Interesting! > the most utility are fluorescent imaging with light microscopy, often at low magnification. These are more amenable to scale-up and machine lear

Interesting! > the most utility are fluorescent imaging with light microscopy, often at low magnification. These are more amenable to scale-up and machine learning Any particular problems there, that you think can be tackled well by machine learning? I just recently started my first ML project in a fluorescence microscopy lab (biochem undergrad with previous software engineering experience), and while I see a lot of things that could benefit from ML for incremental improvements (which often need to be really tailored for each project), as is the case with most disciplines, I haven't really seen anything where I thought that there was potential for something groundbreaking.