検索キーワード： 機械理論・人工知能

Grokking Artificial Intelligence Algorithms is a fully illustrated and interactive tutorial guide to the different approaches and algorithms that underpin AI. Written in simple language and with lots of visual references and hands-on examples, you'll learn the concepts, terminology, and theory you need to effectively incorporate AI algorithms into your applications. And to make sure you truly grok as you go, you'll use each algorithm in practice with creative coding exercises.

GANs in Action teaches you how to build and train your own Generative Adversarial Networks, one of the most important innovations in deep learning. In this book, you'll learn how to start building your own simple adversarial system as you explore the foundation of GAN architecture: the generator and discriminator networks.

James Gleick, the author of the best sellers Chaos and Genius, now brings us a work just as astonishing and masterly: A revelatory chronicle and meditation that shows how information has become the modern era’s defining quality - the blood, the fuel, the vital principle of our world. The story of information begins in a time profoundly unlike our own, when every thought and utterance vanishes as soon as it is born.

Artificial Intelligence helps choose what books you buy, what movies you see, and even who you date. It puts the "smart" in your smartphone and soon it will drive your car. It makes most of the trades on Wall Street, and controls vital energy, water, and transportation infrastructure. But Artificial Intelligence can also threaten our existence. In as little as a decade, AI could match and then surpass human intelligence. Corporations and government agencies are pouring billions into achieving AI’s Holy Grail - human-level intelligence.

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.

Every day, we use our computers to perform remarkable feats. A simple web search picks out a handful of relevant needles from the world's biggest haystack. Uploading a photo to Facebook transmits millions of pieces of information over numerous error-prone network links, yet somehow a perfect copy of the photo arrives intact. Without even knowing it, we use public-key cryptography to transmit secret information like credit card numbers, and we use digital signatures to verify the identity of the websites we visit.

In How To Think About AI, Richard Susskind draws on his experience of working on AI since the early 1980s. For Susskind, balancing the benefits and threats of artificial intelligence is the defining challenge of our age. He explores the history of AI and possible scenarios for its future. His views on AI are not always conventional. He positions ChatGPT and generative AI as no more than the latest chapter in the ongoing story of AI and claims we are still at the foothills of developments.

You're probably aware that generative AI can output quality text and create stunning images in seconds. But smart managers are now using gen AI for high-level work—problem-solving, driving innovation, strategic thinking, and dozens of other applications. Managers who develop their generative AI capabilities will soon be leaping ahead of those who don't. Fortunately, you can start today and see immediate results. The HBR Guide to Generative AI for Managers is packed with practical tips, prompts, and case studies to accelerate and improve countless aspects of your work.

Drawing from her experience at Google and Meta, Dr. Marily Nika delivers the definitive guide for product managers building AI and GenAI powered products. Packed with smart strategies, actionable tools, and real-world examples, this book breaks down the complex world of AI agents and generative AI products into a playbook for driving innovation to help product leaders bridge the gap between niche AI and GenAI technologies and user pain points.

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.

Veteran software developer and GitHub community hero Kurt Dowswell delivers an insightful and hands-on exploration of GitHub's powerful, new AI coding assistant, Copilot. In the book, you'll discover how to use the tool's capabilities to push the boundaries of what you thought was possible in programming. Even if you've used autocomplete tools-like VS Code's TabNine extension—before, you'll be floored by GitHub Copilot's potential to transform the way you code.

Whether you're an aspiring entrepreneur, an established business owner looking to increase sales, or someone seeking new and innovative ways to generate extra income, ChatGPT Money Machine is your ultimate roadmap to success. Equip yourself with the knowledge and skills necessary to navigate the exciting world of artificial intelligence and transform your online ventures into profitable and sustainable income sources.

A new industrial revolution has begun. Like mechanization or electricity before it, artificial intelligence will touch every aspect of our lives—and cause profound disruptions in the balance of global power, especially among the AI superpowers: China, the United States, and Europe. Autonomous weapons expert Paul Scharre takes listeners inside the fierce competition to develop and implement this game-changing technology and dominate the future.

This book breaks through both the hype and the doom-and-gloom surrounding automation and the deployment of artificial intelligence-enabled—“smart”—systems at work. Management and technology experts Thomas Davenport and Steven Miller show that, contrary to widespread predictions, prescriptions, and denunciations, AI is not primarily a job destroyer. Rather, AI changes the way we work—by taking over some tasks but not entire jobs, freeing people to do other, more important and more challenging work.

In their bestselling first book, Prediction Machines, eminent economists Ajay Agrawal, Joshua Gans, and Avi Goldfarb explained the simple yet game-changing economics of AI. Now, in Power and Prediction, they go deeper, examining the most basic unit of analysis: the decision. The authors explain that the two key decision-making ingredients are prediction and judgment, and we perform both together in our minds, often without realizing it.

For all of neuroscience's advances, we've made little progress on its biggest question: How do simple cells in the brain create intelligence? Jeff Hawkins and his team discovered that the brain uses maplike structures to build a model of the world—not just one model, but hundreds of thousands of models of everything we know. This discovery allows Hawkins to answer important questions about how we perceive the world, why we have a sense of self, and the origin of high-level thought.

We are now on the doorstep of a fourth change brought about by two technologies: AI and robotics. The Fourth Age provides extraordinary background information on how we got to this point, and how - rather than what - we should think about the topics we’ll soon all be facing: machine consciousness, automation, employment, creative computers, radical life extension, artificial life, AI ethics, the future of warfare, superintelligence, and the implications of extreme prosperity.

Machine learning (ML) is changing virtually every aspect of our lives. Today ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations. The book addresses real-life problems faced by practitioners on a daily basis and explains scientifically sound solutions using math, supported by code and examples.

In this audiobook, machine learning expert Ethem Alpaydin offers a concise overview of the subject for the general listener, describing its evolution, explaining important learning algorithms, and presenting example applications. Alpaydin offers an account of how digital technology advanced from number-crunching mainframes to mobile devices, putting today's machine learning boom in context.

■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