Predicting with All-Caps confidence that autonomous driving is "decades away" is at least as indefensible as overly optimistic predictions were.
Why? It never exceeded consumer expectations, which are extremely high for automated systems. Even a correctness rate of 99.9% means multiple errors per day for most people. Consumers expected approximately zero errors, despite not being able to achieve that themselves, sometimes even with their own handwriting!
Because handwriting is made by humans, there is some percentage of it that simply cannot be reliably recognized at all. But people hold that against computers more than other people because computers are supposed to be labor saving devices.
Likewise because roads are made by people, and other cars are driven by people, so a self driving car will never be able to be perfectly safe. But that is essentially what advocates are promising.
That’s especially true if people expect the same level of convenience, especially in terms of time. People speed and take risks all the time when driving, in the name of saving time. I think it’s likely that an autonomous car optimized for safety would also be a car that just takes a lot longer to get anywhere with.
Speed matters. It’s a big reason we all use touch keyboards on our phones instead of handwriting recognition.
The only handwriting recognition system which ever worked correctly with a low error rate was Palm Graffiti. It forced the user to learn a new shorthand writing style designed specifically to avoid errors.
I think this supports the grandparent's point about using the actual strokes, including angle and azimuth, to reconstruct intent.
I was also fairly proficient with Graffiti, back in the day, but I consider that an input method, not handwriting recognition. I was facile with T9 as well.
Because it asked users to learn a new way of writing, when the recognition failed, users were more likely to blame themselves, like, "Oh, I must have not done that Graffiti letter right, I'll try again."
But when it came to recognizing regular (i.e. natural) handwriting, users believed inherently (i.e. somewhat unconsciously) that they already knew how to write, and the machine was new, so mistakes were the machine's fault.
There is little market demand for handwriting recognition, and thus little active research goes into it. Not because it is a difficult or problematic technology, but because better alternatives exist that make it irrelevant.
Even if someone were to come up with an absolutely perfect handwriting recognition system, most people wouldn't use it. Why? because the advent of multi-touch screens means that most people can type much faster than they can hand-write anyway.
What changed was that touch screens became better. The old capacitive touch screens were clunky, slow, inaccurate. You could put a keyboard on them, but the lag and poor accuracy meant you couldn't really touch type comfortably. Then multitouch came along and made on-screen keyboards much more responsive and accurate.
But also, Blackberry and (pre-smartphone) phones with SMS made people more comfortable with the idea of using keyboards for text entry on handheld devices. And crucially, auto-correct and predictive text entry covered up for accuracy errors and made text entry by keyboard even more attractive.
Excellent point, stealing that. I work in automotive and an engineer, traveled around the world, think the realistic possibility of self driving cars without major changes in how we make roads, everywhere, is extremely low.
An other handicap for self-driving cars is that the problem is effectively harder at the start when the majority of the traffic will still be operated by human drivers who are a lot harder to predict reliably than an other autonomous vehicles.
Beyond that, I strongly believe that software engineering is still ridiculously immature and unable to deliver safe, reliable solutions without strong hardware failovers. We have countless examples of this. We simply don't have the maturity yet, we're still figuring out what type of screwdrivers we should use and whether a hammer could do the trick.
The visual recognition needed is well beyond the systems today.
It probably made a lot of sense in the Southern California design center. In Upstate New York, that camera is covered in road spray and salt, and my brain cannot see anything or act effectively without cleaning it. Even after doing that, it will get dirty again after a few minutes of driving.
I’d guess that a least a few dozen people will hurt by this decision.
Take this problem to the self-driving car and things get even worse. You’re going to have a lot of problems with sensor effectiveness that cannot be magically fixed with software.
I was waiting for my bus to work one morning after a large snowfall. The snow clearing crews were hard at work, but the street was effectively blocked by piles of snow, men, and machines.
Yet, my bus arrived on time *driving down the sidewalk".
I am not sure how any self-driving system could have figured that out :)
Something like half your human brain is devoted to visual processing.
There's a tendency to think that things like language is what makes the human brain special, or our ability to plan or think abstractly, and we talk about things like "eagle eyes", but the truth is humans are seeing machines with most everything else as an afterthought.
The reason your cat will attack paint spots on glass for hours and flips the hell out about laser pointers is because their visual systems are too simple to distinguish between those and the objects that actually interest them, like insects.
Vision is not the easy part of AI.
I think it is, actually. Going from raw pixels to objects is the (relatively speaking) easy part. It's the next part (using that for planning and common-sense reasoning) that's the hard part. Machine learning has already advanced past humans in this regard for many classes of problems - which is part of the reason why captchas are getting so hard.
This was several years ago, hence the move away from obfuscated text (which was getting harder and harder to read): https://spectrum.ieee.org/tech-talk/artificial-intelligence/...
I'd be surprised if basic perception tasks as human-ness tests last more than a few more years.