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Path: nntp.eternal-september.org!news.eternal-september.org!eternal-september.org!feeder3.eternal-september.org!2.eu.feeder.erje.net!3.eu.feeder.erje.net!feeder.erje.net!weretis.net!feeder8.news.weretis.net!reader5.news.weretis.net!news.solani.org!.POSTED!not-for-mail From: Mild Shock <janburse@fastmail.fm> Newsgroups: sci.logic Subject: =?UTF-8?Q?Analogy_as_a_Core_of_Intelligence_=28Human_&_Artificial?= =?UTF-8?Q?=29_=28Was:_Gian-Carlo_Rota=e2=80=99s_legacy_and_modern_AI=29?= Date: Thu, 17 Jul 2025 12:13:49 +0200 Message-ID: <105aics$2botd$1@solani.org> References: <1056abq$2ar22$4@solani.org> <105ahlr$2boci$2@solani.org> MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8; format=flowed Content-Transfer-Encoding: 8bit Injection-Date: Thu, 17 Jul 2025 10:13:48 -0000 (UTC) Injection-Info: solani.org; logging-data="2483117"; mail-complaints-to="abuse@news.solani.org" User-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:128.0) Gecko/20100101 Firefox/128.0 SeaMonkey/2.53.21 Cancel-Lock: sha1:oVeQZjo9FvmgIlTksQHpZbMwm8w= X-User-ID: eJwNysEBwCAIA8CVpAlBxqEo+4/Q3vscMnVQLvr44E1C+azA5prd4p42Ku49ulE+xwsZxrYsWAN1/2MME9cHMTAUgQ== In-Reply-To: <105ahlr$2boci$2@solani.org> Hi, Rota often celebrated symbolic, analogical, and conceptual understanding over brute calculation. This philosophy has come full circle in modern AI: - Large Language Models (LLMs) like GPT-4 don't just store facts — they recognize patterns, make analogies, and generate new structures from old ones. - Rota’s work in combinatorics, symbolic logic, and operator theory is essentially pattern-based manipulation — exactly the kind of reasoning LLMs aim to emulate at scale. Rota had a clear aesthetic. He valued clean formalisms, symbolic beauty, and well-defined structures. Rota wanted mathematics to mean something — to be not just correct, but intelligible and expressive. In contrast, modern AI (especially LLMs like GPT) thrives on the messy, including: Noisy data , Inconsistency , Uncertainty, Contradiction. AI engineers today are mining meaning from noise. What counts as “structure” is often just the best pragmatic/effective description available at that moment. Bye Mild Shock schrieb: > Hi, > > Spotting Trojan Horses is a nice example > of creativity that also needs ground truth. > Gian-Carlo Rota was phamous for this truth: > > "The lack of understanding of the simplest > facts of mathematics among philosophers > is appalling." > > You can extend it to GitHub acrobats, > paper mill balerinas and internet trolls. > But mathematics itself had a hard time, > > allowing other objects than numbers: > > - Blissard's symbolic method > He was primarily an applied mathematician and > school inspector. His symbolic method was a way > to represent and manipulate sequences algebraically > using formal symbols. > > - Gian-Carlo Rota (in the 1970s) > Gian-Carlo Rota (in the 1970s) gave Blissard’s > symbolic method a rigorous algebraic foundation. Rota > admired the symbolic reasoning of 19th-century mathematicians > and often described it as having a “magical” or “mystical” > elegance — again hinting at interpretive, almost poetic, qualities. > > - Umbral calculus > Modern formalization of this method, often involving > linear operators and algebraic structures. "Umbral" > means “shadow” — the power-like expressions are > symbolic shadows of actual algebra. > > Bye > > > Mild Shock schrieb: >> Henri Poincaré believed that mathematical >> and scientific creativity came from a deep, >> unconscious intuition that could not be >> >> captured by mechanical reasoning or formal >> systems. He famously wrote about how insights >> came not from plodding logic but from sudden >> >> illuminations — leaps of creative synthesis. >> >> But now we have generative AI — models like GPT — that: >> >> - produce poetry, proofs, stories, and code, >> >> - combine ideas in novel ways, >> >> - and do so by processing patterns in massive >> datasets, without conscious understanding. >> >> And that does seem to contradict Poincaré's belief >> that true invention cannot come from automation. >