[CGamesPlay]

The announcement elucidated this, and it's IMO worse than this. They don't downgrade to a cheaper model ([edit] for certain classes of offense they suspect you of). They sabotage the model's outputs in other, undisclosed, ways (specifically, "prompt modification, steering vectors, or parameter-efficient fine-tuning"). So, for example, they might load in a steering vector that just forgets the API to PyTorch. But it isn't just "we redirected you to a cheaper model!"

[buildbot]

It honestly explains so many issues I have been having, as I used it primarily for ML research (on my personal account, doing things not related to my job I should note). It would literally typo package names and spend huge amounts of time failing to setup simple environments…then do stupid things like set the learning rate to 1e-7, and use the eval set as training data.

[notrealyme123]

It burned through all of my tokens in a very short time. I wonder if it their ML mitigations leads to model into deadlocks.

[peyton]

That’s insane. I hope they fix it.

[baq]

Nothing to fix. This is working as designed.

Using codex for this use case is the fix.

[sterlind]

just imagine if they made it sneaky. get things just subtly wrong enough that your training runs just never quite go as well as you think they should.

[razster]

This explains why I've been running into some odd roadblocks. Welp that sealed the deal, I'm going to be cancelling our company sub, not worth it.

[yaur]

Did my Claude get permanently dumber today because I asked fable to assess my Fairplay integration?