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Title: Arllecta Group Introduces Groundbreaking Sense-to-Sense Paradigm in AI

  Singapore, 18th Jun 2025 - After long and complex research, the Arllecta Group has completed the development of 25 core modules of its S2S AI. The uniqueness of this solution lies in the use of its own Sense-to-Sense technology, authored by the founder of the Arllecta Group, Egger Mielberg. The key difference between S2S AI and other current LLM solutions is at least two things. First, S2S AI does not use transformer technology, nor does it include submodules for determining the probability of the next sequence of words or symbols. In simple terms, S2S AI does not make predictions. Second, to determine the quality of our AI, we use our own key metrics such as sense entropy, sense energy, and semantic efficiency coefficient (SEC). These metrics are critical for defining and monitoring the implementation of real AI. By real AI, we mean self-adapting and self-developing AI. The basic version of S2S AI uses the properties of the sense space to determine the meaning of the analyzed text as a single sentence, or, for example, an entire paragraph, a book, or a large amount of data. It is important that the paradigm of the sense space used allows finding even several meanings in one sentence, which no existing model on the AI ​​market can do. Another key difference between S2S AI and existing AI LLM solutions on the market is the ability to determine semantic connections without using billions of tokens or millions of weighting factors. Instead of weighting factors, the semantic efficiency coefficient (SEC) in the sense space is used. In addition, a small team of Arllecta Group developers forms its own anthological database, which is translated into sense space, leaving only semantic components, the rest is deleted. In other words, after ind...

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