At a Glance
> At a Glance
> – Andrew Ng remains a leading AI voice with 2.3 million LinkedIn followers.
> – He warns that AI is amazing yet highly limited and may not reach AGI soon.
> – Ng calls for transparency laws to guard against a possible AI bubble.
> – Why it matters: Readers see how a top AI expert balances optimism with caution, shaping policy and industry trends.
**Andrew Ng, the founder of Coursera and former chief scientist at Baidu, is one of the most influential figures in artificial intelligence. In a recent interview and series of remarks, he outlined his view that while AI’s progress is impressive, its limits and the risk of a market bubble demand careful regulation. His insights touch on everything from coding education to the future of voice and agentic AI.
A Career Built on AI
Andrew Ng co-founded Google Brain, which became part of Google’s flagship DeepMind division that now produces some of the world’s best AI systems. He also served as chief scientist at Baidu and teaches computer science at Stanford University. In 2012 he launched Coursera, one of the world’s largest online learning platforms, and now runs DeepLearning.AI.
- LinkedIn Top Voice with 2.3 million followers
- Co-founder of Google Brain and Coursera
- Former chief scientist at Baidu
The Limits and Promise of AI
Andrew Ng told News Of Fort Worth:
> “The tricky thing about AI is that it is amazing and it is also highly limited,” Ng told News Of Fort Worth in an interview on the sidelines of his AI Developers Conference in November. “And understanding that balance of how amazing and how limited it is, that’s difficult.”
He added:
> “I look at how complex the training recipes are and how manual AI training and development is today, and there’s no way this is going to take us all the way to AGI just by itself,” Ng said.
Ng also said:
> “When someone uses AI and the system knows some language, it took much more work to prepare the data, to train the AI, to learn that one set of things than is widely appreciated,” he added.
He believes that the early stages of AI, the training or pre-training phase, carry the most risk. A table below shows the difference between training and inference.
| Stage | Focus | Importance |
|---|---|---|
| Training (pre-training) | Build the model | High capital cost |
| Inference | Run the model for users | Growing demand |
Ng says the inference demand is massive and will keep growing:
> “We need to build a lot more data centers to serve this demand,” Ng added.
He also warned that the hype around AGI is premature:
> “I think for a lot of AI models, the benefit is so much greater than the harm,” he said.
Regulation and the Future
Ng is a strong proponent of transparency laws, citing the recently passed SB 53 in California and the RAISE Act in New York:
> “If I had my druthers, if I were a regulator, transparency of large platforms is what I will push for, because that gives us a much better chance of being able to clearly see what problems there are, if any, and then work for their solution,” Ng said.
He cautions against a potential bubble collapse:
> “Whatever happens, it will be good for the industry, but certain businesses might do poorly,” Ng said, referring to the possibility of a bubble collapse.
Ng also highlighted the need for more data centers and the rise of voice AI:
> “I think people underestimate how big voice AI will get. If you look at Star Trek movies, no one envisioned everyone typing on the keyboard, right?”
He added that the field of agentic AI will keep growing:
> “During the summer of last year, a bunch of marketers got hold of the ‘agentic AI’ term and slapped it as a sticker on everything in sight, which caused the hype to just take off incredibly rapidly.”
> “I’m very confident that the field of agentic AI will keep on growing and rising in value,” Ng said. “I don’t know what the hype will do. That’s hard to predict. But the actual commercial value will keep rapidly rising.”
Key Takeaways
- Andrew Ng stresses that AI is amazing yet highly limited.
- He calls for transparency laws to avoid an AI investment bubble.
- The future will see growth in voice AI and agentic AI, but training remains costly.
Andrew Ng’s balanced perspective reminds industry leaders that while AI’s potential is vast, careful regulation and realistic expectations are essential for sustainable progress.
