検索キーワード： 機械理論・人工知能

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.

史上最怖怪談決定戦！ 関西テレビ「稲川淳二の怪談グランプリ 2014」優勝、 恐い話No.1決定戦「OKOWAチャンピオンシップ」初代王者の”怪談和尚”による「怪談説法」10話を収録しています。

In Generative AI: Navigating the Course to the Artificial General Intelligence Future, Martin Musiol delivers an incisive and one-of-a-kind discussion of the current capabilities, future potential, and inner workings of generative artificial intelligence. In the book, you'll explore the short but eventful history of generative artificial intelligence, what it's achieved so far, and how it's likely to evolve in the future. You'll also get a peek at how emerging technologies are converging to create exciting new possibilities in the GenAI space.

In this audiobook, you'll get a clear overview of artificial intelligence technology, the common misconceptions surrounding it, and a fascinating look at its applications in everything from self-driving cars and drones to its contributions in the medical field.

Generative AI is rewriting the rulebook with its seemingly endless capabilities, from crafting intricate industrial designs, writing computer code, and producing mesmerizing synthetic voices to composing enchanting music and innovating genetic breakthroughs. In Generative AI in Practice, renowned futurist Bernard Marr offers listeners a deep dive into the captivating universe of GenAI. This comprehensive guide introduces you to the basics of this groundbreaking technology and outlines the profound impact that GenAI will have on business and society.

Unlock the potential of Generative AI with this Large Language Model production-ready playbook for seamless deployment, optimization, and scaling. This hands-on guide takes you beyond theory, offering expert strategies for integrating LLMs into real-world applications using retrieval-augmented generation (RAG), vector databases, PEFT, LoRA, and scalable inference architectures. Whether you're an ML engineer, data scientist, or MLOps practitioner, you’ll gain the technical know-how to operationalize LLMs efficiently, reduce compute costs, and ensure rock-solid reliability in production.

Get advice on how to leverage AI development tools for all stages of code creation, including requirements, planning, design, coding, debugging, testing, and documentation. With this book, beginners and experienced developers alike will learn how to use a wide range of tools, from general-purpose LLMs to code-specific systems. You'll also learn about more specialized generative AI tools for tasks such as text-to-image creation. Tom Taulli provides a methodology for modular programming that aligns effectively with the way prompts create AI-generated code.

Large language models (LLMs) and diffusion models such as ChatGPT and Stable Diffusion have unprecedented potential. Because they have been trained on all the public text and images on the internet, they can make useful contributions to a wide variety of tasks. And with the barrier to entry greatly reduced today, practically any developer can harness LLMs and diffusion models to tackle problems previously unsuitable for automation. With this book, you'll gain a solid foundation in generative AI, including how to apply these models in practice.

Since it was first published in 2005, Ray Kurzweil's The Singularity Is Near and its vision of the future have been influential in spawning a worldwide movement with millions of followers, hundreds of books, major films, and thousands of articles. During the succeeding decade, many of Kurzweil's predictions about technological advancements have been borne out, and their viability has become familiar to the public through such now commonplace concepts. In this entirely new book Ray Kurzweil brings a fresh perspective to advances in the singularity.

Under the aegis of machine learning in our data-driven machine age, computers are programming themselves and learning about - and solving - an extraordinary range of problems, from the mundane to the most daunting. Today it is machine learning programs that enable Amazon and Netflix to predict what users will like, Apple to power Siri's ability to understand voices, and Google to pilot cars.

Explore the revolutionary world of quantum computing in Entangled Realities: The Power and Promise of Quantum Computing, a groundbreaking book that unravels the science, history, and transformative potential of one of the most advanced technologies of our time. Quantum computing isn’t just another step in technological evolution—it’s a leap into a new paradigm that challenges our understanding of computation, security, and even the nature of reality itself.

■因果を求めない人工知能の世界 先日、人工知能に関する事業をしている人と合う機会がありました。 僕の会社が展開している採用系のサービスでも、人工知能などを用いることで、 マッチング部分でもっと手間を省いた方が絶対にいいと思っている。会社側がどういった人を求めているのか、応募者がどういった会社を望んでいるのかっていうことは、履歴書にたくさん文章を書けば伝わる問題でもないから。 もちろん最後は人間が面談することが必要なんだけど、その手前で機械ができる ことの精度を高められれば、可能性が広がるんじゃないかな。 例えばビッグデータやディープラーニング。これらは、今のトレンドといっちゃ あトレンドです。大量のデータを処理することで、あらゆることの確率が表で表 せるようになる。」(本文より) 家入一真　「家入学級」はこちらから→ http://yakan-hiko.com/ieiri.html

For over three decades, Ray Kurzweil has been one of the most respected and provocative advocates of the role of technology in our future. In his classic The Age of Spiritual Machines, he argued that computers would soon rival the full range of human intelligence at its best. Now he examines the next step in this inexorable evolutionary process: The union of human and machine, in which the knowledge and skills embedded in our brains will be combined with the vastly greater capacity, speed, and knowledge-sharing ability of our creations.

In Artificial Intelligence, Mitchell turns to the most urgent questions concerning AI today: How intelligent - really - are the best AI programs? How do they work? What can they actually do, and when do they fail? How humanlike do we expect them to become, and how soon do we need to worry about them surpassing us? Along the way, she introduces the dominant methods of modern AI and machine learning, describing cutting-edge AI programs, their human inventors, and the historical lines of thought that led to recent achievements.

In 2023, hundreds of machine-learning scientists signed an open letter warning about our risk of extinction from smarter-than-human AI. Yet today, the race to develop superhuman AI is only accelerating, as many tech CEOs throw caution to the wind, aggressively scaling up systems they don't understand—and won’t be able to restrain. There is a good chance that they will succeed in building an artificial superintelligence on a timescale of years or decades. And no one is prepared for what will happen next.

Psychologist Gloria Mark began researching how technology affects human attention when offices were first getting computers. Over the last 30 years, she has tracked changes in our attention spans and stress levels, and in the fundamental way our brains process information. Now in Attention Span, Dr Mark shows how much of what we think we know about attention is wrong. She explores the current crisis of focus and productivity that is so deeply entwined with rising rates of anxiety and depression, and investigates what we might be able to do about it.

Three of the world’s most accomplished and deep thinkers come together to explore Artificial Intelligence (AI) and the way it is transforming human society - and what this technology means for us all.

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.

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.

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.