本部纪录片以深入浅出的手法，从现代企业的本质、演变、冲击和可能的未来四个方面，批判地揭示了现代企业所隐含的内在运作、发展的历史、其所带来极具争议性的冲击及未来的可能发展。影片开篇便采用了“世卫组织国际疾病分类第10版”和“心理疾病诊断统计手册第4版”的诊断标准，对那些财团法人或大企业进行人格检查，试图揭开跨国大企业的真面目。本片耗时六年完成，采访了来自不同业界的40位人士，这些业界精英现身说法，道出了企业机构以牟取利润为终极使命的惊人秘密。我们的确患病了，唯利是图、人情冷漠、反社会人格等等，我们所能做的就是依靠我们的勇气、智慧和决心去阻止它。 　　由马克·阿克巴与詹尼弗·阿尔伯特联合执导的发人深省的纪录片《大企业》，根据乔尔·巴肯的《企业的性格与命运》改编拍摄而成。本片荣获2004年圣丹斯电影节世界电影单元-纪录片大奖在内的26项国际大奖以及10项观众票选最佳影片。

Artificial "neural networks" are widely used as flexible models for classification and regression applications, but questions remain about how the power of these models can be safely exploited when training data is limited. This book demonstrates how Bayesian methods allow complex neural network models to be used without fear of the "overfitting" that can occur with traditional training methods. Insight into the nature of these complex Bayesian models is provided by a theoretical investigation of the priors over functions that underlie them. A practical implementation of Bayesian neural network learning using Markov chain Monte Carlo methods is also described, and software for it is freely available over the Internet. Presupposing only basic knowledge of probability and statistics, this book should be of interest to researchers in statistics, engineering, and artificial intelligence.

"Written by three experts in the field, Deep Learning is the only comprehensive book on the subject." -- Elon Musk, co-chair of OpenAI; co-founder and CEO of Tesla and SpaceX
Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.
The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.
Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

本书是一部媒介文化研究的经典著作。作者认为，电话、电报、广播、电视等电子媒介的广泛使用，塑造了一个新的文化形态和传播方式。通过对不同媒介的比较，以及与种种文化现象的关联，作者勾画了一种电子媒介文化社会的图景，并对其发展趋向作出了某些预言

Since its founding in 1989 by Terrence Sejnowski, Neural Computation has become the leading journal in the field. Foundations of Neural Computationcollects, by topic, the most significant papers that have appeared in the journal over the past nine years.This volume of Foundations of Neural Computation, on unsupervised learning algorithms, focuses on neural network learning algorithms that do not require an explicit teacher. The goal of unsupervised learning is to extract an efficient internal representation of the statistical structure implicit in the inputs. These algorithms provide insights into the development of the cerebral cortex and implicit learning in humans. They are also of interest to engineers working in areas such as computer vision and speech recognition who seek efficient representations of raw input data.

With all the financial know-how and experience of the wizards on Wall Street and elsewhere, how is it that the market still goes boom and bust? How can people be so willing to get caught up in the mania of speculation when history tells us that a collapse is almost sure to follow? In this primer, the renowned economist John Kenneth Galbraith reviews the major speculative episodes of the last three centuries - from the 17th century tulip craze to the calamitous junk-bond follies of the 1980s. His insights provide important lessons on speculative economics, and demonstrate conclusively that money and intelligence are not necessarily linked.

Discover how artificial intelligence can improve how your organization practices law with this compelling resource from the creators of one of the world’s leading legal AI platforms.
AI for Lawyers: How Artificial Intelligence is Adding Value, Amplifying Expertise, and Transforming Careers explains how artificial intelligence can be used to revolutionize your organization’s operations. Noah Waisberg and Dr. Alexander Hudek, a lawyer and a computer science Ph.D. who lead prominent legal AI business Kira Systems, have written an approachable and insightful book that will help you transform how your firm functions.
AI for Lawyers explains how artificial intelligence can help your law firm:
Win more business and find more clients
Better meet and exceed client expectations
Find hidden efficiencies
Better manage and eliminate risk
Increase associate and partner engagement
Whether focusing on small or big law, AI for Lawyers is perfect for any lawyer who either feels uneasy about how AI might change law or is looking to capitalize on the evolving practice. With contributions from experts in the fields of e-Discovery, legal research, expert systems, and litigation analytics, it also belongs on the bookshelf of anyone who’s interested in the intersection of law and technology

卜正民将体制与意识的综合考察作为本书史论结合的主线，文中十八篇文章组成一段以鸦片为核心的连贯历史。勾勒了跨越一百三十年，焦点集中于政治和经济影响下的东亚地区的鸦片贸易。第一部分介绍了十九世纪鸦片贸易的基础；第二部分考察鸦片在中国如何被分运和消耗；第三部分研究国家与地方努力控制鸦片的方式，以及这些方式如何进一步推动近代中国政府的统一与权力渗透；第四部分分析日本利用鸦片对现有鸦片政权的冲击。

