If you look across the roof of the Tesla it totally failed to imitate the car in front of it too, that's a double fault, it had more than one indication the lane was changing direction.

Here is an article with a bit more info about that crash:

https://www.digitaltrends.com/cars/tesla-driver-error-autopi...

There's more like these:

https://www.theguardian.com/technology/2015/oct/21/tesla-aut...

It should probably be both to avoid moving goal posts. That would make even chess algorithms still AI.

Self driving cars and image recognition are both definitely still AI.

"AI" does not typically mean strong or general AI.

Perfecting safety on human drivers first is the way to go and will most of the risk of lettings computers drive.

I'm not sure that's a fair analogy. Without the canal network to cheaply transport goods and resources in bulk, it's hard to imagine how Britain could ever have industrialised to the point where building a railway network became possible in the first place!

Besides, railways did not immediately obsolete the canals as you seem to suggest. Some canals were still being built and extended until the early 1900s (70+ years after the railway boom), and the last commercial freight services lasted until as late as 1970 - suggesting it was really motorways that "killed off" commercial canal traffic.

One key point of difference is that (like road freight) pretty much anyone could operate a freight service using canals, where as the railways were in the hands of a few huge corporations. That meant a lot of niche, point-to-point freight was more viable to transport over water than rail.

The "you don't actually own the hardware you paid for" model is slowly becoming untenable for hardware sold to individuals.

To add to it there are techniques like applying shadow to a bright image.

When we combine some of these techniques, the task does become possible, even in in adverse conditions.

Also, various techniques often complement each other. For e.g. We may derive a steering angle out of a Machine learning system, and we can cross check that against the lane detection, vehicle detection (no collision) etc.

To think of it, we when we drive ourselves, we just use the eyes. So there is a view that cameras alone are sufficient. But definitely as Radar and Lidar complement the cameras and make the driving system more robust. As Lidar gets cheaper, we are bound to see it being used more even in camera only approaches.

- investing in such a fleet would be like investing in any other kind of business: it's easier if you have the money, but if not you can go to any bank and get a loan.

- prices for a trip with a self-driving taxi will drop immensely, this is probably going to be a big liability if you would start the aforementioned business

- other effects that I can't think of right now

It is true that in a lot of places rich people have an edge on the less-wealthy (it's easier getting/staying rich if you are rich), but that's more of a generic problem than something that would be amplified by change to self-driving cars.

The lane-holding feature (autosteer) does expect you to keep slight pressure on the wheel. It has, that I can discern, four modes ...

freeway following (another vehicle in front) freeway leading nonfreeway following nonfreeway leading.

Only in the first case, you have five minutes before it starts pestering you to hold the wheel. In the other cases it's one minute.

Lane holding and adaptive cruise control in freeway following mode is a WONDERFUL feature. It drastically reduces the driver's workload in heavy traffic. And, it has speed control features that contribute to the melting of compression-wave traffic jams.

Lane holding can be a little squirrely when the road surface is dirty. I think the car sometimes mistakes tire marks for lane markings. There are parts of my regular route where I just take over from lane holding.

Snow or heavy rain? the lane holding feature goes first, then the adaptive cruise control. Snow, rain, or frost on the windshield interferes with the forward looking camera. Snow or ice on the nose interferes with the radar. Ice on the bumpers interferes with the near-field sonar proximity sensors.

Autonomous driving on the Stanford campus and up Sand Hill Road is one thing. Autonomous driving in a nor'easter snowstorm on winding Atlantic Coast roads is another. We shall see.

I admire and support people who tackle hard problems fearlessly. Tesla's doing that.

Volvo CEO said already in 2015 that Volvo will accept full liability whenever one of its cars is in autonomous mode.

http://fortune.com/2015/10/07/volvo-liability-self-driving-c...

Why does this argument hold true only for self-driving cars, and not current cars ? As such, self-driving cars are just a point in continuous evolution. Current cars are already quite different from what they were a few decades ago. Why is now a good time to draw a line ? Every change in this eveolution goes through government approval. If it is approved, it should be safe enough for everyone.

Waymo want a system that has a zero accident rate, even if that means it can't operate in the rain.

