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.
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.
you keep missing the fact that I don’t know out of nowhere. You would have just shown me one and told me what it was. Yes of course I’d be able to tell you what it was. You just taught me. With one example.
To understand a recumbent bicycle you have to understand bicycles. To understand bicycles you have to understand wheels. You have to understand humans, and human transportation. What IS transportation. What are roads. What is a pedal. What is steering. How physics works for objects in motion. Etc etc etc etc.
You truly underestimate the amount of context and previous knowledge you need to understand even the simplest things.
You point to me and tell me this is a bike. If we go around it 90 degrees and you ask me what it is, I can still tell you it’s a bike, even though I don’t know what one does or is used for. absolutely none of what you mentioned. i need no context. I only need to be able to tell that you pointed to the same object the second time even though I’m viewing it from a slightly different angle.
You point and say “this is a bike”, we walk around it, you point again and ask me “what is that?” I reply “a bike… you’ve just told me!”
Neural networks simply can’t do that. It won’t even recognize that it is the same object if it wasn’t specifically trained to recognze it from all angles. You’re talking about a completely different thing, which I never mentioned.