Nobody Knows What AGI Means, and That's the Point
Nvidia's Jensen Huang declared his company had 'achieved AGI' on an earnings call, then called the milestone 'senseless' in the same breath. He's not wrong. The term has no agreed definition, and tech leaders like it that way.
Key points
- Nvidia CEO Jensen Huang said on a May 2025 earnings call that the company had "achieved AGI" for "many tasks," then immediately dismissed the milestone as "senseless."
- AGI, or artificial general intelligence, has no agreed scientific definition across the industry.
- OpenAI defines AGI as systems that "outperform humans at most economically valuable work" but its CEO has called that standard "not a super useful term."
- OpenAI reportedly has a separate, financial definition agreed with Microsoft: systems that generate at least $100 billion in profits.
- Anthropic CEO Dario Amodei has called AGI a "marketing term."
Jensen Huang, CEO of Nvidia, the company whose chips power most AI systems, dropped a remarkable claim on a recent earnings call. "For many tasks," he said, "we could say that we've already achieved AGI."
AGI stands for artificial general intelligence, the idea of an AI system that can match or beat human thinking across subjects well beyond any single narrow task. It's widely treated as the industry's ultimate goal.
Huang then called the milestone "senseless." That second part, at least, is defensible.
What does AGI actually mean?
No one agrees. That's the honest, short answer.
OpenAI, the company founded to build AGI, defines it in its charter as "highly autonomous systems that outperform humans at most economically valuable work." CEO Sam Altman admitted last year that AGI is "not a super useful term." The Verge AI first reported that OpenAI also holds a separate, private definition worked out with Microsoft: systems capable of generating at least $100 billion in profits. Chief research officer Mark Chen said in a recent Time interview that OpenAI is "80% of the way" to AGI, while Altman has predicted he'd be calling something AGI by end of 2025.
Anthropics's Dario Amodei prefers "powerful AI" and has called AGI "imprecise" and a "marketing term." Meta talks about "personal superintelligence." Microsoft uses "humanist superintelligence." Amazon says "useful general intelligence." Google DeepMind's Demis Hassabis describes the current moment as the "foothills of the singularity," a hypothetical point where AI growth becomes self-sustaining.
New vocabulary. Same fog.
Has Huang said this before?
Yes. In March 2025, on the Lex Fridman podcast, Huang said plainly: "I think we've achieved AGI." When Fridman proposed a definition, specifically an AI that could build and run a tech company worth more than $1 billion, Huang backed off. "The odds of 100,000 of those agents building Nvidia is zero percent," he said.
On the earnings call, Huang shifted entirely. What actually matters, he argued, is AI "doing productive and useful work" and "generating profitable tokens," meaning billable AI outputs. More computing power, more outputs, more revenue. That framing serves a company selling the chips behind all of it. We covered Nvidia's push to extend its customer base beyond the big tech platforms in our 27 August story, and this AGI claim fits the same pattern: language that keeps investors leaning in.
What does this mean for ordinary people?
Practically, nothing has changed. No new AI product launched, no patient got a better diagnosis, and no new capability appeared overnight.
What shifted is the language around expectations. When tech leaders declare a goal achieved before anyone agrees what the goal is, accountability becomes nearly impossible.
For anyone tracking AI in health or public services, the useful question isn't "has AGI arrived?" It's: what specific problem does this tool solve, for which people, with what evidence? Those questions have real answers. "AGI" does not, and the people coining it know that perfectly well.
