[natch]

This is a perfect example. He said it could happen, pending regulatory approval that Tesla does not control, in certain locales, possibly with human supervisory drivers at the beginning, not at, but by (a different word with a different meaning) the end of next year. He had so many qualifiers on his statements, yet you missed every single one of them and came up with a totally different statement you just projected and attributed to him. Did you even listen to the event? This is basic listening comprehension 101.

Edit: ok you got the word "by" right but... everything else... wow. But it's not just you... the crazy thing is how many people do the same thing.

[hellllllllooo]

Regulations are not the problem here. He is clearly trying to imply something about his technology that, given the reality of self driving cars, can not happen next year even if everything else went positivity for him. The fact that he is using caveats around regulation etc. doesn't get him off the hook. He knows people will report the story as some amazing breakthrough that will help pump stock and sell cars. It's dishonest.

[mrep]

> given the reality of self driving cars, can not happen next year even if everything else went positivity for him.

Why is that? They've now got tens if not hundreds of thousands of cars running their FSD tech all the time comparing it to what the driver actually does and using that to get edge cases to add their every growing dataset to test and train their algorithms. The average American has a commute of 16 miles [0] which gives an estimate 13173 miles driven per car by the end of next year. At a low estimate of 10,000 cars, that would give them a subset of driving data for 131,733,333 miles driven. Presumably, they label these interactions with what should have been done and then throw it into a training/test pipeline. The US car fatality rate is just over 1 per 100,000,000 miles driven [1] so they should have a training/test suite multiple times the US car fatality rate and that's not even counting regular crashes. Granted, it won't actually be that large since they don't report back when the car is running fine, but I don't see why it is 100% impossible for them to get their FSD tech to human quality driving in certain conditions (like geofenced and only run during nice weather) at some point next year when they have that much data to work with.

[0]: https://itstillruns.com/far-americans-drive-work-average-744...

[1]: https://en.wikipedia.org/wiki/Transportation_safety_in_the_U...

[hellllllllooo]

There's a lot more problems involved than just data collection. The algorithms do not exist to safely and reliably solve these problems even with all the data in the world. Simply put Tesla is declaring it can do something with a restricted set of sensors and compute that the current state of the art in research doesn't support. Even Waymo who have no real production restrictions and can spend >$100k in equipment per car and have a lot more compute is not claiming anything like this will be feasible in the next year. He is claiming cheaper, faster and better than anyone else.

The problems just get harder and harder as you move from a nice controlled environment like a freeway and even there Tesla has shown there are many issues with the system where a driver needs to pay full attention for it to be safe.

From first hand experience with these problems and their complexity I fully expect a slightly better version of autopilot to be delivered and Musk to declare success despite it not being anywhere close to an autonomous fleet of Tesla robo-taxis and justify the difference with the caveats he quietly snuck in that he knew wouldn't make headlines.

That might be enough for his customers and investors so from a business sense it might pay off.

[mrep]

Can you give some examples of those problems because you are coming off as very hand-wavy about it?

[hellllllllooo]

Simple case that Waymo etc still struggle with is making a left turn through an intersection or an unprotected left. Even something as common and predictable as crossing oncoming traffic that humans do every day is still causes disengaments for these cars. Cruise has a team just focused on issues at intersections. Throw in some pedestrians and this is very hard. Humans can intuit a lot from a pedestrians behavior that these cars just cannot handle. Is someone standing by the corner or about to walk into the street? People do a lot of weird unpredictable things in downtown areas. Tesla has done ok with the easiest part of driving, freeways, with the support of an attentive human but three are still many reported problems. Moving on to complex environments with multiple moving actors at such high reliability that it is a hands free production-grade system in 1-2 years is not likley, but good luck to them.

[mrep]

Isn't that the exact type problem that massively benefits from having tons of real world data because they will have examples to train their neural nets for practically every possibility?