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points by derefr 3 days ago | 0 comments

“Origin” isn’t part of the Pareto frontier because it’s not a quantitative dimension.

(You could say that “ability to be trusted by US government/military users” is quantifiable, but I would argue that by that metric, this model falls behind non-US-originated open-weight models that have more eyes on them!)

[–] Routine8502 3 days ago

Discrete dimensions can exist in Pareto considerations. Not that I'm too fond of this game, but given that "Origin" is definitely part of the calculus of model deployment, it makes sense to consider it in a Pareto calculation.

[–] getcrunk 3 days ago

Ahh I run into this issue all the time with ai when applying any sort of dimensional reasoning abstractly it always implicits continuous

[–] bastawhiz 3 days ago

It's just a different pareto frontier because you're filtering out items that don't fit your criteria. "Model was made by Anthropic" would be an equivalent dimension. You would never plot this, you're just reducing the subset of models you're comparing.

By that logic, any model is a frontier model. My GPT-2 clone is a frontier model when you compare it against models that were trained on my homelab.

[–] kennywinker 3 days ago

Which you're welcome to do and then people are welcome to disagree that is an important frontier to consider.

[–] bastawhiz 2 days ago

That's literally the point. It's a different frontier. If you say "frontier model" and don't specify which frontier you're either being deceptive or naive.

[–] kennywinker 2 days ago

All marketing relies on some degree of deception.

[–] jhgb 2 days ago

But Pareto optimality only considers ordinal information. Surely there's no reason why binary choices can't be dimensions in it.