[chordalkeyboard]

> This is what the human brain does.

The human brain is embodied in a human flesh and uses language to exchange models and data about the real world with other fleshy vessels. This provides a basis to assign meaning to the language. Furthermore we know that humans understand to a greater or lesser extent because we are human and have insight into the human experience of language and reality.

These machine learning algorithms lack this fundamental basis for ascribing meaning to the symbolic tokens they deal with. Furthermore we lack the common experience for inferring meaning and understanding, we have to interpret from the output whether there is meaning and understanding on the machine's end. Without access to internal experience we must always harbor some doubt but given some level of nonsensical outputs we can say with confidence that there is no indication of understanding.

> A human can be inconsistent and even lie. It does not mean the human does not understand you. Thus because your logic is applicable to humans it is akin to saying humans don't understand you. That is why your logic is incorrect.

Like everyone else, I interpret statements from humans differently than statements from machines. This is because I know that humans and machines are different, and therefore the meaning assigned to the symbols involved is also different.

[HervalFreire]

Flesh and understanding are separate concepts. The experience of being human is a separate concepts from understanding.

Everything in the universe has a set of rules governing it's existence. To understand something means that one can create novel answers to questions about something. Those answers however must make sense with the rules that govern the "something" at hand. This answer must also not be "memorized" in some sort of giant query-response lookup table.

That's it. That's what I'm saying.

For example if I ask chatGPT to emulate a bash terminal and create a new directory it can do so indicating it understands how a filesystem works. That is understanding.

I never said that LLMs are human. However understanding things is an aspect of being human and chatGPT captures a part of that aspect.

[chordalkeyboard]

> Flesh and understanding are separate concepts. The experience of being human is a separate concepts from understanding.

The experience of being human is what allows me to infer meaning from the words, phrases, sentences, etc. that a human generates. This is what allows me to make the leap from text to understanding (or lack, or incomplete understanding, or confusion, or deception) with human-generated responses. This is what I have in that case of humans, which allows me to interpret their statements one way; and what I lack with machines, which means I have no basis for inferring understanding the same way I do with a human. If I was not human, I would not be able to infer meaning from the noises a human makes, except by observing correlations between those noises and their behavior. This is well understood in cognitive science and animal behavior.

> To understand something means that one can create novel answers to questions about something. Those answers however must make sense with the rules that govern the "something" at hand. This answer must also not be "memorized" in some sort of giant query-response lookup table.

chatGPT is functionally equivalent to a lookup table with randomization.

> For example if I ask chatGPT to emulate a bash terminal and create a new directory it can do so indicating it understands how a filesystem works. That is understanding.

It replies with a text output that is a probabilistic representation of the text that one might find on the internet in response to such a query. The emulation occurs in your mind when you read the response and assign meaning to the words and phrases it contains.

> However understanding things is an aspect of being human and chatGPT captures a part of that aspect.

You have not shown that chatGPT is anything different than a fancy lookup table with some randomization.