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In June of 2024, thirty-one years after its founding in a Denny’s restaurant, Nvidia became the most valuable corporation on Earth. The Thinking Machine is the astonishing story of how a designer of video game equipment conquered the market for AI hardware, and in the process re-invented the computer. Essential to Nvidia’s meteoric success is its visionary CEO Jensen Huang, who more than a decade ago, on the basis of a few promising scientific results, bet his entire company on AI.

Artificial intelligence does the seemingly impossible - driving cars, trading stocks, and teaching children. But facing the sea change that AI will bring can be paralyzing. How should companies set strategies, governments design policies, and people plan their lives for a world so different from what we know? In Prediction Machines, three eminent economists recast the rise of AI as a drop in the cost of prediction. With this single, masterful stroke, they lift the curtain on the AI-is-magic hype and show how basic tools from economics provide clarity about the AI revolution and a basis for action by CEOs, managers, policy makers, investors, and entrepreneurs.

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.

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.

We are about to cross a critical threshold in the history of our species. Everything is about to change. Soon we will live surrounded by AIs. They will carry out complex tasks-operating businesses, producing unlimited digital content, running core government services and maintaining infrastructure. This will be a world of DNA printers and quantum computers, engineered pathogens and autonomous weapons, robot assistants and abundant energy. It represents nothing less than a step change in human capability. We are not prepared.

How will artificial intelligence affect crime, war, justice, jobs, society, and our very sense of being human? The rise of AI has the potential to transform our future more than any other technology - and there's nobody better qualified or situated to explore that future than Max Tegmark, an MIT professor who's helped mainstream research on how to keep AI beneficial.

Today's "machine-learning" systems, trained by data, are so effective that we've invited them to see and hear for us - and to make decisions on our behalf. But alarm bells are ringing. Systems cull résumés until, years later, we discover that they have inherent gender biases. Algorithms decide bail and parole - and appear to assess black and white defendants differently. We can no longer assume that our mortgage application, or even our medical tests, will be seen by human eyes. And autonomous vehicles on our streets can injure or kill.

A gripping journey of discovery, The Catalyst moves from the early experiments that first hinted at RNA's spectacular powers, to Cech's own paradigm-shifting finding that it can catalyze cellular reactions, to the cutting-edge biotechnologies poised to reshape our health.

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 The Patient Will See You Now, Eric Topol, one of the nation's top physicians, examines what he calls medicine's "Gutenberg moment". Much as the printing press liberated knowledge from the control of an elite class, new technology is poised to democratize medicine. In this new era, patients will control their data and be emancipated from a paternalistic medical regime in which "the doctor knows best."

今、何が起きているのか？これからどうなるのか？人工知能とそれを支えるクラウド技術などの進化を長年追い続けてきた著者による、今後10年の社会変革を理解するためのベーシック・レポート

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.

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.

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.

A riveting, fast-paced inside look at one of the most incredible private-sector achievements in history, Moonshot recounts the intensive nine months in 2020 when the scientists at Pfizer, under the visionary leadership of Dr Albert Bourla, made 'the impossible possible' - creating, testing and manufacturing a safe and effective COIVD-19 vaccine that previously would have taken years to develop.

Once, we humans could only observe evolution. Suddenly, we had conquered it. And yet, in Life as We Made It, evolutionary biologist Beth Shapiro argues that - despite how amazing our new technologies are - our ability to alter the course of evolution isn’t new. What is new is that where once we shaped evolution through brute force, we can now do it as artisans. That power comes not a moment too soon. If we are going to survive in the next few centuries, we must revise the book of life.

In Trustworthy AI, award-winning executive Beena Ammanath offers a practical approach for enterprise leaders to manage business risk in a world where AI is everywhere by understanding the qualities of trustworthy AI and the essential considerations for its ethical use within the organization and in the marketplace. The author draws from her extensive experience across different industries and sectors in data, analytics and AI, the latest research and case studies, and the pressing questions and concerns business leaders have about the ethics of AI.

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.

■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