guy recently linked this essay, its old, but i don't think its significantly wrong (despite gpt evangelists) also read weizenbaum, libs, for the other side of the coin
guy recently linked this essay, its old, but i don't think its significantly wrong (despite gpt evangelists) also read weizenbaum, libs, for the other side of the coin
Okay, so, what is your basis for thinking that, for example, if a brain was given some set of rules such as 'if you are given the symbol "A", think of number 1 and go to the next symbol' and 'if you are given the symbol "B" and are thinking of number 1, think of number 2 and go back by two symbols' and some sequence of symbols, that that brain wouldn't be capable of working with those rules?
As in, they are modelled by Turing machines sufficiently well in some sense? Sure.
What? What are 'non-Turing machines operations'? The term 'Turing machine' refers to generalisations of finite automata. In this context, what they are doing is receiving input and reacting to it depending on their current state. I can provide some examples of finite automata implementations in Python code, if you want me to.
The word 'decision' doesn't carry any meaning in this context.
I don't recall you asking this question before, and I do not have an answer. I also don't see the question as relevant to the exchange so far.
A bit is a unit of information. If we treat the signal that the eyes send to the brain as carrying any sort of information, you can't argue that the brain doesn't (EDIT: I initially forgot to include the word 'doesn't) receive the information in bits. If you claim otherwise, you don't understand what information is and/or what bits are.
Nobody is claiming, however, that your brain pulls up an analogue of a
.bmp
when you recall an image. You likely remember some details of an image, and 'subconsciously' reconstruct the 'gaps'. Computers can handle such tasks just fine, as well.