AGI Remains a Mystery—Even to AI Pioneer Fei-Fei Li
Artificial General Intelligence (AGI)—the holy grail of AI development—remains poorly defined, even among the field’s brightest minds. OpenAI may have raised $6.6 billion to pursue it, but what exactly is AGI? According to Fei-Fei Li, one of AI’s most influential researchers, even she isn’t entirely sure.
The ‘Godmother of AI’ Admits Uncertainty
At Credo AI’s Responsible AI Leadership Summit, Li—often called the “godmother of AI”—was candid about her confusion regarding AGI and related concepts like “AI singularity.”
“I come from academic AI and have been educated in the more rigorous and evidence-based methods, so I don’t really know what all these words mean,” Li told the audience in San Francisco. “I frankly don’t even know what AGI means. Like people say you know it when you see it, I guess I haven’t seen it.”
Li, who pioneered ImageNet in 2006—a breakthrough that catalyzed modern AI—now leads Stanford’s Human-Centered AI Institute (HAI) and her startup, World Labs. Yet, despite her deep expertise, she finds AGI’s definition elusive.
How Do Experts Define AGI?
- Sam Altman (OpenAI CEO): Describes AGI as “the equivalent of a median human that you could hire as a coworker.”
- OpenAI’s Charter: Defines it as “highly autonomous systems that outperform humans at most economically valuable work.”
- OpenAI’s Internal Levels: A five-tier framework tracking progress from chatbots (Level 1) to AI capable of running entire organizations (Level 5).
Despite these attempts, Li—and many others—remain skeptical. “This all sounds like a lot more than a median human coworker could do,” she noted.
From ImageNet to AI Regulation
Li reflected on AI’s evolution, crediting three key breakthroughs:
- Big data (like ImageNet)
- Neural networks (e.g., AlexNet)
- GPU computing
Today, she balances her research with advising California on AI policy. Governor Newsom recently vetoed SB 1047, a controversial AI bill Li opposed, and instead formed a task force including Li to develop balanced AI regulations.
“We need to look at potential impact on humans rather than penalizing technology itself,” Li argued, comparing AI regulation to car safety measures like seatbelts and speed limits.
The Future: Spatial Intelligence and Diversity in AI
At World Labs, Li is pioneering “large world models”—AI that understands 3D environments (spatial intelligence). She believes this is far more complex than language models, given vision’s 540-million-year evolutionary head start.
She also emphasized the need for diversity in AI:
“We are far away from a very diverse AI ecosystem. Diverse human intelligence will lead to diverse artificial intelligence—and better technology.”
While AGI’s definition remains murky, Li’s focus is clear: advancing AI responsibly, with humanity at the center.
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