For more than two years, every new AI announcement has lived in the shadow of ChatGPT. No model from any company has eclipsed or matched that initial fever. But perhaps the closest any firm has come to replicating the buzz was this past February, when OpenAI first teased its video-generating AI model, Sora.
This week, OpenAI launched what its chief executive, Sam Altman, called “the smartest model in the world”—a generative-AI program whose capabilities are supposedly far greater, and more closely approximate how humans think, than those of any such software preceding it. The start-up has been building toward this moment since September 12, a day that, in OpenAI’s telling, set the world on a new path toward superintelligence.
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Google is taken for granted as a dominant force in the generative-AI market—so it’s easy to forget that, in the initial frenzy following the release of ChatGPT, the search giant was caught flat-footed. The company raced to catch up with OpenAI, and its early models made some basic and highly publicized errors.
The images and videos were hard to miss in the days leading up to November 5. There was Donald Trump with the chiseled musculature of Superman, hovering over a row of skyscrapers. Trump and Kamala Harris squaring off in bright-red uniforms (McDonald’s logo for Trump, hammer-and-sickle insignia for Harris). People had clearly used AI to create these—an effort to show support for their candidate or to troll their opponents. But the images didn’t stop after Trump won.
Democrats will spend the next four years debating why the party suffered a sweeping defeat last week. Maybe it was inflation, or the culture wars, or Joe Biden’s hubris, or podcasts, that drove voters in every swing state to the Republican presidential nominee. At least one theory, however, can already be put to rest: Elon Musk did not “steal” the election for Donald Trump.
If the presidential election has provided relief from anything, it has been the generative-AI boom. Neither Kamala Harris nor Donald Trump has made much of the technology in their public messaging, and they have not articulated particularly detailed AI platforms. Bots do not seem to rank among the economy, immigration, abortion rights, and other issues that can make or break campaigns.
But don’t be fooled.
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Among the most tangible and immediate effects of the generative-AI boom has been a total upending of English classes.
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Even for Silicon Valley, where executives have spent the past two years likening their chatbots to fire, electricity, and nuclear weapons, the past few months have been extraordinary.
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The list of Nobel laureates reads like a collection of humanity’s greatest treasures: Albert Einstein, Marie Curie, Francis Crick, Toni Morrison. As of this morning, it also includes two physicists whose research, in the 1980s, laid the foundations for modern artificial intelligence.
When the Swedish inventor Alfred Nobel wrote his will in 1895, he designated funds to reward those who “have conferred the greatest benefit to humankind.” The resulting Nobel Prizes have since been awarded to the discoverers of penicillin, X-rays, and the structure of DNA—and, as of today, to two scientists who, decades ago, laid the foundations for modern artificial intelligence.
Terence Tao, a mathematics professor at UCLA, is a real-life superintelligence. The “Mozart of Math,” as he is sometimes called, is widely considered the world’s greatest living mathematician. He has won numerous awards, including the equivalent of a Nobel Prize for mathematics, for his advances and proofs. Right now, AI is nowhere close to his level.
But technology companies are trying to get it there.
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A disaster is brewing on dark-web forums, in messaging apps, and in schools around the world: Generative AI is being used to create sexually explicit images and videos of children, likely thousands a day.
When the Three Mile Island power plant in Pennsylvania was decommissioned in 2019, it heralded the symbolic end of America’s nuclear industry. In 1979, the facility was the site of the worst nuclear disaster in the nation’s history: a partial reactor meltdown that didn’t release enough radiation to cause detectable harm to people nearby, but still turned Americans against nuclear power and prompted a host of regulations that functionally killed most nuclear build-out for decades.
After weeks of speculation about a new and more powerful AI product in the works, OpenAI today announced its first “reasoning model.” The program, known as o1, may in many respects be OpenAI’s most powerful AI offering yet, with problem-solving capacities that resemble those of a human mind more than any software before. Or, at least, that’s how the company is selling it.
As with most OpenAI research and product announcements, o1 is, for now, somewhat of a tease.
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Today’s generative-AI tools can concoct stunning designs and playful prose with the push of a few buttons. That, in turn, has bred fears about how the technology could hurt human artists and writers, and led many, in their defense of humanity, to a well-intentioned but confused claim.
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Year three of AI college is about to begin, and instructors across the country still seem to have no clue how to handle the technology: no good way to stop students from using ChatGPT to write essays, and no clear way to instruct students on how AI might enhance their work.
