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AGI should have morals, opinions, self-reflection, learn continuously from sensor data, reason, realize when they’re proven wrong and update their model of the world, and be creative. So far LLMs exhibit none of those. But LLMs exhibit a digestible distillation of a very large body of data which may be a component of an AGI.

But you can have an AGI that doesn’t have encyclopedic knowledge but it’s still highly intelligent, so I don’t think LLMs have to be an intrinsic component.



That is not what AGI means. AGI = Artificial General Intelligence.

1. Artificial = we made it

2. General = it can solve problems in any field

3. Intelligence = the ability to solve problems

A chess engine is a very strong Artificial Intelligence. But it’s not very General, it can only evaluate chess positions.

GPT-4 is very General, you can ask it about any question and get a somewhat reasonable answer. But it’s not very intelligent, often the answer is wrong.

You’re talking about an Artificial Human. That’s a different problem. Intelligence is not species dependent. Dolphins are intelligent (a bit), aliens can be intelligent and have zero emotions or conception of self. There’s certainly plenty of amoral intelligent serial killers.


> That’s a different problem.

That's news to me. AGI (or strong AI) is typically defined as "human-level intelligence", or "perform any task that a human or animal can." Humans and animals often perform tasks that are critically reliant on being conscious, emoting, reading body language, reasoning, etc.

Not only that but prominent thinkers who have carved out the notion of AGI (or Strong AI) tend to have consciousness, mental states, and emotions at the core of it.

I think what you're talking about is a multi-task AI, not an AGI.


We don't have a good computer model of dolphin intelligence and the llms are not even remotely close to consciousness or dolphins, dogs, parrots on the intelligence Front.


Consciousness ≠ intelligence.

Consciousness: being “awake” and perceiving the world.

Intelligence: solving problems, finding the truth.

Consciousness is perceiving the world, whereas intelligence is understanding it.


GPT-4 solves only 1 problem: what is the most likely stream of tokens to follow what we already have.

It is remarkably good at this. But there's absolutely zero reason to believe it can solve any other problem at all.


How do humans write if not by intuiting what word comes after another?

Intelligence is the ability of that next word decision procedure to determine a next word that is aligned with our human intuition and model of truth.

I believe what you’re getting at is modality, that GPT-4 only provides responses in text. You can’t ask it to drive a car, or paint like Dall-e. And that’s a fair criticism, but it’s mostly just because it would make the models too large and slow, not because we don’t know how to do it. The thing we don’t know how to do is make a model reason as well as a human, and it makes sense to try to solve that in the text domain first rather than making highly multimodal models that reason poorly in all domains.


> How do humans write if not by intuiting what word comes after another?

We don't know. It may turn out that we use mechanisms similar to LLMs, or it might be something entirely different.

As for the rest: nobody knows how to make ChatGPT butter a piece of toast, let alone drive a car.

ChatGPT does not reason about text, either.


>nobody knows how to make ChatGPT butter a piece of toast

There is plenty of research on LLMs successfully piloting robots.

It's but no means a solved problem but "Nobody knows how" is a stretch.

https://tidybot.cs.princeton.edu/ https://innermonologue.github.io/

>ChatGPT does not reason about text, either.

It does and there's plenty of output to demonstrate that.



That's an interface, not an implementation.

("The most likely" out of what distribution? The model's distribution. So that just means "what the model thinks the answer to your question is".)




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