DEEP LEARNING IMPLEMENTATION IN THE ENTERPRISE – CURRENT PROBLEMS AND CHALLENGES

As it is easy to see, in a short period starting from 2012 there is a massive increase in the popularity of venture investments, conferences and business inquiries related to "machine learning" and further "deep learning". At the same-most CEOs of technology companies often have problems with determining where and how their business can actually apply machine learning (ML) and deep learning (DL) to specific business problems. With the emergence of new terms and words, or bussewords, from the sphere of artificial intelligence (AI), which appear weekly, it seems difficult to understand what applications are really viable, and which are simply a buzz, hyperbole or deception. The paper examines the question of modern condition of use of AI and its components – deep learning in production companies. Special attention is paid to the latest reports of famous analytical companies, particularly the agency O'Reilly, dedicated to this issue. The article also highlights important issues arising in the implementation of business projects. And what is important to pay attention to when choosing the application of deep learning. The issues of bottlenecks implementation of deep learning are considered. Also paid attention to personnel recruitment and steps made by companies to develop talents and educate employees. Materials discussed in the article are directed to the audience from among the specialists on implementation of modern software systems and startups, programmers, readers from business environment, promising businessmen and students.