书籍介绍
"This colorful page-turner puts artificial intelligence into a human perspective. Through the lives of Geoff Hinton and other major players, Metz explains this transformative technology and makes the quest thrilling."
—Walter Isaacson, author of The Code Breaker
Recipient of starred reviews in both Kirkus and Library Journal
THE UNTOLD TECH STORY OF OUR TIME
What does it mean to be smart? To be human? What do we really want from life and the intelligence we have, or might create?
With deep and exclusive reporting, across hundreds of interviews, New York Times Silicon Valley journalist Cade Metz brings you into the rooms where these questions are being answered. Where an extraordinarily powerful new artificial intelligence has been built into our biggest companies, our social discourse, and our daily lives, with few of us even noticing.
Long dismissed as a technology of the distant future, artificial intelligence was a project consigned to the fringes of the scientific community. Then two researchers changed everything. One was a sixty-four-year-old computer science professor who didn’t drive and didn’t fly because he could no longer sit down—but still made his way across North America for the moment that would define a new age of technology. The other was a thirty-six-year-old neuroscientist and chess prodigy who laid claim to being the greatest game player of all time before vowing to build a machine that could do anything the human brain could do.
They took two very different paths to that lofty goal, and they disagreed on how quickly it would arrive. But both were soon drawn into the heart of the tech industry. Their ideas drove a new kind of arms race, spanning Google, Microsoft, Facebook, and OpenAI, a new lab founded by Silicon Valley kingpin Elon Musk. But some believed that China would beat them all to the finish line.
Genius Makers dramatically presents the fierce conflict between national interests, shareholder value, the pursuit of scientific knowledge, and the very human concerns about privacy, security, bias, and prejudice. Like a great Victorian novel, this world of eccentric, brilliant, often unimaginably yet suddenly wealthy characters draws you into the most profound moral questions we can ask. And like a great mystery, it presents the story and facts that lead to a core, vital question:
How far will we let it go?
AI导读
核心看点
- 揭秘深度学习发展史，聚焦辛顿等关键人物。
- 展现谷歌、微软、百度等巨头对AI人才的争夺。
- 探讨AI技术突破背后的信念、八卦与行业变迁。
适合谁读
- 对人工智能发展史及幕后故事感兴趣的读者。
- 科技行业从业者，尤其是关注AI与深度学习的人。
- 喜欢阅读科技传记、商业竞争与人物群像的读者。
读前提醒
- 成书较早，未涵盖ChatGPT等最新大模型进展。
- 侧重人物叙事与八卦，非硬核技术教程，轻松易读。
- 建议结合当下AI热点，对比阅读以获更完整视角。
读者共识
- 叙事精彩流畅，像看故事一样了解AI发展脉络。
- 细节丰富，还原了大佬们的性格与关键决策瞬间。
- 虽有时效局限，但仍是理解深度学习起源的佳作。
本导读基于书籍简介、目录、原文摘录、短评和书评生成，不等同于全文精读。
精彩摘录
- "“自信的力量非常强大。我认识的最成功的人对自己的信任几乎到了妄想的地步，。。。如果你不相信自己，你就很难对未来有逆向的想法，而这正是创造大部分价值的地方。”（萨姆 奥特曼）"
