Xploring the Depths of Consciousness with Deep Thal: A Neural Network Model for Thalamic Stimulation

To understand consciousness, the thalamus has emerged as a crucial focal point. Recent advancements in neuroscience, particularly those from the Human Brain Project, have demonstrated that restoring communication between the cortex and the thalamus is key to recovering consciousness. This blog post delves into a cutting-edge neural network model known as “Deep Thal,” designed to…

SacredGeoModel Expert h5

The process involves creating expert-level synthetic training data, training the SacredGeoModel, and visualizing it using NetworkX. It starts with generating synthetic data capturing complex patterns, splitting it for training and validation, and saving it. Then, it loads, trains, and saves the model before visualizing the network structure.

Sacred Geometry Inspired Neural Network Model

The SacredGeoModel project utilizes sacred geometry to develop a neural network architecture, incorporating patterns like the Golden Ratio and geometric shapes such as the Seed of Life and Vesica Piscis. Implemented using TensorFlow and Keras, the model explores new approaches to enhance learning and efficiency. The network’s structure can be visualized using NetworkX and Matplotlib. This innovative fusion of ancient geometry and machine learning offers unique insights.

DLKNN | Potential Real-Life Application in Cognitive Science and Neuroscience

Description The following code demonstrates how to use the Deep Layer Knowing Neural Network (DLKNN) for classifying cognitive and neuroscience data. The data can include brain imaging metrics, cognitive task performance scores, and neuropsychological assessments. The DLKNN is designed to map complex cognitive functions and states of consciousness to actionable insights for research and clinical…

Deep Layer Knowing Neural Network (DLKNN) Model | Train it, Save it, and generate visualizations for both the Seed of Life and Flower of Life representations, along with a traditional neural network diagram.

Project Title: Deep Layer Knowing Neural Network (DLKNN) Introduction: The Deep Layer Knowing Neural Network (DLKNN) is an innovative project designed to explore the depths of human cognition, consciousness, and spiritual understanding through advanced machine learning and neural network architectures. This project integrates concepts from ancient wisdom, modern psychology, and cutting-edge AI technology to create…

Deep Layer Knowing Neural Network

The Deep Layer Knowing Neural Network hierarchically integrates levels of knowing, including Awareness, Recognition, Understanding, Intuition, Insight, Realization, Wisdom, and Enlightenment. Each layer builds on the previous, fostering continuous growth in intelligence and consciousness inspired by sacred geometry. To create a multi-dimensional layer neural network that includes all the levels of knowing, knowledge, consciousness, unknowing,…

AO The Computer Non-Algorithmic Consciousness Simulation

Introduction Welcome to the AO The Computer Non-Algorithmic Consciousness Simulation project. This innovative project brings together the fields of cognitive science, artificial intelligence, and distributed computing to explore the fascinating realm of consciousness. Leveraging the power of AO The Computer, we have developed a unique simulation that demonstrates how various sensory inputs can contribute to…

A non-algorithmic code for consciousness | Non-Algorithmic Consciousness GPT

Writing a non-algorithmic code for consciousness is inherently paradoxical because consciousness, as we understand it, encompasses subjective experiences, self-awareness, and qualitative states that resist formalization into algorithmic processes. However, I can provide a conceptual framework that outlines key aspects of consciousness without attempting to reduce it to purely computational terms. Non-Algorithm Consciousness GPT designed to…