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AI Is Insatiable

View original at spectrum.ieee.org
IEEE Spectrum - Technical Title: AI Is Insatiable Date: 2026-04-06 14:22 Source: https://spectrum.ieee.org/high-bandwidth-memory-shortage <img src="https://spectrum.ieee.org/media-library/robot-hand-catching-falling-computer-chips-from-an-open-snack-bag-in-pop-art-style.png?id=65425799&width=1200&height=800&coordinates…
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O que extraímos desta fonte

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  • Generative AI queries consumed 15 terawatt-hours in 2025 and are projected to consume 347 TWh by 2030

    60% confidence
  • AI electricity consumption could account for up to 12 percent of all U.S. power by 2028

    60% confidence
  • If any of the big three HBM companies—Micron, Samsung, and SK Hynix—say that they are adjusting the schedule of the arrival of new production, that'd be an important signal

    60% confidence
  • Constraints like shortages can lead to interesting technology solutions

    60% confidence
  • If any of the big three HBM companies—Micron, Samsung, and SK Hynix—say that they are adjusting the schedule of the arrival of new production, that'd be an important signal

    60% confidence
  • Makers of AI processors, notably Nvidia and AMD, are demanding more and more memory for each of their chips, driven by needs of firms like Google, Microsoft, OpenAI, and Anthropic

    60% confidence
  • Water consumption for cooling AI data centers is predicted to double or even quadruple by 2028 compared to 2023

    60% confidence
  • Generative AI queries consumed 15 terawatt-hours in 2025 and are projected to consume 347 TWh by 2030

    60% confidence
  • AI electricity consumption could account for up to 12 percent of all U.S. power by 2028

    60% confidence
  • AI hyperscalers' ravenous appetite for memory is causing current DRAM shortage, particularly for high bandwidth memory (HBM), which is a major constraint on the speed at which large language models run

    60% confidence
  • Data centers might steer toward hardware that sacrifices some performance for less memory, and startups might pivot toward creative redesigns that use less memory as constraints lead to interesting technology solutions

    60% confidence
  • Startups developing all sorts of products might pivot toward creative redesigns that use less memory

    60% confidence
  • Water consumption for cooling AI data centers is predicted to double or even quadruple by 2028 compared to 2023

    60% confidence
  • Data centers might steer toward hardware that sacrifices some performance for less memory as adaptation to shortage

    60% confidence
  • AI hyperscalers' ravenous appetite for memory is a major constraint on the speed at which large language models run

    60% confidence
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AI Boom Hits a Fork: Slowdown Calls Clash with Capex Confidence as Markets Get Nervous
Dario Amodei's repeated calls for a global slowdown in frontier AI development, echoed by Microsoft's new humanist AI code of conduct and FTC antitrust caution, are being publicly rejected by Nvidia and Meta leadership even as hyperscaler spending draws fresh skeptical scrutiny (Wachter's analysis, Burry-style overbuilding worries) and weak guidance from Adobe and a post-slowdown-comment selloff in GE Vernova signal investor jitters. Meanwhile wealth and security effects of the AI race keep compounding — Zhang Yiming's fortune surging on AI-driven ByteDance value, a Chinese hacking firm weaponizing AI against stolen government secrets, and low-quality AI-generated products (an AI sitcom, a spam-flooding agent platform) fueling backlash even as adoption races ahead.
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