Comment by milesrout

Convolutional neural networks for image recognition and more generally image processing. They are much better than they were a few years ago, when they were all the rage, but the hype has disappeared. These systems improve the performance of radiologists at detecting clinically significant cancers. They can be used to detect invasive predators or endangered native wildlife using cameras in the bush, in order to monitor populations, allocate resources for trapping of pests, etc.

ML generally is for pattern recognition in data. That includes anomaly detection in financial data, for example. It is used in fraud detection.

Image ML/AI is used in your phone's facial recognition, in various image filtering and analysis algorithms in your phone's camera to improve picture quality or allow you to edit images to make them look better (to your taste, anyway).

AI image recognition is used to find missing children by analysing child pornography without requiring human reviewers to trawl through it - they can just check the much fewer flagged images.

AI can be used to generate captions on videos for the deaf or in text to speech for the blind.

There are tons of uses of AI/ML. Another example: video game AI. Video game upscaling. Chess and Go AI: NNUE makes Chess AI far stronger and in really cool creative ways which have changed high level chess and made it less drawish.