Themata.AI
Themata.AI

Popular tags:

#developer-tools#ai-agents#discussion#trending#llms#claude#ai-ethics#code-generation#ai-safety#openai

AI is changing the world. Don't stay behind. Clear summaries, community insight, delivered without the noise. Subscribe to never miss a beat.

© 2026 Themata.AI • All Rights Reserved

Archive

|

Topics

|

Privacy

|

Cookies

|

Contact
llmshuaweiai-trainingnorwegian-language

Norway's 2 petabytes of Huawei flash storage and LLM training

Norway’s 2 petabytes of Huawei flash storage and LLM training

blocksandfiles.com

May 25, 2026

4 min read

🔥🔥🔥🔥🔥

63/100

Summary

Norway's National Library is developing a large language model (LLM) for the Norwegian language using 2 petabytes of Huawei OceanStor Dorado flash storage. Marius Husnes, Head of IT Platform, stated that no commercial LLM provider is currently developing a local Norwegian language model.

Key Takeaways

  • Norway's National Library is developing a sovereign large language model (LLM) for the Norwegian language using 2 petabytes of Huawei OceanStor Dorado flash storage.
  • The library has the largest digital collection of Norwegian cultural heritage, which includes books, newspapers, and web content, and is legally mandated to preserve this data.
  • The LLM training process involves overcoming challenges related to data quality, cleaning, and the integration of different storage systems for efficient data pipeline management.
  • The library is creating its own evaluation tools for the LLM due to the lack of standard metrics for assessing a sovereign Norwegian language model.
Read original article

Community Sentiment

Mixed

Positives

  • The national library's initiative to train a sovereign LLM could enhance the representation of Norwegian culture and language in AI, addressing a significant gap.
  • The Olivia system's powerful hardware setup, with 448 GPUs, indicates a serious investment in advancing AI capabilities, even if concerns about its utility remain.
  • The existing user interface of the national library is praised for its functionality, suggesting a strong foundation for integrating AI to improve text searchability.

Concerns

  • Training a sovereign LLM with limited hardware raises doubts about its effectiveness and usefulness, suggesting a potential waste of resources.
  • Concerns about the lack of a clear application for the LLM indicate skepticism about its impact on the Norwegian language and culture.
  • The notion that a locally trained LLM might be inferior to existing models raises questions about the rationale behind this initiative.

Related Articles

Exploring Claude/GPT Knowledge Cutoffs

Exploring Claude/GPT Knowledge Cutoffs and Pre-Training Timelines

Aug 10, 2026

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

MegaTrain: Full Precision Training of 100B+ Parameter LLMs on a Single GPU

Apr 8, 2026

Open-Sourcing Sarvam 30B and 105B | Sarvam AI

Sarvam 105B, the first competitive Indian open source LLM

Mar 7, 2026

You could have invented transformers from memory

You could have invented transformers from memory

Oct 16, 2026

GitHub - cobanov/PS5LM: llama.cpp on a jailbroken PS5: run any GGUF model natively on the console, starting with Qwen 3.8

Llama.cpp on a jailbroken PS5: run any GGUF model natively on the console

Oct 16, 2026