> It feels kind of odd that almost no one is talking about self-driving now, compared to how hot of a topic it used to be
Probably because it's just here now? More people take Waymo than Lyft each day in SF.
Probably because it's just here now? More people take Waymo than Lyft each day in SF.
Getting this tech deployed globally will take another decade or two, optimistically speaking.
If it's not a technological limitation, why aren't we seeing self-driving cars in countries with lax regulations? Mexico, Brazil, India, etc.
Tesla launched FSD in Mexico earlier this year, but you would think companies would be jumping at the opportunity to launch in markets with less regulation.
So this is largely a technological limitation. They have less driving data to train on, and the tech doesn't handle scenarios outside of the training dataset well.
And those moments where the car gives up and waits for async assistance are very obvious to the rider. Most rides in Waymos don't contain any moments like that.
Even if it's just a high level instruction set, it's possible that that occurs often enough to present scaling issues. It's also totally possible that it's not a problem, only time will tell.
What I have in mind is the Amazon stores, which were sold as being powered by AI, but were actually driven by a bunch of low-paid workers overseas watching cameras and manually entering what people were putting in their carts.
https://www.businessinsider.com/amazons-just-walk-out-actual...
And San Francisco doesn’t get snow.
Or cows sharing the thoroughfares.
It should be obvious to all HNers that have lived or travelled to developing / global south regions - driving data is cultural data.
You may as well say that self driving will only happen in countries where the local norms and driving culture is suitable to the task.
A desperately anemic proposition compared to the science fiction ambition.
I’m quietly hoping I’m going to be proven wrong, but we’re better off building trains, than investing in level 5. It’s going to take a coordination architecture owned by a central government to overcome human behavior variance, and make full self driving a reality.
"Driving data is cultural data."
The optimists underestimate a lot of things about self-driving cars.
The biggest one may be that in developing and global south regions, civil engineering, design, and planning are far, far away from being up to snuff to a level where Level 5 is even a slim possibility. Here on the island I'm on, the roads, storm water drainage (if it exists at all) and quality of the built environment in general is very poor.
Also, a lot of otherwise smart people think that the increment between Level 4 and Level 5 is the same as that between all six levels, when the jump from Level 4 to Level 5 automation is the biggest one and the hardest to successfully accomplish.
The goal for a working L5 should be “if piloting a rickshaw, will it be able to operate as a human owner in normal traffic.”
Guangzhou: https://www.youtube.com/watch?v=3DWz1TD-VZg
I’m positing that the models encode cultural decision making norms- and using global south regions to highlight examples of cases that are commonplace but challenge the feasibility of full autonomous driving.
Imagine an auto rickshaw with full self driving.
If in your imagination, you can see a level 5 auto, jousting for position in Mumbai traffic - then you have an image which works.
It’s also well beyond what people expect fully autonomous driving entails.
At that point you are encoding cultural norms and expectations around rule/law enforcement.
This bet aged well: videos of FSD performing very well in wildly different settings -- crowded Guangzhou markets to French traffic circles to left-hand-drive countries -- seem to indicate that this approach is working. It's nailing interactions that it didn't learn from suburban America and that require inferring intent using complex contextual clues. It's not done until it's done, but the god of the gaps retreats ever further into the march of nines and you don't get credit for predicting something once it has already happened.
I liked the use of the God of the gaps - an effective analogy for the counter position.
I’m rejecting the idea of the march of the 9s eventually getting to FSD - the cultural norms issue is about decision making not about physics.
Eg - You have to decide how aggressively to drive, overtake, or jockey for position.
My estimation is that this is not solvable by on board decision making, because that would be accepting unacceptable legal risk.
My city had Car2Go for a couple of years, but it's gone now. They had to pull out of the region because it wasn't making them enough money
I expect Waymo and any other sort of vehicle ridesharing thing will have the same problem in many places
High speed connectivity and off vehicle processing for some tasks.
Density of locations to "idle" at.
There are a lot of things that make all these services work that means they can NOT scale.
These are all solvable but we have a compute problem that needs to be addressed before we get there, and I haven't seen any clues that there is anything in the pipeline to help out.
Waymo needs to be proving 5-10x the number of daily rides as Lyft before we get excited
You can provide almost any service at a loss, for a while, with enough money. We shouldn't get excited until Waymo starts turning an actual profit.
And as I understand it; These are systems, not individual cars that are intelligent and just decide how to drive from immediate input, These system still require some number of human wranglers and worst-case drivers, there's a lot of specific-purpose code rather nothing-but-neural-network etc.
Which to say "AI"/neural nets are important technology that can achieve things but they can give an illusion of doing everything instantly by magic but they generally don't do that.