minor change

Former-commit-id: b1025408767461426ec95f75ec3f438bd2a3dafa

README.md

-![Milvuslogo](https://github.com/milvus-io/docs/blob/branch-0.5.0/assets/milvus_logo.png)
+![Milvuslogo](https://github.com/milvus-io/docs/blob/master/assets/milvus_logo.png)
 
 ![LICENSE](https://img.shields.io/badge/license-Apache--2.0-brightgreen)
 ![Language](https://img.shields.io/badge/language-C%2B%2B-blue)
@@ -19,11 +19,11 @@ Milvus is an open source similarity search engine for massive feature vectors. D
 
 Milvus provides stable Python, Java and C++ APIs.
 
-Keep up-to-date with newest releases and latest updates by reading Milvus [release notes](https://milvus.io/docs/en/Releases/v0.4.0/).
+Keep up-to-date with newest releases and latest updates by reading Milvus [release notes](https://milvus.io/docs/en/Releases/v0.5.0/).
 
-- GPU-accelerated search engine
+- Heterogeneous computing
 
-  Milvus uses CPU/GPU heterogeneous computing architecture to process feature vectors, and are orders of magnitudes faster than traditional databases.
+  Milvus is designed with heterogeneous computing architecture for the best performance and cost efficiency. 
 
 - Multiple indexes
 
@@ -31,14 +31,30 @@ Keep up-to-date with newest releases and latest updates by reading Milvus [relea
 
 - Intelligent resource management
 
-  Milvus optimizes the search computation and index building according to your data size and available resources. 
+  Milvus automatically adapts search computation and index building processes based on your datasets and available resources.
 
-- Horizontal scalability 
+- Horizontal scalability
 
-  Milvus expands computation and storage by adding nodes during runtime, which allows you to scale the data size without redesigning the system.
+  Milvus supports online / offline expansion to scale both storage and computation resources with simple commands.
+
+- High availability
+
+  Milvus is integrated with Kubernetes framework so that all single point of failures could be avoided.
+
+- High compatibility
+
+  Milvus is compatible with almost all deep learning models and major programming languages such as Python, Java and C++, etc.
+
+- Ease of use
+
+  Milvus can be easily installed in a few steps and enables you to exclusively focus on feature vectors. 
+
+- Visualized monitor
+
+  You can track system performance on Prometheus-based GUI monitor dashboards.
 
 ## Architecture
-![Milvus_arch](https://github.com/milvus-io/docs/blob/master/assets/milvus_arch.jpg)
+![Milvus_arch](https://github.com/milvus-io/docs/blob/master/assets/milvus_arch.png)
 
 ## Get started