検索キーワード： 機械理論・人工知能

脳科学とコンピュータの融合が私たちの常識を覆す！　自動運転車、ドローン、ロボット兵器、雇用・産業構造…

In this advisedly optimistic book, Rewiring Democracy, security technologist Bruce Schneier and data scientist Nathan Sanders cut through the AI hype and examine the myriad ways that AI is transforming every aspect of democracy—for both good and ill. The authors describe how the sophistication of AI will fulfill demands from lawmakers for more complex legislation, reducing deference to the executive branch and altering the balance of power between lawmakers and administrators

After many years during which it languished in relative obscurity, in remote classrooms of computer science departments and in small prototype projects for tech companies, artificial intelligence (AI) is now a searingly hot topic across the media. Yet much of the public discussion is so feverish that an understanding of the basic scientific and engineering elements of the field is easily lost, often resulting in exaggerated claims, as well as dangerously neglected threats.

Researchers, developers, business leaders, policy makers, and others are expanding the technology-centered scope of artificial intelligence (AI) to include human-centered AI (HCAI) ways of thinking. This expansion from an algorithm-focused view to embrace a human-centered perspective can shape the future of technology to better serve human needs. The remarkable progress in algorithms for machine and deep learning have opened the doors to new opportunities, and some dark possibilities.

In the AI Content Paradox, attorney and AIO (Artificial Intelligence Optimization) strategist Carl Taylor exposes why traditional legal marketing such as PPC, SEO, and AI-churned blog posts will collapse in the next five years, and what lawyers must do now to survive and thrive in the new age of AI referrals.

How to Use AI to Manifest Your Dreams reveals the groundbreaking intersection of ancient manifestation wisdom and cutting-edge AI technology. This isn't about positive thinking or wishful visualization—it's about using scientifically-proven methods amplified by artificial intelligence to systematically create the life you desire.

Take a data-first and use-case-driven approach with Low-Code AI to understand machine learning and deep learning concepts. This hands-on guide presents three problem-focused ways to learn no-code ML using AutoML, low-code using BigQuery ML, and custom code using scikit-learn and Keras. In each case, you'll learn key ML concepts by using real-world datasets with realistic problems.

Artificial Intelligence is changing everything—how we work, how we communicate, even how we make decisions. Yet public understanding of AI is still riddled with sensationalism, fear, and misunderstanding. Is AI a conscious entity preparing to take over the world? Is it going to replace every human job? Is it inherently fair, objective, or creative? The answer to all of these questions is far more nuanced than headlines suggest.

Sixty-five years ago, a middle-aged woman working with a small group of collaborators out of a converted shed on the outskirts of Cambridge predicted the future of Artificial Intelligence. As world powers raced to discover and exploit the capabilities of the first computers during the Cold War, Masterman emerged from obscurity to become an unlikely prophet of artificial intelligence.

Beginning with post-WW2 monitoring devices, Listening In traces an arc through the Cold War era into the present day in which state and commercial spyware can record our calls, copy messages and secretly film us. Exploring how mass audio surveillance is carried out through devices such as smart phones, speakers and baby monitors and used to inform and train AI algorithms, the book provides fresh insights into how we are allowing our personal privacies to be traded for enhanced social connectivity and technological convenience.

Constantly overwhelmed by decisions that drain your time and focus? Feel like you're falling behind while others are scaling effortlessly with AI? What would it be worth to reclaim hours of your week and lead with clarity, speed, and confidence? You’re not failing as a leader — you’re operating in a system that wasn’t designed for the velocity of today. The meetings, messages, and decision fatigue - it’s not a lack of effort. It’s a lack of leverage.

性愛、家族愛、推しへの愛……言語哲学のプロが徹底解剖！　この愛の言葉を、AIは理解できるのか？古くから、それはきっと人類が誕生したころから、“愛”という概念、感情は存在している。

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.

◎仕事が速い人は、AIに“仕事を任せている”――そのノウハウを徹底解説◎秘訣は「プロンプトの型」にあり。作業時間は「1時間→30秒」に！

Recent breakthroughs in AI have not only increased demand for AI products, they've also lowered the barriers to entry for those who want to build AI products. The model-as-a-service approach has transformed AI from an esoteric discipline into a powerful development tool that anyone can use. Everyone, including those with minimal or no prior AI experience, can now leverage AI models to build applications. In this book, author Chip Huyen discusses AI engineering: the process of building applications with readily available foundation models.

We've arrived in a new era—GenAI is reshaping industries and decision-making processes across the board. As a result, understanding their potential and pitfalls has become crucial. But in order to stay ahead of the curve, you'll need to develop fresh perspectives on leveraging AI beyond mere technical know-how. Geared toward business leaders and tech professionals alike, this book demystifies the strategic integration of AI into business practices, ensuring you're equipped not just to participate but to lead in this new landscape.

Generative AI is the hottest topic in tech. This practical book teaches machine learning engineers and data scientists how to use TensorFlow and Keras to create impressive generative deep learning models from scratch, including variational autoencoders (VAEs), generative adversarial networks (GANs), Transformers, normalizing flows, energy-based models, and denoising diffusion models.

What does the rapid rise and astonishing rate of improvement of AI mean for brands in the next five years? Listen to what OpenAI CEO Sam Altman told authors Adam Brotman and Andy Sack when he met them: "It will mean that 95 percent of what marketers use agencies, strategists, and creative professionals for today will easily, nearly instantly, and at almost no cost be handled by AI. No problem." Upon hearing that astonishing statement, the authors began a journey of discovery to understand what the transition to an AI first world would mean.

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.

La storia di come le reti di informazione hanno fatto e disfatto il nostro mondo, dall’autore del bestseller mondiale Sapiens. Negli ultimi centomila anni, noi Sapiens abbiamo accumulato un enorme potere. Eppure, nonostante tutte le nostre scoperte, invenzioni e conquiste, oggi ci troviamo in una crisi esistenziale. Il mondo è sull’orlo del collasso ecologico. La disinformazione dilaga. E ci stiamo buttando a capofitto nell’era dell’intelligenza artificiale, una nuova rete di informazioni che minaccia di annientarci. Perché siamo così autodistruttivi?