Over just a few months, ChatGPT went from correctly answering a simple math problem 98% of the time to just 2%, study finds. Researchers found wild fluctuations—called drift—in the technology’s abi…::ChatGPT went from answering a simple math correctly 98% of the time to just 2%, over the course of a few months.
This is what was addressed at the start of the comment, you can just roll back to a previous version. It’s heavily ingrained in CS to keep every single version of your software forever.
I don’t think it’s that easy. These are vLLMs that feed back on themselves to produce “better” results. These models don’t have single point release cycles. It’s a constantly evolving blob of memory and storage orchestrated across a vast number of disk arrays and cabinets of hardware.
[e]I am wrong the models are version controlled and do have releases.
That’s not how these LLMs work. There is a training phase which takes a large amount of compute power, and the training generates a model which is a set of weights and could easily be backed up and version-controlled. The model is then used for inference which is a less compute-intensive process and runs on much smaller hardware than the training phase.
The inference architecture does use feedback mechanisms but the feedback does not modify the model-weights that were generated at training time.
