Subways not trains/trams, which makes sense since they are in a mostly closed system. The French one is closed off and doors slide open on the dock so that passengers can board the cars. This particular system also runs on pneumatic wheels on a rail. I guess for easier accuracy with braking/acceleration?
We-ell, there have been bugs causing train collisions, but there also have been train collisions caused by machinist’s error or some other misfortune, so.
Now AI may or may not be overhyped but Tesla’s self-driving nonsense isn’t AI regardless. Just pattern recognition it is not the neural net everyone assumes it is.
It really shouldn’t be legal, this tech will never work because it doesn’t include lidar so it lacks depth perception. Of course humans also don’t have lidar, but we have depth perception built in thanks billions of years of evolution. But computers don’t do too well with stereoscopic vision for 3D calculations, and really can do with actual depth information being provided to them.
If you lack depth perception, and higher reasoning skills, for a moment you might actually think that a train driving past you is a road. 3D perception would have told the software that the train was vertical and not horizontal, and thus was a barrier and not a driving surface.
Just pattern recognition it is not the neural net everyone assumes it is.
Tesla’s current iteration of self-driving is based on neural networks. Certainly the computer vision is; there’s no other way we have of doing computer vision that works at all well and, according to this article from last year it’s true for the decision-making too.
Of course, the whole task of self-driving is “pattern recognition”; neural networks are just one way of achieving that.
We have gone from cruise control to cars being able to drive themselves quite well in about a decade. The last percentage points of reliability are of course the hardest, but that’s a tremendously pessimistic take.
This is that “AI” that investors keep jerking themselves purple over.
Real “Self driving cars” will not be available in our lifetimes.
self-driving vehicles have existed for decades, and they are very safe.
They are trains 🚊 / trams 🚋
Trams and trains have drivers.
I can afford to have a driver if I’m splitting the cost with 400 of my closest friends.
Subways not trains/trams, which makes sense since they are in a mostly closed system. The French one is closed off and doors slide open on the dock so that passengers can board the cars. This particular system also runs on pneumatic wheels on a rail. I guess for easier accuracy with braking/acceleration?
We-ell, there have been bugs causing train collisions, but there also have been train collisions caused by machinist’s error or some other misfortune, so.
Now AI may or may not be overhyped but Tesla’s self-driving nonsense isn’t AI regardless. Just pattern recognition it is not the neural net everyone assumes it is.
It really shouldn’t be legal, this tech will never work because it doesn’t include lidar so it lacks depth perception. Of course humans also don’t have lidar, but we have depth perception built in thanks billions of years of evolution. But computers don’t do too well with stereoscopic vision for 3D calculations, and really can do with actual depth information being provided to them.
If you lack depth perception, and higher reasoning skills, for a moment you might actually think that a train driving past you is a road. 3D perception would have told the software that the train was vertical and not horizontal, and thus was a barrier and not a driving surface.
Tesla’s current iteration of self-driving is based on neural networks. Certainly the computer vision is; there’s no other way we have of doing computer vision that works at all well and, according to this article from last year it’s true for the decision-making too.
Of course, the whole task of self-driving is “pattern recognition”; neural networks are just one way of achieving that.
We have gone from cruise control to cars being able to drive themselves quite well in about a decade. The last percentage points of reliability are of course the hardest, but that’s a tremendously pessimistic take.