At a rally this past April in Michigan, surrounded by a cadre of law-enforcement officials, Donald Trump suddenly began railing against electric cars. President Joe Biden’s decision to support EVs, he decried, “is one of the dumbest I’ve ever heard.” Minutes later, he was back to praising the sheriffs behind him: “We have to get law and order back. These are the best people in the world,” he said to a smattering of applause.
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For the past two years, the biggest tech firms have begun spending historic amounts of money to develop generative-AI products and spread them across the web. The build-out may demand a trillion dollars or more of investment across the economy this decade—more than the Apollo missions or the interstate-highway system.
Every second of every day, people across the world type tens of thousands of queries into Google, adding up to trillions of searches a year. Google and a few other search engines are the portal through which several billion people navigate the internet. Many of the world’s most powerful tech companies, including Google, Microsoft, and OpenAI, have recently spotted an opportunity to remake that gateway with generative AI, and they are racing to seize it.
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Yesterday OpenAI made what should have been a triumphant entry into the AI-search wars: The start-up announced SearchGPT, a prototype tool that can use the internet to answer questions of all kinds. But there was a problem, as I reported: Even the demo got something wrong.
Whenever AI companies present a vision for the role of artificial intelligence in the future of searching the internet, they tend to underscore the same points: instantaneous summaries of relevant information; ready-made lists tailored to a searcher’s needs. They tend not to point out that generative-AI models are prone to providing incorrect, and at times fully made-up, information—and yet it keeps happening.
Overnight, much of the world ground to a halt: Tens of thousands of flights and trains were canceled or delayed, hospitals stopped elective surgeries, doctors couldn’t book appointments, banks struggled to process transactions, television networks stopped broadcasting. The culprit was not a war, an earthquake, a mounting heat wave, or a terrorist attack, but some faulty computer code. It was likely the largest IT failure in history.
For more than 40 years in a row, Ford’s F-150 and its family of pickup trucks have been the best-selling vehicles in America. So when Ford released an electric version in 2022, the F-150 Lightning, it should have been a turning point for electric cars in the country—if not, that is, for the price tag.
Today, at Apple’s annual developers conference—where new software products are previewed in slick video presentations—the company finally joined the generative-AI race. The company introduced Apple Intelligence, a suite of AI features that will be rolled out to the tech giant’s latest operating systems starting this fall. New generative-AI models will help Apple users write work memos and highly personalized text; create images and emoji; connect and organize photos, calendar events, and emails.
In April, a group of people in a red Tesla driving through the Moroccan desert were glued to the odometer on the car’s giant touch screen. “Two million, Hans! Two million,” exclaimed the front-seat passenger to the owner and driver, Hansjörg von Gemmingen-Hornberg. His 2014 Model S had become likely the first electric vehicle to drive 2 million kilometers, or more than 1.2 million miles. The car could have traveled from the Earth to the moon and back, twice, then circled the equator 11 times.
OpenAI appears to be in the midst of a months-long revolt from within. The latest flash point came yesterday, when a group of 11 current and former employees—plus two from other firms—issued a public letter declaring that leading AI companies are not to be trusted. “The companies are behaving in a way that is really not in the public interest,” William Saunders, a signatory who, like several others on the letter, left OpenAI earlier this year, told me.
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This week has felt like the early days of the generative-AI boom, filled with dazzling events concerning the future of the technology.
On Monday, OpenAI held a last-minute “Spring Update” event in which the company announced its newest AI model, GPT-4o, in an impressive live demo.
Earlier today, Google presented a new vision for its flagship search engine, one that is uniquely tailored to the generative-AI moment. With advanced technology at its disposal, “Google will do the Googling for you,” Liz Reid, the company’s head of search, declared onstage at the company’s annual software conference.
Googling something rarely yields an immediate, definitive answer.
Earlier today, OpenAI announced its newest product: GPT-4o, a faster, cheaper, more powerful version of its most advanced large language model, and one that the company has deliberately positioned as the next step in “natural human-computer interaction.
Moments after receiving my lunch order, the robots whirred to life. A clawlike contraption lurched forward, like a bird pecking at feed, to snatch dishes holding a faux-chicken cutlet and potatoes, then inserted them onto a metal track that snakes through a 650-degree-Fahrenheit oven. Seven minutes, some automatic food dispensers, and two conveyor belts later (with a healthy assist from human hands), my meal was sitting on a shelf of mint-green cubbies.