Artificial intelligence pioneer Andrew Ng said the industry is decades away from developing artificial general intelligence (AGI).
In an interview with Fast Company posted Friday (Feb. 27), Ng said he defines AGI as AI that can perform any intellectual task that humans can, such as learning to drive a truck or writing a PhD thesis.
“We’re still very far from AI meeting that definition of AGI,” Ng said.
Ng is the founder of DeepLearning.AI and Coursera, executive chairman of LandingAI, and founding lead of Google Brain, according to the report.
Some businesses have pushed definitions of AGI that are less stringent, Ng said, but by his definition of the term, “we are closer than before, yet many decades away from an AI that matches human intelligence. If you stick with the original definition — aligned with what people genuinely imagine AGI to be — we remain very, very far away.”
PYMNTS reported in April 2024 that AGI had captured the attention of researchers, tech enthusiasts and media alike, though the field of AGI research remained in its early stages and its progress had been slower than some proponents had suggested.
According to that report, some experts argued that the complexity of the human brain and the nature of intelligence itself may pose insurmountable challenges to creating truly human-like AI, while others pointed to the lack of a clear roadmap for AGI development and the difficulty in defining and measuring progress toward this goal.
Elon Musk said in January that AGI will be achieved this year. He added: “I’m confident by 2030, AI will exceed the intelligence of all humans combined.”
Researchers from AI Impacts and the universities of Oxford and Bonn published a study in October 2025 saying that AI experts gave a 50% probability that advanced AI systems capable of performing all tasks better and more cheaply than humans would be feasible by 2047. They placed a 10% probability on such systems by 2027.
It was reported in August 2025 that tech giants such as Meta and Google are offering massive salaries to top AI talent and that this reflects the stakes for these companies in the race to develop AGI.
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