I’d use the term Machine Learning to avoid the baggage of what AI implies/promises. But ML has tons of real world applications that other tech can’t solve. I view it as the best tool for fuzzy or approximate data. It’s used in statistical modeling, which can be applied to the automated generation of potential new drugs or proteins. ML can be used in image processing, with image recognition being a huge use case, as well as real-time upscaling like DLSS. And it can be great for Speech-to-Text, natural language processing is a difficult problem to solve but ML approaches do it fairly consistently. These are applications that can generally tolerate the sizable margin of error that a statistical model inherently possesses, either by not being mission critical or by being designed to get reviewed by human experts; I don’t think ML should ever be applied to areas which need guaranteed precision or accuracy. Also note that of all of these examples, only one uses an LLM, and none vie for the title of “AGI” or claim consciousness or intelligence lol. So that’s why I avoid the term AI. ML can imply some of the same stuff but it hasn’t been buzzwordified the same way