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@konstmish

I'm surprised this post didn't get more attention. Most papers arguing we are far from AGI just show LLMs failing on tasks too big for their context window. Sergey identifies something more fundamental: while LLMs learned to mimic intelligence from internet data, they never had… https://t.co/SGhOh15OIT

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                                  "text": "@svlevine \"AI\" is incapable of reason, creativity, innovation, curiosity, art, poetry, research, and exalted idealism. \n@nntaleb\n\nNobody has any clue as to how to build AGI, or else they would build it.  Instead they hype their failing, money-burning, ai-slop hallucinating LLMs as \"future AGI any day now lol we promise.\"  \n\nThis is similar to how failed physicists built careers on hyping the failed multiverse/string theory/BICEP2, and may sometimes include the same players, as hypesters have a domain-independent skillset.\n\nAI and AGI are generally hyped in inverse proportion to the number of actual contributions an academic has made to their field.  As they do not fully comprehend how to contribute original thought, deeper meaning, or foundational research, they have no problem seeing intelligence where there is none.   \n\nSo often it seems AI hypers are also hypers of vast, well-funded, failed physics programs often dealing with stringy multiverses and such.   \n@GaryMarcus\n\n@MrEwanMorrison\n\n@DrBrianKeating\n\n@skdh\n\n@WKCosmo\n\n@EricRWeinstein\n\n@ChombaBupe\n\n@LKrauss1\n\n@michiokaku\n\n@martinmbauer\n\n@ThomasVanRiet2\n\n@WhyStringTheory\n\n@tegmark\n\n@ednewtonrex\n\n@MrEwanMorrison\n\n@lexfridman\n\nAI does nothing well in reality. \n\nThe elephant in the room is that AI does nothing well when it comes to creativity, original research, or innovation.  \n@ScottAdamsSays\n\n@matdryhurst\n\n@ednewtonrex\n\nThose who say AI is capable of humor have no sense of humor.  Those who say AI is capable of creating art have never created art.  Those who claim that AI will be capable of advancing physics never studied, let alone advanced, physics.  Those who say AI is capable of composing music have never composed music anyone would wish to listen to.  Those who say AI is cabable of photography have never created a photograph that anyone will ever hang anywhere.  Those who say AI is capable of writing literature have never penned a poem, and most often they detest Shakespeare, Homer, Dante, Melville, and Milton.\n\nAI is good at, well, nothing much.\n\nYann LeCun's ignorance of photography and music perhaps even trancends his ignorance of AI.  Yann Lecun thinks that he is capable of creating artistic photographic portraits such as those found in this book with his iPhone lol: https://t.co/yjtT01dlOG\n\nYann LeCun considers himself a Cartier Bresson, Avedon, Lange, Leibowitz, Ritts, Penn, Arbus, McCurry and Newton with his iPhone.  \n\nPerhaps Yann Lecun has never seen, nor enjoyed, a Sergio Leone film such as The Good, the Bad, and the Ugly.  And thus he thinks his \"AI\" is capable of the art of film.  \n\nAI is incapable of creating any new, soulful, or meaningful art or media whatsoever.  \"AI\" is incapable of reason, creativity, innovation, curiosity, art, poetry, and exalted idealism. It has been said that God created man in His own image, but these days many AI bros are trying to create AI in their own image and call that God, or at least a \"Ph.D. in your pocket lol bro.\"  But AI can only ever be as ethical as the foundations it was built upon--the art, science, poetry and beautiful human creativity it was trained on.  Plato saw beauty in Justice, but their AI sees no beauty.  Were Natural Rights, Artists' Rights, Copyright, and Human Rights respected during the training? If not, the AI is not, and cannot be ethical--as Hamlet noted--\"It is not, and it cannot, come to good.\"  And all for what? OpenAI's o1 strawberry pop-tart/stochastic parrot is incapable of simple logic and reason, exalted art, truth, and beauty.  To demonstrate this, give it the geometric definitions in Book 1 of Euclid's Elements, and then ask it to complete the rest of Euclid's Elements using simple logic and reason oft employed by junior high schoolers.  It won't be able to.  So it is that AI algorithms are incapable of simple logic, reason, meaningful scientific research, useful invention, or creative art. They can only mimic and degrade that which they copied and stole.  There will be no AGI from LLMS nor any other \"AI\" fantasy.  Getting AGI from an LLM is like trying to turn a Model X Tesla into the Millenium Falcon by buiding it bigger.  All of scientific cultural advancement--all science and technology--is centered upon humans answering questions that nobody knew the answer to, and even more importantly, it is premised upon humans asking questions nobody has asked before.  LLMs cannot do any of this.   Einstein reminds us that \"imagination is more important than knowledge,\" and too, he stated, \"Never lose a holy curiosity.\"  AI has no curiosity.  AI LLMS are utterly incapable of AGI, logic, reason, and creative logos.  This is easily demonstrated. No AI/LLM could produce Euclid's Elements from the simple definitions give in Book I.  