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This happened after Silo trained an LLM on the AMD-powered LUMI supercomputer.

petesergeant 2y ago
Seems like an excellent exit strategy in hindsight. Spend a gazillion dollars of investor money on AMD hardware, get bought back by AMD because you worked out how to use that hardware
- jacobgorm 2y ago
  Except the EU paid for the hardware https://eurohpc-ju.europa.eu/supercomputers/our-supercomputers_en https://eurohpc-ju.europa.eu/supercomputers/our-supercompute...
  - Pandabob 2y ago
    Came here to point this out. Silo never had to invest huge amounts on GPUs. A shrewd move by the founders.
    - rubatuga 2y ago
      There is debate about public investment into private ventures, but in this case it may provide long term benefits to Finland
  - petesergeant 2y ago
    Even better!
  - baobabKoodaa 2y ago
    Where in that source does it claim that Silo didn't have to pay to use the hardware?
    - jacobgorm 2y ago
      I don’t think it is possible to pay for access to LUMI. I know my company has been in talks about getting free access as it sits under utilized most of the time. These supercomputers are mostly vanity projects for EU politicians, there is no commercial use case.
      - Certhas 2y ago
        I don't know about Lumi specifically, but top tier scientific supercomputers should typically have 80+% utilisation rate: https://doku.lrz.de/usage-statistics-for-supermuc-ng-11483092.html https://doku.lrz.de/usage-statistics-for-supermuc-ng-1148309... Smaller machines will tend lower from what i have seen. If you give a large enough pool of scientists access to significant compute resources, they will generally figure out how to saturate them. Also, scientific teams often can't pay top software engineers. Lots of hardware is a way to compensate for inefficient code. If Lumi is underutilized to such an extent someone is funking up. There is of course no commercial use case for these computers. That's not the point of these machines.
- stefan_ 2y ago
  An inverse Nadella, wherein you buy a chunk of OpenAI and they turn around and buy a bunch of Azure time (then give it away to people on ChatGPT cuz ain't no one about making money in that business)
kakoni 2y ago
Well actually it was Silo + Turku University's TurkuNLP group [1] [1] https://www.amd.com/content/dam/amd/en/documents/resources/case-studies/building-llms-with-the-power-of-amd-instinct-gpus-and-amd-epyc-cpus.pdf https://www.amd.com/content/dam/amd/en/documents/resources/c...

Seems like an excellent exit strategy in hindsight. Spend a gazillion dollars of investor money on AMD hardware, get bought back by AMD because you worked out how to use that hardware

jacobgorm 2y ago
Except the EU paid for the hardware https://eurohpc-ju.europa.eu/supercomputers/our-supercomputers_en https://eurohpc-ju.europa.eu/supercomputers/our-supercompute...
- Pandabob 2y ago
  Came here to point this out. Silo never had to invest huge amounts on GPUs. A shrewd move by the founders.
  - rubatuga 2y ago
    There is debate about public investment into private ventures, but in this case it may provide long term benefits to Finland
- petesergeant 2y ago
  Even better!
- baobabKoodaa 2y ago
  Where in that source does it claim that Silo didn't have to pay to use the hardware?
  - jacobgorm 2y ago
    I don’t think it is possible to pay for access to LUMI. I know my company has been in talks about getting free access as it sits under utilized most of the time. These supercomputers are mostly vanity projects for EU politicians, there is no commercial use case.
    - Certhas 2y ago
      I don't know about Lumi specifically, but top tier scientific supercomputers should typically have 80+% utilisation rate: https://doku.lrz.de/usage-statistics-for-supermuc-ng-11483092.html https://doku.lrz.de/usage-statistics-for-supermuc-ng-1148309... Smaller machines will tend lower from what i have seen. If you give a large enough pool of scientists access to significant compute resources, they will generally figure out how to saturate them. Also, scientific teams often can't pay top software engineers. Lots of hardware is a way to compensate for inefficient code. If Lumi is underutilized to such an extent someone is funking up. There is of course no commercial use case for these computers. That's not the point of these machines.
stefan_ 2y ago
An inverse Nadella, wherein you buy a chunk of OpenAI and they turn around and buy a bunch of Azure time (then give it away to people on ChatGPT cuz ain't no one about making money in that business)

kakoni 2y ago

Well actually it was Silo + Turku University's TurkuNLP group [1] [1] https://www.amd.com/content/dam/amd/en/documents/resources/case-studies/building-llms-with-the-power-of-amd-instinct-gpus-and-amd-epyc-cpus.pdf https://www.amd.com/content/dam/amd/en/documents/resources/c...