Does the the undecidability of the Halting Problem eliminate the possibility of 'Hard AI'? I'm defining 'Hard AI' as a human-equivalent intelligent machine, or beyond that. Contrast with 'Soft AI' the type of software that runs on your email filter for example.

I've been chewing on this problem for a little while now, and would like some feedback on my logic. This is the only place I could think to put it, so please feel free to move/remove if this is not appropriate.

My argument hinges on the definition of 'human-equivalent intelligence' as 'capable of solving any given instance of the Halting Problem'. This is something no machine can ever do - while they may be able to solve for sub-sets of the Halting Problem, they can never accept an arbitrary instance of it (ie, specific inputs I for a specific program P) and produce an answer.

Humans, however, do this all the time! The entire profession of programming revolves around fixing incarnations of the Halting Problem that pop up in one's own codebase. There are problem-tracking instances full of real-world examples of the Halting Problem - "Subsystem Z stops responding after receiving A with B options", etc. These examples are fixed by humans, and the problem goes away. Sometimes instructions are written for the machine to verify that the problem hasn't returned, taking advantage of the recognizability of solutions to the Halting Problem.

Since any 'Hard AI' would need to be just as capable as humans in any intellectual pursuit, and we KNOW that a machine that solves the Halting Problem cannot exist, we must conclude that there can never be human-intelligent machines.
You're understanding of "solve all instances of the Halting Problem" is flawed. All instances means ALL instances. Every single one, ever.

For example, no human knows if a Turing Machine verifying the Collatz Conjecture will halt. Bam, right there, your premise that humans can solve "all" incarnations of the Halting problem is flawed.

There is no reason to think that a sufficiently good AI wouldn't be able to solve the same, or more, instances of the Halting Problem that humans can.

The undecidability of the Halting problem means that there is no algorithm which solves the halting problem. That means there is no algorithm Humans can use, and no algorithm machines can use. The proof doesn't rely on what the algorithm runs on.

Another way to look at it is that the halting problem, and other undecidable problems, essentially boil down to searching an infinite space. The inability of humans to time travel and examine an infinite number of instances doesn't negate our intelligence, so there's no reason it would for machines either.