We are finding that strict, rule-based approaches are actually essential in an LLM-enabled architecture. Right now, we are looking at putting something like Watson in front of GPT4 in order to filter, route & contextualize our system.

Generative AI architectures get a lot of attention, but classification is the real magic for making something that looks as polished as ChatGPT. The determinism you get with something like an SVM is much more certain than adjusting a spiciness slider between 0 and 1.

I feel like if an AI Algo is coming up with the rules, is it really rules based?

I think yes, if only to distinguish this from other AI approaches that aren’t merely rule generators.

A physical machine that automates the laying of bricks is still laying bricks. A similar machine that builds a “brick” wall through some other mechanism (perhaps by directly/dynamically creating a continuous structure) would be meaningfully different.

That actually makes sense. We need proper category names to have better conversations. I didn't think of it that way.

I think people make too much of the thin layer of “prompts” or “commands”. It is literally a tiny piece of the pipeline and when yoi have LLMs giving commands to LLMs and swarms of Zapier etc. I can see it easily becoming more like what you see in Eagle Eye… the swarm simply starts employing/threatening a lot of humans for no discernable purpose. Destroying reputations and forums be the lowest hanging fruit.

It'll be LLM's all the way down! always has been. :astronaut: