Neural Networks, Types, and Functional Programming

Christopher Olah · 3 Sept 2015 · colah.github.io ↗

2 korrents from this piece

Christopher Olah did not write this page.

Every claim below was made in this piece, quoted word for word and numbered in the order the piece makes them, so you can read it there rather than take our word for it. The sentence above each quote is our reading of the claim, not their wording. Each quote was checked against a stored copy of the page at build time; where the two differ, the quote is the fact.

Our reading
Deep learning will be understood very differently in thirty years than it is today.

Their wordsI think it is very likely that, reflecting back in 30 years, we will see deep learning very differently.
Our reading
The connection between representations and types may be fundamentally significant, akin to links among geometry, logic, topology and functional programming.

Their wordsThe known connection between geometry, logic, topology, and functional programming suggests that the connections between representations and types may be of fundamental significance.