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Large Language Models (+PJ) tackle emergence ! V. Towards an understanding of complex relational networks that better reflects the true nature of human intelligence
Illustration by DALL·E (+PJ) P.J.: Great! I’m totally reassured about your grasping the emergent process. Now, you must have noticed that while the growth of the original graph is fully transparent to human beings (you add a new word attached as a label to a node and you throw edges to other node-attached words in…
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Large Language Models (+PJ) tackle emergence ! IV. An approach consistent to learning in biological neural networks
Illustration by DALL·E (+PJ) P.J.: Ok. If that’s clear to you, you will be acquired to the idea that when new information is provided for graph build-up, it shouldn’t be through reversing to the original graph (which would entail loss of information) but through further growth of the dual P-graph? Claude 3: Absolutely! If we…
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Large Language Models (+PJ) tackle emergence ! III. Information gains when a graph is transposed into its dual
Illustration by DALL·E (+PJ) P.J.: Ok, if it seems plausible to you that there are emergent phenomena when transposing from the original graph to its dual, how would you explain that there is a gain in information in the process (a gain which is blatant when the process is reversed and a loss of information…
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Large Language Models (+PJ) tackle emergence ! II. Can it be observed with a simple transpose?
Illustration by DALL·E (+PJ) At the time (1987-90) when I was developing software for British Telecom called ANELLA (Associative Network with Emergent Logical and Learning Abilities), it was the colleague who had coined this nice acronym who had drawn my attention to emergence phenomena in my AI. At the heart of the process was a…