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Fable 5 – Median thinking declined in August

428 points · 293 comments · espeed

  1. talon8635 · · focus · HN ↗
    Could there be a benefit to releasing a new model, slowly dumbing it down over a couple months, then releasing a new model that’s marginally if at all better than the original to create a perceived improvement when in reality there isn’t really one?

    For an industry that’s stagnant in progress yet relies on new frequent releases to survive (non-progress being an existential risk), this could make sense.

    I have no idea if that’s what’s happened, I completely pulled it out of my butt. And I have no idea is the actual frontier is stagnating.

    1. AmazingTurtle · · focus · HN ↗
      > Could there be a benefit to releasing a new model, slowly dumbing it down over a couple months, then releasing a new model that’s marginally if at all better than the original to create a perceived improvement when in reality there isn’t really one?

      Exactly what I am saying for months now. And it's exactly the reason why I am shifting to open weight models now. Just bought myself a 2x DGX Spark Cluster. Will run Qwen3.8 Flash Next on it, maybe Qwen4 when it comes out.

      Not only do I have full control over quantization and inference, but also will I experience a constant level of quality. It won't be frontier. But it will be stable, and that's enough reason for me to switch. Also I will likely save some money on subscriptions.

      1. zeroonetwothree · · focus · HN ↗
        Last time I estimated it was like 30 years to pay back. I doubt the hardware will even last that long.
        1. mike_d · · focus · HN ↗
          I have 2 x ChatGPT Pro 20x, Claude Max 20x, and Kimi Vivace. It's about ~12 months payback for two units and the cable.

          The problem is they can't fit any frontier level open models.

          1. tiagod · · focus · HN ↗
            I rent two cars, a bus, a small aeroplane and an excavator. At that rate, if I buy this bicycle it will be paid back in an hour!
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