Many modern architectures, such as Memorizing Transformers, RETRO and PKM have an explicit memory where the model can retrieve information from and optionally even store it. Some hypothesise that Mixture-of-Experts embeds fuzzy representations of books and other things it must memorise into its weights.\
That's why adding explicit memory to our models could give them a considerable boost in performance. Instead of storing this information in dense layers and having the weights fight about whether they should be storing concepts or memorising sequences, our model would be able to do both.\
This issue is about implementing such an explicit memory (be it PKM, MoE or even a new architecture) and improving the convergence of our language model at the same runtime.
Many modern architectures, such as Memorizing Transformers, RETRO and PKM have an explicit memory where the model can retrieve information from and optionally even store it. Some hypothesise that Mixture-of-Experts embeds fuzzy representations of books and other things it must memorise into its weights.\ That's why adding explicit memory to our models could give them a considerable boost in performance. Instead of storing this information in dense layers and having the weights fight about whether they should be storing concepts or memorising sequences, our model would be able to do both.\ This issue is about implementing such an explicit memory (be it PKM, MoE or even a new architecture) and improving the convergence of our language model at the same runtime.