t_rexinated

t_rexinated t1_j89jsip wrote

the overhype-underdelivery cycle is real and that's led to very understandable vaporware vibes amongst bigger biotech and pharma.

honestly, if you think that you'll simply be able to just pop the data from your absolute trash of an experiment into a magical shiny black box and get anything meaningful out of it, then you're an idiot and you deserve to lose your money on something you think will solve all of your problems for you.

agreed: if you're shoveling hot garbage in, hot garbage is def gonna be coming out.

when done properly and when done well, AI/ML,/GNNs/CNNs/GANs/blah blah blah are absolutely amazing and powerful tools. it just takes a lot of hard work to get to that point, and few do it well. when done well though, peeps are doing some really awesome work tho...especially in image processing phenotypic profiling:

https://www.nature.com/articles/d41586-022-02964-6

1

t_rexinated t1_j89cjqf wrote

they use a combo of already available public datasets in addition to strategic partnership or licensings that give them accessibility to otherwise walled-off, yet potentially highly valuable data sources.

Regardless of where it comes from, everything is regulatory/HIPAA compliant prior to the data actually moving hands.

1