Whether or not you agree, a lot of people do. There is a trivial sense in which a perfect compression algorithm is a perfect predictor (if it ever mispredicted anything, that error would make it a sub-optimal compressor for a corpus that included that utterance), and there are plenty of ways to prove that a perfect predictor can be used as an optimal actor (if you ever mispredicted the outcome of an event worse than what might be fundamentally necessary due to limited observations or quantum shenanigans, that would be a sub-optimal prediction and hence you would be a sub-optimal compressor), a.k.a. an AGI.
Where a lot of us get off the fence is when we remove "perfect" from the mix. I don't personally think that performance on a compression task correlates very strongly with what we'd generally consider as intelligence. I suspect good AGIs will function as excellent compression routines, but I don't think optimizing on compression ratio will necessarily be fruitful. And I think it's quite possible that a more powerful AGI could perform worse at compression than a weaker one, for a million reasons.
Where a lot of us get off the fence is when we remove "perfect" from the mix. I don't personally think that performance on a compression task correlates very strongly with what we'd generally consider as intelligence. I suspect good AGIs will function as excellent compression routines, but I don't think optimizing on compression ratio will necessarily be fruitful. And I think it's quite possible that a more powerful AGI could perform worse at compression than a weaker one, for a million reasons.