In early 2019, senior Microsoft leadership began coming through the OpenAI office. First came Kevin Scott, the tech giant’s excitable chief technology officer, who had followed OpenAI and grown particularly fond of the startup; then came Craig Mundie, a senior adviser to Nadella who had served on Microsoft leadership, including as its chief research and strategy officer, for over twenty years. Bill Gates also turned up, reserved and tight-lipped as usual, as he watched a series of demos. Most employees were left in the dark about Microsoft’s engagement. Altman told the small team working on the deal to keep knowledge of a possible investment limited.

As ChatGPT swept the world by storm in early 2023, a Chinese AI researcher would share with me a clear-eyed analysis that unraveled OpenAI’s inevitability argument. What OpenAI did never could have happened anywhere but Silicon Valley, he said. In China, which rivals the US in AI talent, no team of researchers and engineers, no matter how impressive, would get $1 billion, let alone ten times more, to develop a massively expensive technology without an articulated vision of exactly what it would look like and what it would be good for.

In the coming months, Amodei and Altman would clash over how and when to release GPT-3; Altman would win out, pushing the model into the world on an accelerated timeline. Years before ChatGPT, these two decisions—the one to explode GPT-3’s size and the one to quickly release it—would change the course of AI development. It would set off a rapid acceleration of AI advancement, sparking fierce competition between companies and countries. It would fuel an unprecedented expansion of surveillance capitalism and labor exploitation. It would, by virtue of the sheer resources required, consolidate the development of the technology to a degree never seen before, locking out the rest of the world from participating. It would accelerate the vicious cycle of universities, unable to compete, losing PhD students and professors to industry, atrophying independent academic research, and spelling the beginning of the end of accountability. It would amplify the environmental impacts of AI to an extent that, in the absence of transparency or regulation, neither external experts nor governments have been able to fully tabulate to this day.

Microsoft was also a challenging partner; many felt it had far too much bureaucracy and required too much hand-holding to make the most of OpenAI’s models. By relying on the tech giant to deliver its technologies to the public, OpenAI was also losing visibility into and data from its users and, most importantly, control over its vision.

As OpenAI concentrated its bets, Altman was applying the same strategy to his other projects and investments. Over the years, as he’d shifted toward more hard-tech innovation, he had developed a belief in betting big and long on the most important projects.

“If you could wave a wand, change anything about the tech, startup, entrepreneurship ecosystem, what would you change?” his brother Jack had asked him at an event as he’d stepped down from YC. “It would be to get everyone in the ecosystem to take a much longer time horizon,” Altman had said. “This world where people start a company and plan to run it for four or five years, join a company and only plan to stay for one or two—that’s not how important shit gets done.”

Along those lines, 2021 seemed to mark a major shift in Altman’s personal investment strategy away from taking a large number of small bets toward taking a small number of really large ones. That year a startup he’d cofounded in 2019 called Tools for Humanity that had remained largely quiet saw an influx of funding and media coverage and a concerted ramp-up in its operations, as Altman directed more external attention to the company. The venture was a dedicated effort to develop a working mechanism for universal basic income, or UBI, a popular Silicon Valley idea to give everyone a regular minimum distribution of income. Altman often passionately discussed UBI as the possible antidote to a future world where AI could create mass economic fallout. At YC he had started the largest pilot in the US to study the concept, spinning out a nonprofit in the process called OpenResearch that administered the program. Over three years, OpenResearch gave a $1,000 monthly stipend to a randomly selected group of one thousand out of three thousand low-income people, with the rest getting fifty dollars a month as a control. In July 2024, OpenResearch would release its findings, showing that the unconditional cash helped people meet their basic needs, assist others, and have more economic leeway.