Data analytics and deep learning applied to health, work and Industry 4.0
Across the world, the quantity of digital data continues to multiply, and we can expect it to be 10 times what it is today by 2020. Affordable computing resources, optimized algorithms, and the huge volumes of available data have enabled the application of deep learning techniques, paving the way for the breakthrough of artificial intelligence. Now, things that seemed impossible just a few years ago are already a reality and even more efficiently. Nevertheless, these developments present researchers and developers with some weighty challenges. We still have difficulty explaining exactly how and why deep neural networks (DNNs) reach specific conclusions, and what exactly they use to acquire their knowledge. And yet, it is precisely this information that forms the basis of strategic business decisions, medical diagnostics and treatment (pain detection, for example), and the acceptance of these machine-driven techniques in everyday application (smart tools).