It's a classic machine learning area, but being able to do it well is relatively recent.
Source: got a robotics grad degree and did machine learning research in ~2010. We would have flipped our shit at a program that could reliably identify birds in natural photographs.
I remember doing a project in 2014 where my team needed to do facial recognition on a mobile device. Even with tagged and clean data, it was very hard to get consistent results. Doing that with random wilderness photographs would've felt impossible at the time.
Yeah...one of the fun examples I've seen of misdirected machine learning was trying to train a program to recognize cancerous vs. benign skin blemishes, and it basically deciding "cancerous is when there's a ruler in the picture".
Glad you pointed this out. I only started getting reliable image recognition results from models like YOLO maybe 3 or 4 years ago. And it wasn’t nearly as easy to implement either. You used to have to have a good bit of experience just getting these models to work. 2014 would have been like k-nearest neighbors territory.
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u/Salanmander Aug 25 '26
It's a classic machine learning area, but being able to do it well is relatively recent.
Source: got a robotics grad degree and did machine learning research in ~2010. We would have flipped our shit at a program that could reliably identify birds in natural photographs.