Spatial Generative Multimodal Dynamic AGI as Model of Consciousness

Creating a spatial, generative, multimodal, dynamic artificial general intelligence (AGI) is a complex and multifaceted task. It involves developing a system capable of performing human-like intellectual tasks, such as learning, abstraction, self-regulation, and adaptation. This requires modeling basic cognitive functions and developing methods for long-term storage and retrieval of information. Perception and understanding of the surrounding world: processing sensory data, creating internal representations. Problem solving and planning using solution-finding algorithms. Linguistic thinking and communication: modeling the understanding and generation of natural language. Integration of multilayer and multifaceted models: creating architectures that combine perception, thinking, memory, and motivation. Using a spatial, generative, multimodal, dynamic AGI as a model of consciousness for simulating cognitive processes is planned, using neuromorphic platforms of spiking neural networks and transformers on transformable neurochips. The neuromorphic platform will also facilitate the modeling of metacognitive processes of consciousness, such as the ability to evaluate ones knowledge and strategies. An important stage is, firstly, the creation of test environments to evaluate universality and adaptability; secondly, the gradual increase in task complexity to increase intelligence; and thirdly, the development of infrastructure for large-scale computing. Today, the creation of spatial, generative, multimodal, dynamic artificial general intelligence is considered a feasible, integrative task for multidisciplinary projects. These projects are aimed at, firstly, the ability to solve diverse problems without reprogramming for each specific problem-from data analysis to creative thinking; secondly, the ability to acquire new skills in various ways: independently, through mentoring, and through research; thirdly, maintaining up-to-date information, understanding the situation as a whole, and predicting consequences; fourthly, flexible switching between strategies, choosing the optimal solution under conditions of uncertainty; and fifthly, awareness of ones own cognitive processes, assessing ones knowledge and limitations. The implementation of the projects will require an interdisciplinary international effort of highly qualified scientists, researchers and developers in various fields such as neuroscience, linguistics, artificial intelligence, intelligent modeling and manufacturing based on modern technologies.