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Sam Altman now says AGI, or human-level AI, is 'not a super useful term’ — and he's not alone

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Sam Altman now says AGI, or human-level AI, is 'not a super useful term’ — and he's not alone

OpenAI CEO Sam Altman stated that the term "artificial general intelligence" (AGI) is losing relevance due to its ambiguous definition and the continuous, exponential growth in AI capabilities, advocating for a focus on "levels of progress" instead. This shift in narrative from a leading AI firm, whose multi-billion-dollar valuation is predicated on achieving AGI, comes as its latest GPT-5 model receives criticism for being an incremental upgrade rather than a revolutionary one. Industry experts echo this sentiment, suggesting "AGI" often serves to attract funding and hype, potentially obscuring tangible, specialized AI advancements and warranting a more grounded assessment of AI development for investors.

Analysis

OpenAI CEO Sam Altman is strategically shifting the narrative away from "artificial general intelligence" (AGI), a concept that has been central to the company's mission and its formidable multi-billion-dollar valuation. By labeling AGI an increasingly irrelevant and ambiguous term, and instead advocating for a focus on "levels of progress," management may be tempering expectations following the launch of its new GPT-5 model, which some experts have criticized as an "incremental, not revolutionary" upgrade. This rhetorical pivot is significant for a company whose last valuation was $300 billion and is reportedly seeking a $500 billion valuation in an upcoming secondary sale, as the promise of AGI has been a key driver for such figures. The sentiment is echoed by industry analysts who suggest the AGI concept is primarily a tool for fundraising and hype, obscuring tangible, specialized advancements. While Altman still forecasts major scientific breakthroughs within two years, this move to de-emphasize the binary goal of AGI suggests a recalibration toward a more sustainable, albeit potentially less spectacular, path of continuous model improvement, placing more pressure on demonstrating concrete utility and monetization over chasing a nebulous, sci-fi-esque objective.

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