>Funny, the ones I work with get updated with new information all the time. No reason it couldn't happen after every single encounter. What? Do you not know ho

>Funny, the ones I work with get updated with new information all the time. No reason it couldn't happen after every single encounter. What? Do you not know how any of this works at all? Updating LLM weights means calculating the gradients and back propagating. And that's only for unsupervised learning, for the reinforcement learning you want the gradients need to be accumulated until you have some way to score the episode. For usefully large language models there are serious logistical problems doing this at all, it's one of the most computationally intensive tasks you can use computers for currently. It certainly can't be done for every interaction.