From 07f9b711a36bb89e1f99738ee1d531fa48a2fb31 Mon Sep 17 00:00:00 2001 From: Yuchen Pei Date: Tue, 18 Sep 2018 11:28:08 +0200 Subject: added an mpost --- microposts/rnn-turing.md | 5 +++++ 1 file changed, 5 insertions(+) create mode 100644 microposts/rnn-turing.md (limited to 'microposts') diff --git a/microposts/rnn-turing.md b/microposts/rnn-turing.md new file mode 100644 index 0000000..40777c1 --- /dev/null +++ b/microposts/rnn-turing.md @@ -0,0 +1,5 @@ +--- +date: 2018-09-18 +--- + +Just some **non-rigorous** rambling: Feedforward networks are like combinatorial logic, and recurrent networks are like sequential logic (e.g. data flip-flop is like the feedback connection in RNN). Since NAND + combinatorial logic + sequential logic = von Neumann machine which is an approximation of the Turing machine, it is not surprising that RNN (with feedforward networks) is Turing complete (assuming that neural networks can learn the NAND gate). -- cgit v1.2.3