I disagree that intelligence can't be brute forced, at least if you don't care about computational resources. Presumably, what we mean by 'intelligence' is the passing of some Turing test (otherwise, if you just define 'intelligence' to be passing a Turing test with some kind of "elegance" in the design of the program, then your claim is true but only because you defined it to be that way).
If computational resources truly weren't bounded, then we could build a massively inefficient lookup table whose search grows exponentially (or worse) in the length of the input. See this paper and this one for arguments about how to bound the complexity of such a lookup table argument. This paper is also very useful and the writing style is great.
What you cannot do, however, is claim that intelligence cannot be brute forced (again, under the assumption we ignore resources), without some appeal to computational complexity theory.
In particular, the Aaronson paper points out that according to Searle's (flawed) Chinese room argument and Ned Block's criticisms of the Turing test, complexity theory puts us in the situation where it is exactly the efficiency of an algorithm that gives it the property we ascribe to intelligence. We only know something's intelligent because any reasonable Turing test that "respects" human intelligence will also function like a zero-knowledge proof that any agent who can pass the test does not have an algorithm that's exponential in the size of the input.
Watson achieves the necessary speed (for the greatly restricted test of playing Jeopardy) but as you mentioned, Watson is easy to unmask simply by asking for the second or third best answers. However, in terms of complexity theory, Watson's program fails the Turing test detrimentally... the program's resource efficiency is dismal compared to humans. It's doing something 'stupid' like a slow lookup with some correlations and statistical search. With similar resources to a human, this approach would be doomed to failure, so IBM just scaled up the resources until this bad approach no longer failed on the desired test cases.
Thus, if you would want to use 'intelligence' to label a planet sized computer which solves human Turing tests by brute forcing them with tremendously outrageous resource consumption, this would be a fundamental departure from what the literature I linked above considers 'intelligence.' If the planet-sized computer did fancy, efficient algorithms, then its massive resources would imply it can blow away human performance. The Turing test should be testing for the "general capacity" to do something, whether by lookup table or some equally stupid way, or by efficient intelligence.
Complexity theory really plays a large large role in all this. I would also add that I see no reason not to call a massive look-up table intelligent... assuming it is implemented in some kind of hardware and architecture that's much better than anything human's know about. If it turned out that human minds, for example, were some kind of quantum gravity look-up table (I absolutely do not believe this at all, but just for the sake of argument) I would not instantly believe that humans are not intelligent.
Thus, if you would want to use 'intelligence' to label a planet sized computer which solves human Turing tests by brute forcing them with tremendously outrageous resource consumption, this would be a fundamental departure from what the literature I linked above considers 'intelligence.'
A planet-sized computer isn't big enough to brute-force a Turing test. At least, it isn't big enough to build a look-up table. Actually brute forcing a Turing test would require figuring out how the human would react to each possible output, in which case you've already s...
Some interesting numbers to contextualize IBM’s Watson:
To put this in perspective, a conservative upper bound for a human being standing still is at most about 150w — less than 1/10 of 1% of Watson — and the person just holds the buzzer and operates it with a muscular control system.
Each of the servers generates a maximum of 6,649 BTU/hour. Watson overall would generate about 600,000 BTU/hour and require massive amounts of air conditioning. I don’t know a good estimate on heat removal, but it would up Watson’s energy cost significantly.
I don’t mean to criticize Watson unduly; it certainly is an impressive engineering achievement and has generated a lot of good publicity and public interest in computing. The engineering feat is impressive if for no other reason than that it is the first accomplishment of this scale, and pioneering is always hard… future Watsons will be cheaper, faster, and more effective because of IBM’s great work on this.
But at the same time, the amazing power and storage costs for Watson really kind of water it down for me. I’m not surprised that if you throw power and hardware and memory at a problem, you can use rather straightforward machine learning methods to solve it. I feel similarly about Deep Blue and chess.
A Turing test that would be more impressive to me would be building something like Watson or Deep Blue that is not allowed to consume more power than an average human, and has comparable memory and speed. The reason this would be impressive is that in order to build it, you’d have to have some way of representing data and reasoning in the system that is efficient to a similar degree that human minds are. One thing you could not do is simply concatenate an unreasonable number of large feature vectors together and overfit a machine learning model. Since this is an important open problem with lots of implications, we should use funding and publicity to drive research organizations like IBM towards that goal. Maybe building Watson is a first step and now the task is to miniaturize Watson, and in doing so, we’ll be forced to learn about efficient brain architectures along the way.
Note: I gathered the numbers above by looking here and then scouring around for various listings of specific hardware specs. I'm willing to believe some of my numbers might be off, but probably not significantly.