diff --git a/content/en/docs/tasks/manage-gpus/scheduling-gpus.md b/content/en/docs/tasks/manage-gpus/scheduling-gpus.md
index d02a20577e7f4..bd13d60a30578 100644
--- a/content/en/docs/tasks/manage-gpus/scheduling-gpus.md
+++ b/content/en/docs/tasks/manage-gpus/scheduling-gpus.md
@@ -81,12 +81,22 @@ kubectl label nodes node2 accelerator=other-gpu-k915
 That label key `accelerator` is just an example; you can use
 a different label key if you prefer.
 
-## Automatic node labelling {#node-labeller}
+## Automatic node feature discovery {#node-feature-discovery}
 
-If you're using AMD GPU devices, you can deploy
+As and administrator, you can automatically discover and label all your GPU enabled nodes
+by deploying the K8S-Sig project Node Feature Discovery [NFD](https://github.com/kubernetes-sigs/node-feature-discovery).
+NFD enables node feature discovery for Kubernetes. 
+It detects hardware features available on each node in a Kubernetes cluster, and advertises those features using node labels and optionally node extended resources, annotations and node taints. 
+Node Feature Discovery is compatible with any recent version of Kubernetes (v1.21+).
+
+Administrators can leverage NFD to also taint nodes with specific features, so that only pods that request those features can be scheduled on those nodes.
+
+NFD exposes an API to allow vendors to leverage the automatic labeling functionality. 
+NVIDIA has implemented this API in the [GPU feature discovery](https://github.com/NVIDIA/gpu-feature-discovery/blob/main/README.md).
+
+### Using custom labellers
+
+For AMD GPUs, you can use the
 [Node Labeller](https://github.com/RadeonOpenCompute/k8s-device-plugin/tree/master/cmd/k8s-node-labeller).
 Node Labeller is a {{< glossary_tooltip text="controller" term_id="controller" >}} that automatically
-labels your nodes with GPU device properties.
-
-Similar functionality for NVIDIA is provided by
-[GPU feature discovery](https://github.com/NVIDIA/gpu-feature-discovery/blob/main/README.md).
+labels nodes in a Kubernetes cluster with AMD GPU device properties.