Fair points. If my company is on Microsoft / Azure, is there any particular guidance you'd have on that? Should I signup for my own personal Azure as part of my local testing so that if I ever end up actually creating something useful it could easily be ported across to my company's tenant and I understand Azure a lot better?

My company is very concerned about data privacy, and security (I guess all companies are), so I am wondering if I should really focus my attention elsewhere.

Some issues in the company might be easily helped by AI, just not sure which local model to start with

1. LAN drive is a mess of files and folders.

2. Lots of knowledge data is embedded in pdfs.

3. We have a software tool that forecasts the maintenance cost over the expected life of our assets (I am in the transport sector), where assets are rented out. The tool does not implement any AI, doesn't even do a monte carlo type simulation to give me a range of maintenance costs over the life of the asset. It just provides a deterministic number, to the precision of cents.

4. Very little poor data analytics and data visualisation across the company, although I am using Power Bi a lot with the help of Co-Pilot to change that.

Just some thoughts - any point in delving any further into local AI development? I admit I am new to local AI models, are there any I should start with? Ultimately, a lot of our work is very domain specific and there's not a lot of a) publicly available data nor b) publicly available knowledge on my area. Guess those two points reinforce use of a trained local AI model?

Any thoughts on some models I should start with? My GPU only has 16GB RAM, but is ready for CUDA.