Showing results for "Self" in Computer Science

In 24 thought-provoking lectures designed for nonscientists, this course explores today's exciting field of genomics, the study of the vast storehouse of information contained within chromosomes. Your professor is Princeton University biologist Lee M. Silver, an acclaimed teacher, scientist, and author of popular books on biotechnology, genetics, and their impact on society.

How does a neural network become a brain? While neurobiologists investigate how nature accomplishes this feat, computer scientists interested in AI strive to achieve this through technology. The Self-Assembling Brain tells the stories of both fields, exploring the historical and modern approaches taken by the scientists pursuing answers to the quandary: What information is necessary to make an intelligent neural network? As Peter Robin Hiesinger argues, "the information problem" underlies both fields.

As Vikram Mansharamani shows in this eye-opening book, our complex, data-flooded world has made us ever more reliant on experts, protocols, and technology. We've stopped thinking for ourselves. Of course, experts, protocols, and computer-based systems are essential to helping us make informed decisions. What we need is a new approach for integrating these information sources more effectively. The author provides principles and techniques for doing just that, empowering listeners with a more critical and nuanced approach to making decisions.

As humans compete for work against faster, cheaper, and smarter technology, the flood of AI-generated information undermines traditional expertise, eroding essential skills like writing, analysis, and decision-making. Despite these challenges, AI presents immense opportunities for those who master its intricacies, such as driving innovation, improving efficiency, and creating new markets. Can we thread the needle balancing the immeasurable benefits with the profound risks that AI presents to our future?

The decisions to trust—or not—are pervasive throughout our everyday lives. Whether or not we trust others, for example, depends on many factors, and they all have a history. The battle to trust or mistrust, as experienced at the personal, political and cultural levels, are revealed in this well-documented story. This book illuminates the nature of trust, a deeply abstract and critically important concept.

AI and Self-Discovery: Risks and Opportunities addresses the complex and multifaceted relationship between AI and spirituality, exploring both the potential dangers and the exciting possibilities that lie ahead. From a spiritual perspective, the ongoing development of AI raises important questions about the nature of consciousness and the role of technology in shaping our understanding of the world. On the one hand, the ability to create machines that can process large amounts of data raises important ethical and moral dilemmas.