OpenAI’s Sam Altman expressed admiration for the new AI model developed by Chinese startup DeepSeek, calling it "impressive" due to its cost-efficiency.
In a social media post, Altman acknowledged the capabilities of DeepSeek’s R1 model, particularly noting how much it delivers at a fraction of the cost typically associated with similar AI projects.
DeepSeek’s R1, developed using around 2,000 Nvidia chips, challenges industry assumptions about the resources needed to train advanced AI models. It also has broader implications, affecting not only the AI development sector but also energy companies that depend on data centers for their operations.
Traditionally, AI growth has been accompanied by rising costs in computing and energy, as these sectors rely on large-scale data centers to power AI models. However, DeepSeek’s breakthrough in reducing the necessary energy and computing power is sparking interest and concerns, especially among energy companies.
On Monday, energy stocks, including Constellation Energy, saw significant declines as investors reassessed the potential impact of DeepSeek’s technology on future energy needs. Travis Miller from Morningstar noted that DeepSeek’s R1 model exemplifies how increased efficiency in computing could pose a threat to power providers.
Meanwhile, major tech companies like Google, Microsoft, and Amazon have heavily invested in expanding data center infrastructure, with a focus on energy sustainability through nuclear and renewable sources. However, energy demand for data centers is expected to rise significantly, as these facilities currently consume about 1% of global electricity.
Despite these efficiencies, experts like Andrew Lensen warn that improvements in technology often lead to greater demand—an effect known as Jevons paradox. Lensen also pointed out that DeepSeek's “chain-of-thought” model, while more energy-intensive, could see broader use due to cost reductions.
Altman’s praise for DeepSeek adds to the growing conversation on how advancements in AI could reshape both the technology and energy industries.
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