AI LLMs are mere autocomplete, and thus have very little (perhaps nothing) to do with human intelligence. AI is incapable of creating anything new or beautiful beyond that which it ingested/copied/stole.  One of the problems with LLM/\"AI\" development is that all too often the CEOs are recreating it in their own image--folks who never created art nor culture nor ingested nor trained their souls on the data found in Beethoven's, Van Gogh's, Shakespeare's, and Einstein's works.  For instance, while Sam Altman's AI may well be able to duplicate/parrot the String Theory hoax, it, like Altman, will utterly fail to advance physics, or any other noble field, in any manner.   GPT-5 will be far, far, far inferior to all the artists and physicists it copied, ingested, and stole from.  Let us quickly prove this.  Train AI on all music known to humanity before Beethoven. Then ask it to create Beethoven's symphonies, or just the third or ninth. Train AI on all literature known to humanity before Shakespeare, and then ask it to write Hamlet. Train AI on all science known to humanity before relativity, and then ask it to create special and general relativity. Train AI on all math and physics known before Newton, and then ask it to write Principia. Train AI on all philosophy known before Plato, and then ask it to write Socrates' Apology. Train AI on all music known before the Beatles, and then ask it to create the White Album. Train AI on all the art created before Michelangelo, and then ask it to create the ceiling of the Sistine Chapel. Train AI on all the techonology created before Steve Jobs, and then ask it to create Apple. Train AI on all the music that existed before the blues, and then ask it to describe love and heartbreak in music, or just to recognize it. Train AI on all art known before Van Gogh, and then ask it to paint starry nights, sunflowers, and self portraits such as those that are worth hundreds of millions of dollars today.  Train AI on all epic poetry known to humanity before Homer, and then ask it to write Homer's Iliad and Odyssey. Train AI on all films before Sergio Leone, and then ask AI to create The Good, the Bad, and the Ugly.  So it is that AI is most often championed by those who have little appreciation for or understanding of Beethoven, Shakespeare, Einstein, Newton, Plato, The Beatles, Van Gogh, Homer, Michelangelo, Steve Jobs, music, literature, science, math, philosophy, art, technology, love, and epic poetry. Perhaps they even detest these exalted entities on some level.\n\n@tsarnick\n\n@nntaleb\n\n@jordanbpeterson\n\n@GaryMarcus\n\n@EricRWeinstein\n\n@elonmusk\n\n@tegmark\n\n@lexfridman\n\n@kortizart\n\n@neilturkewitz\n\n@TrevyLimited\n\n@RahllProduce\n\n@WKCosmo\n\n@ylecun",
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                              "full_text": "@konstmish Very interesting article. The Three Controversial Hypotheses Concerning Computation in the Primate Cortex paper it references was really interesting too. \n\nThank you for sharing! 🙏",
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                                  "full_text": "Standard “AI is literally intelligent” shtick, which begs the question, misses the point, and is itself guilty of a kind of magical thinking, as I show here: https://t.co/qDrxKxq4Rs",
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                              "full_text": "@konstmish I suspect philosophy/theology will be surprising beneficiaries of AI as humans (except scientists who can't see what they can't measure) know that AI is not 'doing' what a human does \nGreat example of both sides ...\nhttps://t.co/gix5NegA2q",
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                                      "text": "Many people assume that LRM reasoning breaks down past a certain \"complexity\" or \"number of steps\" threshold. This is incorrect. It breaks down past an unfamiliarity threshold. And that threshold is very low.\n\nThere is no limit to the complexity of tasks you can solve with these models, no limit to the number of steps in the reasoning chains they can master -- as long as they have been covered during training / tuning. However, show them something unfamiliar, even very simple and requiring just a handful of reasoning steps (e.g. an ARC 2 task), and they will fail.\n\nThe reason you see a steps/complexity threshold when testing on problems like Towers of Hanoi is because these are familiar problems. To see a breakdown you need to turn such a familiar task into a novel one, and one way to achieve this is to scale up the problem variables. The complexity increase is just a roundabout way to generate novelty.\n\nIt's not about simple vs complex. It's familiar vs novel. Always has been.",
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                                  "full_text": "Many people assume that LRM reasoning breaks down past a certain \"complexity\" or \"number of steps\" threshold. This is incorrect. It breaks down past an unfamiliarity threshold. And that threshold is very low.\n\nThere is no limit to the complexity of tasks you can solve with these…",
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