(more) on a.i.

Three groups of folks were kind enough to ask me about A.I. today.  

My "nutshell" view on A.I. for the savviest operators who want to know how to think of A.I.: It's not just about prioritizing where A.I. & machine learning can create value & how its applications can reduce costs, it's also very much about how we are not going to create more problems &/or make future generations pay for our choices today.

Get savvier about A.I., like you should have yesterday. You owe it to yourself, your stakeholders, your shareholders, etc. because, I'm certain, that the future of the free world depends on all of us being a lot smarter about how to work better with machines. Start with what the so called hyperscalers offer, for free, especially if you read a lot less now. Otherwise, for the fun of learning & love of having context, dig into the math, logic, matricies, transformations, Turing, Claude Shannon, NLP, etc. maybe even while you work the other end of optimization, recommenders, accelerating training, LLMs, ethics, &  all contemporary A.I. has to offer as the field evolves.