By asking the LLM to generate a formula though, it doesn't actually need to do any number crunching of its own which makes solving the challenge a bit more reliable when it comes to LLMs.
By asking the LLM to generate a formula though, it doesn't actually need to do any number crunching of its own which makes solving the challenge a bit more reliable when it comes to LLMs.
Would love to hear your perspective on the space!
However, what seems to be the business proposition is giving managers shallow access to documents but won't lead to rigorous information.
There's a few middle grounds where it can yield insights. like regulatory scenarios where you want to understand how public orgs satisfy permits with written plans.
however, what I don't believe will yield is the context size. when I want to explore my knowledge base, I need far more than 128k and there's sever orders of structure that language itself is not going to bridge.
Regarding the context size, the research community is doing some stunning work. If you're interested, you should check out the new Mamba (Transformers replacement) architecture: https://arxiv.org/abs/2312.00752