Sure we can, there are diseases which greatly hampers your ability to understand the world but doesn't hamper your verbal abilities at all, Williams syndrome for example. They are great at generating nonsense stories that doesn't make sense. GPT-3 is like that but much worse.
Say we apply the diagnostic criteria of William's syndrome to language models and deduce that they meet the criteria for diagnosis, then the diagnostic itself ie: the test results are the grounding for the conclusion not the computational substrate. In that way the discussion surrounding the computation substrate is a red herring or at the very least a unclear and roundabout way of grouping of the characteristic we're actually interesting in.
Byron can understand what's happening in the world around him and can communicate it through body language (just see the warmth in his eyes and his smile) but when he speaks everything comes out in a stream of nonsense.
If we tried to apply a language-model-centric view of intelligence we would rate Byron is unintelligent. That would clearly be a mistake, as anyone can plainly see that he is intelligent.
The contrapositive would be to show a clearly intelligent human with no communication ability that can still model the human world accurately. Past such examples don't tend to show this, though the co morbidity with no early human contact and severe developmental nutritional deficiency makes it hard to be sure.
> conditioned on the basis of a present reality
If we grant this hypothetical, we might find what it "says" fundamentally alien to us --- we might not even know it is saying anything at all.
Spiking neural networks are possibly closer to being biologically analogies, but they kind of suck to train and don't have good performance.
It takes a lot of computer "neurons" to simulate a single human neuron, and we can't simulate it perfectly in any case.
The way airplanes fly doesn't even vaguely resemble how birds fly. Same with neural networks and brains.
Wouldn't the fact that people's facts do not match up prove that they do not?
There's some romanticism in common between magicians, con artists, and fraudsters about how unclearly 'normal people' perceive the world so perhaps there's some truth to what you say. And the perpetual problem with artists and visionaries is that they see the world before everyone else does. For the one group they see things as they are now while everyone else seems to see things as they were 2, 5 years ago. For the other they see what the world could be, by exercising the tools near at hand.
One wonders then how an AI that actually understand things would be seen. As a trickster? A misunderstood intellectual? A madman?
Intelligence has been concisely defined as "the ability to profit from one's experiences." GPT-3 seems unable to profit from its ample experience being told who the president is.
People get so incredibly gullible when an exciting fantasy like sentient AI is in front of them. ELIZA was a laughably simple program and still fooled people.
The article correctly recognizes this, but then fails to actually make any meaningful contributions. Say the model was in fact conditioned on the basis of a present reality, would that change the interviewee's mind? The fact that it's difficult to say simply hints that the interviewer didn't really do that great of a job drilling down to the interesting questions.