Comment on Nvidia loses $500 bn in value as Chinese AI firm jolts tech shares

• Womble@lemmy.world ⁨3⁩ ⁨days⁩ ago

  Wow ok, you really dont know what you’re talking about huh?

  No I dont have thousands of almost top of the line graphics cards to retain an LLM from scratch, nor the millions of dollars to pay for electricity.

  I’m sure someone will and I’m glad this has been open sourced, its a great boon. But that’s still no excuse to sweep under the rug blatant censorship of topics the CCP dont want to be talked about.

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  • UnderpantsWeevil@lemmy.world ⁨3⁩ ⁨days⁩ ago

    No I dont have thousands of almost top of the line graphics cards to retain an LLM from scratch

    Fortunately, you don’t need thousands of top of the line cards to train the DeepSeek model. That’s the innovation people are excited about. The model improves on the original LLM design to reduce time to train and time to retrieve information.

    Contrary to common belief, an LLM isn’t just a fancy Wikipedia. Its a schema for building out a graph of individual pieces of data, attached to a translation tool that turns human-language inputs into graph-search parameters. If you put facts about Tianamen Square in 1989 into the model, you’ll get them back as results through the front-end.

    You don’t need to be scared of technology just because the team that introduced the original training data didn’t configure this piece of open-source software the way you like it.

    that’s still no excuse to sweep under the rug blatant censorship of topics the CCP dont want to be talked about.

    Wow ok, you really dont know what you’re talking about huh?

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    • Womble@lemmy.world ⁨3⁩ ⁨days⁩ ago

      www.analyticsvidhya.com/blog/2024/…/deepseek-v3/

      Huh I guess 6 million USD is not millions eh? The innovation is it’s comparatively cheap to train, compared to the billions OpenAI et al are spending. (and that is with acquiring thousands of H800s not included in the cost)

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      • UnderpantsWeevil@lemmy.world ⁨3⁩ ⁨days⁩ ago

        The innovation is it’s comparatively cheap to train, compared to the billions

        Smaller builds with less comprehensive datasets take less time and money. Again, this doesn’t have to be encyclopedic. You can train your model entirely on a small sample of historical events in and around Beijing in 1989 if you are exclusively fixated on getting results back about Tienanmen Square.

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    • MrTolkinghoen@lemmy.zip ⁨2⁩ ⁨days⁩ ago

      Idk why you’re getting downvoted. This right here.

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      • UnderpantsWeevil@lemmy.world ⁨2⁩ ⁨days⁩ ago

        Just another normal day in the Lemmyverse

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      • JasSmith@sh.itjust.works ⁨2⁩ ⁨days⁩ ago

        Because the parent comment by Womble is about using the Chinese hosted DeepSeek app, not hosting the model themselves. The user above who responded either didn’t read the original comment carefully enough, or provided a very snarky response. Neither is particularly endearing.

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