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Fair point, GPUs are often used too, and have other uses for HPC workloads.
There is still a major misallocations of resources for AI. This infrastructure is badly needed by big tech for their AI growth plans. No one else need this much.
There’s no good reasons to build at that scale and so fast, for any reason.
There’s a need to lower overall energy and resources usage, and improve efficiency. Building many large datacenters for LLMs go in the wrong direction.
I work in research and I have dire need of GPUs. I do not work on LLMs.
Recently we got granted access to 500 GPUs for 2 months; all of them are spinning - and this is the work of 5 researchers. A normal research HPC institute normally has some 100-200 GPUs. In this sector there are startups which need to execute simulator calculations.
Yes, GPU infrastructure is very much needed and lacking in Europe.
I’m all for GPUs and memory being available to research that benefit public good, within limit. And less of it being available to LLMs.
AI companies are swallowing a large part of memory and some chips production, meaning less availability and higher prices for everyone. This is part of the resources misallocation. https://www.cnbc.com/2026/01/10/micron-ai-memory-shortage-hbm-nvidia-samsung.html
This project is making computing power available to research and small companies.
https://digital-strategy.ec.europa.eu/en/policies/ai-factories
GPUs are now more widely available than ever before.
Interesting. Hopefully this provide resources to worthwhile research projects, not generative AI (research) projects.
Given the homepage emphasis on (generative) AI, it’s not very encouraging. But hopefully I’m wrong.