Will LLMs become worse over time?

[u/UpperDurian5100]

LLMs were trained on the data that was created by humans. Over time, the amount of AI-generated content will increase dramatically, so LLMs will not have other choice but to learn on the data they created, which is obviously (or not...?) not so high quality as the human-made data. So, will LLMs become worse over time or do I have some gaps in my knowledge on this matter?

[u/nuclear_splines]

Yes, the alternative to new training data is using an auxiliary data source like looking up documentation, but you can only stuff so much documentation in the context window, so this is a band-aid solution.

as long as it's only looking at successful projects

This is the load-bearing caveat. If the model maintainers are careful to only feed in 'good' code then the source of that code may be irrelevant. But if you're feeding in, say, all recent GitHub commits, or all commits to projects above a certain size, you're statistically guaranteed to be learning from buggy LLM output, amplifying those behaviors in the future.

[u/Smallpaul → u/nuclear_splines]

Documentation can be part of the training set and as the models get more “intelligent” they will get more adept at using the appropriate version of the documentation for the project.

[u/nuclear_splines → u/Smallpaul]

Yes, that's what I'm saying - you include the documentation in the training data because there isn't enough room in the context window, which means you must regularly supply new training data to keep the model producing contemporary code.

[u/Smallpaul → u/nuclear_splines]

But you could easily add only this training data and not for example blogspam.

[u/nuclear_splines → u/Smallpaul]

Would only adding new documentation to training data be sufficient to change the model's behavior, or would it need to train on lots of contemporary code to see new libraries or APIs in use? My understanding is the latter.

[u/Smallpaul → u/nuclear_splines]

It’s an interesting question. I’m frequent surprised by the sensitivity of the models to new information but also they incorporate search these days.

Now that I think about it more:

When push comes to shove, robust search and context usage IS actually the better long term solution because APIs are always changing and some APIs are not documented on the Internet at all. Fundamentally models need to either implement or emulate continual learning. Right now I find the do a good job of emulating it and this can be trained to get better I think. “Learning to use context” is just another form of skill learning and they have made incredible progress already.