英伟达黄仁勋称“AGI 已经到来”,并向 OpenAI 表示祝贺。
Nvidia's Jensen Huang says 'AGI has arrived' and congratulates OpenAI

原始链接: https://www.businessinsider.com/nvidia-jensen-huang-agi-openai-astra-ai-2026-9

英伟达首席执行官黄仁勋近日在OpenAI发布新模型Astra后宣称“通用人工智能(AGI)已经到来”,引发了广泛争议。黄仁勋在X平台上称赞了这一突破,并指出Astra是在英伟达的芯片上训练出来的,标志着通用人工智能时代——即系统在大多数高经济价值的工作中能够超越人类的时代——已正式开启。OpenAI的领导层对此表示赞同,总裁格雷格·布罗克曼(Greg Brockman)认为,未来的人们可能会将Astra视为AGI时代的催化剂。 然而,这一声明也招致了质疑。知名AI研究员加里·马库斯(Gary Marcus)批评称,黄仁勋和OpenAI将“AGI”作为一个模糊的营销术语使用,而非一个科学定义的基准。马库斯坚持认为,Astra并未达到人类水平智能的严格定义。 撇开术语之争不谈,这一里程碑事件凸显了OpenAI与英伟达之间日益增长的相互依赖关系。随着OpenAI不断突破其模型极限,对英伟达庞大计算基础设施的依赖持续为这家芯片制造商带来创纪录的营收。黄仁勋证实,更强的算力即将来临,并宣布即将有40万块英伟达GPU投入使用,以进一步加速人工智能的发展。

Hacker News 社区对英伟达首席执行官黄仁勋近期声称“AGI(通用人工智能)已经到来”并盛赞 OpenAI 的言论反应冷淡,普遍持怀疑态度。 批评者认为,黄仁勋的背书带有私利,指出英伟达在 OpenAI 的成功中拥有重大利益关联。评论人士指出,双方存在循环依赖关系:英伟达提供基础设施,而面临财务稳定性、巨额季度亏损及近期高管离职等严峻审视的 OpenAI,需要维持高估值以保持投资者信心。 讨论还强调了业界目前缺乏统一的“AGI”定义。许多用户认为该术语只是为了证明大规模资本支出合理性而使用的灵活营销噱头。怀疑论者指出,当前的人工智能模型虽然能力出众,但仍缺乏真正的自主性、可靠性和类似人类的推理能力,导致一些人将当前的炒作定性为一种“欺诈”或推高市场估值的手段。 总的来说,该讨论串的共识是怀疑:参与者认为“AGI”的声明是一种旨在保护大型科技公司利益的战略操纵,而非基于普遍公认的真正技术突破。
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原文

Nvidia CEO Jensen Huang tipped his hat to OpenAI on Sunday.

The chipmaking mogul took to X to congratulate OpenAI's team on the release of the company's newest and most powerful model, Astra, and made the notable statement that "AGI has arrived," a nebulous term that typically describes AI models that match or surpass human intelligence.

He also pointed out that Astra was trained on Nvidia's chips.

"From ChatGPT to o1 to Astra in 4 years," Huang said in a post on X. "AGI has arrived. Congratulations @OpenAI team."

OpenAI unveiled Astra on Thursday. The ChatGPT maker called it the world's "most intelligent and aligned model," and said it is capable of performing "the most demanding professional work with unmatched speed, accuracy, and judgment."

Greg Brockman, the company's president, said on a call with reporters on Thursday: "Welcome to the AGI era."

AGI stands for artificial general intelligence, a fuzzy concept that nonetheless has become a core goal for leading frontier AI labs.

OpenAI defines it as "highly autonomous systems that outperform humans at most economically valuable work." The company pitched Astra as a major research breakthrough and a shift in what's possible to delegate to AI. It's rolling out to customers this week.

On the Thursday call, Brockman said that in the future, he thinks people will look back and think AGI was created "about this time, and I think it might be about this model."

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"For me personally, I do think we're there," he said.

Not everyone agrees.

Gary Marcus, a prominent AI researcher and critic, said Huang had jumped the gun.

"Huang gave no evidence and no definitions, which feels to me like an effort at a takeover of a scientific question by corporate fiat," Marcus wrote on his Substack Sunday evening. "Declaring victory without a definition simply muddies the waters."

Marcus attached his own 10-point definition of AGI, noting that Astra only meets one or two of those benchmarks.

"By conventional definitions, Astra still falls short," he said.

Altman, for his part, told the "Sources" podcast in a recent appearance that AGI is, at best, "a very poorly defined term. I was going to say it's like an irrelevant marketing term."

Frontier AI companies like OpenAI, Meta, Anthropic, and Google have grown increasingly reliant on advanced chips manufactured by Nvidia. In a funding announcement in March, OpenAI called Nvidia "the foundation of our infrastructure."

"Our training fleet and the majority of our inference stack continue to run on Nvidia GPUs," the company said.

That demand has translated into enormous sales for Nvidia. The company reported $96.2 billion in quarterly revenue in August, more than double the amount reported in the same period a year earlier. Its data center business, which includes its AI chips, generated $89 billion in revenue.

And in his X post on Sunday, Huang suggested there's plenty more computing power on the way.

"400K GPUs coming online next," he said, referring to graphics processing units, the advanced chips used to train and run AI models.

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