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.
> 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.
I assume you’ve calculated expected cost vs subscription.
How do the numbers pan out? Ack that it isn’t always juts about cost, so even if it is pricier to self/host it might still be better for you for other reasons.
reliability and self reliance is worth a lot to most. Heck, you could be the best in the world at what you do, but if you're unreliable you wont find stable employment. So, not having some amoral shady company errode model quality out from under you constantly is also worth a lot more than simple cost balancing calculations can capture.
I'm getting really sick of the constant rot and "magic breakthrough" cycle, so im going full local, at expense on paper but being able to trust something which I need to understand the reliability of is priceless.
I like predictable. I'll take slightly less capable over unreliably capable, since with reliable i can calibrate my expectations and learn what aspects of my workflows to entrust and trust it will work. You simply cannot do that with models you don't control and in my experience they will all errode after the initual marketing wave passes, likely you eventually get fed heavily quantized versions and are expected to accept degraded service when what convinced you to pay was a far superior product. No such issues with local.
Picked a local model I was happy with, then figured out what is required to get it running at acceptable tok/s, where I settled on a amd "ai" variant NUC with 96gb vram avaliable to gpu. This arrived recently, and qwen3.8 27b runs fast enough for me on that, with full context, and plenty of paralell streams. That said i'm in a fortunate position, so also got an rtx6000 to continue rlhf based finetunes in data I amass over the years from myself and friendly highly knowledgable/skilled friends, since that is in essence what makes fronteir labs models better, so i figure, why shouldnt we benefit from our expertise and input direcerly, instead of having it sold back to me by some amoral company? If that eventuates in a model that genuinly beats current, obviously we'd give back to the community by releasing that.
talon8635 · · focus · HN ↗
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.
AmazingTurtle · · focus · HN ↗
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.
andsoitis · · focus · HN ↗
How do the numbers pan out? Ack that it isn’t always juts about cost, so even if it is pricier to self/host it might still be better for you for other reasons.
Grimblewald · · focus · HN ↗
I'm getting really sick of the constant rot and "magic breakthrough" cycle, so im going full local, at expense on paper but being able to trust something which I need to understand the reliability of is priceless.
I like predictable. I'll take slightly less capable over unreliably capable, since with reliable i can calibrate my expectations and learn what aspects of my workflows to entrust and trust it will work. You simply cannot do that with models you don't control and in my experience they will all errode after the initual marketing wave passes, likely you eventually get fed heavily quantized versions and are expected to accept degraded service when what convinced you to pay was a far superior product. No such issues with local.
andsoitis · · focus · HN ↗
Grimblewald · · focus · HN ↗