Volvo is plugging for magnets in roads in Sweden, so they can find lanes in the snow. It might happen, because it can also be used for snowplow guidance. In heavy-snow areas, posts, poles, and even over-road arrows (Japan uses this in Hokkaido) are placed to provide guidance. It's not intended to replace vision and LIDAR, just as additional guidance hints for bad conditions.

It wouldn't need to do anything but "ping", the battery could last for years. You could even have a mechanism to disable it when the lines are repainted, though normally roads that use the existing version of these reflectors would have them removed when moving lines.

The transmitter would have to be powerful enough to go through a small amount of snow in some states.

The question is can we get the car companies to agree on a standard for this? Would it make sense to put it in the frequency range allocated for vehicle radar systems?

What we get instead is an attempt to define the whole system de jure, including full V2V protocols and specifications.

Humans are still better at interpreting many things and probably dealing with weather and construction and when there is no data.

If I buy a car and want to take the engine out, or a light and resell it - I would be very stupid, but, it is my property and I should be able to.

If Tesla want to lend instead of sell you something - fine, just be honest!

What I am saying is that Apple sells you a product. You own it. You can do whatever you want with it. Feel free to alter any part of it, just don't expect it to work or keep your warrantee. The fact the product has limitations out of the box is a different matter. (Kind of like no one complains that kitchen timer can't boil water, or doesn't have nanoseconds precision — you want those things, you buy a different thing or make your own.)

What Apple doesn't do is to restrict you in how you use their product. There's no such thing like "you can only non-commercially photograph your family" or "never resell your iPhone", or "detaching screen is illegal".

And, more importantly, there is nothing Apple can do to stop you from doing any of those things.

Now, I'm not saying we get rid of all laws. End of copyright will not allow me to put a maliciously crafted copy of Microsoft Windows or Google chrome online in order to deceive users into thinking they are genuine. I still may not misrepresent when I copy things. In fact, I think these laws need strengthening which we can if we ditch copyright.

Reading road signs optically is a solved problem. Mobileye and similar systems have been doing this for a decade or more.

However, since the number of features is quite small, I'm sure owners will quickly get used to what the car does and doesn't do. The autopark and summon is surely going to run over far fewer children than human drivers do in those situations. That leaves just adaptive cruise control and lane changing. Well, if you forget to change lanes because you trusted the car, you still won't crash since the front crash detection (and your eyes) should protect you from that. So I don't see any safety issue there.

That sounds speculative.

If the car fails to detect one in a thousand cars in front of you, or one in a thousand corners, I can see that being highly dangerous.

Let's say you change lane 5 times while commuting. That's 50 times per week. Now, are you going to pay attention well enough that you catch it twice a year just before it pulls out right into another car?

Perhaps likening it to having another person driving you would be good. If you were given a perfect chauffeur, except with the knowledge that they'll drive straight through one in a thousand red lights with no warning, are you confident you'll catch them?

the fact that safety features such as seatbelts and airbags save lives is undeniable. they didn't lead to uncanny valleys of complacency for anyone but drivers who chose to abuse those features with wreckless driving. the data for AP already indicates this trend will continue with ML drivers.

As you can imagine, anybody intending to use the left-most lane for high-speed driving is now forced to use the brakes, execute a [rarely safe] lane merge to the right, pass the slower vehicle on the right, and then aggressively execute a merge back to the left.

Roughly 100 people die in car accidents on a daily basis https://en.m.wikipedia.org/wiki/List_of_motor_vehicle_deaths... For further context, the World Trade Center attack on September 11, 2001 resulted in 3,000 deaths and has led to a brief but complete shutdown of air traffic, complete overhaul of homeland security, passage of PATRIOT Act, at least one major war and countless "military operations" that don't count as wars.

If you seriously want to play the inane game of "well if a human doesn't have it then a Tesla doesn't need it" then let's play that game and talk about the things humans have that the Tesla lacks.

What's interesting about human's vision system is that the human eyeball is, relatively speaking, poor. We have digital cameras far better than that already. It is what the human brain that does with that raw data which makes us, as a species, thrive. Most of what we believe we "see" we never actually see, our brain fills in the gaps dynamically and infers information over time.

So this human processing ability, much of it automated rather than conscious, is totally relevant if you want to have this "Tesla Vs. human" debate. It is also why Lidar might be needed to make up the massive shortfall in a Tesla's processing ability relative to the human brain.

But hey, you want to keep to the "but HUMANS don't need it" then I ask where is my 38 petaflops and 1 TB of memory...

