AI's Rapid Growth Faces a Slowdown

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Demis Hassabis, a leading figure in artificial intelligence, has a warning for the tech industry: the rapid progress of AI systems, particularly chatbots, may soon slow down. For years, AI researchers have relied on one simple formula—more data means better performance. Large language models, the technology behind chatbots, improved significantly as they analyzed vast amounts of digital text from the internet. However, Hassabis, who oversees Google DeepMind, now cautions that this method is reaching its limits. "Everyone in the industry is seeing diminishing returns," he said in a recent interview.

Hassabis is not alone in his concern. Interviews with AI experts and executives reveal a growing sense of unease within the industry. The internet’s digital text, once a seemingly endless resource, is now running out. This poses a challenge as billions of dollars continue to flow into AI development. While some, including OpenAI CEO Sam Altman, remain optimistic that progress will continue with new techniques, others worry that the industry's reliance on expanding datasets may hit a plateau.

The issue dates back to 2020, when Jared Kaplan’s research on "Scaling Laws" showed that large language models grow more powerful with more data. This finding spurred companies like OpenAI and Google to race for vast amounts of digital content. But as the available data dwindles, the big question is whether AI can maintain its explosive growth or if the industry will face a slowdown. The future of AI now hinges on finding new methods to fuel its development.

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