Sometimes I wonder why is the top-5 image classification task so difficult. If you are giving me 5 chances to look at an image and correctly classify it from ~1000 Imagenet classes, I can surely do better than 5-10% error rate.
Also, now that the top-5 error rate been brought down considerably, what is the next benchmark for the research community to beat? A new dataset, top-1 error rate on Imagenet?
There is a point of view out there that Europe's higher than average reliance on renewables has bumped up electricity prices there and contributed in making the place less competitive for industries. You can see that argument in action when European miners are losing out to others due to high power costs.
There is a point of view out there that Europe's higher than average reliance on renewables has bumped up electricity prices there and contributed in making the place less competitive for industries. You can see that argument in action when European miners are losing out to others due to high power costs.
Yeah, but it seems manufacturing is not that popular in AI research. Maybe this is because getting the desired data and performing the entire research process is much slower for this domain.