<p><em>Sequence to Sequence Learning using Neural networks</em> is a way to use Neural Networks to translate sequences. The general goal is you have a source sequence(say a sentence in English), a target sequence(it's translation in French) and the task is to generate target sequence looking at source sequence.</p>

<p>Challenges for traditional Feed Forward Neural Networks are varying source and target lengths. <a href="http://arxiv.org/abs/1409.3215" rel="nofollow">In this paper</a>, they use a Recurrent neural Network(RNN) to encode the source sequence i.e, the RNN reads the individual elements in source sequence one-by-one. Once it finishes, the encoder would be having a fair idea of what the source sequence is.</p>

<p>You use the last state of the encoder and provide this additional information to Decoder(which is basically a language model) to generate the target sequence element by element.</p>

<p>In your case, you can use it to generate responses. Say you have chat messages between two users. Now chat message of user 1 would be source sequence and the corresponding reply from user 2 would be target sequence. The training is done as said in the paper. The model after training would be trying to mimick user 2 response.</p>
What is Sequence to Sequence Learning with Neural Networks
<p>Chat bot can be created with Sequence to Sequence Learning with Neural Networks, I have training chat-data but how to use it?</p>