Earlier quoted context omitted.
Machines currently are at an amateur level, but amateurs across the board on the knowledge base. Amateurs at Python, Fortran, C, C++ and all programming languages. Amateurs at car engineering, airplane engineering, submarine engineering etc. Amateurs at human biology, animal biology, insect biology and so on. I don't know anyone who is an amateur at everything.
> Machines currently are at an amateur level, but amateurs across the board on the knowledge base. No, and that is a one of their limitations. LLMs are human-level or above on some tasks - basically on what they were trained to do - generating text, and (at least at some level) grokking what is necessary to do a good job of that. But, they are at idiot level on many other tasks (not to overuse the example, but I just…
Also take a look at rare diseases and doctors [1], in which machines are already better at diagnosing thousands of different rare diseases. Is is fair to say that machines are better at diagnosing diseases in general, just because they diagnose rare diseases, which each one, every doctor will need to diagnose once or twice in his career? Not clear at all.
Right now we are constrained by data, but that constraint will go away in 5 years or so. Will AGI will be achieved by then effortlessly? I have my doubts. My sentiment is that, even if AGI is never achieved, every small advancement in reasoning ability, in context window, in multimodal sensors and actuators, will have a very broad effect on jobs, on the economy and the way we are currently producing anything.