Updated README

README.md

@@ -3,12 +3,12 @@ Linguist
 
 An AI running on [NuPIC](https://github.com/numenta/nupic) using the CLA to build a model of language, and predict the rest of a user's word, phrase, sentence.
 
-The current application works as a "story teller", it'll train on a dataset you give it and then produce a story for you. You can specify number of sentences the story 
-should have and the beginig words to kick off "There were two brothers ". 
+The current application works as a "story teller", it'll train on a dataset you give it and then produce a story for you. You can specify number of sentences the story
+should have and the starting words to kick it off (for example, "There were two brothers").
 
-Research: 
+## Reference
 
-The CLA learns sentences letter-by-letter, we'd like to observe if grammatical features can emerge. See [Jeff Hinton's text-generation deep NNs](https://class.coursera.org/neuralnets-2012-001/lecture/91) for reference. 
+The CLA learns sentences letter-by-letter, we'd like to observe if grammatical features can emerge. See [Jeff Hinton's text-generation deep NNs](https://class.coursera.org/neuralnets-2012-001/lecture/91) for reference and inspiration.
 
 Usage
 ========
@@ -20,3 +20,5 @@ Then, run:
     python client/linguist.py data/tiny.txt
 
 It'll run on the tiny.txt dataset, feeding it the sentence over and over again, printing out Linguist's next 10 timestep predictions at each step.
+
+After it finishes training, it will enter "story teller" mode.