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Did it understand, or did it just give you something that sounded like what you wanted to hear? My money would be on the latter for reasons I've already gone into at length.
You bring up zero energy particles and my mind goes immediately to my old professor's bit about frictionless spherical cows. They're a fun thought experiment but aren't going to teach you anything about the behavior of bovines in the real world. You want to talk about "the latest scientific advances" I say" Show me the experiment". Better yet, show me three other labs replicating that experiment and a patent detailing practical applications.
You ask me where is my epistemic humility? I ask you where is your belief in the scientific method?
You claim to have already thoroughly debunked my claims but that's not how I remember things going down. What I remember is you asking GPT to debunk my claims for you, and it failing to do so.
Finally, I feel like this ought to be obvious but for the record; training a regression engine on a larger datasets is only as useful in so far as the datasets are good. A regression engine will by it's nature regress and is thus more prone to generating false positives and being led astray (either by an adversary or by poorly sanitized inputs) than convergence or diffusion-based models of similar complexity.
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