Quick Introduction We have all been on forums, chats, reddit, discord, youtube, or somewhere and heard “Oh! Model XYZ is AMAZEBALLZ!zomgwtfbbq” then downloaded it (or more likely, some quantized form of it) and said “eww… This sucks!” This post is going to be a rather technical series of experiments to demonstrate the impact of implementation-specific hazards with inference. I will be using the term “reference implementation” to describe the lab that published and offers first-party hosting of ...
Well, theres a lot of experimentation with actual neural nets mimicing biology (or literally using biological neurons), and I think that could start to raise the spectre.
World model research could be a significant component of that.
In principle, OP is right; humans are just machines. All I constest is that transformers LLMs are even in the same ballpark, or possibly a path there… they are not.
Well it sounds like we agree then.
I would think you would need actual biological structures to achieve sentience. That’s a lot different than what these people are calling AI tho.
Edit: Also, if it is built out of natural biological pieces, at what point does it cease to be “artificial”?
Well biological structures can be replicated mechanically. So at risk of being pedantic, that’s not strictly true.
I view “artificial” as just a term for conscious, purpose construction, whereas “natural” does not involve any conscious intelligence, as in “naturally occurring in nature.” But even that is a spectrum, I guess, with genetic manipulation, BCIs, all sorts of intermediate possibilities.
I’d call a constructed, purely biological brain “artificial” because, even if it was grown naturally, it was built with conscious intent.
Correct, nothing is special about biological consciousness. If these exact functions are replicated mechanically/artificially, the outcomes would be the same.