Review first page and add next steps to Ollama on GKE Learning Path

Author: jasonrandrews

content/learning-paths/servers-and-cloud-computing/multiarch_ollama_on_gke/_index.md

@@ -1,20 +1,19 @@
 ---
-title: Run ollama on both arm64 and amd64 nodes, using the same multi-architecture container image on GKE.
+title: Use GKE to run Ollama on arm64 and amd64 nodes using a multi-architecture container image
 
 minutes_to_complete: 30
 
-who_is_this_for:  This learning path will show you how easy it is to migrate from homogenous amd64 k8s clusters, to a hybrid (arm64 and amd64) cluster with multi-architectural container images on GKE.  Demonstrated with the ollama application, you'll see for yourself the price/performance advantages of running on arm64. Although tutorial will be GKE-specific with ollama, the provided YAML can act as a template for deployment on any on any multi-architectural application and cloud.
+who_is_this_for: This topic explains how migrate a homogenous amd64 k8s cluster to a hybrid (arm64 and amd64) cluster using a multi-architecture container image on GKE. Ollama is the application used to demonstrate the migration. 
 
 
 learning_objectives:
   - Spin up a GKE cluster with amd64 and arm64 nodes.
-  - Apply ollama amd64-based and arm64-based Deployments and Services using the same container image.
-  - Ping, pull models, and make inferences to experience each architectures' performance first-hand.
-  - Experiment further on your own by researching which existing, and future workloads could benefit most from single, or multi-architectural clusters.
+  - Apply Ollama amd64-based and arm64-based deployments and services using the same container image.
+  - Ping, pull models, and make inferences to experience the performance of each architecture.
 
 prerequisites:
     - A [Google Cloud account](https://console.cloud.google.com/).
-    - A computer with [Google Cloud CLI](/install-guides/gcloud) and [kubectl](/install-guides/kubectl/) installed.
+    - A local computer with the [Google Cloud CLI](/install-guides/gcloud) and [kubectl](/install-guides/kubectl/) installed.
     - The [GKE Cloud Plugin](https://cloud.google.com/kubernetes-engine/docs/how-to/cluster-access-for-kubectl#gcloud)
 
 
@@ -26,35 +25,34 @@ skilllevels: Introductory
 
 subjects: Containers and Virtualization
 cloud_service_providers: Google Cloud
-
 
 armips:
     - Neoverse
 
 operatingsystems:
     - Linux
-    - MacOs
+    - macOS
 
 tools_software_languages:
-  - LLM
-      - ollama
-      - GenAI
+    - LLM
+    - Ollama
+    - GenAI
 
 further_reading:
   - resource:
-      title: ollama - Get up and running with large language models
+      title: Ollama - Get up and running with large language models
       link: https://ollama.com/
       type: documentation
   - resource:
-      title: ollama API calls
+      title: Ollama API calls
       link: https://github.com/ollama/ollama/blob/main/docs/api.md
       type: documentation
   - resource:
       title: Dockerhub for Ollama
       link: https://hub.docker.com/r/ollama/ollama
       type: documentation
   - resource:
-      title: ollama build docs
+      title: Ollama build docs
       link: https://github.com/ollama/ollama/blob/main/docs/development.md
       type: documentation
   - resource:

content/learning-paths/servers-and-cloud-computing/multiarch_ollama_on_gke/_next-steps.md

@@ -0,0 +1,8 @@
+---
+# ================================================================================
+#       FIXED, DO NOT MODIFY THIS FILE
+# ================================================================================
+weight: 21                  # Set to always be larger than the content in this path to be at the end of the navigation.
+title: "Next Steps"         # Always the same, html page title.
+layout: "learningpathall"   # All files under learning paths have this same wrapper for Hugo processing.
+---