Résultats pour "Adam" dans Sciences informatiques

What is life? Humans have been asking this question for thousands of years. But as technology has advanced and our understanding of biology has deepened, the answer has evolved. For decades, scientists have been exploring the limits of nature by modifying and manipulating DNA, cells, and whole organisms to create new ones that could never have previously existed on their own.

For millennia, humans have tried—and often failed—to master nature and transcend our limits. But this has started to change. The new scientific frontier is the human body: the greatest engineers of our generation have turned their sights inward, and their work is beginning to revolutionize...

Everywhere we turn, a new device promises to transfigure our lives. But at what cost? In this urgent and revelatory excavation of our Information Age, leading technology thinker Adam Greenfield forces us to reconsider our relationship with the networked objects, services, and spaces that define us. It is time to re-evaluate the Silicon Valley consensus determining the future. We're told that innovations - from augmented - reality interfaces and virtual assistants to autonomous delivery drones and self-driving cars - will make life easier, more convenient, and more productive.

In this ground-breaking work, James Adams and Richard Kletter clearly explain the potential and likely ramifications of AI. They show how ill-prepared we are for the forthcoming "fourth industrial revolution" and look at how human beings might fare as it unfolds. Meticulously researched and extensively referenced, this audiobook to the brave new world is created by two highly credible authors, who use all of their experience, insight and contacts to give listeners a privileged look into that which is to come.

Grab this layman guide. Sound interesting? The author thinks so too! Listen to Machine Learning: Machine Learning in 2020, Vol 1 and learn about machine theory and computer networks.

Grab this layman guide. Sound interesting? The author thinks so too! Listen to Machine Learning and learn about machine and information theory.