Comment by gremlinsinc
3 years ago
That or they're working on something like a 10-30B input model, dubbed GPT-NextGen, that essentially has the same results as gpt4, but with a lot more performance gains, and speed, and improvements. GPT-5 will suck, if it's a similar ratio slower to gpt-4, than gpt-4 is to gpt-3.5.
So, I think there's a lot of improvements where maybe gpt-4, is as far you go in terms of inputting data, and maybe better use cases are more customization of data trained on, or finding ways of going smaller, or even some model that just trains itself on the data requirements, similar to how we jump on google when we're stuck, it'd do the same and build up its knowledge that way.
I also think we need improvements in vector stores that maybe add weights to "memories" based on time/frequency/recency/popularity.
That sounds like having a mixture of experts model (at high scale popularly developed by Google): train multiple specialised models (say embedders from text to a representation) that could be fed into a single model at the end. Each expert would be an adapter of sorts, activating depending on the type of input