AI is quite fit for the task of understanding what might be the purpose of code
Disagree.
I don’t know how some non-AI tool could be better for such task.
ClamAV has been filling a somewhat similar use case for a long time, and I don’t think I’ve ever heard anyone call it “AI”.
I guess bayesian filters like email providers use to filter spam could be considered “AI” (though old-school AI, not the kind of stuff that’s such a bubble now) and may possibly be applicable to your use case.
If you’re talking about naive bayes filtering, it most definitely is an ML model. Modern spam filters use more complex ML models (or at least I know Yahoo Mail used to ~15 years ago, because I saw a lecture where John Langford talked a little bit about it). Statistical ML is an “AI” field. Stuff like anomaly detection are also usually ML models.
Disagree.
ClamAV has been filling a somewhat similar use case for a long time, and I don’t think I’ve ever heard anyone call it “AI”.
I guess bayesian filters like email providers use to filter spam could be considered “AI” (though old-school AI, not the kind of stuff that’s such a bubble now) and may possibly be applicable to your use case.
Bayesian filters are statistical, they have nothing to do with machine learning.
If you’re talking about naive bayes filtering, it most definitely is an ML model. Modern spam filters use more complex ML models (or at least I know Yahoo Mail used to ~15 years ago, because I saw a lecture where John Langford talked a little bit about it). Statistical ML is an “AI” field. Stuff like anomaly detection are also usually ML models.