In The Optimist, the Wall Street Journal reporter Keach Hagey presents the most detailed account yet of Altman’s rise, from his precocious childhood in St. Louis to his first, failed startup experience; his time as legendary entrepreneur Paul Graham’s protégé and successor as head of Y Combinator, the start-up accelerator where Altman became the premier power broker in Silicon Valley; the founding of OpenAI and his recruitment of a small yet superior team; and his struggle to keep his company at the cutting edge while fending off determined rivals, including Elon Musk.

Nvidia is the darling of the age of artificial intelligence: the company’s chips are powering the generative-AI revolution, and demand is insatiable. For all the current interest and attention, however, Nvidia is not of our time. Founded more than three decades ago in a Denny’s in East San Jose, for years it was known primarily in the then-niche world of computer gaming. In fact, the company’s leather-jacketed leader, Jensen Huang, is the longest-serving CEO in an industry marked by near constant turmoil and failure.

Confused about AI and worried about what it means for your future and the future of the world? You’re not alone. AI is everywhere—and few things are surrounded by so much hype, misinformation, and misunderstanding. In AI Snake Oil, computer scientists Arvind Narayanan and Sayash Kapoor cut through the confusion to give you an essential understanding of how AI works, why it often doesn’t, where it might be useful or harmful, and when you should suspect that companies are using AI hype to sell AI snake oil—products that don’t work, and probably never will.

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.

For listeners of Walter Isaacson’s Steve Jobs and Chris Miller’s Chip War, a riveting look at how Apple helped build China’s dominance in electronics assembly and manufacturing only to find itself trapped in a relationship with an authoritarian state making ever-increasing demands.

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 difference between growing your business and going out of business is your ability to think strategically. The problem is, most leaders are stuck in the operational weeds, struggling to find the time to make better strategic decisions. This challenge is only heightened by the rise of AI. While you know AI is the future, current demands leave you with no time to explore its benefits. Meanwhile, your competition is gaining an edge by integrating AI. The time to act is now.

Something new entered our world in November 2022—the first general purpose AI that could pass for a human and do the kinds of creative, innovative work that only humans could do previously. Wharton professor Ethan Mollick immediately understood what ChatGPT meant: after millions of years on our own, humans had developed a kind of co-intelligence that could augment, or even replace, human thinking. Through his writing, speaking, and teaching, Mollick has become one of the most prominent and provocative explainers of AI.

To trace the history of the twenty-first century so far is to trace a history of unaffordability and shortage. After years of refusing to build sufficient housing, America has a national housing crisis. After years of limiting immigration, we don’t have enough workers. Despite decades of being warned about the consequences of climate change, we haven’t built anything close to the clean-energy infrastructure we need. Ambitious public projects are finished late and over budget—if they are ever finished at all.

Tech billionaires have decided that they should determine our futures for us. According to Elon Musk, Jeff Bezos, Sam Altman, and more, the only good future for humanity is one powered by technology: trillions of humans living in space, functionally immortal, served by superintelligent AIs. In More Everything Forever, science writer Adam Becker investigates these wildly implausible and often profoundly immoral visions of tomorrow—and shows why, in reality, there is no good evidence that they will, or should, come to pass.

The ultrarich hold more of America’s wealth than they did in the heyday of the Carnegies and Rockefellers. Here, Evan Osnos’s incisive reportage yields an unforgettable portrait of the tactics and obsessions driving this new Gilded Age, in which superyachts, luxury bunkers, elite tax dodges, and a torrent of political donations bespeak staggering disparities of wealth and power. With deft storytelling and meticulous reporting, this is a book about the indulgences, incentives, and psychological distortions that define our economic age.

In Money Machine: A Trailblazing American Venture in China, Weijian Shan delivers a compelling account of one of the most significant deals in private equity history: the first and only foreign acquisition of control of a Chinese national bank. Money Machine is the fascinating inside story of the transaction as told by the man who led it, from the intrigues of dealmaking to the complex and uncharted process of securing control by a foreign investor of a Chinese nationwide financial institution, a feat that had never before been attempted, nor has it been repeated.

Curious about AI, but unsure how it works? Want to tap into the lucrative potential of this rapidly advancing technology? Unlock the immense potential of AI with this transformative book! Welcome to Fundamentals of Artificial Intelligence & Large Language Models, the second in a series of books crafted to help you join a movement toward a more financially fruitful future.

As an immigrant who came to the West, El Akkad believed that it promised freedom. A place of justice for all. But in the past twenty years, reporting on the War on Terror, Ferguson, climate change, Black Lives Matter protests, and more, and watching the unmitigated slaughter in Gaza, El Akkad has come to the conclusion that much of what the West promises is a lie. That there will always be entire groups of human beings it has never intended to treat as fully human—not just Arabs or Muslims or immigrants, but whoever falls outside the boundaries of privilege.

A globe shows the world we think we know: neatly delineated sovereign nations that grant or restrict their citizens’ rights. Beneath, above, and tucked inside their borders, however, another universe has been engineered into existence. It consists of thousands of extraterritorial zones that operate largely autonomously, and increasingly for the benefit of the wealthiest individuals and corporations. Atossa Abrahamian traces the rise of this hidden globe to thirteenth-century Switzerland, where poor cantons marketed their only commodity.

