Thomas Bayes develops Bayesian Inference

Thomas Bayes developed this statistical framework, published posthumously by Richard Price, allowing for the quantification of uncertainty and the updating of probabilities based on new evidence. It has wide applications in fields such as artificial intelligence and data science. It contributed to the development of machine and deep learning when in 1964 Ray Solomonoff combined Bayesian probability-based reasoning and theoretical computer science to make predictions based on the past. Solomonoff and Andrej Kolmogorov would go on to expand upon information theory—discussed more in chapters 3 and 4—to develop Occam’s razor, a key concept to neural networks.