A top AI researcher says the growing chorus warning of an AI bubble is detached from reality, arguing that rapid advances inside frontier labs point to something much larger on the horizon.
In a new interview on the MAD Podcast, Anthropic scientist Julian Schrittwieser says progress in artificial intelligence is accelerating at a pace that many outside the lab are calling for an AI bubble.
He compares public skepticism to the early stages of an exponential trend that were underestimated until they suddenly became overwhelming.
“And then I started thinking about this and like, all the talk about AI bubbles I’ve seen on X… this discussion. And it seemed very divorced from what was happening in frontier labs and what we were seeing. And that made me start to wonder a bit like, is it that things are moving so fast that people maybe struggle a bit to extrapolate and understand intuitively?”
He says AI’s growth pattern mirrors Covid-19’s exponential curve, when people were slow to notice before turning unstoppable.
“But you know, it’s doubling every so many months, which means that once it gets close to us, it’s going to move past and become really good very quickly. And that reminded me a lot in like a different way, but like what happened during early Covid where we had a similar situation, where at the beginning, it’s like very few cases. It’s never going to happen. It’s only a few hundred people who care. But if you understand the math, and if you look at it, it’s like, ‘Oh, it’s going to double every week, two weeks.
Clearly, it’s going to be on a massive scale. But it’s very hard for us to intuitively understand these exponential trends.”
According to Schrittwieser, model capability is doubling so consistently that frontier systems could soon operate independently for extended periods, handling complex tasks from start to finish without human help.
“And we see that in a year from now, maybe two years from now, the top models are going to be able to work completely on their own for like a whole day or more.”
He believes that trajectory alone guarantees widespread disruption across knowledge-based industries.
“Combined with this, combined with the fact that there’s a huge number of knowledge-based jobs in the economy, knowledge-based tasks, and combine that in the frontier labs, we are not seeing any slowdown of progress, just extrapolating those things together over a very short time, like half a year, one year. Already, that is enough to know that there is going to be a massive economic impact.”
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