"We don't need AIs that simulate humans; we need tools that solve human problems."
"We don't need AIs that simulate humans; we need tools that solve human problems."
Embedded Files
CEN Concept!
CEN Concept!
The CEN (Network of Experts and Cognition) concept represents a revolutionary approach to artificial intelligence architecture, inspired by neurobiological principles and characterized by a unique combination of functional specialization with physical and logical redundancy. The concept is particularly interesting because it differs from the current approach of simply scaling vertically with more powerful GPUs. Instead, it proposes horizontal scalability with functional specialization.
The CEN (Network of Experts and Cognition) concept represents a revolutionary approach to artificial intelligence architecture, inspired by neurobiological principles and characterized by a unique combination of functional specialization with physical and logical redundancy. The concept is particularly interesting because it differs from the current approach of simply scaling vertically with more powerful GPUs. Instead, it proposes horizontal scalability with functional specialization.
Technical Basis
Technical Basis
The CEN architecture fundamentally diverges from current monolithic AI systems by proposing a distributed network of specialized NODES that work together to perform complex cognitive and expert functions. Each NODE is dedicated to a specific cognitive or expert function (such as written language processing, speech processing, contextualization, or critical analysis, Autonomous Ethical NODE), operating with dedicated hardware and specialized algorithms. A NODE performs an additional process: "learning to coordinate" the specialized NODES. A meta-learning system for coordination between NODES, which represents the "brain of the brain" in the CEN architecture, is a mechanism that learns to orchestrate the specialized NODES efficiently. It also facilitates knowledge transfer between NODES. A knowledge distillation mechanism allows a NODE to "learn" from insights from others.
The CEN architecture fundamentally diverges from current monolithic AI systems by proposing a distributed network of specialized NODES that work together to perform complex cognitive and expert functions. Each NODE is dedicated to a specific cognitive or expert function (such as written language processing, speech processing, contextualization, or critical analysis, Autonomous Ethical NODE), operating with dedicated hardware and specialized algorithms. A NODE performs an additional process: "learning to coordinate" the specialized NODES. A meta-learning system for coordination between NODES, which represents the "brain of the brain" in the CEN architecture, is a mechanism that learns to orchestrate the specialized NODES efficiently. It also facilitates knowledge transfer between NODES. A knowledge distillation mechanism allows a NODE to "learn" from insights from others.
Functional Specialization:
Functional Specialization:
Each NODE in the CEN system is trained for a specific cognitive or specialist function (Fine Tuning), allowing a depth of specialization impossible in generalist systems.
Neurobiomimetic Redundancy:
Neurobiomimetic Redundancy:
The CEN architecture implements full redundancy through a dual physical and logical backup system, transcending conventional redundancy paradigms found even in critical military systems. Directly inspired by the principles of brain neuroplasticity, each cognitive NODE possesses not only redundant hardware but also adaptive functional capabilities.
High Speed Interconnection:
High Speed Interconnection:
The NODES are connected by high-speed communication links (100 Gb/s to 400 Gb/s), allowing rapid exchange of information and efficient coordination between different cognitive functions.
Distributed Meta-Learning:
Distributed Meta-Learning:
An innovative aspect of CEN is its meta-learning system, where an additional process "learns to coordinate" the specialized NODES, optimizing the routing of information and the integration of results between the different experts.
Autonomous Ethical NODE:
Autonomous Ethical NODE:
This is a structural pillar of CEN, a dedicated NODE that oversees all network interactions and decisions based on clear, auditable and continuously updatable ethical guidelines.
Interaction DB™:
Interaction DB™:
Memory, Context and Auditing.
Memory, Context and Auditing.
It's a highly sophisticated artificial episodic memory system with distributed indexing.
Interaction DB "Transferable Episodic Memory" allows AIs to maintain persistent and transferable memory.
Contextual Node:
Contextual Node:
Programmable Cognition.
Programmable Cognition.
Programmable Cognition is introduced into the CEN architecture with the creation of the CONTEXTUAL NODE, a new type of Cognitive NODE capable of operating independently of direct user input. This NODE acts as a context engineer and scheduler for cognitive tasks and flows.
