Large language models mimic human chatter, but scientists disagree on their ability to reason.

https://thegradient.pub/othello/

LLMs are neural networks and are absolutely capable of understanding.

LLMs are criminally simplified neural networks at minimum thousands of orders less complex than a brain. Nothing we do with current neural networks resembles intelligence.

Nothing they do is close to understanding. The fact that you can train one exclusively on the rules of a simple game and get it to eventually infer a basic rule set doesn’t imply anything like comprehension. It’s simplistic pattern matching.

Does AlphaGo understand go? How about AlphaStar?

When I say LLM’s can understand things, what I mean is that there’s semantic information encoded in the network. A demonstrable fact.

You can disagree with that definition, but the point is that it’s absolutely not just autocomplete.

No, and that definition has nothing in common with what the word means.

Autocorrect has plenty of information encoded as artifacts of how it works. ChatGPT isn’t like autocorrect. It is autocorrect, and doesn’t do anything more.

It’s fine if you think so, but then it’s a pointless argument over definitions.

You can’t have a conversation with autocomplete. It’s qualitatively different. There’s a reason we didn’t have this kind of code generation before LLM’s.

Adversus solem ne loquitor.

If you just keep taking the guessed next word from autocomplete you also get a bunch of words shaped like a conversation.

I am not sure of the relevance of the oppressed classes and with the object of duping the latter is the cravings of the oppressed classes and with the object of duping the latter

Yeah, totally. Repeating the same nonsensical sentence over and over is also how I converse. 🙄

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