AI companies don't want you to waste tokens, they benefit when you use them efficiently because they can serve more users on the infra that's the main bottleneck for them. It's Jevons' paradox in action.
I don't think thats necessarily true, they aren't really capacity constrained in practice (they might be behind the scenes and adjust training on the fly, but thats speculation), so wasting tokens effectively helps utilize their (potentially idle) inference GPU's
>AI companies don't want you to waste tokens, they benefit when you use them efficiently because they can serve more users on the infra that's the main bottleneck for them.
No, the actual incentive is that people will eventually benchmark their models on bang-per-buck basis and models that chew through tokens are not going to be competitive. It's the same reason why the "Intel/AMD are intentionally sandbagging their CPUs so they can sell more CPUs" theory doesn't work.