François Chollet+ Your Authors @fchollet Deep learning @google. Creator of Keras, neural networks library. Author of 'Deep Learning with Python'. Opinions are my own. Dec. 26, 2019 1 min read + Your Authors

So, "deep learning" is the idea of doing representation learning via a chain of learned feature extractors. It's all about describing some input data via *deep hierarchies of features*, where features are *learned*.

A further question is then: is the brain "deep learning"?

The only good answer here: the brain is an incredibly complex thing, encompassing many parts that are structured differently, and we know extremely little about it. We cannot definitely answer the question.

However, my gut feeling is that the brain is generally not DL, although some submodules could be described as DL or part-DL (e.g. the visual cortex is a deep hierarchy of features, albeit not all are learned, and has been a considerable source of inspiration in DL).

I would add that our current understanding and usage of modern deep learning -- its genealogy -- lies mostly in earlier modern machine learning techniques, not in neuroscience. The influence of neuroscience has been one of high-level conceptual inspiration, not direct emulation.

You can follow @fchollet.


Tip: mention @threader_app on a Twitter thread with the keyword “compile” to get a link to it.

Enjoy Threader? Sign up.

Since you’re here...

... we’re asking visitors like you to make a contribution to support this independent project. In these uncertain times, access to information is vital. Threader gets 1,000,000+ visits a month and our iOS Twitter client was featured as an App of the Day by Apple. Your financial support will help two developers to keep working on this app. Everyone’s contribution, big or small, is so valuable. Support Threader by becoming premium or by donating on PayPal. Thank you.