update README

Author: yinyinl

README.md

@@ -8,7 +8,22 @@ NLP Architect is an open-source Python library for exploring the state-of-the-ar
 language understanding. It is intended to be a platform for future research and
 collaboration.
 
-The library consists of core modules (topologies), data pipelines, utilities and end-to-end model examples with training and inference scripts. Each of the models includes algorithm descriptions and results in the [documentation](http://www.nlp_architect.nervanasys.com/).
+The current version of NLP Architect includes these features that we found interesting from both research perspectives and practical applications:
+
+* NLP core models that allow robust extraction of linguistic features for NLP workflow: for example, dependency parser (BIST) and NP chunker
+* NLU modules that provide best in class performance: for example, intent extraction (IE), name entity recognition (NER)
+* Modules that address semantic understanding: for example, colocations, most common word sense, NP embedding representation (e.g. NP2V)
+* Components instrumental for conversational AI: for example, ChatBot applications, including dialog system, sequence chunking and IE
+* End-to-end DL applications using new topologies: for example, Q&A, machine reading comprehension
+
+<center> <img src="doc/source/assets/nlp_archtiect_v0.1.png"></center>
+
+The library consists of core modules (topologies), data pipelines, utilities and end-to-end model examples with training and inference scripts. We look at these as a set of building blocks that were needed for implementing NLP use cases based on our pragmatic research experience. Each of the models includes algorithm descriptions and results in the [documentation](http://www.nlp_architect.nervanasys.com/).
+
+Some of the components, with provided pre-trained models, are exposed as REST service APIs through NLP Architect server. NLP Architect server is designed to provide predictions across different models in NLP Architect. It also includes a web front-end exposing the model annotations for visualizations. Currently, we provide 2 services, BIST dependency parsing and NER annotations. We also provide a template for developers to add a new service.
+
+<center> <img src="doc/source/assets/bist_service.png"></center>
+
 
 Because of its current research nature, several open source deep learning frameworks are used in this repository including: