During Nvidia's earnings call on Wednesday, CEO Jensen Huang casually announced that the company had 'achieved AGI,' one of the tech industry's most coveted milestones - a prize that some of its biggest players have spent years and billions of dollars chasing. Then, with the nonchalance of someone discarding a used tissue, Huang dismissed the achievement as 'senseless.'

He's not wrong. For a supposed finish line in the AI race, there's no consensus on what artificial general intelligence actually means, let alone how we'll know when we've crossed it. That makes 'achieving' it about as meaningful as declaring victory in a game where no one agreed on the rules.

Asked about OpenAI's pursuit of AGI, Huang said that for Nvidia, 'for many tasks, we could say that we've already achieved AGI.' He didn't bother with a precise definition or benchmark, adding, 'I think of all of those milestones and all those, you know, they're kind of senseless at this point.' He also mused about AI evolving from responding to simple prompts to autonomous agents that can learn new skills and improve themselves 'recursively.' What really matters, Huang argued, 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.'

This isn't Huang's first rodeo with declaring AGI achieved. In March, on the Lex Fridman podcast, he plainly stated, 'I think we've achieved AGI.' When Fridman proposed his own oddly specific definition - an AI system capable of 'essentially do your job,' meaning start, grow, and run a successful tech company worth more than $1 billion - Huang walked it back, admitting that 'the odds of 100,000 of those agents building Nvidia is zero percent.'

Over the years, other tech leaders have exploited the term's fuzziness, producing a veritable grab bag of definitions and benchmarks, all orbiting the same nebulous concept: AI that can match or surpass human intelligence across a broad range of domains. This, despite the fact that 'intelligence' itself lacks a universally agreed-upon definition.

OpenAI, a company founded with the explicit goal of building AGI, defines it in its charter as 'highly autonomous systems that outperform humans at most economically valuable work.' Sam Altman has admitted this is hardly measurable, calling AGI 'not a super useful term.' To complicate matters, OpenAI's financially-driven definition, worked out with Microsoft, reportedly refers to 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'd 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 to talk about 'powerful AI.' Others have similarly reached for their own terms: Meta talks about 'personal superintelligence,' Microsoft about 'humanist superintelligence,' and Amazon about 'useful general intelligence.' Google DeepMind's Demis Hassabis has taken to describing our arrival 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. 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.