I think TA's argument fundamentally rests on two premises (quoting): (a) If we were on the path toward intelligence, the amount of training data and power requ

I think TA's argument fundamentally rests on two premises (quoting): (a) If we were on the path toward intelligence, the amount of training data and power requirements would both be reducing, not increasing. (b) [LLMs are] data bound and will always be unreliable as edge cases outside common data are infinite. The most important observed consequences of (b) are model collapse when repeatedly fed LLM output in further training iterations; and increasing hallucination when the LLM is asked for something truly novel (i.e. arising from understanding of first principles but not already enumerated or directly implicated in its training data). Yes, humans are capable of failing (and very often do) in the same ways: we can be extraordinarily inefficient with our thoughts and behaviors, we can fail to think critically, and we can get stuck in our own heads. But we are capable of rising above those failings through a commitment to truths (or principles, if you like) outside of ourselves, community (including thoughtful, even vulnerable conversations with other humans), self-discipline, intentionality, doing hard things, etc... There's a reason that considering the principles at play, sitting alone with your own thoughts, mulling over a problem for a long time, talking with others and listening carefully, testing ideas, and taking thoughtful action can create incredibly valuable results. LLMs alone won't ever achieve that.