Re: Such problems were known _way_ before the current hype
This is precisely the problem.
What "neural nets", "machine learning", etc. are actually doing is "brute force to find a set of conditions that result in the desired criteria the majority of the time".
- "That's a banana."
- "Okay. All bananas are 400 pixels wide."
- "That's NOT a banana."
- "Okay. Most bananas are 400 pixels wide but they all have a white pixel in the top left."
- "That's a banana"
- "Okay. Most bananas have a white pixel in the top-left, are 400 pixels wide, and look a bit yellowy overall".
- "That's a banana"
- "Okay. Most bananas have a white pixel in the top-left, are 400 pixels wide, and look a bit yellowy overall, and say Getty Images on them".
...
And so on. In between, there is NO introspection into the criteria that are being inferred upon. And it will fit the training data, for the most part. And if the training data is large, you might get lucky and it might be useful enough to put a set of ears on a webcam image in roughly the right place. But the training data can't be COMPLETE and so you cannot use it with any surety. This is why "machine-learning AI self-driving cars" are basically suicide-murder-boxes.
Not only that, they plateau quickly because they can't "unlearn" those early basic assumptions (because you can't even tell what they were, let alone itself!), so trying to train it to recognise planes and/or apples without literally starting from scratch is almost a complete waste of time.
Say it takes 1,000,000 pieces of training data to recognise a banana... it surely takes 10-100m pieces of training data to "untrain" it or retrain it to also recognise other things, and what's "not a banana". Literally, you have to show it enough "not a bananas" for it to the be retrainable on "is an apple" without just assuming everything that's not a banana is an apple.
"AI", "machine learning", "neural nets" are all toys. Sure, they can do some funny things if you let them, but they are uncontrolled, uncontrollable, single-purpose toys.
At no point has anyone made an AI that literally can say "Hold on, so that's not a banana? But I was using this criteria. Can you tell me what the difference is between something that meets all this criteria but isn't a banana?". And yet that's a classification game we play with kids in primary school, where you make a "20-questions" like tree to identify species, etc.**
The day we have an AI breakthrough is the day we have a computer that you program/operate by just clicking at the screen, and a big "Yes/No" switch to tell it off until it understands what it is that you want it to do.
Clicks icons.
Loads up PDF in Microsoft Reader.
Hastily press the NONONO! button.
It reverts back a bit, closes Microsoft Reader, opens it in Notepad.
Hastily press the NONONO! button.
It reverts back a bit, closes Microsoft Reader, opens it in FoxIt
Press the Yes! button. Now it knows what you wanted, and changes your settings to reflect that.
To program:
Hold down the "programming shift modifier" key.
Click button on screen.
"Alright, so what do i do when you click that?"
Click-and-drag to the printer icon on the desktop.
"Ah, right, so you want me to print something when you click that button".
Press the Yes! button.
"Oh, I'd print this... <shows screenshot>"
Press No button.
Hold programming modifier.
Click-and-drag around the current window in the screenshot.
Press Yes button.
(** Ironically, I can remember an early piece of programming I did was to make a game where you give the computer the name of two objects, it asks you for a question that would distinguish them, then you give it another object, it runs through the question, and builds the tree as you answer Yes/No to the distinguishing questions. Each time it ends up as something it doesn't know, you get to type in a question to distinguish it from the nearest thing. Does it have four legs? Does it live underwater? etc.
The computer had no intelligence, but you classified things by having it demand a distinguishing question. And after sufficient such training, it could play a decent game of 20 questions (for at least 2^20 possible objects!)