diff --git a/openvino/README.md b/openvino/README.md
index 7f16baec..08279536 100644
--- a/openvino/README.md
+++ b/openvino/README.md
@@ -1,48 +1,10 @@
 # Using the Intel OpenVINO toolkit
 
-The Intel OpenVINO toolkit is a set of tools and libraries for computer vision applications. It also includes a complete build of OpenCV installed with the Intel OpenVINO. It uses computer vision and imaging algorithms developed at Intel.
+The Intel OpenVINO toolkit is a set of tools and libraries for computer vision applications, that uses computer vision and imaging algorithms developed at Intel. It also includes a complete build of OpenCV.
 
-GoCV support for the Intel OpenVINO Photography Vision Library (PVL) can be found here in the "gocv.io/x/gocv/openvino/pvl" package. Check out the README.md in the `pvl` directory for more information.
+GoCV support for the Intel OpenVINO Photography Vision Library (PVL) which can be found in the "gocv.io/x/gocv/openvino/pvl" package. Check out the README.md in the `pvl` directory for more information.
 
-## How to install the Intel OpenVINO toolkit
-
-You will need to install various dependencies before you will be able to run the Intel OpenVINO installer:
-
-```
-sudo apt-get update
-sudo apt-get install build-essential ffmpeg cmake checkinstall pkg-config yasm libjpeg-dev curl imagemagick gedit mplayer unzip libpng12-dev libcairo2-dev libpango1.0-dev libgtk2.0-dev libgstreamer0.10-dev libswscale.dev libavcodec-dev libavformat-dev
-```
-
-### Installing OpenCL Support
-
-If you also want to use the OpenCL support for GPU-based hardware acceleration, you must install the OpenCL runtime. First, install the dependencies:
-
-```
-sudo apt-get update
-sudo apt-get install build-essential ffmpeg cmake checkinstall pkg-config yasm libjpeg-dev curl imagemagick gedit mplayer unzip libpng12-dev libcairo2-dev libpango1.0-dev libgtk2.0-dev libgstreamer0.10-dev libswscale.dev libavcodec-dev libavformat-dev
-```
-
-Next, obtain the OpenCL runtime package:
-
-```
-wget http://registrationcenter-download.intel.com/akdlm/irc_nas/11396/SRB5.0_linux64.zip
-unzip SRB5.0_linux64.zip -d SRB5.0_linux64
-cd SRB5.0_linux64
-```
-
-Last, install the OpenCL runtime:
-
-```
-sudo apt-get install xz-utils
-mkdir intel-opencl
-tar -C intel-opencl -Jxf intel-opencl-r5.0-63503.x86_64.tar.xz
-tar -C intel-opencl -Jxf intel-opencl-devel-r5.0-63503.x86_64.tar.xz
-tar -C intel-opencl -Jxf intel-opencl-cpu-r5.0-63503.x86_64.tar.xz
-sudo cp -R intel-opencl/* /
-sudo ldconfig
-```
-
-### Installing Intel OpenVINO toolkit
+## Installing Intel OpenVINO toolkit
 
 The most recent version of the Intel OpenVINO toolkit is currently R1. You can obtain it from here:
 
diff --git a/openvino/pvl/README.md b/openvino/pvl/README.md
index 9513270b..f129d501 100644
--- a/openvino/pvl/README.md
+++ b/openvino/pvl/README.md
@@ -1,6 +1,6 @@
 # Using the Intel OpenVINO Photography Vision Library
 
-The Intel OpenVINO Photography Vision Library (PVL) is a set of extensions to OpenCV that is installed with the Intel CV SDK. It uses computer vision and imaging algorithms developed at Intel.
+The Photography Vision Library (PVL) is a set of extensions to OpenCV that is installed with the Intel OpenVINO toolkit. It uses computer vision and imaging algorithms developed at Intel.
 
 GoCV support for the PVL can be found here in the "gocv.io/x/gocv/openvino/pvl" package.
 
@@ -79,25 +79,3 @@ func main() {
 ```
 
 Some PVL examples are in the [cmd/openvino/pvl directory](../cmd/openvino/pvl) of this repo, in the form of some useful commands such as the [smile detector](../cmd/openvino/pvl/smiledetector).
-
-## How to build/run code
-
-Setup the environment for the Intel OpenVINO toolkit, by running the `setupvars.sh` program included with OpenVINO:
-
-```
-source /opt/intel/computer_vision_sdk/bin/setupvars.sh
-```
-
-Then set the needed other exports for building/running GoCV code by running the `env.sh` that is in the GoCV `openvino` directory:
-
-You only need to do these two steps one time per session. Once you have run them, you do not need to run them again until you close your terminal window.
-
-Now you can run the version command example to make sure you are compiling/linking against Intel OpenVINO:
-
-```
-$ go run ./cmd/version/main.go 
-gocv version: 0.7.0
-opencv lib version: 3.3.1-cvsdk_2017_R3.2
-```
-
-Examples that use the Intel OpenVINO toolkit can be found in the `cmd/openvino/pvl` directory of this repository.