继《阅读史》之后，《书斋漫步》生动讲述了书斋或图书馆在人类文明中的重要作用。曼古埃尔在法国的家里策划修建了一个书斋，他受到这件事的启发，进而告诉我们书斋或图书馆怎样体现了许多个人乃至整个文明的回忆。本书轶事连篇，扣人心魄，从作者幼时的书架一直说到国际互联网的“全套”图书，从古代埃及、希腊到阿拉伯世界，从中国、罗马讲到“谷歌”。这里有已消逝的亚历山大图书馆；有撒缪尔？派匹斯的私人书斋：他给体积小的书本装上“高跟”，好让书架上的书整齐好看；还有文学家的书斋，狄更斯、博尔赫斯等等…… 曼古埃尔在书中还讲到诗人兼建筑家米开朗基罗的纪念碑式的图书馆，慈善家卡内基建立的图书馆，监狱里囚犯的口头“回忆图书馆”等。

《理解媒介:论人的延伸(增订评注本)》是“20世纪为数不多的重要思想著作之一”。这是神使墨丘利的杰作，洞悉未来，深入分析，是思想史转折的路标。麦克卢汉将传播媒介作为主要动因，以异乎寻常的方式解释历史。他认为，媒介是塑造历史和社会的隐蔽力量，常常被人忽视；媒介的“讯息”在于其如何“扭曲”现存的社会秩序；由于忽视媒介，我们常常对其熟视无睹，被其遮蔽，这是“书面文化”或西方式感知能力的失败。书面文化执著于媒介的内容，它必须在新的电子环境里革故鼎新。麦克卢汉邀请我们抛弃旧的思维习惯，采纳感知和知识的新标准。
《理解媒介:论人的延伸(增订评注本)》初版于1964年，麦克卢汉借以登上世界舞台，成为我们时代最杰出的公共知识分子之一。在这部极富胆略的著作里，他把媒介解释推向新的高度。他向我们发出挑战，让我们与他一道纵身投入他所谓的“创新认知过程”。

《经济和你想的不一样:经济学十大误解》内容简介：经济是不公平的，经济是不稳定的，经济是不可持续的。谁也没有真正预测到2008年经济危机的到来，包括所有的经济学家。是经济发生了改变。还是我们没有看到经济的真相。
《经济和你想的不一样:经济学十大误解》针对经济学的十大正统观点，追溯历史，正本清源，最终还给你一个真实的经济世界。
经济学对经济的十大误解——经济可以用经济规律来描述，经济由相互独立的个体组成，经济是稳定的，经济风险可以轻而易举地用统计学来管理，经济是理性的、有效率的，经济是无性别差异的，经济是公平的，经济可以无限增长下去，经济增长会让我们快乐，经济增长总是好事。

Brand-new INTRODUCING guide to the subject that really makes the world go round. Economics was described by the English economist Lionel Robbins in 1935 as 'the science of scarcity' but these days economics is everywhere, and it's never been more popular - as bestselling books such as Freakanomics attest. But what is economics really all about? What do the great economists think, and what can economics do for us today? David Orrell, author of Economyths, explains all in Introducing's trademark intelligent but witty stle, accompanied by brilliant illustrations from the legendary Borin van Loon.

In the spirit of Freakonomics and A Short History of Progress , The Future of Everything is a compelling, elegantly written history of our future. For centuries, scientists have strived to predict the future. But to what extent have they succeeded? Can past events--Hurricane Katrina, the Internet stock bubble, the SARS outbreak--help us understand what will happen next? Will scientists ever really be able to forecast catastrophes, or will we always be at the mercy of Mother Nature, waiting for the next storm, epidemic, or economic crash to thunder through our lives? In The Future of Everything , David Orrell looks back at the history of forecasting, from the time of the oracle at Delphi to the rise of astrology to the advent of the TV weather report, showing us how scientists (and some charlatans) predicted the future. How can today's scientists claim to anticipate future weather events when even thee-day forecasts prove a serious challenge? How can we predict and control epidemics? Can we accurately foresee our financial future? Or will we only find out about tomorrow when tomorrow arrives?

