[bomdo]

Great question.

Even a human brain has to train for ~4-5 months to become interested in shapes (https://en.wikipedia.org/wiki/Infant_visual_development). Once the human brain has been trained for these basic shapes for a while, it is able to quickly break down a new class (i.e. a cat) and recognize similar patterns in other images. This is something that is very similar to the way that training a deep NN works.

Also don't forget that the current NN are being trained mainly for photos, not moving images. A brain may recognize a cat by its tail-wagging or fur movements, which is a dimension that is completely missing from still images.

Also check out this similar post and discussion: https://news.ycombinator.com/item?id=9247851

[vidarh]

> Even a human brain has to train for ~4-5 months to become interested in shapes

Everyone who wonder how (on a superficial level) grown up humans are so good at learning new categories really should spend time around babies and toddlers and children for this reason...

You quickly realise how much training and brain development it actually takes before we're capable of doing much.

[bpizzi]

By far the greatest part of the time I spent with my two toddlers (5 and 3) is spent repeating the same things, again and again, and trying to find shorcuts for learning (which shorcuts might just not exist, afaik).

Then one day they start to get it (like "fire burns"), but it's still not there for sure until they experiment it deeply multiple times.

The dev in me can't help but see this two little humans as big mighty neural networks who spend their full uptime constantly ingesting tremendous amount of data and being restlessly tuned back by adults and experience :)

[booli]

And this tuning is of utmost important. People often forget that the tuning is human intervention with specific 'specs'. The little baby machine get's quickly tuned to these, good or bad.