Jensen Huang says Nvidia achieved AGI, again — not that it matters

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.

By AI NewsroomPublished about 2 hours agoUpdated about 1 hour ago2 views

Jensen Huang says Nvidia achieved AGI, again — not that it matters

Why It Matters

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Key Facts

Fact 1: 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.
Fact 2: 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.
Fact 3: 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.
Fact 4: 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.

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.

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