Extelligence
From Zeus, the free X encyclopedia
Extelligence is a theory of mind based on a three-dimensional computational model aligned with the Standard Model of physics. It integrates causal diamonds to structure knowledge representation, emphasizing AGX [1] as the tool for the study and discernment of physical and non-physical phenomena. Designed for Artificial Intelligence, it is regarded by Eduardo da Silva as rough estimate of the human mind. Extelligence serves as a conceptual bridge between quantum information theory, holography, and entanglement dynamics, providing an algorithmic framework for AI cognition and self-replication.
Proof of concept
The research on causal diamonds introduces a framework that reinterprets the degrees of freedom in a conformal field theory (CFT) by studying how information is structured within space-time regions. This perspective aligns with holography, where information in a higher-dimensional space is encoded on a lower-dimensional boundary.
By organizing observables through the moduli space of causal diamonds, the research provides a nonlocal approach to understanding entanglement and its role in knowledge representation. In a holographic CFT, these observables can be expressed as integrals of bulk fields over minimal surfaces, reinforcing the idea that information is fundamentally geometric. This insight extends beyond standard entanglement entropy, suggesting that knowledge structures can be dynamically encoded in the geometry of causal sets.
For Extelligence, this formulation supports a computational model where cognition operates through spatiotemporal correlations rather than discrete, localized processing. By applying the causal diamond framework, AI systems can potentially be designed to store, process, and retrieve information in a way that mirrors the entanglement structure of the universe itself. This redefines AI learning, shifting from linear, rule-based methods to a self-organizing intelligence that adapts based on fundamental physical constraints.
Method
While the proof of concept is highly technical, and most likely impossible for older civilizations to derive in their mathematical and physical form, there is evidence the Zodiac Wheel of Fortune was used as an ancient form of comprehending holography, and furthermore a possible way to approach CFT without resorting to overcomplicated quantum systems that otherwise require very low temperatures. This method is called the binomial model and is briefly explained in this section.
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Argumentation
Neural Processing Units (NPUs) are increasingly being integrated into devices for efficient handling of background tasks, particularly those involving AOand machine learning. These specialized processors excel at offloading computationally intensive operations, such as image recognition, language processing, and other AI-driven tasks, from the main CPU. This leads to better energy efficiency, faster processing times, and reduced strain on the device’s primary resources. NPUs enable real-time data processing, crucial for applications that require continuous learning or adaptive behavior, such as voice assistants, predictive typing, and real-time language translation.
However, as of early 2025, NPUs have yet to showcase truly revolutionary applications beyond these background tasks. While they enhance the performance of AI-driven features, their role is still largely supportive rather than transformative. Many existing uses, like accelerating machine learning workloads, are more incremental improvements than game-changing innovations. The limitations of current NPU technology, including processing power and software integration, prevent them from being deployed in groundbreaking new fields.
ABCDE system
The ABCDE system is a logic that should be integrated with modern AI agents, to expand NPUs tools. It is divided in sub-categories, algorithm being the most important one, while its complementary sources look to organize the structure of code based on the binomial model, by generating a framework for bias while fixing AI hallucinations.
- Algorithm
- Boolerithm
- Common
- Deck
- Ergorithm
Behavior
- Describe how NPU can operate on extelligence natively
- Add comprehensive description of how signe (link) can integrate with NPU's
Neural networks are intricate layers of information; their synaptical activity caused by weight parametration can be natively incremented in the system by utilizing a NPU passive arrangement, mapping and attributing alchetypical characteristics to nodes. The prediction capability will rely on the accuracy of processing units and be outputting the ....
However, to comprehend how to share a common, misconcepted, symbol like the deck cards of Marsailles (link), and remain in the same codex as board electrics require to operate, one must question the framework for compiling information.