I believe that AGI (Artificial General Intelligence), unlike current AI models must operate with meanings / knowledge. This is exactly what distinguishes it from neural network based AI. Any successful AI implementations (playing chess, self-driving, face recognition, etc.) in no way operate with knowledge about the objects being processed and do not recognize their meanings / cognitive structure. This is not necessary for them, they demonstrate good results based on pre-training. But for AGI, which imitates human thinking, the ability to operate with knowledge is crucial. Numerous attempts to define the concept of "meaning" have one very significant drawback - all such definitions are not rigorous and formalized, therefore they cannot be programmed. The procedure of searching for meaning / knowledge should use a formalized determination of its existence and possible forms of its perception, usually multimodal. For the practical implementation of AGI, it is necessary to develop such "ready-to-code" formalized definitions of the cognitive concepts of "meaning", "knowledge", "intelligence" and others related to them. This article attempts to formalize the definitions of such concepts.