Is Deep Learning hitting the wall?

We own a full exclusive full license to this photo.. In the world of the rising numbers of Machine Learning (ML) related projects, simplified ML frameworks and environments, and prepackaged ML solutions in the cloud -- the voice of disappointment can be heard more and more often. This ever growing voice is coming from the top experts in the matter, so we at Avenga Tech would like to take a moment to share our opinion about whether deep learning is really hitting the wall. Is the current state of enterprise AI in need of another major breakthrough, or can we use current techniques and not worry? Avenga has extensive expertise in data science and deep learning in particular. So, here we are to help you understand the reasons and practical implications of the current situation. AI has improperly, but surely, become synonymous with Machine Learning, and machine learning is almost always related to deep learning (also false, because there are more techniques), and deep learning usually relates to Convolutional Neural Network (CNN, a type of artificial neural networks that learns how to recognize and classify the patterns in input data). For a given set of problems, usually pattern recognition, deep learning enables very high accuracy, relatively quick learning, and the fast and low resources model execution including mobile battery powered devices.