Deep learning continues to make significant advances, including the development of specialized software and major breakthroughs in hardware capabilities. This ebook offers an overview of deep learning milestones and what the future is likely to hold.

From the ebook:

As society enters an era where AI will take life-or-death decisions—spotting whether moles are cancerous and driving us to work—trusting these machines will become ever more important. The difficulty is that it’s almost impossible for us to understand the inner workings of many modern AI systems that perform human-like tasks, such as recognizing real-life objects or understanding speech.

The models produced by the deep-learning systems that have powered recent AI breakthroughs are largely opaque, functioning as black boxes that spit out a result but whose operation remains mysterious. This inscrutability stems from the complexity of the large neural networks that underpin deep-learning systems. These brain-inspired networks are interconnected layers of algorithms that feed data into each other and can be trained to carry out specific tasks. The way these systems represent what they have learned is spread across these sprawling and densely connected networks, and dispersed in such a way that their workings are very tricky to make sense of.

Technology giants such as Google, Facebook, Microsoft and Amazon have laid out a vision of the future where AI agents will help people in their daily lives, both at work and at home: organizing our day, driving our cars, delivering our goods.