{"id":"f-91677779fp1-da666121-ee56-51bb-8df1-4e8c9007c51e","title":"AI's Resource Footprint: Sam Altman on Energy and Water Debates","description":"This article delves into OpenAI CEO Sam Altman's perspective on the energy and water consumption of AI, addressing common misconceptions and offering a different viewpoint on resource efficiency. It explores his comparison of AI training to human development and his stance on data center water usage.","timestamp":1771833900,"category":"technology","headline":"AI's Resource Footprint: Sam Altman on Energy and Water Debates","modifiedHeadline":"Altman Debunks AI Energy Myths","subCategories":["scid_b7e786a9"],"region":"IN","bundleMetaData":{"bundleId":"c35cfc57-1bba-4539-a24c-695ea99ac023","bundleTitle":"Mastering AI","cardData":null},"iabCategoryId":"597","fcSummary":"sam altman, openai’s ceo, argues ai’s energy efficiency rivals or surpasses human development when considering lifetime energy consumption. he refuted claims about high query energy use (like 1.5 iphone charges) and dismissed myths about data center water usage, highlighting evolving cooling methods. altman anticipates rapid ai advancement toward agi and stresses the need for renewable energy to meet escalating ai demand.","summary":"OpenAI CEO Sam Altman refutes AI energy/water myths, comparing AI's resource use to human development. He urges a shift to renewable energy sources.","ctaUrl":"https://trends.glance.com/newz/Daily_Digest/IN/en/feedpost-specials/f-91677779fp1-da666121-ee56-51bb-8df1-4e8c9007c51e","sourceUrl":"https://trends.glance.com/newz/Daily_Digest/IN/en/feedpost-specials/f-91677779fp1-da666121-ee56-51bb-8df1-4e8c9007c51e","bannerImage":"https://g-mob.glance-cdn.com/public/fc/image/qAugrFXZlbh0.webp","content":"

\n Explore Sam Altman's insights on AI's resource demands. Discover his thoughts on energy efficiency comparisons and debunked water usage myths for data centers.\n

Energy Efficiency Debate

Sam Altman, the CEO of OpenAI, recently ignited a significant online discussion regarding the substantial energy resources required for artificial intelligence,

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particularly in the context of training and operating large language models like ChatGPT. During an event at Express Adda, Altman proposed a novel comparison for AI energy efficiency: juxtaposing the energy cost of a single AI query with the total energy a human has consumed throughout their lifetime to reach a comparable level of understanding and response capability. He argued that many existing discussions unfairly focus solely on the intensive energy needed for initial AI model training, without considering the cumulative energy investment in human development. Altman elaborated by stating that training a human involves approximately 20 years of life and all the sustenance consumed during that period, in addition to the evolutionary advancements of billions of humans over millennia. From his perspective, when measuring the energy cost for a trained AI to answer a query against a human’s equivalent response, AI has likely already achieved a comparable, if not superior, level of energy efficiency. This viewpoint challenges the common narrative that AI is inherently more resource-intensive per task than humans.

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Query Energy Claims

Altman specifically addressed a widely circulated claim, brought up by Anant Goenka of The Indian Express Group, suggesting that a single ChatGPT query consumes the equivalent of 1.5 iPhone battery charges. He firmly refuted this assertion, stating that the actual energy consumption is significantly lower. Furthermore, Altman touched upon the rapid advancement towards Artificial General Intelligence (AGI), a theoretical stage where AI can perform any intellectual task a human can with superior speed and precision. He indicated that AGI appears to be closer than many anticipate, and given the potential for a swift \"takeoff,\" artificial superintelligence might not be far behind. This accelerated development trajectory underscores the growing importance of understanding and managing the resource demands of AI infrastructure, which includes the vast network of data centers that power these advanced systems. The increasing scale of AI deployment has intensified scrutiny over these facilities, especially concerning their considerable energy needs and their potential impact on electricity prices.

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Data Center Water Myths

Addressing concerns about the water footprint of data centers, Sam Altman dismissed claims regarding the significant water consumption associated with cooling AI hardware as 'totally fake.' He clarified that the methods of cooling data centers have evolved, moving away from older evaporative cooling techniques that did use substantial amounts of water. Altman strongly refuted online assertions, such as those claiming that each ChatGPT query uses 17 gallons of water, labeling them as baseless and disconnected from reality. While he downplayed the water usage aspect, Altman reiterated his concern about the overall energy consumption of AI. He emphasized that the collective demand for AI services is escalating globally, necessitating a rapid transition towards renewable energy sources like nuclear, wind, and solar power to meet these growing energy needs sustainably. He also shared his skepticism about space-based data centers, citing prohibitive launch costs and the practical difficulties of maintaining equipment in orbit as reasons why they are unlikely to be viable at scale within the current decade, especially when contrasted with massive terrestrial facilities.

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AI's Resource Footprint: Sam Altman on Energy and Water Debates

SUMMARY