Friday, September 4, 2026
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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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  • Data centers might steer toward hardware that sacrifices some performance for less memory as adaptation to shortage

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

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

    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
  • 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
What we know · the intelligence behind this page
Live from the substrate
What we're seeing
AI Funding Surge: Capital Floods Fintech, Foundation Models, and Autonomous Systems
A concentrated burst of AI-linked funding on 2026-08-28 pushed well over $1.5B into companies spanning fraud/identity fintech (Socure, which also acquired Fravity), foundation models (Stability AI), AI agents and enterprise tooling (Instinct, Generalist AI, Emerald AI, Owner), and AI-adjacent autonomous/aerospace ventures (Gatik, Regent Craft). The breadth and simultaneity of these rounds signal that investor appetite for AI is not concentrated in a single vertical but is broadening into applied and infrastructure-adjacent domains, with consolidation (Socure-Fravity) beginning alongside fresh capital formation.
Our read on the data ›
Signals we're tracking
EPKINLY Regulatory-Clinical Success Cascade
High probability of expanded label indications, additional combination approvals, and competitive positioning strength in follicular lymphoma market. Predicts positive commercial uptake and potential accelerated review for related indications.
Patterns we're watching ›
Where sources disagree
Morgan Stanley & Co. LLC
The same metric (eps) for the same entity (Morgan Stanley & Co. LLC) reported for the identical fiscal period (Q1 2026) and observation date (2026-03-31) has two conflicting values: 3.43 USD_per_share vs 3.08 USD. This is not a temporal change — both observations claim to measure the same point in time. The ~10% discrepancy (0.35 USD difference) is material for a financial metric.
We flag conflicts openly ›
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