Researchers have long noted that artificial neural networks take much more time to absorb and apply new knowledge than people do, since training them requires tremendous amounts of both energy and data. That's no longer the case, Hinton argues, noting that systems like GPT-4 can learn new things very quickly once properly trained by researchers. That's not unlike the way a trained professional physicist can wrap her brain around new experimental findings much more quickly than a typical high school science student could.

That leads Hinton to the conclusion that AI systems might already be outsmarting us. Not only can AI systems learn things faster, he notes, they can also share copies of their knowledge with each other almost instantly.

“It’s a completely different form of intelligence,” he told the publication. “A new and better form of intelligence.”

Eoin Treacy's view

I attended Hinton’s presentation at the EmTech Digital conference today. He expressed a great deal of caution about the evolution of AI while also saying that the reasoning capability necessary for outright competition with human thought is not yet in place. He is worried about the fact that when one model learns, every model can transfer the knowledge instantly and therefore the rate of improvement can only accelerate. Taken to a logical conclusion, the ability of AI models will eventually exceed the ability of the human mind.