In The Optimist, the Wall Street Journal reporter Keach Hagey presents the most detailed account yet of Altman’s rise, from his precocious childhood in St. Louis to his first, failed startup experience; his time as legendary entrepreneur Paul Graham’s protégé and successor as head of Y Combinator, the start-up accelerator where Altman became the premier power broker in Silicon Valley; the founding of OpenAI and his recruitment of a small yet superior team; and his struggle to keep his company at the cutting edge while fending off determined rivals, including Elon Musk.

Is artificial intelligence going to take over the world? Have big tech scientists created an artificial lifeform that can think on its own? Is it going to put authors, artists, and others out of business? Are we about to enter an age where computers are better than humans at everything? The answer to these questions, linguist Emily M. Bender and sociologist Alex Hanna make clear, is “no,” “they wish,” “LOL,” and “definitely not.” This kind of thinking is a symptom of a phenomenon known as “AI hype.”

Large language models (LLMs) and diffusion models such as ChatGPT and Stable Diffusion have unprecedented potential. Because they have been trained on all the public text and images on the internet, they can make useful contributions to a wide variety of tasks. And with the barrier to entry greatly reduced today, practically any developer can harness LLMs and diffusion models to tackle problems previously unsuitable for automation. With this book, you'll gain a solid foundation in generative AI, including how to apply these models in practice.

For listeners of Walter Isaacson’s Steve Jobs and Chris Miller’s Chip War, a riveting look at how Apple helped build China’s dominance in electronics assembly and manufacturing only to find itself trapped in a relationship with an authoritarian state making ever-increasing demands.

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.

Nvidia is the darling of the age of artificial intelligence: the company’s chips are powering the generative-AI revolution, and demand is insatiable. For all the current interest and attention, however, Nvidia is not of our time. Founded more than three decades ago in a Denny’s in East San Jose, for years it was known primarily in the then-niche world of computer gaming. In fact, the company’s leather-jacketed leader, Jensen Huang, is the longest-serving CEO in an industry marked by near constant turmoil and failure.

This is a practical, non-technical guide for business leaders, entrepreneurs, and curious minds. This comprehensive guide on agentic AI cuts through the hype and offers a clear, jargon-free strategic roadmap to understanding and applying this technology. The authors bring a rare perspective, having implemented agentic AI across diverse organizations—from global enterprises to agile startups—witnessing both remarkable successes and sobering failures.

In 1928, a young social worker and hobby pilot named Amelia Earhart arrived in the office of George Putnam, heir to the Putnam & Sons throne and hitmaker, on the hunt for the right woman for a secret flying mission across the Atlantic. A partnership—professional and soon otherwise—was born.

Confused about AI and worried about what it means for your future and the future of the world? You’re not alone. AI is everywhere—and few things are surrounded by so much hype, misinformation, and misunderstanding. In AI Snake Oil, computer scientists Arvind Narayanan and Sayash Kapoor cut through the confusion to give you an essential understanding of how AI works, why it often doesn’t, where it might be useful or harmful, and when you should suspect that companies are using AI hype to sell AI snake oil—products that don’t work, and probably never will.

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.

Tech billionaires have decided that they should determine our futures for us. According to Elon Musk, Jeff Bezos, Sam Altman, and more, the only good future for humanity is one powered by technology: trillions of humans living in space, functionally immortal, served by superintelligent AIs. In More Everything Forever, science writer Adam Becker investigates these wildly implausible and often profoundly immoral visions of tomorrow—and shows why, in reality, there is no good evidence that they will, or should, come to pass.

In The Little Book of Data, each chapter illustrates one of the core principles of solving problems with data by featuring an expert who has solved a big problem with data—from the entrepreneur creating a “loneliness score” to the epidemiologist trying to save lives by finding disease “hotspots.”

An arrest for cocaine possession on the last day of a sweltering New York summer leaves Smith, a queer Black Stanford graduate, in a state of turmoil. Pulled into the court system and mandated treatment, he finds himself in an absurd but dangerous situation: his class protects him, but his race does not. It’s just weeks after the death of his beloved roommate Elle, the daughter of a famous soul singer, and he’s still reeling from the tabloid spectacle—as well as lingering questions around how well he really knew his closest friend.

Jewel Stone has it all—the perfect marriage, a bestselling author career, her dream home—or so she likes everyone to believe. But between her writer’s block and her husband losing his job, her picture-perfect life is in shambles. And inspiration just isn’t hitting…until she receives a call she never expected: her former best friend needs her help. When Shelby Andrews wakes up in the hospital after a biking accident, she can’t remember the last twelve years. She knows she owns a bookstore on the beach, but she has no memory of Lacey, her nineteen-year-old adopted daughter.

When Evie Steinberg’s family moves right before seventh grade, she promises her dad that she’ll make sure everything goes perfectly. Maybe if she keeps her promise, he’ll finally forgive her for accidentally ruining the biggest moment of his cryptozoology career last spring. Perfect means taking care of her little sister, fitting in at her new school, and never complaining or causing problems. Perfect definitely doesn’t mean being bullied by a girl who’s turning the whole school against her and failing math class.