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submitted 3 days ago by schizoidman@lemmy.zip to c/europe@feddit.org
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[-] ranzispa@mander.xyz 2 points 2 days ago

Is Germany allocating a lot of money to LLM stuff? I see positively the increase in computing power available in the EU: consumption is there, just outsourced from other countries.

I do see positively European projects such as AI factories. Eventually they may not even be used for AI development, but a strong computing infrastructure accessible to researchers and small companies will definitely be useful for the development of European technology.

[-] Hirom@beehaw.org 1 points 2 days ago* (last edited 2 days ago)

LLMs require specialized processors, ie TPUs and ASICs. Using GPUs or CPUs would be even less efficients. AI datacenters layout and cooling are specifically designed to accomodate those specialized processors.

My understanding is that repurposing such datacenter for other kind of computing would be expensive. Doing this shortly after building them would mean loosing a signifiant portion of the initial investment. ie would require replacing processors, cooming, and redisigning the overall layout to optimize for another type of processing.

[-] ranzispa@mander.xyz 1 points 1 day ago

AI factories have CPUs and GPUs. Either way, TPUs can be used for other kinds of calculations as well. And definitely, given enough availability of TPUs, specialized software will be optimized to run on them.

But either way, no this is not the case. I know people who work with LLMs and they mostly use GPUs, even when they work on US computing clusters.

[-] Hirom@beehaw.org 1 points 1 day ago* (last edited 1 day ago)

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.

[-] ranzispa@mander.xyz 1 points 1 day ago

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.

[-] Hirom@beehaw.org 1 points 1 day ago* (last edited 1 day ago)

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

[-] ranzispa@mander.xyz 1 points 1 day ago

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.

[-] Hirom@beehaw.org 1 points 21 hours ago* (last edited 21 hours ago)

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.

this post was submitted on 25 Jul 2026
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