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…
Can the magic of the human brain not also be attributed to "large scale statistical knowledge assimilation" as well, aka learning?
> 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 gave garbled output; more likely that GPT3 had seen similar training data.)
This is a bug, they did not encode digits properly. They should have encoded each digit as a separate token but instead they encoded them together. Later models fixed this.
The human brain is full of bugs too, e.g. optical illusions. https://en.m.wikipedia.org/wiki/Optical_illusion
> It's a fad
No, it's objectively not a fad. The PaLM paper shows that Google's model exceeds average human performance on >50% of language tasks. The set of things that make us us is vanishing at an alarming rate. Eventually it will be empty, or close to it.
Do I think Google's models are sentient? No, they lack several necessary ingredients of sentience such as a self and long-term memory. However we are clearly on the road to sentient AI and it pays to have that discussion now.