Jensen Huang: AGI has arrived! NVIDIA is behind OpenAI Astra, and 400,000 GPUs are about to be deployed.

Nvidia CEO Jensen Huang declared the official start of the era of artificial general intelligence, attributing this historic milestone to OpenAI's latest flagship model, Astra—which was trained on Nvidia chips. This statement once again places Nvidia in the position of AI infrastructure leader and hints at an even larger-scale expansion of computing power.

On Sunday, Jensen Huang posted a message on the X platform congratulating the OpenAI team, saying "AGI has arrived," and revealing that Astra was trained on more than 100,000 NVIDIA Grace Blackwell NVLink72 chips. He also stated that "400K GPUs are coming soon," sending a strong signal that NVIDIA's computing power supply will further leap forward.

This statement has direct implications for the market. Nvidia's data center business has become its core growth engine, and Jensen Huang's announcement of adding 400,000 GPUs indicates that order demand from leading AI customers continues to expand.

Astra releases: OpenAI calls it the "most intelligent" model

OpenAI launched Astra last Thursday, positioning it as "the world's most intelligent and human-value-aligned model," claiming it can "perform the most demanding professional tasks with unparalleled speed, accuracy, and judgment." OpenAI President Greg Brockman told the media at the launch event, "Welcome to the AGI era."

Brockman further predicted that in the future, when people look back on history, they will think that AGI was born "around this time, and I think that's probably the model." "Personally, I do think we've arrived," he said. Astra began rolling out to users this week.

OpenAI defines AGI as "highly autonomous systems that outperform humans in most economically valuable jobs" and positions Astra as a major research breakthrough that marks a fundamental shift in the boundaries of tasks that can be entrusted to AI.

The controversy continues: the definition of AGI itself remains controversial.

However, not everyone agrees with this announcement. Gary Marcus, a well-known AI researcher and critic, directly pointed out that Jensen Huang was "rushing things."

"Huang provided neither evidence nor a definition, which seems to me like an attempt to force corporate control over a scientific issue," Marcus wrote on his Substack. "Declaring victory without a definition only makes the issue more confusing."

Marcus then listed his own 10 defining criteria for AGI, noting that Astra only meets one or two of them. "By the commonly accepted definition, Astra still falls short," he said.

Even OpenAI's own CEO, Sam Altman, is quite cautious about this concept. He recently stated on the "Sources" podcast that AGI is, at best, "a very vaguely defined term. I would have said it's more like a trivial marketing term."

Nvidia: The Core Support of AI Infrastructure

Regardless of how the debate over the definition of AGI unfolds, NVIDIA's position as the core computing power supplier for leading AI companies is undisputed. In a funding announcement in March of this year, OpenAI called NVIDIA "the cornerstone of our infrastructure" and stated that "our training clusters and most of our inference stack continue to run on NVIDIA GPUs."

Leading AI companies such as Meta, Anthropic, and Google also heavily rely on high-end chips manufactured by Nvidia. This demand has translated into Nvidia's impressive financial performance—the company reported quarterly revenue of $96.2 billion in August, more than doubling year-on-year; of which, data center revenue reached $89 billion, with businesses including AI chips constituting the main source of growth.

Jensen Huang's post on X stated that the next batch of 400,000 GPUs will be deployed, further reinforcing external expectations for Nvidia's computing power expansion. From ChatGPT to o1, and then to Astra, each technological leap in the past four years has been built on Nvidia's continuously upgraded chip foundation.

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