4 ms·

This viewpoint seems to be a strange version of Schneier's law. Just because you learned ML and can't think of a way to make a car drive itself doesn't mean it

by mike_d 5y ago

This viewpoint seems to be a strange version of Schneier's law. Just because you learned ML and can't think of a way to make a car drive itself doesn't mean it is impossible. I believe within the next few years we will see driverless long haul freight operations. Freeways are orders of magnitude easier than dynamic city streets, longer routes can be taken at little cost to avoid adverse conditions (a human rider isn't going to be ok with adding 10 hours to avoid a snow storm, a truck load of coffee beans doesn't care), and the cost of humans in this case is stupid high. Once it is demonstrated in the real world that corporations stand to profit from eliminating drivers, you'll start to see pressure on the public sector to annotate the world. Stop signs will by law include an RF beacon, lanes will no longer be defined by paint but by transmitters in the pavement, federal law will mandate that personal vehicles transmit their location and dimensions to other nearby cars, etc. Eventually once we have the infrastructure built, every new car will piggyback on it. Remember the Interstate Highway System was started in 1955 and completed in 1992 - progress just takes time.

ikerdanzel 5y ago
He learnt the field and know what can be done and what cannot be done. Go lookup the history of Ai with lisp and then deep blue vs Karpersky. Back then people believe humanoid like Star Trek Data is possible within our lifetime. If you have studied the AI of its day you would know it is near impossible. The OP above you is right, based on current ML knowledge self-driving car is impossible. Assisted self-driving car is more likely. The problem of self-driving car isn't like chess or go. There isnt simplified rules. Humans and humans needs are messy. What you're thinking of is some new technology say super LIDAR++ and new method say doubly deep organic learning might solve the problem. But as of now, they are not yet invented or extremely infant stage. But one thing for sure those aren't the current knowledge ML. Perhaps Waymo will get there...perhaps no. Many decades ago, there are tesla-like cars but it was successful because of battery tech and cheap oil price. They basically went out of business. So Waymo maybe be like them, full of possibility but the isn't ripe yet. Just like Friendster and MySpace before FB.
javagram 5y ago
Annotating every object on the road with RFID beacons seems like it actually would be an impossible project. Yes, you can attach beacons to stoplights and signs (although they already have “beacons” that display in the visible light spectrum). But you can’t attach them to people like the homeless pedestrian killed by Uber’s test self driving car, animals, trash thrown on the roadway or falling off a truck, or a boulder falling from the side of a mountain. And looking at the decades-long process it took to install PTC on train lines, it would take decades to install radio beacons on everything we can and by then technology should have advanced to the point where we don’t need them.
- mike00632 5y ago
  I saw a trash bag on the highway yesterday. It was full but looked light, as if it were stuffed with pillows or plastic bags. I could have safely hit it with my car (I didn't) whereas other objects that size I wouldn't. This decision making happens often like with pieces of paper or plastic bags. I thought about how much contextual knowledge it takes for us to make these everyday decisions.
  - secondaryacct 5y ago
    There s however one thing you cant do but an ML solution probably could: share your contextual experience at the instinct level with every driver. Say you're right and an ML model cannot know intrinsically the trash bag is safer to hit than to avoid, however, if a few car hit or avoid those for a little while they can learn of the consequence of both actions and then share them back to every other car. I suppose as long as it can properly learn, it'll get there (and, more valuable: STAY there) eventually. The brain is an efficient machine that can work in highly complex network, but I dont know if the fact every brain is born mostly blank of experience is a good or bad thing to build much more complex specialized behaviour like driving with 0 death in an entire nation.
    - jazzyjackson 5y ago
      The leg up that I gave over a super-networked AI: I’ve seen a trash bag before. If the cars have to hit every item they see to find out what happens then we’re going to be here a while!
metalforever 5y ago
Nah, this person saying ML cars don’t work is right unfortunately
acover 5y ago
Small nit - drivers are only about a third of the cost of shipping. Adding 10 hours to remove the driver probably wouldn't make sense in a lot of cases. PDF page 20 - https://truckingresearch.org/wp-content/uploads/2018/10/ATRI-Operational-Costs-of-Trucking-2018.pdf https://truckingresearch.org/wp-content/uploads/2018/10/ATRI...
- mike_d 5y ago
  Stated another way: You can ship something for 60% of the cost without a driver. The commercial trucking industry goes bonkers over a solution that cut costs by even .5%.
neillyons 5y ago
I don't think stop signs with RF beacons is needed. The cameras on the car can provide just as good an image as what a human eye can. The problem to be figured out is generating a mental model of the environment and reasoning about it. Think "Brain in a vat" analogy https://en.wikipedia.org/wiki/Brain_in_a_vat https://en.wikipedia.org/wiki/Brain_in_a_vat
jjav 5y ago
> Freeways are orders of magnitude easier than dynamic city streets Yes they are. Although it's still not an easy problem. Occasionally I get sucked in to watching highway accident and road rage videos on youtube and try to consider which ones a ML could realistically handle. It's still a very complex random environment, even on interstates far away from cities. I don't believe full self-driving has any chance of being a reality this century. It's far too complex a problem in an environment where all the edge cases do matter. > annotate the world This I do believe may start to happen in coming decades. But this is effectively an admission that actual self-driving isn't really possible, so the problem gets redefined to a smaller and easier scope. Although even that will only work in limited access roads where nothing else can be present. Like barrier-separated HOV lanes but for these trucks.

