Because self-driving is never a well-defined term, and we all know that’s best for scams.
Even after $100B, self-driving cars are going nowhere
481–490 of 501 posts
Re: Even after $100B, self-driving cars are going nowhere
#482In the short run, technological progress is much slower than anyone hopes, but in the long run it is much faster than anyone expects. My favorite example is that in 1987, the scientific consensus was that it would take "at least 100 years" and likely much longer to sequence the entire human gnome.[a] But the vast majority of it was sequenced by 2000, only 13 years later. Moreover, just two decades later, anyone could…
Human genome sequencing is a well defined problem, but self driving is not.
Re: Even after $100B, self-driving cars are going nowhere
#483Earlier quoted context omitted.
Earth size? When was the last time you drove in Madagascar? Most driven miles are the same commute in the same city 10 times a week.
People in Madagascar would answer differently.
People in Madagascar depend on 4x4 monsters. Yet manufacturers still sell RWD coupes. It's worthwhile without them as a target market.
Re: Even after $100B, self-driving cars are going nowhere
#484Earlier quoted context omitted.
> Everything has been carefully mapped out ahead of time This doesn’t scale. This is also how Zoox, Tesla, and Cruise do their demo videos to scam more money out of investors: they collect ultra-HD maps in a very narrow area or a very specific route. Then they drive the route/area about a thousand times, recording each drive. Then they upload the drive with the fewest mistakes to YouTube. Just like me taking a thousa…
Telsa doesn't have such ultra-HD maps at all. They build some maps for some simulations and training but the car does not locate itself in such maps when driving. > Then they drive the route/area about a thousand times, recording each drive. Then they upload the drive with the fewest mistakes to YouTube This is certainty not what Tesla does, from Tesla vehicles you will find literally 1000s of videos uploaded by Test…
> Telsa doesn't have such ultra-HD maps at all. They build some maps for some simulations and training but the car does not locate itself in such maps when driving.
They do have such maps, but only for the routes of their demo videos. That’s the entire accusation — it’s a Fugazi. A man behind a curtain. A mechanical Turk. Fake.
This video was posted 3 years ago: https://m.youtube.com/watch?v=tlThdr3O5Qo
I have never seen a Tesla perform as well as the one in that video in ANY user video. I drove a Model 3 with FSD for 4 months and it never came close to performing that well. Not even close. They either recorded a special map for that scam video, drove the route a thousand times and took the best recording, or both.
> This is certainty not what Tesla does, from Tesla vehicles you will find literally 1000s of videos uploaded by Testers on every possible routes
In the real videos, the cars fail to navigate simple scenarios constantly. You can’t even watch the videos without cringing at the constant mistakes and dangerous maneuvers. For Pete’s sake, just search “Tesla phantom braking” on YouTube and behold.
https://m.youtube.com/watch?v=Zu18KYAhSzo
https://m.youtube.com/watch?v=9iGWDdnoONE&t=50
> And Tesla has also never relied on VC funding for any of its self-driving tech.
No, just unsophisticated customers paying $12k for vaporware and massive government subsidies. So sorry — they’re not scamming VCs. Just real customers and the taxpayers.
Re: Even after $100B, self-driving cars are going nowhere
#485Earlier quoted context omitted.
Or perhaps it will be their advantage in the short term. Imagine a foggy condition that causes a 50 car pile up on the highway. Which is more likely to avoid the collision, a Tesla that slowed down because it couldn't see or a Waymo/Cruise blasting down the highway at 65 mph because it's Lidar can see through the fog?
Lidar can't see through fog (or snow/rain to enough of a degree), which is one reason tesla has avoided it. Do you mean radar? In the case of radar, I would hope that it becomes a base features of all cars eventually to avoid/mitigate rear endings by preemptive braking.
Many modern lidars absolutely can see through fog/snow/dust/rain, albeit degraded.
Blackmore, and Aeva can see through fog and dust that others can’t. Most sensors can see sufficiently through rain and snow.
Re: Even after $100B, self-driving cars are going nowhere
#486Earlier quoted context omitted.
We have a lot more signal than vision only. For example audio, the “feel of the road”, like feedback on the steering wheel and traction that we physically experience. Most of all we have actual intelligence and reasoning - not just pattern recognition.
Do you drive much? It would be QUITE the stretch to say most drivers have "actual intelligence and reasoning." Pattern matching for driving is probably better, frankly. You don't have people who are stressed out, pissed off, inattentive or in a hurry doing risky stuff on the road.
> It would be QUITE the stretch to say most drivers have "actual intelligence and reasoning."
The accidents caused by people with a lapse in judgement are much more memorable than the billions driving safely and preventively every day.
Re: Even after $100B, self-driving cars are going nowhere
#487I'd rather see we remove all non professionnal motorized vehicles from the road and invest those billions in high frequency and coverage public transport. That would mean more accessible transport to everyone, including disabled people, less people dying on the road, safer transport for pedestriants, cyclists, bicycles, scooters, rollerskates, better emergency services who don't have to deal with ugly traffic. Our wo…
"Our world do not need one car for everyone." Where you live. Where I live, it's not unreasonable for everyone to need a couple of vehicles each depending on what they're doing.
"Where I live, it's not unreasonable for everyone to need a couple of vehicles each depending on what they're doing. "
Because you guys and your parents chose to make you dependent on that. The solution is not to build more killing machines and spend more time behind the wheel. All that has been done in the second half of the century can be made differently.
Re: Even after $100B, self-driving cars are going nowhere
#488Earlier quoted context omitted.
What data is that model based off? Tesla has the data based on real world failures to build that model. Does anyone else?
You can't discount all the data they Waymo has collected over nearly a decade or the scenarios they've manually created. They also have the world's most complete map and spatial dataset, which could easily be extended to create a model that creates tricky roadways. Stimulating obstructions or hardware failures doesn't require very much data at all. If you are modeling scenarios like a game engine, a "discriminator" m…
I'm not discounting their data, I just think Tesla has so much more. If you were looking at just those opted into the FSD Beta you have a larger fleet actively running the model with feedback loops capturing every failure. But cars without FSD are still running the model and capturing data as well.
Re: Even after $100B, self-driving cars are going nowhere
#489Quoted post unavailable.
Please stop posting unsubstantive comments and flamebait to HN. We're trying for something else here.
Re: Even after $100B, self-driving cars are going nowhere
#490Earlier quoted context omitted.
That counterargument only holds if Tesla can build software that can approximate the human brain. I think it's laughable to expect they can do that, at least on any reasonable timeframe. Even if they could, a goal of self driving should be to do better than a human driver. Avoiding technology that can "see" in ways a human cannot is just short-sighted, and a huge missed opportunity. And all that still even ignores th…
Why is it laughable that Tesla can build software that approximates the human brain? There is software that is better at chess, better at go and better at poker than humans. Why is driving so special? Agree with your other points.
i agree with the principle of your comment, but pure games like the ones you mentioned seem like they would be much easier for a machine to solve. traffic and driving are more complex and require much faster response times, not to mention the high variability (and the literal speed) of factors