Alex, The only relevant item in that reference is a publication that is cited before the paywall: https://arxiv.org/pdf/2309.06979.pdf
What they prove is that you can train a system of LLMs to simulate a Turing machine. But that proves nothing. Almost every AI system designed in the past 60 years can be "trained" to simulate a Turing machine. Every LLM that is trained on natural language data is limited to the kind of "thinking" that is done in natural languages. As I pointed out in Section6.pdf (and many other publications), NL thinking is limited to all the ambiguities and limitations of NL speaking. In human communication, NLs must be supplemented by context, shared background knowledge, and gestures that indicate or point to non-linguistic information. The great leap of science by the Egyptians, Stone-hengers, Babylonians, Chinese, Indians, Greeks, Mayans, etc., was to increase the precision and accuracy of their thinking by going beyond what can be stated in ordinary languages. And guess what their magic happens to be? It's DIAGRAMS!!!! Translating thoughts from diagrams to words is a great leap in communication. But it cannot replace the precision and generality of the original thinking expressed in the original diagrams. As I said, you cannot design the great architectures of ancient times, the complex machinery of today, or any of the great scientific innovations of the past 500 years without geometrical diagrams that are far more complex than anything you can state in humanly readable natural language. I admit that it is possible to translate any geometrical design or any bit pattern in a digital computer into a specification that uses the words and syntax of a natural language. But what you get is an immense amount of verbiage that no human could read and understand. That is the most important message that we can get across in the forthcoming mini-summit. LLMs trained on NL input cannot go beyond NL thinking, and they cannot do any thinking that can go beyond thoughts expressible in NLs. To test that statement, show somebody (anybody you know) a picture, have them describe it, and have somebody else draw or explain what they heard, and have a fourth person compare the original to the explanation. (By the way, my previous sentence would be much clearer if I had included a drawing.) John ---------------------------------------- From: "Alex Shkotin" <alex.shko...@gmail.com> Hi Andrea, The topic you touched is so hot that there should be a lot of overview done yet. For me one source of it is a medium portal. Unfortunately it's a little bit paywalled :-( Have a look at the newest [1]. Alex [1] https://medium.com/@paul.k.pallaghy/llms-like-gpt-do-understand-agi-implications-dc54f4f86494
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