These comments are filled with confidently held, poorly justified assertions. Let's (again) challenge them:
1. "LLMs don't really reason. They've tricked everyone." -- This is the No True Scotsman fallacy for AI. It makes grand explanatory claims without falsifiable predictions. In other words: pseudoscience.
2. "LLMs are just fancy autocomplete, just next word prediction." -- This conflates the simplicity of a system's mechanism with its behavior. It's like dismissing a world full of rich phenomena because it's "just" F = MA. Or dismissing your mind because it's "just" propagating electrical firings.
3. "LLMs are statistical parrots, just combining their training data." -- Demonstrably not. LLMs always extrapolate and never interpolate. (LeCun et al, 2021) They also learn new abilities in zero/few-shot prompting. They're also many orders of magnitude short of the parameter count needed to store their training. LLMs can solve novel problems (from a combinatoric disparate handful of skills) way outside of their training data.
4. "People are just anthropomorphizing computer programs." -- No, critics are anthropomorphizing intelligence. We don't even have a consensus definition, let alone understanding, of intelligence/consciousness/qualia/agency/etc. Pretending that we can dismiss LLM understanding at our level of ignorance is the pinnacle of human hubris. Ignorance is okay. Pretending we aren't isn't.
5. "Look how this LLM failed . It can't understand." -- The is usually something that many humans fail at too. Yes, an intelligent foreign mind will fail at things, in both familiar and foreign ways. Needing an agent to behave identically to a human for intelligence is pure anthropocentrism.
If present AI systems are intelligence imposters, then show, don't tell. Otherwise, you're just providing meaningless metaphysical hairsplitting.