[biddit]

Strongly disagree with the thesis.

Everything points to commoditization of models. Open/distilled models lag behind frontier only by 6-12 months.

Regulatory capture is the only thing I’m scared of with regards to tooling options and cost.

[supern0va]

>Everything points to commoditization of models. Open/distilled models lag behind frontier only by 6-12 months.

Yes, but every high performing open weights model coming out of China has (supposedly) been caught distilling frontier models.

It seems like a lot of people are making assumptions about the state of the open weights ecosystem based on information that may not be accurate. And if the big labs are able to reliably block distillation, we could see divergence between the two groups in terms of performance.

[dragonwriter]

> And if the big labs are able to reliably block distillation,

The big labs will not be able to reliably block distillation without further inhibiting general use of the models, which itself will help tip the balance away from commercial models.

[reenorap]

No, you're wrong. It won't tip it away from commercial models. Trying to run open weight modesl to do inference is something 99% of people around the world can't do because it's expensive and technically challenging and the results are poor compared to the main companies. If they get rid of free usage people will simply pay for it.

[dragonwriter]

> Trying to run open weight modesl to do inference is something 99% of people around the world can't do because it's expensive and technically challenging and the results are poor compared to the main companies.

Just because a model is open doesn't mean that there aren't services that will run it for you (and which won't share any limits that the commercial model vendors impose to fight distillation because neither the host not the model creator cares if you are using the service to distill the model.)

Many users of, particularly the larger, open models now are using such services, not running them using their own local or cloud compute.

[raincole]

The article is obviously bad (I quitted reading after the second paragraph) but one side effect of AI training is the increasing cost of hardware. We have commoditization of models... while reversing commoditization of hardware.