Not to mention all the other ways they can screw you:

- Middle of the day, servers busy? Swap to Sonnet while pretending it's still Opus. Many people won't notice, and nobody can prove anything if they suspect.

- Middle of the night, server load is light? Put it into extra thinky mode so it burns more tokens to ramp up the bills. Flip the switch where it gets really pedantic about writing lots of extra test cases and verifying against documentation.

- Demand increases, but don't feel like running more hardware? Switch to low bit quants, but have a monitor model swap back to quality if it can tell you're running a benchmark.

Assuming model capability plateaus (I think it will), token providers will be in a race to the bottom to maximize profits at the expense of quality that's very difficult to measure.

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mister_mort 23 minutes ago | parent | next [-]

It all sounds like having to rely on a dodgy housing contractor that wants to steal from you, take shortcuts AND choose the gold-plated options from their supplier friends, and will start doing this the minute you are not on site supervising. You don't do it yourself (because the contractor is faster and stronger than you in many ways) but you can't leave, so you're stuck on the worksite just watching them.

	▲	xscott 4 minutes ago \| parent [-]
		It's worse though, because you can't really watch them at all. It's very difficult to get quantitative numbers for quality. Even within the same model family, same tokenizer, and complete control over the weights and logits, perplexity and KL-divergence isn't really what you want. Now put it behind an HTTP endpoint, and it's just opaque. I've seen local models recognize when the task I'm asking them for is likely to be an artificial benchmark. And any smart company is going to use lightweight models to monitor your sessions. If their sentiment analysis suspects you're close to cancelling, they'll up the knob for a few days until you calm down. Or worse, their accounting tells them that you're getting too much value from your fixed price subscription, so they turn the knob down to encourage you to cancel. In the short term, the "frontier" models are too good to ignore. But if (when?) that plateaus, I don't see how anyone could trust a non-local model. When you pay an ISP to serve your web site, you can tell if they over-compress your images to save storage and bandwidth. With LLMs, it's just JSON with more errors and pointing to the fine print that models are not deterministic.

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wolttam 11 minutes ago | parent | prev | next [-]

What areas do you think model capability will plateau in, and why?

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dannyw an hour ago | parent | prev | next [-]

These kind of tricks will completely break API customers (although selectively applying it to consumer subs is probably beyond likely at this point).

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htrp an hour ago | parent | prev [-]

Ugh... didn't think about extra thinky mode in the middle of the night.

So many ways for enshittification here.