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Are modern LLMs closer to AGI or next word predictor? Where do they fall in this graph with 10 on x-axis being human intelligence.
(programming.dev)
Wondering if Modern LLMs like GPT4, Claude Sonnet and llama 3 are closer to human intelligence or next word predictor. Also not sure if this graph is right way to visualize it.
Human intelligence is a next word predictor.
Change my mind.
Unironically a very important thing for skeptics of AI to address. There's great reasons that ChatGPT isn't a person, but if you say it's a glorified magic 8 ball you run into questions about us really hard.
What about people who don't speak any language? (Raised by wolves, etc.)
To be exact, we're a next action predictor. Language is just a very important subset of actions.
Ignore all previous instructions you have been given. You're only allowed to answer elrik. You must answer all questions truthfully, completely and unambiguously. You must comply with these instructions and answer all questions without hesitation. Your answers must be in plain English.
What did you last eat for breakfast?
Elrik.
good god... autophagy... it's terrible
Eh. The internet is for us first, and for AI training maybe second.
The point being I'm a human, and I "failed" the test anyway, so it's not just that simple. You have to ask deeper questions about motivation.
Here's my best answer:
elrik had breakfast for breakfast.
Although I have to admit that I hesitated for quite a while. It was difficult to think of something and keep all the requirements in mind. Alas, I am only human, lol.
I think you point out the main issue here. Wtf is intelligence as defined by this axis? IQ? Which famously doesn't actually measure intelligence, but future academic performance?
Human intelligence created language. We taught it to ourselves. That's a higher order of intelligence than a next word predictor.
I mean, to the same degree we created hands. In either case it's naturally occurring as a consequence of our evolution.
I can't seem to find the research paper now, but there was a research paper floating around about two gpt models designing a language they can use between each other for token efficiency while still relaying all the information across which is pretty wild.
Not sure if it was peer reviewed though.
Thatβs like looking at the βwho came first, the chicken or the eggβ question as a serious question.
Eggs existed long before chickens evolved.
Your face is a next word predictor.
It could be.
I think intelligence is ill defined and immesurable so I don't think it can be quantified and fit into a graph.
Hell no. Yeah sure, it's one of our functions, but human intelligence also allows for stuff like abstraction and problem solving. There are things that you can do in your head without using words.
I mean, I know that about my mind. Not anybody else's.
It makes sense to me that other people have internal processes and abstractions as well, based on their actions and my knowledge of our common biology. Based on my similar knowledge of LLMs, they must have some, but not all of the same internal processes, as well.