4 ms·
Huh? 6% of the systems outdoing a human who spent years training for her profession is supposed to be bad news? That's awesome! Especially considering that thes
by m0zg 5y ago
Huh? 6% of the systems outdoing a human who spent years training for her profession is supposed to be bad news? That's awesome! Especially considering that these are not supposed to replace radiologists (yet), but merely to augment expert judgment.
- cratermoon 5y agoThat's assuming they can consistently do it, that the results in the paper were not just random luck, and not taking into account the costs and risks associated with inaccurate diagnoses.
- m0zg 5y agoSure, but this is all _very_ early. You should see the kind of AI "techniques" some of those papers are using. It's not Imagenet, but people just take "academic" models from papers (sometimes from prehistoric times, like 7-10 years ago) and try their luck with them. News flash: model architectures and training regimes are overfitted quite severely to academic datasets such as Imagenet, OpenImages and MSCOCO at this point. When you see a bear riding a bicycle, you don't complain that the bear rides poorly. You're in awe that it can ride at all. Wait until people who know what they're doing move in. Right now a lot of those people are in academia, trying to squeeze the last 0.01% of lift out of Imagenet dog breeds via architecture searches at $100K a pop.