Intelligence is not artificial… so why expect leading technology to be?
We made the leap from artificial to abstract.
Current artificial intelligence is based on the manipulation of information (words, images, sounds, etc.). However, at the heart of all information-based technologies we discovered a contradiction (the Miem paradox) which shows why it is impossible for machines to understand and think. However, inspired by this paradox we found the only solution: Abstract Intelligence. Instead of handling information, with Abstract Intelligence the machine handles the abstractions that model the world allowing it to finally understand and think.
The Abstractions’ Advantage
With abstractions, the machine cannot be confused as it happens with LLMs and other Ai. For example, in current AI, the word “apple” creates confusion because the computer and fruit both share the same name, “a-p-p-l-e.” However, thanks to abstractions, Q&Ai never gets confused, because the abstractions of a computer and fruit are completely different. In fact, it’ll never confuse two apple computers even when both look the same.
Why are other Ai paradoxical? Why other Ai cannot understand?
Any system that is paradoxical, especially in its roots, is doomed. This is why current Ai (ex., LLMs, symbolic Ai) fails to understand and think. Paradoxes can be difficult to comprehend. To use a simple example, imagine yourself walking in a jungle and hearing the sentence: “there is a tiger behind the bush.” What do you immediately conceive?
An object (the carnivore) behind another object (the plant);
The word “tiger” behind the word “bush”? or
Nouns, verb and preposition?
Clearly, option 1 is correct; however, the best Ai techs today pick options 2 or 3.
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