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Home » Semiotica Cybernetics Introduces Solution to Achieve Artificial General and Super Intelligence (AGI/ASI)
Press Release

Semiotica Cybernetics Introduces Solution to Achieve Artificial General and Super Intelligence (AGI/ASI)

By News RoomJanuary 24, 20263 Mins Read
Semiotica Cybernetics Introduces Solution to Achieve Artificial General and Super Intelligence (AGI/ASI)
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Semiotica Cybernetics Logo

SINGAPORE, Jan. 24, 2026 (GLOBE NEWSWIRE) — Semiotica Cybernetics, an AI startup founded by Mark Dennis Robinson, PhD, today announced the release of its white paper presenting a novel patented system that enables Semiotica Cybernetics to offer a unique method for developing Artificial General Intelligence (AGI) capable of understanding language, which maps onto human meaning, and which enables autogenous logical deductive reasoning.

The white paper addresses the limitations of current AI models, which generate responses but do not truly understand words and meaning. Semiotica Cybernetics provides a technical system that integrates semiotics — the study of signs and meanings — into AI systems, enabling machines to map onto human meaning webs, turn the real world into usable data, recognize patterns at scales beyond human perception, including microscopic-level changes, and interpret concepts. Additionally, by focusing on the connection between words, context, and real-world meaning, the system moves beyond simple pattern recognition toward genuine comprehension.

“By enabling semiotic capability, this solution not only helps computers to understand human meaning, but also unlocks a stack of related capabilities for AI and humanoid robots, including the capacity to engage with human emotions, process actions, engage in behaviors, and execute myriad other tasks that become newly possible,” said Prof. Mark Dennis Robinson, founder of Semiotica Cybernetics. “While this approach focuses on meaning, it simultaneously unlocks a large catalog of related capabilities for AI and humanoid robots. This could open new possibilities for AI and robots to assist in critical decision-making, communication, and creative problem-solving in science and medicine.”

Key components highlighted in the white paper include:

  • Semiotic Layer – A comprehensive technical system that links diverse phenomena, such as words, images, and more, to concepts, helping AI and robots interpret real-world inputs accurately.
  • Metasemiotic Pattern Recognition – Algorithms designed to detect deeper patterns across a variety of phenomena, allowing AI to locate, understand, and analyze patterns in specialized ways.
  • AI Inspector Gadget Bot – A system allowing AI to explore the real world by querying humans and conducting experiments beyond its training data.
  • AEPM (Mimicry System) – Allows robots to learn by understanding the reasoning, context, and multidimensional dynamics behind emotions, behaviors, and actions, rather than simply imitating them.

The technology holds potential across multiple applications, including predicting medical emergencies such as heart attacks and strokes, facilitating communication for non-verbal humans and animals, and developing robots capable of emotional understanding, decision-making, and creative expression. According to the white paper, this innovation by Semiotica Cybernetics enables the development of AI capable of generating novel solutions to cure cancer, since only then can AI and robots understand what ‘cancer’ means.

About Semiotica Cybernetics

Founded by Mark Dennis Robinson, PhD, Semiotica Cybernetics creates trailblazing, millennium-defining innovations in artificial intelligence, robotics, decision-support systems, and computational bioethics. The company is committed to developing AI systems that can meaningfully support society and advance innovation.

Read the full white paper here: https://semioticacybernetics.com/agi

Media Contact:
Michael Chang
Semiotica Cybernetics
[email protected]
Semioticacybernetics.com

A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/081ec416-a459-4ee0-8545-2d2958dac6ac

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