by mike_d 5y ago

ikerdanzel 5y ago

He learnt the field and know what can be done and what cannot be done. Go lookup the history of Ai with lisp and then deep blue vs Karpersky. Back then people believe humanoid like Star Trek Data is possible within our lifetime. If you have studied the AI of its day you would know it is near impossible. The OP above you is right, based on current ML knowledge self-driving car is impossible. Assisted self-driving car is more likely. The problem of self-driving car isn't like chess or go. There isnt simplified rules. Humans and humans needs are messy. What you're thinking of is some new technology say super LIDAR++ and new method say doubly deep organic learning might solve the problem. But as of now, they are not yet invented or extremely infant stage. But one thing for sure those aren't the current knowledge ML. Perhaps Waymo will get there...perhaps no. Many decades ago, there are tesla-like cars but it was successful because of battery tech and cheap oil price. They basically went out of business. So Waymo maybe be like them, full of possibility but the isn't ripe yet. Just like Friendster and MySpace before FB.

javagram 5y ago

Annotating every object on the road with RFID beacons seems like it actually would be an impossible project. Yes, you can attach beacons to stoplights and signs (although they already have “beacons” that display in the visible light spectrum). But you can’t attach them to people like the homeless pedestrian killed by Uber’s test self driving car, animals, trash thrown on the roadway or falling off a truck, or a boulder falling from the side of a mountain. And looking at the decades-long process it took to install PTC on train lines, it would take decades to install radio beacons on everything we can and by then technology should have advanced to the point where we don’t need them.

mike00632 5y ago
I saw a trash bag on the highway yesterday. It was full but looked light, as if it were stuffed with pillows or plastic bags. I could have safely hit it with my car (I didn't) whereas other objects that size I wouldn't. This decision making happens often like with pieces of paper or plastic bags. I thought about how much contextual knowledge it takes for us to make these everyday decisions.
- secondaryacct 5y ago
  There s however one thing you cant do but an ML solution probably could: share your contextual experience at the instinct level with every driver. Say you're right and an ML model cannot know intrinsically the trash bag is safer to hit than to avoid, however, if a few car hit or avoid those for a little while they can learn of the consequence of both actions and then share them back to every other car. I suppose as long as it can properly learn, it'll get there (and, more valuable: STAY there) eventually. The brain is an efficient machine that can work in highly complex network, but I dont know if the fact every brain is born mostly blank of experience is a good or bad thing to build much more complex specialized behaviour like driving with 0 death in an entire nation.
  - jazzyjackson 5y ago
    The leg up that I gave over a super-networked AI: I’ve seen a trash bag before. If the cars have to hit every item they see to find out what happens then we’re going to be here a while!

metalforever 5y ago

Nah, this person saying ML cars don’t work is right unfortunately

acover 5y ago

Small nit - drivers are only about a third of the cost of shipping. Adding 10 hours to remove the driver probably wouldn't make sense in a lot of cases. PDF page 20 - https://truckingresearch.org/wp-content/uploads/2018/10/ATRI-Operational-Costs-of-Trucking-2018.pdf https://truckingresearch.org/wp-content/uploads/2018/10/ATRI...

mike_d 5y ago
Stated another way: You can ship something for 60% of the cost without a driver. The commercial trucking industry goes bonkers over a solution that cut costs by even .5%.

neillyons 5y ago

I don't think stop signs with RF beacons is needed. The cameras on the car can provide just as good an image as what a human eye can. The problem to be figured out is generating a mental model of the environment and reasoning about it. Think "Brain in a vat" analogy https://en.wikipedia.org/wiki/Brain_in_a_vat https://en.wikipedia.org/wiki/Brain_in_a_vat

jjav 5y ago

> Freeways are orders of magnitude easier than dynamic city streets Yes they are. Although it's still not an easy problem. Occasionally I get sucked in to watching highway accident and road rage videos on youtube and try to consider which ones a ML could realistically handle. It's still a very complex random environment, even on interstates far away from cities. I don't believe full self-driving has any chance of being a reality this century. It's far too complex a problem in an environment where all the edge cases do matter. > annotate the world This I do believe may start to happen in coming decades. But this is effectively an admission that actual self-driving isn't really possible, so the problem gets redefined to a smaller and easier scope. Although even that will only work in limited access roads where nothing else can be present. Like barrier-separated HOV lanes but for these trucks.