[antonvs]

> They are token predictors that use statistical techniques to emit the randomly weighted next most likely token given the previous token list.

Sounds like an implementation detail. Now describe how human reasoning works and explain why that process of chemical and electrical signals results in "reasoning" whereas what LLMs do isn't.

The problem with being this reductive is you can do it to anything, including humans. You can’t be reductive about LLMs and refuse to be reductive about humans - that's poor reasoning, and an LLM would out-reason you on this point, further negating your case.

[claytongulick]

Human cognition is poorly understood and much more complex than it seems.

For an example, look at some of Julia Mossbridge's work.

If even a small part of her work is true and valid, it points to something far outside our current framework.

You don't need to go as far afield as Mossbridge, though - that's an extreme example. Pretty much any modern neuroscience will make you question a lot of assumptions, at least it did for me.

[CrazyStat]

> For an example, look at some of Julia Mossbridge's work.

Never heard of her but I just spent about 5 minutes looking.

Her PhD is in communication sciences and disorders [1], but apparently she’s a quantum physicist now:

> AMELIA is built on the Causally Ambiguous Duration-Sorting (CADS) effect — a breakthrough discovery by Dr. Julia Mossbridge showing that light, under classical boundary conditions, behaves differently based on future temporal boundaries. [2]

Filed under crank, not going to bother investigating further.

[1] https://books.google.com/books/about/Have_a_Nice_Disclosure....

[2] https://americanelectrodynamics.com/#technology