What makes you think I don't shitpost in the #engineering channel?
And heuristics don't even scratch the surface of the bigger problem where it's trained on people who aren't great at their jobs but type a lot of words on slack about circling back on KPIs.
Through regularization techniques, data augmentation, loss functions, and gradient optimization, ensuring the model focuses on meaningful patterns and reduces overfitting to noise.
It’s not obvious how any of those would do anything but better approximate the average of a noisy dataset. RLHF might help, but only if it’s not done by idiots.
The whole world’s “sh*tposting”: Reddit, blogs, and the rest of the internet.
But also books and Wikipedia and what not.
You can “smooth” all the crap out via the training procedure.
But even more, Slack can easily filter training data to, say, only posts in high-use channels.
Further, slack has other options: eg, use their customer data only for marginal fine-tuning, for example.
Or, they don’t even know their use case yet - but want to wrap their arms around your data pronto.