How Smart Machines Think by Sean Gerrish. Sean is a Senior Engineering Manager at Google leading machine learning and data science teams. He holds a PhD in machine learning from Princeton.
This book is providing readers with a wonderful overview to advances in artificial intelligence, and specifically how machine leaning is now the most popular subset of AI.
How Smart Machines Think is addressing three key areas that reveal the leaps in advancements of machine learning development: The DAPRA Grand Challenge, the Netflix recommendation engine, and Neural Networks.
Each section is well written, providing above all, deep insights tied to objectives driving new business models.
While Sean is certainly providing a solid grounding in algorithms and their methodologies, I was certainly surprised at the depth of autonomous vehicles, recommendation engines, and game-playing. The larger lessons from his book include amazing progress in neural networks.
Machine Learning for autonomous vehicles
Clearly Sean understands the full picture of how this emerging technology began. The 2004 initial contest found team only to achieve a small distance, perhaps less than twenty five percent of the course before their AI systems failed.