this post was submitted on 07 Aug 2024
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LLMs will not give us AGI. This is obvious to anyone who knows how they work.
Maybe it can. If you find a way to port everything to text by hooking in different models, the LLM might be able to reason about everything you throw at it. Who even defines how AGI should be implemented?
LLMs do not reason, they probabilistically determine the next word based on the words you prompt it with. The most perfect implementation of "AI" was the T9 predictive text system for dumb phones cmv.
And to have conversation, behind the scenes, each prompt gets the entire conversation so far tacked on.
The model itself is static, it doesn't work like a brain that changes in response to stimulus, or form memories.
To converse about something, the entirety of an exchange is fed back into the model all over again each time it needs to produce a response. In fact, this can happen several times over for each word in a response.
It's basically an attempt at duct-taping the ability to form memories onto an otherwise static system. It works, but I don't see how that way of doing it could ever land LLMs in the land of real consciousness.
It basically means these models "think" in frames, but each frame gets exponentially heavier to process, as it has to ingest every frame that came before.
OpenAI at least is now attempting to bolt on a “memory” by having the LLM spit out short snippets of what it might need to know later, which it then has access to when completing later prompts. Like everything else post-GPT-4, it seems fine but doesn’t work really all that well at what it is intended to do.