[Punoxysm]

Lecun's work on LeNet was pioneering, and basically set the template for deep learning. However, it's not as simple as him being "right all along"; incremental advances in neural net architectures, a lot of developments in stochastic gradient methods, and orders-of-magnitude improvements in hardware and data availability have been what made deep learning as powerful as it is today.

The main point is that skeptics in the 2000's were basically right about neural nets being of limited use, but other technologies advanced and broke down the barriers.

Lecun's original convolutional nets in 1998 were run on the then-gigantic dataset of 60,000 images. Consider that a company like Facebook can provide billions of images with some form of tagging, and you see the different world we live in.

[esturk]

I don't think its fair, or sincere, for you to use past tense to describe anyone's current work.

[Punoxysm]

I'm calling his work on LeNet in 1998 pioneering. I'm not trying to disparage his current work.