docs: fixes the known limitations in readme and relnotes

Author: dsuthar-nvidia

README.md

@@ -60,8 +60,7 @@ To get a local copy up and running follow these steps.
 - [CV-CUDA Samples] require driver r535 or later to run and are only officially supported with CUDA 12.
 - Only one CUDA version (CUDA 11.x or CUDA 12.x) of CV-CUDA packages (Debian packages, tarballs, Python Wheels) can be installed at a time. Please uninstall all packages from a given CUDA version before installing packages from a different version.
 - Documentation built on Ubuntu 20.04 needs an up-to-date version of sphinx (`pip install --upgrade sphinx`) as well as explicitly parsing the system's default python version ` ./ci/build_docs path/to/build -DPYTHON_VERSIONS="<py_ver>"`.
-- Python tests fail with numpy 2.0. We recommend using an older version (eg 1.26) until we have implemented a fix.
-- Python bindings installed via Debian packages fail with numpy 2.0. We recommend using an older version (eg 1.26) until we have implemented a fix.
+- Python bindings installed via Debian packages and Python tests fail with Numpy 2.0. We recommend using an older version of Numpy (e.g. 1.26) until we have implemented a fix.
 - The Resize and RandomResizedCrop operators incorrectly interpolate pixel values near the boundary of an image or tensor when using linear and cubic interpolation. This will be fixed in an upcoming release.
 
 ### Installation

docs/sphinx/relnotes/v0.9.0-beta.rst

@@ -43,8 +43,7 @@ Compatibility and Known Limitations
 -----------------------------------
 
   * Documentation built on Ubuntu 20.04 needs an up-to-date version of sphinx (`pip install --upgrade sphinx`) as well as explicitly parsing the system's default python version `./ci/build_docs path/to/build -DPYTHON_VERSIONS="<py_ver>"`.
-  * Python tests fail with numpy 2.0. We recommend using an older version (eg 1.26) until we have implemented a fix.
-  * Python bindings installed via Debian packages fail with numpy 2.0. We recommend using an older version (eg 1.26) until we have implemented a fix.
+  * Python bindings installed via Debian packages and Python tests fail with Numpy 2.0. We recommend using an older version of Numpy (e.g. 1.26) until we have implemented a fix.
   * The Resize and RandomResizedCrop operators incorrectly interpolate pixel values near the boundary of an image or tensor when using linear and cubic interpolation. This will be fixed in an upcoming release.