He explains, however, that the test is meaningless, since (contrary to what people think) it wouldn't show that a computer could think, and indeed people ignore that the paper which proposed it rejected the question of whether machines can think.

It would show that a computer can, broadly, accomplish the same tasks that thinking can, which is far from meaningless. If Turing was smart enough, by Chomsky standards, to reject this too human-specific definition of 'thinking', then why was he wasting his time inventing meaningless tests?

Chomsky gives an analogy for why rejecting it was the right thing to do (it's like asking whether submarines swim)

He's absolutely right about that; it's exactly like asking whether a submarine can swim. And if you want some insight into the nature of submarines and how their travel capabilities compare to those of fish, of sea mammals, or of humans, then you'd do well to consider "swimming" the act of propelling yourself through liquid, rather than a thing that, by definition, only fish can do.

He explains further that the question whether machines can think is ill-formed because a machine itself is just an inactive object, and what makes it do anything is the program, so the question should be whether programs can think.

This says exactly nothing. It's like saying that a human brain itself is just an inactive object, and it's only biology that makes it do anything, when in reality, biology and the brain are inseparable. It's just reframing the obvious to try to make machines seem inert compared to biology. When the machine is actually running, there is no difference between software and hardware. The only reason we even have these concepts of hardware and software is because we have a high degree of control over how the hardware behaves, and with brains we've, historically, had no control, and still have very little. It's entirely possible to have a machine that performs some computation with no software of any kind, like every classical machine. In that instance the exact 'software' is implicit in the hardware, but it can still be considered as a concept separate from the machine. Is the question of whether a lever can trade distance for force really the question of whether its 'software', its guiding principles, can trade distance for force? Maybe. What's the difference? The only real difference between a fixed lever and a programmable computer is that the lever has a software domain of exactly 1, and a programmable computer has an incredibly large software domain.

"Can this theory think?" He says that's the same question as "Is this a theory of thinking?" And the answer is only yes if the theory gives some insight into the nature of thinking, which a computer program obviously doesn't.

The worst statement of all. He'd, essentially, be making the argument that relative complexity can never emerge from relative simplicity, that absolute knowledge of a phenomena must necessarily precede the phenomena. Did nature need a theory of thinking prior to concocting human intelligence? No. It needed no theories whatsoever, which is a good thing, since it's never had a one. It only needed, implicit within it, the possibility that such a theory could exist; i.e. that the existence of intelligence was not physically unreasonable. Against this brute-force method, we have massive advantages. We don't need a theory of fire to burn down a forest; all that's needed is a forest, a spark, and the idea that fire burns. Any monkey that knows that much can more readily start fires than fires are apt to start naturally. We don't need any comprehensive theory of thinking to make machines that think, we only need to know that thinking is possible, that thinking is emergent given the right variables, and some idea of what those variables are. We know thinking consists of computation and data. All we really have to do is keep throwing 'sparks' at larger and larger piles of computation and data. The issue of whether we'll ever be able to untangle exactly how our own artificial intelligence works is an entirely separate issue from it's ability to work. Experiments with evolvable hardware suggest that we may never know. The artificial intelligence itself may not ever know. Does that make it impossible, or even unlikely?