The reality on the ground (for me) has been refreshingly sane.
I work at a company with a substantial BI/ML footprint. Our head of research was tasked with evaluating the applicability of LLMs to either our product or our daily workflows.
To date the consensus is that there isn't much there for our product, that integrating LLMs into our models would introduce more problems than it would solve, and that we should cautiously experiment with allowing engineers to use tools like co-pilot, provided we take adequate steps to protect our IP.
It was a reasonable exercise carried out by a reasonable person for reasonable reasons (from my POV). I imagine this isn't an uncommon story? Color me pessimistically optimistic?
For practical reasons we need to have an answer to the buzzword bingo when communicating with customers/company ownership, and now we do. Now we don't talk much about it because there isn't much to talk about.
Refreshing but rare; usually this kind of eval gets done by someone excited to do it because they've already been "intellectually captured" by the hype.
I work at a company with a substantial BI/ML footprint. Our head of research was tasked with evaluating the applicability of LLMs to either our product or our daily workflows.
To date the consensus is that there isn't much there for our product, that integrating LLMs into our models would introduce more problems than it would solve, and that we should cautiously experiment with allowing engineers to use tools like co-pilot, provided we take adequate steps to protect our IP.
It was a reasonable exercise carried out by a reasonable person for reasonable reasons (from my POV). I imagine this isn't an uncommon story? Color me pessimistically optimistic?
For practical reasons we need to have an answer to the buzzword bingo when communicating with customers/company ownership, and now we do. Now we don't talk much about it because there isn't much to talk about.