I think people are hesitant to call ML “statistical modeling” because traditional statistical models approximate the underlying phenomena; e.g., a logarithmic regression would only be used to study logarithmic phenomena. ML models, by contrast, seldom resemble what they’re actually modeling.
We used to distinguish AI as automatically / programmatically making a decision based on an ML model, but I’m guilty of calling it AI for wow factor, lol.
Now I have to be careful because AI = LLMs in common language .
As an older developer, you could replace “machine learning” with “statistical modeling” and “artificial intelligence” with “machine learning”.
“I’m into if statements lately”
“It’s the same picture.”
I think people are hesitant to call ML “statistical modeling” because traditional statistical models approximate the underlying phenomena; e.g., a logarithmic regression would only be used to study logarithmic phenomena. ML models, by contrast, seldom resemble what they’re actually modeling.
fuzzy logic
I hear this all the time in my field.
“Can you just fuzzy match the records between the systems?”
We used to distinguish AI as automatically / programmatically making a decision based on an ML model, but I’m guilty of calling it AI for wow factor, lol.
Now I have to be careful because AI = LLMs in common language .