Googlielmo's blog

AI, Machine Learning and Deep Learning are getting an hype nowadays even if most part of the algorithms and models at their core are around since long time: 1805 Least Squares 1812 Bayes' Theorem 1913 Markov Chains 1950 Turing's Learning Machine 1957 Perceptron 1967 Nearest Neighbor 1970 Automatic Differentiation 1972 TF-IDF 1980 Neocognitron 1981 Explanation Based Learning 1982 Recurrent Neural Network 1970 Back Propagation 1989 Reinforcement Learning 1995 Random Forest Algorithm 1995 Support Vector Machines 1997 LSTM So what are the reasons that speed up and accelerated the implementation and made possible today for the theory to become reality? There are several factors:  - Cheaper computation: in the past hardware was a constraining factor for AI/ML/DL. Late advance in hardware (coupled with improved tools and software frameworks) and new computational models (in particular around GPUs) have accelerated AI/ML/DL adoption.  - Cheaper storage: the increased number of availab...