diff --git a/docs/mllib-guide.md b/docs/mllib-guide.md
index 7779fbc9c49e498ca95726d1b32103a14cb838bc..3d32d03e35c6294208f1bf81db7d2cb4c48e1e82 100644
--- a/docs/mllib-guide.md
+++ b/docs/mllib-guide.md
@@ -56,25 +56,32 @@ See the **[spark.ml programming guide](ml-guide.html)** for more information on
 
 # Dependencies
 
-MLlib uses the linear algebra package [Breeze](http://www.scalanlp.org/),
-which depends on [netlib-java](https://github.com/fommil/netlib-java),
-and [jblas](https://github.com/mikiobraun/jblas). 
-`netlib-java` and `jblas` depend on native Fortran routines.
-You need to install the
+MLlib uses the linear algebra package
+[Breeze](http://www.scalanlp.org/), which depends on
+[netlib-java](https://github.com/fommil/netlib-java) for optimised
+numerical processing. If natives are not available at runtime, you
+will see a warning message and a pure JVM implementation will be used
+instead.
+
+To learn more about the benefits and background of system optimised
+natives, you may wish to watch Sam Halliday's ScalaX talk on
+[High Performance Linear Algebra in Scala](http://fommil.github.io/scalax14/#/)).
+
+Due to licensing issues with runtime proprietary binaries, we do not
+include `netlib-java`'s native proxies by default. To configure
+`netlib-java` / Breeze to use system optimised binaries, include
+`com.github.fommil.netlib:all:1.1.2` (or build Spark with
+`-Pnetlib-lgpl`) as a dependency of your project and read the
+[netlib-java](https://github.com/fommil/netlib-java) documentation for
+your platform's additional installation instructions.
+
+MLlib also uses [jblas](https://github.com/mikiobraun/jblas) which
+will require you to install the
 [gfortran runtime library](https://github.com/mikiobraun/jblas/wiki/Missing-Libraries)
 if it is not already present on your nodes.
-MLlib will throw a linking error if it cannot detect these libraries automatically.
-Due to license issues, we do not include `netlib-java`'s native libraries in MLlib's
-dependency set under default settings.
-If no native library is available at runtime, you will see a warning message.
-To use native libraries from `netlib-java`, please build Spark with `-Pnetlib-lgpl` or
-include `com.github.fommil.netlib:all:1.1.2` as a dependency of your project.
-If you want to use optimized BLAS/LAPACK libraries such as
-[OpenBLAS](http://www.openblas.net/), please link its shared libraries to
-`/usr/lib/libblas.so.3` and `/usr/lib/liblapack.so.3`, respectively.
-BLAS/LAPACK libraries on worker nodes should be built without multithreading.
-
-To use MLlib in Python, you will need [NumPy](http://www.numpy.org) version 1.4 or newer.
+
+To use MLlib in Python, you will need [NumPy](http://www.numpy.org)
+version 1.4 or newer.
 
 ---