AnalysisOpinion / analysisHardware & Compute1 source · Oct 15, 2026

Hardware is how corporations limit the advancement of OS - what is the solution?

Open source is fantastic, the freedom and all that... but we rely on proprietary hardware, and consumer hardware is becoming too expensive due to production constraints, the fact that companies are diverting funds to DC and hyperscalers, and AI farms are buying consumer GPUs in bulk.

Proof1 community thread

Key points

  • Unfortunately, running increasingly large models will be a privilege reserved for a select group of people, and as hardware becomes obsolete/dies, that number will decrease.
  • Corporations can release revolutionary open-source models while simultaneously doubling or tripling the size of their proprietary models, driving up the purchase of even more memory and silicon production capacity, and all we can do is watch in disbelief.
  • Androids are going to require even more memory, cars, and so on...
  • Unless a revolutionary memory technology with much better bit-per-area density on silicon becomes available and is ready for mass production, or regulators remember that antitrust laws are meant to protect people step in, I don't see a solution.

Sources (1)

  • [1]Hardware is how corporations limit the advancement of OS - what is the solution?
    r/StableDiffusion (top, day) · Oct 15, 10:05 AM
    Open source is fantastic, the freedom and all that... but we rely on proprietary hardware, and consumer hardware is becoming too expensive due to production constraints, the fact that companies are diverting funds to DC and hyperscalers, and AI farms are buying consumer GPUs in bulk.
    Unfortunately, running increasingly large models will be a privilege reserved for a select group of people, and as hardware becomes obsolete/dies, that number will decrease.

Extractive summary: sentences quoted from the sources.

Before this

  1. Oct 15, 2026tencent/Hy-Memory-30B-A3B
  2. Oct 15, 2026I didn't do it, I did something else that might be even better
  3. Oct 14, 2026GPT-Image-style photo editing on your own GPU (12 GB+): I built a zero-setup app for Qwen-Image 2.1 on stable-diffusion.cpp
  4. Oct 14, 2026Event2Vec: additive event embeddings where a linear score on a history decomposes exactly into per-event terms [P]
  5. Oct 14, 2026mistralai/Timestral-209M
  6. Oct 14, 2026Localized Neural learning vs backpropagation [D]

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