Up until now, LLMs have required outside input and interpretation to avoid collapsing under their own weight. This has been known for decades.
What does "for decades" mean? That in 2000 we knew "LLM require outside input"? We didn't even realistically have anything worthy of the name LLM until 3-4 years ago, so what decades are we talking about? Up until know we didn't have any potential AI threat or people in the field worrying about practical AGI either!
Obviously any concern isn't about the AI that required outside input and interpretation to avoid collapsing under their own weight, but about ones that can produce their own input and experiences, even directly outside, as in the robotic bodies considered.
This line of thought dates back to the novel Erewhon, moving on to Turing's posthumously published paper 'Intelligent Machinery' (his 'Applications of Probability to Cryptography,' declassified in the 2010s, is also worth a look), and later to the work emerging from the MIT AI Lab circle (founded in 1959).
We didn't have the computational power back then, but we envisioned it long beforehand and worked toward a common goal. LLMs are far from useless, and I see the major leap forward they represent, but the relentless dystopian hype is just exhausting
There are approaches on different architectures of AI that lead towards your last point but they are not feasible yet (or maybe ever?). The interpretation part is however also very critical as we have a very own way of perceiving reality and interpreting it.
Comments
What does "for decades" mean? That in 2000 we knew "LLM require outside input"? We didn't even realistically have anything worthy of the name LLM until 3-4 years ago, so what decades are we talking about? Up until know we didn't have any potential AI threat or people in the field worrying about practical AGI either!
Obviously any concern isn't about the AI that required outside input and interpretation to avoid collapsing under their own weight, but about ones that can produce their own input and experiences, even directly outside, as in the robotic bodies considered.
This line of thought dates back to the novel Erewhon, moving on to Turing's posthumously published paper 'Intelligent Machinery' (his 'Applications of Probability to Cryptography,' declassified in the 2010s, is also worth a look), and later to the work emerging from the MIT AI Lab circle (founded in 1959).
We didn't have the computational power back then, but we envisioned it long beforehand and worked toward a common goal. LLMs are far from useless, and I see the major leap forward they represent, but the relentless dystopian hype is just exhausting
There are approaches on different architectures of AI that lead towards your last point but they are not feasible yet (or maybe ever?). The interpretation part is however also very critical as we have a very own way of perceiving reality and interpreting it.