive using primarily visual input?

I don't know if machine learning can ever match the human brain for that. The brain does a lot of fairly advanced inferences that require a deep understanding of the world and the people and things in it.

Still, I'm not sure how much additional inputs would help the ML. If you had to drive by "touch" (LIDAR), you probably shouldn't be allowed to drive. It might be useful when the visual system has failed, to stop the vehicle before it hits something, but if the visual system fails that often then the system wouldn't be usable for any purpose.

[jqpabc123]

Don't you drive using primarily visual input?

Visual input combined with a lot of mental projection and inference and understanding/experience and good split second decision making.

Examples: How does a FSD vehicle use it's camera to identify "black ice" on an overpass? How does it identify that a heavy truck tire has just exploded in it's lane a few cars ahead on the freeway? Or how about a bumper dropped from a car ahead or a large truck losing it's load?

All these and more have happened to me and I lived to tell about it.

[senordevnyc]

Still, I'm not sure how much additional inputs would help the ML.

This is a wild take when Waymo is doing 150k+ rides per week with no one in the driver seat.

[LittleTimothy]

Does that matter? Waymo solved FSD. The technical detail of the implementation is moot.

[Zigurd]

Waymo's approach to autonomy, and robotaxi service, are both very different from Tesla's concept of a plan for general purpose autonomous driving plus an AirBnB-like taxi fleet.

In addition to what will turn out to be a foolish fixation on cameras as the only sensor, Tesla FSD hasn't got nearly as much mapping data, or real-time traffic data which Waymo can source from Google Maps, or in-vehicle monitoring of passengers and vehicle condition.

Elon has his online claque for distorting reality. But reality is still there. That's why Elon wants to buy the whole government to get bigger reality-denial tools.

[jqpabc123]

The technical detail of the implementation is moot.

Waymo solved FSD using LIDAR and other sensors that Tesla has publically rejected in favor of visual cameras.

The technical detail is not at all "moot" due to the obvious fact that Tesla has yet to achieve what Waymo has.

https://www.forbes.com/sites/bradtempleton/2022/10/31/former...