>This is just another incarnation of "AI is the thing we haven't done."
I don't think so - it appears to be an objectively correct assessment of the current state of the art.
> Otherwise we're just moving goalposts.
The first movement of the goalposts was to call '80s technology AI. Now they are drifting back to where they started.
On the other hand, I am surprised by the claim that AI is stuck; my outsider's impression is that progress has accelerated. Perhaps the impression of being stuck comes from more people realizing how difficult a problem it is.
Deep learning made practical a large number of applications that were previously intractable by neural network approaches. Advances over the last 10 years have pushed the boundaries of what machine learning systems are capable of doing. However machine learning has algorithmic limits to what it can accomplish, and we are starting to hit those limits. A change in paradigm is required to begin making real progress again. Either a change to something new or a regression to older ideas that were temporarily put on the back burner.
That's not a universally held view, but I think it is the sentiment behind this editorialized title.
How deep an understanding is required to meet the threshold? The skepticism feels like "no true Scotsman" applied to the definition of understanding.
I observe the following in young children when exposed to a new word:
0. First exposure to totally new word used in a sentence with more familiar words.
1. Brief pause
2. Mimic pronunciation 1-2 times
3. Process for minutes, hours, or days.
4. Use the word in a less than 100% correct way
5a. Maybe hear the phrase repeated back with the error "corrected" (hello internet)
5b. Maybe hear more usage of the word in passing from others (with varying degrees of "correctness")
6. Recurse for life.
At what point did the person understand the word? How is AI translation substantially different?
I'm not sure I understand any word in a way that would satisfy AI skeptics.
Ironically, your last sentence has 'no true Scotsman'-like reasoning, along the lines of 'no true AI sceptic would fairly evaluate a claim of machine understanding.'
BTW, I am not a skeptic of the potential of AI, though I am skeptical of some claims being made.
We can understand how individual chemical reactions in Einstein's brain work, but that doesn't make us smarter than him.
> Even Google Translate, which pulls off the neat trick of approximating translations by statistically associating sentences across languages, doesn’t understand a word of what it is translating.
This is just another incarnation of "AI is the thing we haven't done." He's parroting Chomsky's disdain for statistical models and John Searle's fundamental misunderstanding of AI. For the former, Norvig has a fair rundown of Chomsky's complaints (http://norvig.com/chomsky.html).
> bears no resemblance to what a neuroscientist would call intelligent
TensorFlow gets results. The neuroscientist can claim it's a P-zombie, but they need to point to some criteria for accepting something as intelligence. Otherwise we're just moving goalposts.