[draygonia]

So the choice becomes to either 1) Use the AI tools as much as you can before they increase prices/tighten usage or 2) Stop using them so you won't be compelled to pay more later when the price inevitably goes up/your regular plan gets downgraded?

I would think companies would set the usage low and increase it with capacity rather than subsidizing the power users and going into the red. Maybe my strategy wouldn't be aggressive enough to capture the market, which I'm sure the major AI companies are trying to do.

[j45]

There's another option too:

In the short term, resource management can affect prices and allocation, especially when it's being figured out on the go.

A permanent position that technology is fixed assumes the technology will not improve.

This means, the software won't get more efficient with it's use of hardware, or the hardware won't become more power efficient, etc. Open/self-hosted models are a real world example where efficiency is happening.

Thinking technology won't become more efficient is like imagining that cell phones will still run with the poor battery life of the 1990's.

[UncleOxidant]

or 3) start running local models that are competent for most tasks now like Qwen3.6-27B and only use frontier models when the local model gets stuck.

[Someone1234]

Many of us would love to, and the models are there, but we're constrained by heavily inflated hardware costs.

If big AI does crash out, it would be an absolute gold-mine for local LLM. Cheap, efficient, Nvidia GPUs, and RAM that can run the best local models already available, will be a real boon.

PS - And as great as Qwen3.6-27B is, how large you can scale it (i.e. how big of a context/project) is mostly hardware constrained.

[spwa4]

Or 3) a company builds a token producing machine and uses open models that are competitive.