Application of machine learning methods in virtual reality technologies

In recent years, the development of virtual reality (VR) technologies has been largely associated with the introduction of machine learning (ML) methods. The use of ML methods is aimed at increasing the level of comfort, efficiency and effectiveness of VR. ML algorithms can analyze interaction data, recognize patterns and adapt interaction scenarios based on the user's behavior and emotional state. The article analyzes the key modern areas of joint use of VR and ML, which have already been tested in practice and have shown fairly high efficiency. One of these areas is improving interaction in VR, including improving the quality of VR systems, more realistic graphics, adapting content to the user and accurate tracking of movements. The article considers the problems of using ML in VR technologies in the field of education, psychotherapy, rehabilitation, medicine, traffic management, in technologies for the creation, transmission, distribution, storage and use of electricity and other areas. A brief analysis of ML tools used in VR is also provided, among which generative neural networks can be distinguished that can create dynamic virtual environments. The study shows that the combination of VR and ML opens up new possibilities for creating intelligent and interactive systems and can lead to significant breakthroughs not only in VR but also in related technology areas.

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