And you’re just a fancy electro-chemical reaction.
Who says that an LLM with complete access to the sensory world could not pass the Turing Test?
Comment on Major shifts at OpenAI spark skepticism about impending AGI timelines
anarchrist@lemmy.dbzer0.com 3 months agoLLMs 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.
doodledup@lemmy.world 3 months ago
MonkderVierte@lemmy.ml 3 months ago
It’s already fact that the Turing Test only determines how much it can simulate human behavior. Nothing with intelligence to do.
sugar_in_your_tea@sh.itjust.works 3 months ago
Exactly. You could ask a human a lot of questions and make an “AI” that literally just looks up answers to common questions and have it pass the Turing test, provided the pre-answered questions cover what the human proctoring the “test” asks.
If we take it a step further and ask, why can’t an LLM be “conscious,” there’s a lot of studies by experts that explain that. So I’ll refer OP there.
MentalEdge@sopuli.xyz 3 months ago
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 cab 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.
mozz@mbin.grits.dev 3 months ago
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.