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Smart CS students were fooled by ELIZA back in the day.
Smart CS students in the 1960s and professional AI engineers with Ph.D level education (as I believe he has) in 2022 are a world apart.
LLM are definitely not sentient. As someone with a PhD in this domain, I attribute the 'magic' to large scale statistical knowledge assimilation by the models - and reproduction to prompts which closely match the inputs' sentence embedding. GPT-3 is known to fail in many circumstances which would otherwise be commonplace logic. (I remember seeing how addition of two small numbers yielded results - but larger numbers…
In effect this is how humans respond to prompts no? What's the difference between this and sentience?
People also fail to use logic when assimilating/regurgitating knowledge.
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I agree that it's not sentient, but why would commonplace logic be a pre requisite for sentience / consciousness / qualia / whatever you want to call it?
A brilliant colleague Janelle Shane works specifically on how language models fail (obnoxiously often). This is her line of research to show how LLMs are overhyped / given more credit than should be. I think her fun little experiments will give a better answer than I ever can :). She's on substack & Twitter https://janellecshane.substack.com/p/okay-gpt-3-candy-hearts
if anything, this proves that candy hearts should be larger, and less disgusting
Just curious, what evidence do we have that humans are sentient, other than our own conscious observations? Is there any physical feature or process in the human brain you can point to where you can say, “aha, that’s it, this is where the lights turn on”? It seems like this is part of a bigger issue that nobody really has a clear understanding of what sentience actually is (with or without a PhD)
LLM are definitely not sentient. As someone with a PhD in this domain, I attribute the 'magic' to large scale statistical knowledge assimilation by the models - and reproduction to prompts which closely match the inputs' sentence embedding. GPT-3 is known to fail in many circumstances which would otherwise be commonplace logic. (I remember seeing how addition of two small numbers yielded results - but larger numbers…
What is sentience then? Last I checked the Searle Chinese Room argument was still unresolved.
Is it not possible that our brains are also just "large scale statistical knowledge assimilation" machines?