Pinaki Laskar on LinkedIn: #neuralnetworks #AGI #machinelearning

AI Researcher, Cognitive Technologist Inventor - AI Thinking, Think Chain Innovator - AIOT, XAI, Autonomous Cars, IIOT Founder Fisheyebox Spatial Computing Savant, Transformative Leader, Industry X.0 Practitioner The functioning of an intelligent system consists of the manipulation of knowledge. The width of possibilities for manipulating knowledge, in turn, is determined by how knowledge is represented and is characterized by a set of operations on the knowledge that is available for the selected representation variant. Knowledge includes logical entities and relationships between them (which are also logical entities) and attributes of entities, which represent parameters of entities that are not relationships: numerical values, words, texts. The maximum possible set of operations on knowledge includes the ability to add and remove logical entities from the available knowledge set, add and remove relationships between entities, and corresponding operations on entity attributes. The possibilities for the most famous and used implementations: - a natural way realized in humans and animals; - knowledge representation systems based on a fixed set of rules; - neural networks with an invariable graph of the structure of connections; - semantic variable structure graphs; - storing knowledge in the form of natural language texts; - hybrid systems including components of the types listed above; Potential intelligence capabilities include: - adaptation to changing environmental conditions; - detection and identification of known objects/situations; - detection and memorization of unknown objects/situations; - detection of causation; - exchange of information with other systems; The detection of unknown objects/situations and cause-and-effect relationships is de facto the generation of new logical entities and together constitute the essence of self-learning.