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AI and the Environment

2025/3/30
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Consider This from NPR
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Benjamin Lee
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David Craig
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Jeff Brumfield
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Kevin Miller
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Sasha Luccioni
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Sasha Luciani
Topics
Sasha Luciani: 我最初对人工智能领域对环境的影响感到焦虑，这与我的价值观相冲突。我意识到自己可以用人工智能专业知识为环境保护做出贡献，因此我辞去了工作，投身于人工智能可持续发展事业。我认为我们需要一个行业标准来评估人工智能模型的能源效率，但目前科技公司对透明度持谨慎态度。 Benjamin Lee: 生成式人工智能的兴起使得数据中心运营商实现净零排放目标变得更加困难。混合专家模型可以通过使用多个较小的模型来降低能耗，这是提高效率的一种方法。 Jeff Brumfield: 人工智能行业和核能行业的工程文化差异巨大，这给合作带来挑战。核能虽然是低碳能源，但其建设周期长，成本高，且存在安全风险。 David Craig: 我们只有一个地球，应该关注环境保护。液冷技术可以提高数据中心的能效，延长设备寿命，减少能源浪费。但液冷技术目前成本较高，难以大规模应用。 Kevin Miller: 对数据中心和云计算的需求正在增长，这是由数字化经济的整体发展趋势驱动的。我们需要找到平衡点，在满足社会需求的同时，最大限度地减少环境影响。

Deep Dive

Chapters
The rapid growth of AI has raised significant environmental concerns, particularly regarding energy and water consumption. Data centers, crucial for AI operations, are projected to consume a substantial portion of the nation's electricity by 2028. This has led to a growing movement advocating for more sustainable AI practices.
  • AI boom caused a surge in energy consumption
  • Data centers could consume up to 12% of the nation's electricity by 2028
  • AI is leading to increased water consumption
  • Big tech companies have climate goals but lack regulations

Shownotes Transcript

The AI boom has caused a huge surge in energy consumption, so how is the tech industry thinking about its environmental footprint as it invests in new AI models? Emily Kwong), host and reporter for NPR's Short Wave podcast, finds out what solutions are being considered that might meet both consumer demand and address climate concerns.For sponsor-free episodes of Consider This, sign up for Consider This+ via Apple Podcasts or at plus.npr.org).Email us at [email protected]).Learn more about sponsor message choices: podcastchoices.com/adchoices)NPR Privacy Policy)