DeepSeek's Liang Wenfeng Breaks His Silence
www.fredgao.com
In a rare four-hour talk, the reclusive founder reveals an almost Daoist philosophy of AI—AGI as a tide no company can own, he argues China's only real gap with America is compute.
  • 712@discuss.tchncs.deEnglish
    13 hours

    I think it’s important to note that these models are open-WEIGHT and not open-SOURCE. Open-source would mean we could explore the training data itself. Open-weight models are great, but please let’s not call them open-source.

      • Gsus4@mander.xyzEnglish
        51 minutes

        “See, you can see the code in binary, it is open source” :D

      • 712@discuss.tchncs.deEnglish
        2 hours

        Just because a law mislabels something doesn’t mean we need/should follow that.

    • phutatorius@lemmy.zipEnglish
      10 hours

      Yeah, it’s like an open-source distro that won’t work without an accompanying opaque binary blob.

        • motruck@lemmy.zipEnglish
          2 hours

          It is more a question of what hardware is like that and if you look up firmware blobs for Linux you’ll find a lot, starting with graphic cards.

  • eicker@lemmy.worldEnglish
    21 hours

    That’s either incredibly idealistic or a very smart strategy: Open models grow ecosystems faster than walled gardens, but compute still decides who gets to play at the highest level. If AGI really becomes shared infrastructure, the moat shifts from models to chips, data and execution.

    • TheFogan@programming.devEnglish
      20 hours

      A bit of both though. In house models don’t need the power and process of a small city, they need the power to power what their business needs. Also it would seem to me that has a huge advantage on the whole as a model would be more efficient, if it’s focused on the companies needs rather than being a jack of all trades, from poetry to law to code. Cut out the being everything to everyone and you can do far more with far less hardware.

      • eicker@lemmy.worldEnglish
        20 hours

        This. The frontier race is about building the smartest generalist, but most companies don’t need that. They need a specialist tuned to their workflows. Narrower scope means smaller models, lower costs, faster inference and often better results. General models become the foundation, not the finished product. It’s still all to play for! 💪😎✌️

      • okwhateverdude@lemmy.worldEnglish
        18 hours

        Exactly. At work, we’re already looking at getting our own compute for an open model for some automatons we built. Google’s models are alright, but they are retiring them too fast. So we want to get off that treadmill. Plus a local model gives us opportunities to experiment with LoRAs and techniques like what cactus hybrid did with a small head predicting certainty (https://news.ycombinator.com/item?id=49010782). Plus, the big players are removing sampling options thinking they know what’s best when it is obvious they don’t.

    • CosmoNova@lemmy.worldEnglish
      17 hours

      Remember when OpenAI seemed idealistic? To most people, anyway. This is the same. DeepSeek has already been caught lying to inflate hype. They‘re grifters like all the other AI companies.

      • eicker@lemmy.worldEnglish
        17 hours

        OpenAI is a good reminder that mission statements and business incentives don’t always stay aligned. That said, I’d judge DeepSeek less by the rhetoric and more by what they actually release. Hype is cheap: open weights, reproducible results and useful tools are much harder to fake.

  • eicker@lemmy.worldEnglish
    12 hours

    That is indeed an important distinction. However, I expect that it will be a very long time before we see any competitive open-source AI.