Updates to metadata section.

colabs/artifact_basics/Artifact_Basics.ipynb

@@ -234,7 +234,7 @@
         "id": "AyANijPlIN5m"
       },
       "source": [
-        "# Update an Artifact"
+        "# Update Artifact version metadata"
       ]
     },
     {
@@ -243,7 +243,7 @@
         "id": "e4psfYzGeAVS"
       },
       "source": [
-        "You can pass new values to update the `description`, `metadata`, and `alias` of an artifact. Call the `save()` method to update the artifact on the W&B servers. You can update an artifact during or outside a W&B Run.\n",
+        "You can update the `description`, `metadata`, and `alias` of an artifact on the W&B platform during or outside a W&B Run.\n",
         "\n",
         "\n",
         "This example changes the `description` of the `my_first_artifact` artifact inside a run:"
@@ -292,10 +292,10 @@
       "source": [
         "run = wandb.init(project=\"artifact-basics\")\n",
         "artifact = run.use_artifact(artifact_or_name=\"my_first_artifact:latest\")\n",
-        "# downloads the artifact to a local directory.\n",
+        "# This will download the specified artifact to where your code is running\n",
         "datadir = artifact.download()\n",
         "run.finish()\n",
-        "# prints the path of the current artifact directory\n",
+        "# Prints the path of the current artifact directory\n",
         "print(u'\\u2500' * 10)\n",
         "print(\"Data directory located at:\" + datadir)"
       ]
@@ -333,9 +333,9 @@
       "source": [
         "# Next steps\n",
         "1. [Artifacts Python reference documentation](https://docs.wandb.ai/ref/python/artifact): Deep dive into artifact parameters and advanced methods.\n",
-        "2. [Lineage](https://docs.wandb.ai/guides/artifacts/explore-and-traverse-an-artifact-graph): View lineage graphs, which show artifacts logged by a run as well as artifacts used by specific run. \n",
+        "2. [Lineage](https://docs.wandb.ai/guides/artifacts/explore-and-traverse-an-artifact-graph): View lineage graphs, which are automatically built when using W&B artifact system, providing an auditable visual overview of the relationships between specific artifact versions, datasets models and runs.\n",
         "3. [Model Registry](https://docs.wandb.ai/guides/model_registry): Learn how to centralize your best artifact versions in a shared registry.\n",
-        "4. [Artifact Automations](https://docs.wandb.ai/guides/artifacts/project-scoped-automations): Automate downstream actions for versioning artifacts.\n",
+        "4. [Artifact Automations](https://docs.wandb.ai/guides/artifacts/project-scoped-automations): Automatically run specific Weights & Biases jobs based on changes to your artifacts, such as automatically training a new model each time a new version of the training data is logged.\n",
         "5. [Artifacts FAQ](https://docs.wandb.ai/guides/artifacts/artifacts-faqs): Frequently asked questions on Artifact security, workflows, and retention policy."
       ]
     }