On Nvidia’s earnings call Wednesday, CEO Jensen Huang casually announced the company had “achieved AGI,” one of the tech industry’s ultimate goals some of its biggest players have spent years chasing. Almost immediately, Huang dismissed the coveted milestone as “senseless.”
He’s right. For the supposed finish line of the AI race, there is no consensus on what artificial general intelligence means, let alone how we’ll know when we’ve actually got there, which makes achieving it equally arbitrary.
Asked about OpenAI’s pursuit of AGI, Huang said that when it comes to Nvidia, “for many tasks, we could say that we’ve already achieved AGI.” He did not provide a precise definition or benchmark, but added, “I think of all of those milestones and all those, you know, they’re kind of senseless at this point.” He also pointed to AI moving beyond responding to simple prompts to autonomous agents capable of learning new skills and improving themselves “recursively.” What really matters, Huang said, is that AI is “doing productive and useful work” and “generating profitable tokens,” with more compute producing more tokens — and, inevitably, more profit. “This is the exact phase where we’re at. Which is the reason why everybody’s leaning in.”
“… for many tasks, we could say that we’ve already achieved AGI.”
This isn’t the first time Huang has said we’ve reached AGI. In March, during an appearance on the Lex Fridman podcast, he plainly stated, “I think we’ve achieved AGI.” Huang didn’t say exactly what he meant by AGI. Fridman proposed his own oddly specific definition: an AI system that’s able to “essentially do your job,” as in start, grow, and run a successful tech company worth more than $1 billion. Walking back his earlier claims, Huang said that “the odds of 100,000 of those agents building Nvidia is zero percent.”
Over the years, other tech leaders have capitalized on the term’s fuzziness and produced a veritable grab bag of definitions and benchmarks, all orbiting the same nebulous concept: AI capable of matching or surpassing human intelligence across a broad range of domains, despite the fact that “intelligence” also doesn’t have a universally agreed-upon definition.
There is no consensus on what artificial general intelligence means, let alone how we’ll know when we’ve actually got there, which makes achieving it equally arbitrary.
The definition of AGI according to OpenAI – a company founded with the explicit goal of building it – leaves a lot of room for interpretation. In its charter, OpenAI defines AGI as “highly autonomous systems that outperform humans at most economically valuable work.” Altman himself has acknowledged that this is hardly a measurable standard, admitting last year that AGI is “not a super useful term.” Complicating matters is OpenAI’s different, financially-driven definition of AGI it worked out with Microsoft — reportedly systems that can generate at least $100 billion in profits. In a recent Time story, chief research officer Mark Chen estimated OpenAI is “80% of the way” to AGI, while Altman said that by the end of the year the company would have something he would call AGI.
The fact that both AGI and its threshold remain undefined is no secret: tech leaders say so themselves, even as they make predictions predicated on it. Anthropic CEO Dario Amodei has called AGI “imprecise,” even a “marketing term,” preferring instead to talk about “powerful AI.” Others have similarly reached for their own terms to describe broadly similar ideas. In theory, there are supposed to be distinctions between them, but in practice they all bleed together. Meta talks about “personal superintelligence,” Microsoft “humanist superintelligence,” and Amazon “useful general intelligence.” Google DeepMind’s Demis Hassabis has taken to talking about how we’ve arrived at the “foothills of the singularity.” And OpenAI cofounder Ilya Sutskever, who reportedly led employees in chants of “feel the AGI,” now runs a company called Safe Superintelligence.
New terminology hasn’t made the meaning more tangible.
New terminology hasn’t made the meaning more tangible. So long as AGI remains poorly defined and carelessly used, the whole thing is senseless. Well, unless you want a handy tool for hyping up progress. So expect the industry — Huang included — to keep the AGI talk coming. Maybe an AGI will eventually show up and tell us what AGI actually means.
