My conversation with Brockman and Sutskever continued on in circles until we ran out the clock after forty-five minutes. I tried with little success to get more concrete details on what exactly they were trying to build—which by nature, they explained, they couldn’t know—and why then, if they couldn’t know, they were so confident it would be beneficial.

At one point, I tried a different approach, asking them instead to give examples of the downsides of the technology. This was a pillar of OpenAI’s founding mythology: The lab had to build good AGI before someone else built a bad one.

Through the course of my reporting, I would come to conclude something even more startling. Not even in Silicon Valley did other companies and investors move until after ChatGPT to funnel unqualified sums into scaling. That included Google and DeepMind, OpenAI’s original rival. It was specifically OpenAI, with its billionaire origins, unique ideological bent, and Altman’s singular drive, network, and fundraising talent, that created a ripe combination for its particular vision to emerge and take over. “I get the sense that Sam is the most ambitious person on the planet,” a former employee says. In other words, everything OpenAI did was the opposite of inevitable; the explosive global costs of its massive deep learning models, and the perilous race it sparked across the industry to scale such models to planetary limits, could only have ever arisen from the one place it actually did.

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.

For three months, Jones petitioned Microsoft executives to take down the tool until it had better guardrails, or at the very least restrict its rating in the Google and Android app store from “E for Everyone” to one for mature audiences. After Microsoft declined to adopt his recommendation and OpenAI was unresponsive, he sent a letter to the Federal Trade Commission. “They have failed to implement these changes and continue to market the product to ‘Anyone. Anywhere. Any Device,’ ” he wrote to the FTC. This problem “has been known by Microsoft and OpenAI prior to the public release of the AI model last October.” Microsoft did not comment on the latest status or outcome of Jones’s letter.

The bottleneck for producing novel biological weapons, for example, is not about finding a recipe, Weinstein noted. Such recipes already abound online and are easily found via Google. It is about obtaining the materials and equipment to actually make the armaments. Restricting access to so-called frontier models would thus do little to fix this. But the collateral damage of suppressing the publication of AI models would risk weakening the foundations of US AI innovation. Open source—sharing and building on code and software released to the broader community—has long been the bedrock upon which the wealth of US-based startups flourish. Restricting model weights from being published would give smaller developers fewer pathways than ever to create their own AI products and services. It would further entrench the dominance of the giants represented in the Frontier Model Forum. AI models would also become ever harder to scrutinize, such as in the work of Sasha Luccioni, Yacine Jernite, and Emma Strubell, who have relied heavily on open generative AI models to quantify the carbon and environmental costs of continuing to scale them.