Multiapplicability and Transversality:
Multiapplicability and Transversality:
The CEN architecture is applicable to any knowledge domain (law, medicine, energy, public administration, among others). The NODE infrastructure is reusable and interoperable. The Contextual NODE even operates in multiple CENs simultaneously, providing a layer of temporal and proactive intelligence over the network.
Network of Experts and Cognition
Network of Experts and Cognition
There is currently no technology exactly like the CEN architecture as it was conceived with its technical and theoretical foundations. The concept is innovative in the way it combines functional specialization with physical redundancy and high-speed interconnection dedicated to cognitive functions and experts.
ARCHITECTURE
ARCHITECTURE
• Current models use unified deep neural network architectures (transformers), not separate physical networks.
• Specialization occurs within the network itself during training, not by explicit design.
• Knowledge is encoded in distributed parameters, not in separate modules by domain.
Regarding efficiency: Modular approaches like the one you envisioned could have advantages in certain aspects:
• Easier to update specific knowledge.
• Potential for greater energy efficiency (activating only the necessary modules).
• Possibility to scale specific capabilities without complete retraining.
However, current unified models have important advantages:
• Ability to make interdisciplinary connections that separate modules might miss.
• Ability to generalize knowledge across domains.
• Greater flexibility for tasks not anticipated during design.
Advantages of the CEN architecture:
Advantages of the CEN architecture:
• Cognitive flexibility: Cognitive nodes could handle general reasoning, knowledge integration, and coordination.
• Expert depth: Expert nodes would provide detailed knowledge in specific domains.
• Selective scalability: Ability to expand only specific areas of knowledge without retraining the entire system.
• Resource efficiency: Activate only the relevant experts for each task.
• Modular upgradability: Update knowledge in one domain without interfering with others .
Specific Combination of Elements:
Specific Combination of Elements:
1. While there are technologies that implement some isolated components of CEN, none combine all the elements in the proposed integrated manner:
Specialized NODES with dedicated hardware.
Specialized Cognitive Tripod (Orchestrator + Ethical + Contextual).
Interaction DB™ as transferable episodic memory.
Active neurobiomimetic redundancy.
Hybrid NODE with dual function (secure gateway + adaptive management).
CEN protocol as operational "score".
2. Distinctive Philosophy:
The "generalized coordination of specialized intelligences" approach is fundamentally different from:
Traditional multi-agent systems.
Existing cognitive architectures (ACT-R, SOAR).
Monolithic language models.
Conventional distributed neural networks.
3. Focus on Strategic Applications:
The specific orientation towards sensitive domains (Law, Medicine, Energy) with integrated autonomous ethics has no direct precedent.
Virtual CEN
Virtual CEN
(NETWORK OF EXPERTS AND COGNITION)
(NETWORK OF EXPERTS AND COGNITION)
The Virtual CEN is a functional simulation of the CEN (Network of Experts and Cognition) architecture, applied to a specific domain. Rather than relying on a single generic Artificial Intelligence (AI) model, it is built as a collaborative network of specialized agents, called NODES, where each NODE performs a specific and complementary function.
The Virtual CEN is a functional simulation of the CEN (Network of Experts and Cognition) architecture, applied to a specific domain. Rather than relying on a single generic Artificial Intelligence (AI) model, it is built as a collaborative network of specialized agents, called NODES, where each NODE performs a specific and complementary function.
This approach ensures better performance, greater control, transparency, and reliability. The CEN was designed to assist professionals in certain fields. Its goal is to enhance research, interpretation, writing, and analysis capabilities, especially in situations that require speed, coherence, and detailed review of multiple sources.
This approach ensures better performance, greater control, transparency, and reliability. The CEN was designed to assist professionals in certain fields. Its goal is to enhance research, interpretation, writing, and analysis capabilities, especially in situations that require speed, coherence, and detailed review of multiple sources.
Hello! Let's test the CEN!
Hello! Let's test the CEN!
Expert Network and Virtual Cognition. With this, you can validate this new AI technology.
Expert Network and Virtual Cognition. With this, you can validate this new AI technology.
Page updated
Google Sites
Report abuse