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1. yters+GI[view] [source] 2019-12-13 19:06:06
>>mdszy+(OP)
Why is there never any fundamental research whether human intelligence is even computable? All these huge, expensive projects based on an untested premise.
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2. xamuel+JM[view] [source] 2019-12-13 19:36:22
>>yters+GI
There has been some philosophical speculating but that's generally not very actionable, with people clinging to either side of the question. On the practical side, it's the sort of thing which you can't just throw money at and make progress. Ok, you have $100mil to research whether human intelligence is computable. What do you do? Hire lots of humans and assign them noncomputable tasks and tap your foot waiting for one of them to turn out to be the next Oracle of Delphi? That's fantastic if one of them does, but if none of them do, then you've made zero progress: there's no way to know whether you failed because human intelligence is computable, or whether you failed because you chose the wrong tasks/humans.
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3. yters+5T[view] [source] 2019-12-13 20:17:46
>>xamuel+JM
But that's the sort of thing that should be researched: is the question scientifically answerable? The answer is not obviously no. I can think of ways to scientifically test for noncomputability. If I can then certainly much smarter and knowledgeable poeple can. People just assume like yourself it is not and throw lots of money at a certain assumption. If the assumption is wrong, not only is AGI a dead end, but "human in the loop" computation should be a huge win.
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4. drongo+4r1[view] [source] 2019-12-14 01:13:22
>>yters+5T
OK, what experiments would you design to test whether AGI is possible? Given the decades (centuries?) of thought that have gone into the issue, I'm sure a set of experiments would be valuable.
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5. yters+0C1[view] [source] 2019-12-14 04:21:54
>>drongo+4r1
If humans can solve problems that require more computational resources than exist in the universe, then AGI is not possible. I have run one experiment to demonstrate this.
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6. xamuel+G62[view] [source] 2019-12-14 14:41:52
>>yters+0C1
What was the experiment you ran?
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7. yters+Ba2[view] [source] 2019-12-14 15:30:37
>>xamuel+G62
Filling in missing assignments for a boolean circuit. In general it is an NP hard problem, and humans appear to do it pretty well at computationally intractable sizes.
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8. xamuel+0d4[view] [source] 2019-12-15 18:11:40
>>yters+Ba2
Did you publish a paper on these experiments?

I'm not familiar with the boolean circuit problem, but I wonder if it's an instance where the NP hardness comes from specific edge cases, and whether your experiment tested said edge cases. Compare with the fact that the C++ compiler is Turing complete: its Turing completeness arises from compiling extremely contrived bizzarro code that would never come up in practice. So for everyday code, humans can answer the question, "Will the C++ compiler enter an infinite loop when it tries to compile this code?", quite easily, just by answering "No." every time. That doesn't mean humans can solve the halting problem, though.

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