- "Any AI technology that could reliably identify fake news would have passed a much larger milestone. “It would mean AI has reached human-level intelligence,” he said. He also knew that fake news was in the eye of the beholder. Separating the real from the fake was a matter of opinion. If humans could"
- "（马斯克）解释说，人类的受限在于无法足够快地使用自己的应用程序，大脑和机器之间没有足够的“带宽”。人们仍然用“肉棒”------手指------在手机上打字。“我们必须通过与神经皮质的高速带宽连接来突破这个限制。”"
- "Anything that a human could do in a fraction of a second, he (Ilya Sutskever) said, a neural network could also do. It just needed the right data. “The real conclusion is that if you have a very large dataset and a very large neural network,” he told his audience, “then success is guaranteed.” - Cha"
- "In Britain, academia was an intellectual monoculture. In the United States, the landscape was large enough to accommodate pockets of dissent. “There could be different views,” Hinton says, “and they could survive.” Now, if he told other researchers he was working on neural networks, they listened. -"
- "Ideas might fail. Predictions might not be met. But the next idea wouldn’t succeed unless they, and everyone around them, believed that it could. “Self-belief is immensely powerful. The most successful people I know believe in themselves almost to the point of delusion,” he (Sam Altman) once wrote. "
- "我并非物理不及格，也不是从心理学专业退学。 我是心理学不及格，从物理专业退学 ------ 这样讲更有利于维护声誉。（杰夫 辛顿）"
- "“我本应该去伯克利的。”（辛顿）对妻子说。 “伯克利？”他妻子说，“我愿意去伯克利。” “但你说过你不会住在美国。” “那不是美国，是加州。”"
作者简介
About the Author
Cade Metz is a technology correspondent with The New York Times, covering artificial intelligence, driverless cars, robotics, virtual reality, and other emerging areas. Previously, he was a senior staff writer with Wired magazine. He works in The New York Times’ San Francisco bureau and lives across the bay with his wife, Taylor, and two daughters.
用户评论
终于读完了！能在这个激荡的时代里随波逐流也是好的。—————————（在读感受： 在时代即将闭合的缝隙处，几个天才信仰者用力撕开了一道深长的口子。就像《杀死比尔》里被活埋的新娘，赤手穿洞棺材板。他们不仅带进来空气和光明，更是直接创造了一个新世界的基础。他们在这个新世界里挥舞魔杖，创造出一株又一株奇观的树苗。在几株树苗以肉眼可见的速度长成森林的过程中，我这样的青山小蚂蚁，也因此有了一处可以喝山泉、啃坚果的地方。
人工智能发展的八卦合集，足够有趣，Hinton这种一直苦苦求索，有所坚持的人太棒了。虽然算是一手开创了Deep learning的火热，但当很多人涌入又转头去做capsule 了。。相比而下，Gary Marcus感觉就是个碰瓷的骗子，深度学习不仅带火了从业者，也带火了评论家 。
猶如偵探小說般精彩紛呈，扣人心弦，令人欲罷不能，有關人工智慧倫理討論發人深省.
天时地利人和。神经网络的序曲从几十年前娓娓铺开，到如今大公司和大人物在里面的故事。最生动的还是Hinton的种种，串联了整个故事。
深度学习（到 2019 年左右）的发展史，虽然以各种技术进展和突破为话题，但是其实主要是各种 researcher 与 deep learning 相关的八卦和故事。看到这么多熟悉的名字和各种搞笑的轶事还是蛮好玩的，不过作者是在采访了几百人之后整合出来的这么一个故事线，大概在接受采访的时候人们会有一些避讳或者委婉或者疏漏甚至遗忘之类的，有个别事情在知道内情的情况下也可以看出作者的描述不一定准确，而且作者也加了一些有点奇怪的自己的观点，例如把 AlphaGo 去中国比赛比作乒乓球外交之类的。总之作为八卦趣闻看还是蛮不错的。
近年的AI 发展简史。好看，很多八卦，哈哈
A book of Who’s Who of AI. 写得很生动。人工智能领域的竞争就好像当年的曼哈顿工程一样。
有关AI的演进，这是一部很好的汇总。集中不同的神经网络模型的发展和对标关键性事件都有很好的串联。同样是技术传记，作者笔力和walter Issacson相比尽管略微逊色，仍然是一部好书。
近年来大热的AI不乏被媒体形容为国家之间的新型军备竞赛，但如同其他新兴学科，AI自然不缺乏来自学界、公众的质疑及其追求diversity所引发的恐慌和担忧。作为前Wired杂志现NYT记者，Cade Metz对Hinton和Lecun等元老级人物以及Google Facebook和Baidu在AI方面的竞争描述的还是非常有意思的。
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