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I find this to be relevant to the self driving problem - Apple/Foxconn could not detect when things had gone wrong on the automation line and stop it, let alone

I find this to be relevant to the self driving problem - Apple/Foxconn could not detect when things had gone wrong on the automation line and stop it, let alone have the line's robots fix it. However, we expect a self driving car to detect when it encounters a novel situation on the road? And it surely will. If they could not detect it in the confines of a highly controlled factory assembly line (not manufacturing but assembly) then how can a car detect novelty on a cityscape or even a highway?

jfim 6y ago
Those are two pretty different domains. In manufacturing automation, some of the things that are hard include gripping objects, handling fluids and pastes, and adapting to design changes. For self driving cars, the controls are pretty similar, even across car models. Gas, brakes, and steering. It doesn't happen that a supplier ran out of engines and a decision is made to replace the car's propulsion by jet engines, thrust vectoring, or a hovercraft. It doesn't matter too much for self driving cars to be within 0.1 inches of the center of the road, but if your electrical components are offset by 0.1 inches or there's 0.1 fluid ounces too much glue because this batch of glue is more liquid than the previous one, the electronics probably won't work in the end.
- Dahoon 6y ago
  And yet if you look at what actual experts, that aren't trying to sell anything are saying, like automotive testing bodies (EuroNCAP, ADAC, FIA, etc) the consensus is that self-driving cars are at least 15 years away. The gap between reality and what salesmen have sold to common people is gigantic.
- raducu 6y ago
  Also the R&D budget for self-driving cars is bottomless. There's a limit to the R&D budget for assembling THIS year's iphone, above which it's just better to use humans.
  - haltingproblem 6y ago
    Apple manufacturing budget >> Self driving car r&d budget.
- haltingproblem 6y ago
  My comment was not about robotics but about detecting when things had gone wrong. Again, the manufacturing lines are in a very controlled environment - loaded with sensors, compute power, perfect lighting, humidity etc. Compare that to the noisy world of roads, traffic, weather and humans.
advanced-DnD 6y ago
the smaller electronic device is, the higher the precision you need. For such a compact device such as iPhone, the precision is not enough to automate the production yet. For self-driving/flying, there is always some lee-way. The demand of lowering error variance is low.
- pas 6y ago
  > not enough to automate the production * yet * = economically, because low-skilled labor is toooooo cheap
cheschire 6y ago
And in that same vein, why haven't we focused on the infinitely easier realm of rail automation and safety? We jumped right to the hardest problem set. Probably because it's the most sensational and easiest to get broad financial support by selling people the promise of less rush hour drain.
- aaronbrethorst 6y ago
  Less sexy, less money, more government.
- Jyaif 6y ago
  The rail automation is solved, entire metro lines are automatic in several places. Unfortunately while it is an easier problem to solve, it's also a less financialy interesting: in a train the labor cost of the driver is much lower than in a taxi.
- philjohn 6y ago
  to be fair, we do have some autonomous rail infra - Metro line 14 in Paris, the DLR in London, the Victoria Line was designed to be autonomous but scuppered by the unions.
  - agurk 6y ago
    The Copenhagen metro is fully driverless (no staff in any role onboard) and consequently runs 24/7.
- gruturo 6y ago
  Replacing the cost of 1 conductor every 200 passengers is not nearly having the same impact. Moreover as others point out, it has actually been done and there are automated lines. Safety advantages are probably slim - when there's a train accident it makes news, because they're RARE. It's also not going to significantly improve one's choice of transportation - you either have access to rail already, or you don't - regardless of who/what drives the train. Schedules are already tuned and if it was more profitable to put more trains, it would likely happen even with human conductors.
diob 6y ago
I wonder if there are companies focusing on solving the opposite problem. In other words, AI to focus on things humans don't perceive (leaving the driving to the human). For instance, figuring out the person in another car is drunk, then alerting you to avoid them. Or detecting emergency personnel needing you to get out of the way (can't tell you how often I see folks blocking or oblivious). This goes along with my experience in new cars in that the best improvements are those that enhance my ability to drive (such as a backup camera).
- FridgeSeal 6y ago
  The more I work in and watch the ML/AI space, the more I’m convinced the better approach is similar to what you describe: “augmentation” of humans’ abilities and skills rather than replacement of them. Using advanced AI, or even a bunch of semi-decent models to condense information, highlight things humans might miss, enrich with predictions, etc so that humans don’t have to spend as much time wading through data themselves to try and extract meaning and can instead jump straight to more informed decision making seems like a better approach to me than “lol can we make a neural net that does lawyer things?”

