Showing results for "Design Engineering and Science" in Computer Science

Machine learning systems are both complex and unique. Complex because they consist of many different components and involve many different stakeholders. Unique because they're data dependent, with data varying wildly from one use case to the next. In this book, you'll learn a holistic approach to designing ML systems that are reliable, scalable, maintainable, and adaptive to changing environments and business requirements. Author Chip Huyen, cofounder of Claypot AI, considers each design decision in the context of how it can help your system as a whole achieve its objectives.

Two leaders in the field offer a compelling analysis of the current state of the art and reveal the steps we must take to achieve a truly robust artificial intelligence. Despite the hype surrounding AI, creating an intelligence that rivals or exceeds human levels is far more complicated than we...

Already technology enables parents to select some genetic traits for their children, and soon it will be possible to begin to shape ourselves as a species. Countering loud cries of alarm, bioethics expert Ronald Green explains why our fears about genetic engineering are overblown and how we can move forward responsibly to create a better future.