1931: Kurt Gödel shows limits of math, logic, computing, AI
I appeciate how Schmidhuber puts focus on non-US-centric history of Deep Learning and modern AI.<p>He sometimes overdoes these. Even when something is not related to Deep Learning and modern AI. He tries to push very narrow and one-sided views without much room for nuance.<p>For example- <i>&quot;Turing used his (quite inefficient) model only to rephrase the results of Gödel and Church on the limits of computability.&quot;</i><p>He is trying to say that Turing did nothing new, his work is a mere extension of Godel&#x27;s (!), and he only accounted for practical computational reality. That is not true.<p>He goes on further by saying, <i>&quot;Later, however, the simplicity of these machines made them a convenient tool for theoretical studies of complexity.&quot;</i> Like, Turing and Church&#x27;s work was only good for that. I digress. I believe that Turing&#x27;s work is more seminal and paved the way for modern general computers.<p>Another bit here says <i>&quot;The formal models of Gödel (1931-34), Church (1935), Turing (1936), and Post (1936) were theoretical pen &amp; paper constructs that cannot directly serve as a foundation for practical computers.&quot;</i><p>It is putting the works of Turing, Post, Church, and Godel all together. Like they are the same. I see the logic as they are all impractical, but they are different levels of impractical. Putting them all under one bracket like that makes no sense.<p>I respect Schmidhuber a lot, but some of his behaviour is borderline childish which are more pronounced in his claims about AI history. You should be skeptical about what he says (and what anyone says).<p>Despite all this, I did not know many things written in this article. I learned a lot and had fun reading it.<p>I first read about Zuse in Isaacson&#x27;s Innovators book. Did not know that he used a high-level language for a chess program. Fascinating. He is very underrated.