Nvidia CEO Jensen Huang publicly declared that artificial general intelligence (AGI) has arrived, congratulating OpenAI on the release of its newest flagship model, Astra.
Posting on X, Huang highlighted OpenAI’s rapid progression from ChatGPT to o1 and now Astra over a four-year span. He noted that the new model was trained on Nvidia hardware, adding that an additional 400,000 graphics processing units (GPUs) are coming online to power upcoming compute workloads.
OpenAI introduced Astra as its most intelligent and aligned model to date, designed to perform demanding professional tasks with high speed and accuracy. OpenAI President Greg Brockman told reporters during the announcement that the industry had entered the "AGI era," framing Astra's release as a historical turning point. OpenAI traditionally defines AGI as highly autonomous systems that outperform humans at most economically valuable work.
Skepticism and the Definition Problem
Despite the optimistic statements from tech executives, the claim that AGI has been achieved faces pushback from AI researchers and critics who point out the lack of consensus on what the term actually means.
AI researcher Gary Marcus criticized Huang's declaration, arguing that corporate executives are attempting to resolve a complex scientific debate by proclamation. Marcus stated that Astra still falls short on standard benchmarks for general intelligence and warned that declaring victory without a clear, objective definition creates public confusion.
Similarly, researchers associated with the ARC Prize—a benchmark OpenAI cited during Astra's launch—noted that strong test results in bounded environments do not equal general real-world capability. Even OpenAI CEO Sam Altman has acknowledged in recent interviews that AGI remains a loosely defined term often used primarily for marketing.
The Compute Engine Driving the Race
Huang's comments reflect the close commercial alignment between frontier AI development and Nvidia's hardware ecosystem. Leading AI developers, including OpenAI, Meta, Anthropic, and Google, depend heavily on Nvidia infrastructure to build and deploy advanced models.
That demand propelled Nvidia to $96.2 billion in quarterly revenue, driven by $89 billion from its data center segment alone. As frontier labs continue scaling up compute infrastructure in pursuit of human-level capabilities, Nvidia remains the central hardware supplier underpinning the sector's expansion.