Accelerating the Power of AI with Neural Networks - AI Trends

Thanks to the fast improvement of computation, storage and distributed computing infrastructure, ML has been evolving into more complex structured models like Deep Learning (DL), Generative Adversarial Network (GAN) and Reinforcement Learning (RL) – all using neural networks. Supervised neural networks are algorithms that can differentiate and make judgements based on image or pattern recognition, after being trained with labeled data. The concept of neural networks has been around for more than forty years, however, it was near 2014 that deep learning and neural networks began to disrupt different segments and bring us closer to passing the Turing Test. Thanks to today's data gathering capabilities, and sheer volume of said data, neural networking is one of the driving trends in successful ML execution.