Jensen Huang needs a moment.

The CEO of Nvidia enters a cavernous ­studio at the company’s Bay Area headquarters and hunches over a table, his head bowed.

At 62, the world’s eighth richest man is compact, polished, and known among colleagues for his quick temper as well as his visionary leadership. Right now, he looks exhausted. As he stands silently, it’s hard to know if he’s about to erupt or collapse. 

by Charlie Campbell, Andrew R. Chow and Billy Perrigo

Then someone puts on a Spotify playlist and the stirring chords of Aerosmith’s “Dream On” fill the room. Huang puts on his trademark black leather jacket and appears to transform, donning not just the uniform, but also the body language and optimism befitting one of the foremost leaders of the artificial intelligence revolution.

Still, he’s got to be tired. Not too long ago, the former engineer ran a successful but semi-obscure outfit that specialized in graphics processors for video games. Today, Nvidia is the most valuable company in the world, thanks to a near-monopoly on the advanced chips powering an AI boom that is transforming the planet. Memes depict Nvidia as Atlas, holding the stock market on its shoulders. More than just a corporate juggernaut, Nvidia also has become an instrument of statecraft, operating at the nexus of advanced technology, diplomacy, and geopolitics. “You’re taking over the world, Jensen,” President Donald Trump, now a regular late-night phone buddy, told Huang during a recent state visit to the United Kingdom.

For decades, humankind steeled itself for the rise of thinking machines. As we marveled at their ability to beat chess champions and predict protein structures, we also recoiled from their inherent uncanniness, not to mention the threats to our sense of humanity. Leaders striving to develop the technology, including Sam Altman and Elon Musk, warned that the pursuit of its powers could create unforeseen catastrophe.

This year, the debate about how to wield AI responsibly gave way to a sprint to deploy it as fast as possible. “Every industry needs it, every company uses it, and every nation needs to build it,” Huang tells TIME in a 75-minute interview in November, two days after announcing that Nvidia, the world’s first $5 trillion company, had once again smashed Wall Street’s earnings expectations. “This is the single most impactful technology of our time.” OpenAI’s ChatGPT, which at launch was the fastest-growing consumer app of all time, has surpassed 800 million weekly users. AI wrote millions of lines of code, aided lab scientists, generated viral songs, and spurred companies to re-examine their strategies or risk obsolescence. (OpenAI and TIME have a licensing and technology agreement that allows OpenAI to access TIME’s archives.)

But researchers have found that AIs can scheme, deceive, or blackmail. As the leading companies’ models improve, AI systems may eventually outcompete humans—as if an advanced species were on the cusp of colonizing the earth. AI flooded social media with misinformation and deepfake videos, and Pope Leo XIV warned that it could manipulate children and serve “antihuman ideologies.” The AI boom seemed to swallow the economy into “a black hole that’s pulling all capital towards it,” says Paul Kedrosky, an investor and research fellow at MIT. Where skeptics spied a bubble, the revolution’s leaders saw the dawn of a new era of abundance. “There’s a belief that the world’s GDP is somehow limited at $100 trillion,” Huang says. “AI is going to cause that $100 trillion to become $500 trillion.”

This is the story of how AI changed our world in 2025, in new and exciting and sometimes frightening ways. It is the story of how Huang and other tech titansgrabbed the wheel of history, developing technology and making decisions that are reshaping the information landscape, the climate, and our livelihoods. Racing both beside and against each other, they placed multibillion-dollar bets on one of the biggest physical infrastructure projects of all time. They reoriented government policy, altered geopolitical rivalries, and brought robots into homes. AI emerged as arguably the most consequential tool in great-power competition since the advent of nuclear weapons.

This article was reported across three continents and through dozens of conversations with executives and computer scientists, economists and politicians, artists and investors, teenagers and grieving families. It describes a frantic blitz toward an unknown destination, and the struggle to make sense of it

The tone was set at Trump’s Inauguration. Tech moguls streamed into Washington; some sat behind the President during his Inaugural Address, a signal of the power they would wield. Over the next 11 months, they would use their enormous cash reserves, cultural power, and momentum to push their products into homes across the world.

At Meta, Mark Zuckerberg placed a chatbot into flagship products like Instagram and WhatsApp, raided rivals to amass talent, and doled out compensation packages that paid machine-learning engineers more than professional ballplayers. Altmancompleted his transformation of OpenAI, shedding profit caps for investors and paving the way for future investment in the $500 billion colossus. Anthropic, the frontier lab that styles itself as the most safety-conscious, reportedly made plans to go public at a $300 billion valuation. (Salesforce, where TIME owner Marc Benioff serves as CEO, is an investor in Anthropic.) Musk built data centers in record time. Google inserted Gemini AI answers at the top of its search engine. Top investors, like SoftBank’s Masayoshi Son, plowed billions into chips, self-driving cars, and capital infrastructure.

OpenAI, which ignited the boom, continues to set the pace in many ways. Usage of ChatGPT more than doubled, to 10% of the world’s population. “That leaves at least 90% to go,” says Nick Turley, head of ChatGPT. 

Read More: Why the Architects of AI Are TIME’s 2025 Person of the Year

A large language model (LLM), the technology underpinning chatbots like ChatGPT or Anthropic’s Claude, is a type of neural network, a computer program different from typical software. By feeding it reams of data, engineers train the models to spot patterns and predict what “tokens,” or fragments of words, should come next in a given sequence. From there, AI companies use reinforcement learning—strengthening the neural pathways that lead to desired responses—to turn a simple word predictor into something more like a digital assistant with a finely tuned personality. 

About a year ago, OpenAI researchers hit on a new way of improving these models. Instead of letting them respond to queries immediately, the researchers allowed the models to run for a period of time and “reason” in natural language about their answers. This required more computing power but produced better results. Suddenly a market boomed for mathematicians, physicists, coders, chemists, lawyers, and others to create specialized data, which companies used to reinforce their AI models’ reasoning. The chatbots got smarter.

READ MORE: https://time.com/7339685/person-of-the-year-2025-ai-architects/

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