DeepSeek's AI models claim to use significantly less computing power than competitors like Meta's Llama 3.1, raising hopes for a more sustainable future for AI. This potential breakthrough could mitigate the environmental impact of AI development, which currently relies on massive data centers with substantial energy demands. DeepSeek's approach, involving efficient training methods and open-source models, has sparked discussions about the future of AI development and its energy footprint.
DeepSeek startled everyone last month with the claim that its AI model uses roughly one-tenth the amount of computing power as Meta’s Llama 3.1 model, upending an entire worldview of how much energy and resources it’ll take to develop artificial intelligence. Taken at face value, that claim could have tremendous implications for the environmental impact of AI. Tech giants are rushing to build out massive AI data centers , with plans for some to use as much electricity as small cities.
“If we’ve demonstrated that these advanced AI capabilities don’t require such massive resource consumption, it will open up a little bit more breathing room for more sustainable infrastructure planning,” Singh says. “This can also incentivize these established AI labs today, like Open AI, Anthropic, Google Gemini, towards developing more efficient algorithms and techniques and move beyond sort of a brute force approach of simply adding more data and computing power onto these models.
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