# AI

Generative Deep Learning by David Foster is a practical book for machine-learning engineers and data scientists who want to learn how to re-create some of the most impressive examples of generative deep learning models. The book covers various techniques such as variational autoencoders, generative adversarial networks (GANs), encoder-decoder models, and world models. The author demonstrates the inner workings of each technique and provides tips and tricks to make models learn more efficiently and become more creative. The book also includes code examples using Pytorch and a code repository on Github.

In 'Rebooting AI: Building Artificial Intelligence We Can Trust', Gary Marcus and Ernest Davis argue that creating an intelligence that rivals or exceeds human levels is far more complicated than we have been led to believe. They explain what we need to advance AI to the next level, and suggest that if we focus on endowing machines with common sense and deep understanding, rather than simply focusing on statistical analysis and gathering ever larger collections of data, we will be able to create an AI we can trust. The book provides a lucid, clear-eyed assessment of the current science and offers an inspiring vision of how a new generation of AI can make our lives better.