jfim 6y ago

Those are two pretty different domains. In manufacturing automation, some of the things that are hard include gripping objects, handling fluids and pastes, and adapting to design changes. For self driving cars, the controls are pretty similar, even across car models. Gas, brakes, and steering. It doesn't happen that a supplier ran out of engines and a decision is made to replace the car's propulsion by jet engines, thrust vectoring, or a hovercraft. It doesn't matter too much for self driving cars to be within 0.1 inches of the center of the road, but if your electrical components are offset by 0.1 inches or there's 0.1 fluid ounces too much glue because this batch of glue is more liquid than the previous one, the electronics probably won't work in the end.

Dahoon 6y ago
And yet if you look at what actual experts, that aren't trying to sell anything are saying, like automotive testing bodies (EuroNCAP, ADAC, FIA, etc) the consensus is that self-driving cars are at least 15 years away. The gap between reality and what salesmen have sold to common people is gigantic.
raducu 6y ago
Also the R&D budget for self-driving cars is bottomless. There's a limit to the R&D budget for assembling THIS year's iphone, above which it's just better to use humans.
- haltingproblem 6y ago
  Apple manufacturing budget >> Self driving car r&d budget.
haltingproblem 6y ago
My comment was not about robotics but about detecting when things had gone wrong. Again, the manufacturing lines are in a very controlled environment - loaded with sensors, compute power, perfect lighting, humidity etc. Compare that to the noisy world of roads, traffic, weather and humans.

advanced-DnD 6y ago

the smaller electronic device is, the higher the precision you need. For such a compact device such as iPhone, the precision is not enough to automate the production yet. For self-driving/flying, there is always some lee-way. The demand of lowering error variance is low.

pas 6y ago
> not enough to automate the production * yet * = economically, because low-skilled labor is toooooo cheap

cheschire 6y ago

And in that same vein, why haven't we focused on the infinitely easier realm of rail automation and safety? We jumped right to the hardest problem set. Probably because it's the most sensational and easiest to get broad financial support by selling people the promise of less rush hour drain.

aaronbrethorst 6y ago
Less sexy, less money, more government.
Jyaif 6y ago
The rail automation is solved, entire metro lines are automatic in several places. Unfortunately while it is an easier problem to solve, it's also a less financialy interesting: in a train the labor cost of the driver is much lower than in a taxi.
philjohn 6y ago
to be fair, we do have some autonomous rail infra - Metro line 14 in Paris, the DLR in London, the Victoria Line was designed to be autonomous but scuppered by the unions.
- agurk 6y ago
  The Copenhagen metro is fully driverless (no staff in any role onboard) and consequently runs 24/7.
gruturo 6y ago
Replacing the cost of 1 conductor every 200 passengers is not nearly having the same impact. Moreover as others point out, it has actually been done and there are automated lines. Safety advantages are probably slim - when there's a train accident it makes news, because they're RARE. It's also not going to significantly improve one's choice of transportation - you either have access to rail already, or you don't - regardless of who/what drives the train. Schedules are already tuned and if it was more profitable to put more trains, it would likely happen even with human conductors.

diob 6y ago

I wonder if there are companies focusing on solving the opposite problem. In other words, AI to focus on things humans don't perceive (leaving the driving to the human). For instance, figuring out the person in another car is drunk, then alerting you to avoid them. Or detecting emergency personnel needing you to get out of the way (can't tell you how often I see folks blocking or oblivious). This goes along with my experience in new cars in that the best improvements are those that enhance my ability to drive (such as a backup camera).

FridgeSeal 6y ago
The more I work in and watch the ML/AI space, the more I’m convinced the better approach is similar to what you describe: “augmentation” of humans’ abilities and skills rather than replacement of them. Using advanced AI, or even a bunch of semi-decent models to condense information, highlight things humans might miss, enrich with predictions, etc so that humans don’t have to spend as much time wading through data themselves to try and extract meaning and can instead jump straight to more informed decision making seems like a better approach to me than “lol can we make a neural net that does lawyer things?”