Demis Hassabis, one of the most influential minds in artificial intelligence (AI), has a warning for the tech world: Chatbots might not keep evolving at the breakneck speed we've all gotten used to. That's right-after years of jaw-dropping progress, the AI rocket ship may be losing a bit of its fuel.

For years, the secret sauce behind AI improvement was simple-feed large language models endless amounts of data from the internet, and voilà, better performance. But, as Hassabis pointed out in an interview with The New York Times (right before accepting a Nobel Prize for his AI contributions, no less), "everyone in the industry is seeing diminishing returns." Translation: The internet's supply of useful digital text is pretty much tapped out.

This isn't just Hassabis's solo opinion, either. According to The New York Times, interviews with 20 top executives and researchers reveal a growing consensus: The unthinkable has happened-the industry has essentially hit "peak data." And that's a pretty big deal, considering companies are still throwing billions at AI. For example, Databricks just announced a record $10 billion funding round, and tech giants are doubling down on building the data centers that power AI. Yet, according to Hassabis, "we're no longer getting the same progress."

Still, not everyone is ready to hit the panic button. Optimists like OpenAI's Sam Altman and Nvidia's Jensen Huang argue there's plenty of room for innovation-just with a few clever twists on old methods. But even Hassabis, who heads Google DeepMind, acknowledges that while tweaks to existing techniques can squeeze out some gains, the big leaps will require entirely fresh ideas. His goal? Creating machines that rival the efficacy of the human brain. No pressure, right?

One of the proposed solutions is called "synthetic data." It's a fancy way of saying that AI can train itself, generating its own data through a kind of trial and error - solving math problems and discovering what works. This approach was recently demonstrated with a system released by OpenAI, called OpenAI o1. Cool, right? Well, there's a catch - it works best in realms with right and wrong answers, like math and coding. In more subjective fields, such as the humanities or philosophy, AI fails utterly to get even close. "These techniques do not apply where things are actually true in practice," said Dylan Patel, an analyst at SemiAnalysis. In other words, do not expect artificial intelligence to solve moral dilemmas or write poetry that wins your heart and soul anytime soon.

Even so, the implications of an AI slowdown could be enormous. Take Nvidia, for example. The company's meteoric rise as a tech titan has been tied to the AI boom. During a recent earnings call, CEO Jensen Huang said demand for AI infrastructure remains strong, but companies are testing new methods, just in case the pace of AI progress plateaus.

So, what's next for AI? While some remain bullish on AI's future, the reality is that the tech industry may need to rethink its approach. After all, there's only one internet, and we're running out of data to mine. It's a moment of reckoning-can innovation keep the AI dream alive, or is this the beginning of the plateau everyone's dreading? Only time (and perhaps a few genius breakthroughs) will tell.