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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.
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?
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.
Your face is a next word predictor.
What about people who don't speak any language? (Raised by wolves, etc.)
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.
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 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.