On your second point, the important thing here is that you don't need to disperse much of this information to humans. Humans automatically recognise situations based on all of their experience, not just their driving experience. Of course sometimes external information sources like the news might be helpful, but much of it is just down to understanding context. See fresh horse crap on a country road? Someone's probably riding horses nearby. Horses scare easily. So, slow down and try to avoid anything noisy that could startle the animals. How many of today's self-driving algorithms take into account this kind of implied knowledge?

https://www.technologyreview.com/s/415041/new-measure-of-hum... I don't think we know enough about how the human brain works yet to give a precise value, but just on caloric arguments I would say that the mean processing power of the brain is not significantly above what we have now in general purpose computing devices.

I suppose you could make ML avoid sharp changes in recognition, but I don't trust the current neural-network models to do so reliably.

If you take the example of Chess, humans and machines play very different styles. Computers replace predictive understanding with excellent memory and fast search.

Similarly for cars, we want to replace the lack of a powerful predictive model with some compensatory mechanism, such as sophisticated sensors. The problem is that, even with faster reaction times, better sensors and fuller awareness, these cars' compensatory abilities against a lack of powerful predictive models are still far from sufficient.

At this point in time, a car with more sensors and failsafes to augment the human against collision is safer than a self-driving car that depends on a lack of lapses of attention. That depends on proper behavior in the customer. Even dividing tasks, with the human controlling the steering (but allowing the car to takeover when highly certain of danger) and the car controlling acceleration would be safer. This set up acknowledges the human propensity to mind wander when attention is not engaged.

Until self-driving cars no longer require human rescue in difficult situations, one can't rightly say that self-driving software are better drivers than humans.

Another thing is that your eyes can last you 100+ years, technology is not that durable and breaks more often, the objectives in cameras get dirty etc.

The cameras typically aren't as good as human eye, for example there are reports where Tesla wanted to jam into a truck in front only because its back in the camera couldn't be differentiated from the sky.

Yes, relying on cameras only is perfectly fine when you play PS4 game, but when life is on the line you want extra safety checks. Kind of like cars have brakes on every wheel and then also a handbrake. How every car has minimum of 3 stop lights (how often you see that one or more lights are bad in other cars?)

Your belief that we have hard AI (and this is kind of indirectly created by companies like Tesla, Google, Amazon, IBM etc) gives you conclusion that just two cameras should be enough in reality we did not made much progress in that area and instead just concentrated on specialized AI that is capable solving specialized problems, that kind of approach absolutely works better with more sensors.

http://i.imgur.com/fk3OvEW.jpg

This situation generated constant lane departure warnings for the driver.

Humans don't see elephants suddenly because a prior is telling them that an elephant is improbable in that context.

Something like that in a computer system shouldn't be above the current capabilities.

A computer isn't going to look down at a text message on their phone, fall asleep at the wheel, or get in a car while intoxicated. All which occur literally every day. People take driving for granted, because (at least in the US) we have to. Our sprawling suburbs couldn't function without it, so the barrier to entry is simply being a teenager.

Would I completely trust Tesla's auto-driving? No, not at all. But I at least trust them as much as I do an average driver, which is still just barely. The difference with Tesla's system is that one failure leads to improvement of the entire fleet, whereas one human failure maybe improves that one human driver. That means self-driving cars will continuously improve, while humans will just continue to be terrible drivers.

For a human, the noise isn't bad recognition, it's corrupted sensor data via distraction. It's one of the most common causes of accidents. For the AI agent an elephant will never appear unless it's been trained to be recognized. More likely it's recognized as an obstacle, which is ok. But keep in mind that years of Google's autonomous vehicle success make this pretty improbable, certainly less than in the average driver.

Much of the fear here is irrational and natural when humans lose control.

As a human, if you asked me to match these synthetic images to a most-likely real-world match, then my responses will also look "confused."

The truth is people really really stuck a driving, but it's easy enough that the vast majority of mistakes don't result in any problems.

There's plenty of conditions that are more difficult to humans: cars that are painted with the same color of asphalt seem to disappear in highways. Also, fog.

I posit now: "as the problems with automated cars become evident, solutions provided will tend towards Skynet as t increases."

I don't understand where some people get the belief that automated vehicles will suddenly become targets of murderous or sociopathic pranksters?