From the inability of wealth to make us happier, to our catastrophic blindness to the credit crunch, Economyths reveals ten ways in which economics has failed us all. Forecasters predicted a prosperous year in 2008 for financial markets - in one influential survey the average prediction was for an eleven percent gain. But by the end of the year, the Standard and Poor's 500 index - a key economic barometer - was down 38 percent, and major economies were plunging into recession. Even the Queen asked - "Why did no one see it coming?" An even bigger casualty was the credibility of economics, which for decades has claimed that the economy is a rational, stable, efficient machine, governed by well-understood laws. Mathematician David Orrell traces the history of this idea from its roots in ancient Greece to the financial centres of London and New York, shows how it is mistaken, and proposes new alternatives. Economyths explains how the economy is the result of complex and unpredictable processes; how risk models go astray; why the economy is not rational or fair; why no woman has ever won the Nobel Prize for economics; why financial crashes are less Black Swans than part of the landscape; and finally, how new ideas in mathematics, psychology, and environmentalism are helping to reinvent economics.

每天打嗝是什么原因造成的？参加旅行团有什么“潜规则”？酒店早餐是免费的吗？还贷款与购入共同基金，哪个更划算？猫儿为什么每天趴在阳台门口？信用卡为什么会频频消磁？怎样清理带刺的玫瑰？日常生活中会遇到各式各样的问题，你是否认真探究过根源，思考过问题背后真正的原因？你能否养成了科学的思维方式，像科学家一样直捣问题的核心？跟随这本书，踏上探索科学方法的旅程，去揭开生活中大大小小的谜团吧！
本书作者将生活中一个个真实的故事以浅显易懂的语言娓娓道出，让读者获得不少启发和教益。全书生动有趣，易于理解，是了解科学方法不可多得的入门图书。书中提到的许多创意定能让你跳出思维的囹圄，让生活的智慧绽放异彩。

盖·德利斯勒是加拿大动画人，为了帮助朝鲜的外包动画事业，受法国资本家的派遣，不远万里，来到朝鲜……好吧，他为了完成公司的动画项目，在朝鲜的外包公司呆了两个月。期间，他每晚画下一天的见闻，然后整理编绘成这本漫画《平壤》。

维基经济学的得名，缘于维基百科全书网站的巨大成功，它向世界证明：如果有一种方法充分利用组织里每一个人的智慧，它的能量将无比惊人！维基经济学所揭示的四个新法则——开放、对等、共享以及全球运作——正在取代一些旧的商业教条，许多成熟的传统公司正在从这种新的商务范式中受益。我们所熟知的企业如Google、亚马逊、宝洁、IBM、乐高、英特尔、宝马、波音、百思买、Youtube、MySpace等，都已经从维基经济中获得巨大的成功。
《维基经济学》的结论源自900万美元的研究项目，素有“数字经济之父”美誉的新经济学家唐·泰普斯科特向我们展示了个体力量的上升是如何改变商业社会的传统规则，这种利用大规模协作生产产品和提供服务的新方式，正颠覆我们对于传统知识创造模式的认识。
面对变化激烈的未来，企业和个人必须更有远见，掌握维基技术，拥抱维基理念，是21世纪最重要的商业素质。

我们都是被城市化的一员，我们回不去故乡，也离不开城市。
从乡村到城市，全球三分之一的人口正在进行最后的大迁移。
由于从事新闻工作必须四处游历，我走访了全球五大洲二十多个国家与地区，也因此养成了一种观察城市的习惯。从重庆的六公里，到孟买和德黑兰的边缘；从圣保罗与墨西哥城的 山坡地，到巴黎、阿姆斯特丹与洛杉矶的各种社区。我发现，这些落脚于城市的乡村移民，正执着于他们想象中的城市中心，并在世界各地造就了极为相似的都会空间。
搭乘地铁和电车，或是深入城市中心不为人知的隐秘角落，我得以细细观察面前这片由乡村移民构成的城市飞地。我以“落脚城市”称呼这些地区，它们往往位于人们的视线和旅游地图之外，饱受暴力和死亡、漠视与误解，同时又充满了希望与活力。
到21世纪末，人类将成为一个完全生活在城市里的物种。
而上一次人类大迁移，用一个多世纪的城市化，为欧洲和新大陆带来了法国大革命和工业革命，并直接造成了人类在思想、治理与科技领域的彻底变革。如今，世界各地的落脚城市正在创造历史。而对这种历史的冷漠，导致了巴黎、伦敦、阿姆斯特丹持续不断的暴动与骚乱；而在亚洲、非洲与南美洲，莽撞的贫民窟清除计划，正在摧毁数以万计人的生活与未来。
这个时代的历史，其实有一大部分是由漂泊的无根之人造就而成的。
他们因为公民权遭到剥夺，于是采取极端乃至暴力的手段，以求在都市体制中取得一席之地。落脚城市，可能是下一波经济与文化盛世的诞生地，也可能是下一波重大暴力冲突的爆发地。究竟走上那条路，则完全取决于我们自己。