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We observe the success of artificial neural networks in simulating human performance on a number of tasks: such as image recognition, natural language processing, etc. However, there are limits to state-of-the- art AI that separate it from human-like intelligence. Humans can learn a new skill without forgetting what they have already learned and they can improve their activity and gradually become better learners. Today’s AI algorithms are limited in how much previous knowledge they are able to keep through each new training phase and how much they can reuse. In practice, this means that you need to build a new algorithm for each new specific task. There is domain called AGI where will be possible to find solutions for this problem. Artificial general intelligence(AGI) describes research that aims to create machines capable of general intelligent action. “General” means that one AI program realizes number of different tasks and the same code can be used in many applications. We must focus on self-improvement techniques e.g. Reinforcement Learning and integrate it with deep learning, recurrent networks.