> One senior-dev (team-lead also) tried to explain to me that AI is a subfield of machine-learning, and always stochastic in nature (since ChatGPT responds differently to the same prompt).
This "senior dev" has it all mixed up and is incorrect.
"AI" is all encompassing umbrella term that includes other fields of "AI" such as the very old GOFAI (good old fashioned AI) which is rule-based, machine learning (statistical, bayesian) methods, and neural networks which deep learning and more recently generative AI (which ChatGPT) uses.
More accurately, it is neural networks which are more "stochastic" with their predictions and decisions, not just transformer models which ChatGPT is based on.
> Am I just too junior/naive to get this or am I cooked?
Quite frankly, the entire team (except you) is cooked, as you have realized what you don't know.
I wonder if the senior dev actually said LLM, or at least meant LLM. If he said that, most of this checks out. The only thing is that they don't have to be stochastic, but in practice they almost always are.
This "senior dev" has it all mixed up and is incorrect.
"AI" is all encompassing umbrella term that includes other fields of "AI" such as the very old GOFAI (good old fashioned AI) which is rule-based, machine learning (statistical, bayesian) methods, and neural networks which deep learning and more recently generative AI (which ChatGPT) uses.
More accurately, it is neural networks which are more "stochastic" with their predictions and decisions, not just transformer models which ChatGPT is based on.
> Am I just too junior/naive to get this or am I cooked?
Quite frankly, the entire team (except you) is cooked, as you have realized what you don't know.