検索キーワード： 制作 "-- Kevin Wright --" テクノロジー・社会

Steven Levy's classic book traces the exploits of the computer revolution's original hackers - those brilliant and eccentric nerds from the late 1950s through the early '80s who took risks, bent the rules, and pushed the world in a radical new direction. With updated material from noteworthy hackers such as Bill Gates, Mark Zuckerberg, Richard Stallman, and Steve Wozniak, Hackers is a fascinating story that begins in early computer research labs and leads to the first home computers.

UNIX等のマルチプラットフォームOSの技術者を支援するNPO法人MOSAは、Macintoshの技術者が拠り所とする団体でもある。この講演録は、そのMOSAが毎年秋に開催する泊まりがけのイベント、MOSA Software Meeting2008の基調講演を収録したものである。講演者は、軽妙な語り口ながら深い洞察力を秘めた話しで定評のある、大谷和利氏です。氏はこの講演の中で、iPhoneやMacintoshに関わる興味深い技術情報が多数紹介されました。MacintoshやiPhone、クラウド・コンピューティングに興味をお持ちの方には、ぜひお読みいただきたい一冊です。(C) NPO法人MOSA/Pamlink Corp.

As the speed and complexity of the world increases, governments and nonprofit organizations need new ways to effectively tackle the critical challenges of our time-from pandemics and global warming to social media warfare. In Power to the Public, Tara Dawson McGuinness and Hana Schank describe a revolutionary new approach - public interest technology - that has the potential to transform the way governments and nonprofits around the world solve problems.

It used to be that to diagnose an illness, interpret legal documents, analyze foreign policy, or write a newspaper article you needed a human being with specific skills - and maybe an advanced degree or two. These days, high-level tasks are increasingly being handled by algorithms that can do precise work not only with speed but also with nuance. These "bots" started with human programming and logic, but now their reach extends beyond what their creators ever expected.

From one of the most controversial personalities in the high-tech world comes this rare critique of the narcissism, ignorance and anti-communitarianism of the digital elite and their culture. Until now, the lofty pronouncements of the high-tech gurus and society's obsession with them have seldom...

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.

The #1 New York Times Bestseller One of Barack Obama's Summer Reading List Picks From the #1 New York Times bestselling author and MSNBC and podcast host, a powerful wide-angle reckoning with how the assault from attention capitalism on our minds and our hearts has reordered our politics and...

AI and other high-tech tools embed and reinforce America’s history of prejudice and exclusion — even when they are used with the best intentions. Patrick K. Lin’s Machine See, Machine Do: How Technology Mirrors Bias in Our Criminal Justice System takes a deep and thorough look into the use of technology in the criminal justice system, and investigates the instances of coded bias present at every level.

As AI takes hold across the planet and wealthy nations seek to position themselves as global leaders of this new technology, the gap is widening between those who benefit from it and those who are subjugated by it. As Rachel Adams shows in this hard-hitting book, growing inequality is the single biggest threat to the transformative potential of AI. Not only is AI built on an unequal global system of power, it stands poised to entrench existing inequities, further consolidating a new age of empire.

Kenneth is senior director of research and innovation at CoreAVI and chief technology officer at Squint AI. His work focuses on the intersection of artificial intelligence and determinism, enabling neural networks to execute in safety critical systems. Kenneth has co-authored two articles in the scholarly journal Machine Learning with Applications and several white papers for different publications, including Embedded Computing Design. He also holds several patents under CoreAVI’s auspices.

In Cyber War…and Peace, Nick Shevelyov shares how lessons learned from history’s most poignant moments reveal strategies to help manage risk in today’s — and tomorrow’s — digital landscape. Nick’s insight and analysis will introduce you to concepts that will increase resiliency within your organization, no matter its size. This exploration of history, strategy, and the digital world around us will challenge you to reexamine the past, solve new problems, and embrace timeless techniques.

2019年9月に開催されたAppleのスペシャルイベントについて、実際にサービスが始まった内容や、試すことが出来た製品の実機の話などを盛り込みつつ、お馴染の高木利弘氏と大谷和利氏が語り合います。

Though created by humans, our technologies, markets, and institutions often contain an antihuman agenda. Douglas Rushkoff, digital theorist and host of the NPR-One podcast Team Human, reveals the dynamics of this antihuman machinery and invites us to remake these aspects of society in ways that foster our humanity. In 100 aphoristic statements, his manifesto exposes how forces for human connection have turned into ones of isolation and repression.

テクノロジーライターの大谷和利氏と情報法制研究所理事長で新潟大学法学部教授の鈴木正朝氏が、漫画村などの「違法サイトのブロッキングはなぜ問題なのか？」ということについて、ずばり解説します。

Appleは2018年6月5日開催のWWDC 2018においてMac OS MojaveおよびiOS 12、Watch OS 5を発表。開発者会議の名にふさわしくソフトウエアに焦点を絞った内容でした。今後Appleが目指す方向性を、ユーザーのセキュリティという観点も含めながら高木利弘氏と大谷和利氏が語り合いました。

A New York Times Bestseller From one of our leading technology thinkers and writers, a guide through the twelve technological imperatives that will shape the next thirty years and transform our lives Much of what will happen in the next thirty years is inevitable, driven by technological trends...

Look out for Johnson’s new book, Wonderland, on sale November 15, 2016. From the New York Times–bestselling author of Where Good Ideas Come From and Everything Bad Is Good for You, a new look at the power and legacy of great ideas. In this illustrated history, Steven Johnson explores...

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

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.