Comment on Has anyone or anything ever passed the Turring Test? If so how and why?
Epp@lemmus.org 2 weeks agoYour oversimplification is noted. I assume you believe humans are word predictors, too? Just biological, instead of mechanical. In both cases, using input and electrical signals to create an output.
dandi8@fedia.io 2 weeks ago
No, humans are not word predictors, and my claim is absolutely not an oversimplification.
LLMs are word predictors. No amount of attention heads and backpropagation is going to change that. Scientific researchers agree.
The human brain works in a completely different way to how LLMs do and to conflate the two like you did os disingenuous.
Epp@lemmus.org 2 weeks ago
Plants and animals work in completely different ways, but they’re both alive. Just because something works differently doesn’t invalidate it’s results and existence.
If LLM didn’t think, it would be gibberish - just words related to the input. Instead, they are typically logical, sound, relevant responses; often with insight made by extrapolated data in the periphery of the prompt.
What you are expecting is consciousness, which they do not have yet. Thinking, though, yes.
dandi8@fedia.io 2 weeks ago
Except LLM output is largely gibberish. Just confident gibberish. There's a reason we call it "AI slop".
LLM responses are only ever "sound" when they're regurgitating existing information they were trained on. Beyond some simple transformations, they are unable to create original ideas. They very frequently break down on somewhat unique tasks, as evidenced by the ever-prevalent code-slop which is eroding our software.
They don't have a memory of previous conversations (unless you literally copy-paste it into the prompt), they don't learn (Claude "memories" is literally just copy-pasting a summary into the prompt, only automatically). They don't have any "thoughts" of their own between prompts (OpenClaw just keeps prompting them to pretend they are autonomous).
The underlying implementation of "thinking" in LLMs is literally "hallucinate some more text which vaguely looks like thoughts and hope that influences the answer". LLMs are probabilistic models which we figured out how to make so they produce somewhat correct-looking answers at a rate a lityle higher than chance.
Magic 8-balls sometimes give sound responses. Do they think? Where do we draw the line with this interpretation of "thinking"?
Epp@lemmus.org 2 weeks ago
I would disagree with you, and would suspect you are basing your assessment of their abilities on dated usage. I hold a MSc from what is arguably the most prestigious University in Europe, in regards to computer science, and my major was in AI. Believe my when I say I know exactly how they function.
I still assert you are oversimplifying their current capabilities, and seem to be conflating LLM with Markov Chains. LLM do not simply regurgitate existing content, and are in fact capable of creating wholly new content not seen before. Hallucinations occur when their context buffer is too small, and as time goes on, it will largely be a thing of the past.
Magic Eight Balls, as I’m sure you’re aware, have a limited, predetermined number of responses. They are in no way comparable. LLM use the equivalent of synapses, just digital whereas we use biological, but the function is the same. Modern AI is distinguishable only by the medium used, silicon versus organic material. As the number of input parameters, and context windows grows, the difference between them and our own brains will shrink until the medium is the only remaining difference.
We’re not there yet, but I would argue they are capable of thought if we define that to mean reasoning towards a response using all available information, instead of taking a predetermined or random path to one. We draw the line at biological life and LLM, nothing else we are aware of can think.