検索キーワード： 制作 "-emdashery books-" 機械理論・人工知能

Superintelligence asks the questions: What happens when machines surpass humans in general intelligence? Will artificial agents save or destroy us? Nick Bostrom lays the foundation for understanding the future of humanity and intelligent life. The human brain has some capabilities that the brains of other animals lack. It is to these distinctive capabilities that our species owes its dominant position. If machine brains surpassed human brains in general intelligence, then this new superintelligence could become extremely powerful - possibly beyond our control.

In this absorbing and frequently contentious book, Roger Penrose puts forward his view that there are some facets of human thinking that can never be emulated by a machine. The book's central concern is what philosophers call the "mind-body problem". Penrose examines what physics and mathematics can tell us about how the mind works, what they can't, and what we need to know to understand the physical processes of consciousness.

Creating superior intelligence would be the biggest event in human history. Unfortunately, according to the world's pre-eminent AI expert, it could also be the last. In this groundbreaking book on the biggest question facing humanity, Stuart Russell explains why he has come to consider his own discipline an existential threat to his own species, and lays out how we can change course before it's too late. There is no one better placed to assess the promise and perils of the dominant technology of the future than Russell, who has spent decades at the forefront of AI research.

As it absorbs data, gains agency, and intermediates between humans and reality, AI will help us to address enormous crises, from climate change to geopolitical conflicts to income inequality. It might well solve some of the greatest mysteries of our universe, revolutionize fields as diverse as medicine and architecture, and elevate the human spirit to unimaginable heights. But it will also pose challenges on a scale and of an intensity that we have never seen.

This comprehensive audiobook reveals the exact step-by-step system that ordinary people are using to build automated TikTok empires that generate consistent income around the clock. The TikTok automation revolution is happening now, and early adopters are securing massive competitive advantages. Don't let this opportunity pass you by while others build automated empires that generate income while they sleep.

The entirety of the human brain’s 4-billion-year story can be summarised as the culmination of five evolutionary breakthroughs, starting from the very first brains, all the way to the modern human brains. Each breakthrough emerged from new sets of brain modifications, and equipped animals with a new suite of intellectual faculties. These five breakthroughs are the organising map to this book, and they make up our itinerary for our adventure back in time. Each breakthrough also has fascinating corollaries to breakthroughs in AI.

When ChatGPT was released, the world changed overnight. Even as we all played with the new toy, a very real danger was quickly coming to light: that untested automations would undermine our way of life insidiously, sucking value out of our economy, replacing high-level creative jobs and enabling a new, terrifying era of disinformation.

Large language models (LLMs) and generative AI are rapidly changing the healthcare industry. These technologies have the potential to revolutionize healthcare by improving the efficiency, accuracy, and personalization of care.

This is a practical, non-technical guide for business leaders, entrepreneurs, and curious minds. This comprehensive guide on agentic AI cuts through the hype and offers a clear, jargon-free strategic roadmap to understanding and applying this technology. The authors bring a rare perspective, having implemented agentic AI across diverse organizations—from global enterprises to agile startups—witnessing both remarkable successes and sobering failures.

AI will be the defining development of the 21st century. Within two decades, aspects of daily human life will be unrecognizable. AI will generate unprecedented wealth, revolutionize medicine and education through human-machine symbiosis, and create brand-new forms of communication and entertainment. In liberating us from routine work, however, AI will also challenge the organizing principles of our economic and social order.

Your brain responds in a predictable way when it encounters new or difficult tasks. This unique book teaches you concrete techniques rooted in cognitive science that will improve the way you learn and think about code. Learn how to optimize your brain’s natural cognitive processes to read code more easily, write code faster, and pick up new languages in much less time. This book will help you through the confusion you feel when faced with strange and complex code, and explain a codebase in ways that can make a new team member productive in days!

Let Al be your partner in bridging educational gaps, enhancing your students' learning opportunities, and preparing them to make the most of an Al-dominated future.

In Build a Large Language Model (from Scratch) bestselling author Sebastian Raschka guides you step by step through creating your own LLM. Each stage is explained with clear text, diagrams, and examples. You’ll go from the initial design and creation, to pretraining on a general corpus, and on to fine-tuning for specific tasks.

Since their introduction in 2017, transformers have quickly become the dominant architecture for achieving state-of-the-art results on a variety of natural language processing tasks. If you're a data scientist or coder, this practical book shows you how to train and scale these large models using Hugging Face Transformers, a Python-based deep learning library.

In this volume in the MIT Press Essential Knowledge series, computer scientist John Kelleher offers an accessible and concise but comprehensive introduction to the fundamental technology at the heart of the artificial intelligence revolution. Kelleher explains some of the basic concepts in deep learning, presents a history of advances in the field, and discusses the current state of the art.

This friendly guide teaches you how to apply common algorithms to the practical problems you face every day as a programmer. You'll start with sorting and searching and, as you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression and artificial intelligence. This accesible introduction is suitable for self-taught programmers, engineers, or anyone who wants to brush up on algorithms. Each carefully presented example includes helpful diagrams and fully annotated code samples in Python.

A decade ago, developers built information-sharing software by writing a lot of custom code in a single code base, then adding layers of caching. Now we build information systems: interdependent software and services, data platforms, and event streams. Many of our software-to-systems initiatives fail, though, and when they do, we double down on traditional linear approaches. But linear thinking cannot resolve systems challenges. We need to shift to systems thinking.

Something new entered our world in November 2022—the first general purpose AI that could pass for a human and do the kinds of creative, innovative work that only humans could do previously. Wharton professor Ethan Mollick immediately understood what ChatGPT meant: after millions of years on our own, humans had developed a kind of co-intelligence that could augment, or even replace, human thinking. Through his writing, speaking, and teaching, Mollick has become one of the most prominent and provocative explainers of AI.

We are approaching a critical threshold in the history of our species. Everything is about to change. Soon you will live surrounded by AIs. They will organize your life, operate your business, and run core government services. You will live in a world of DNA printers and quantum computers, engineered pathogens and autonomous weapons, robot assistants and abundant energy.

Over the past 10 years, urban planners, technology companies, and governments have promoted smart cities with a somewhat utopian vision of urban life made knowable and manageable through data collection and analysis. Emerging smart cities have become both crucibles and showrooms for the practical application of the Internet of Things, cloud computing, and the integration of big data into everyday life. Are smart cities optimized, sustainable, digitally networked solutions to urban problems? Or are they neoliberal, corporate-controlled, undemocratic non-places?