Fascinating. Also interesting to see the failure modes. Any human would quickly realize that the "boy doing backflip on wakeboard" is actually playing on a trampoline. Or the "two young girls playing with legos toy". Great stuff!
I think I'm a human, but I did not realize that boy was on a trampoline instead of a wakeboard until you pointed it out. I think the water in the background confused me. I was also probably biased by reading the network's label before reaching my own judgment.
Right - impressive though this is, also the cat isn't black, the woman with the bananas might well not be a woman, the girl isn't swinging on a swing, the construction worker is probably not in the road, and the guitarist is tuning the guitar, not playing it. It's pretty much wrong -in detail- on every count.
The weird thing is how at a glance, it seems pretty much correct. And how some people here are willing to look at that and think 'automated law enforcement is clearly imminently possible'.
Wow.. talk about high expectations. This is really well done. Identifying multiple concepts in an image and describe it to a good degree of accuracy. And this will get better further.
No no! Don't misunderstand me! I agree: It's phenomenally impressive! It's also still completely useless at this level of accuracy.
At this point, this software is as useful at describing photographs as a disinterested teenager who is busy trying to text. "This is a picture of my mom with some dude playing I dunno like tennis or something. Whatever."
Which is really impressive! Seriously!
But closing the gap to accuracy is really important, and it's a hard hard problem.
