tweaks - based on roadshow slides

owilliams320 · Feb 16, 2024 · 639b404 · 639b404
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diff --git a/docs/explore-and-analyze-data/index.md b/docs/explore-and-analyze-data/index.md
@@ -4,7 +4,7 @@ sidebar_position: 2
 
 # Explore and analyze data
 
-Learn about AI Unlimited projects, and how to use [ClearScape Analytics](https://www.teradata.com/platform/clearscape-analytics?) functions with your large-scale data sets.
+Learn about AI Unlimited projects, and how to use [ClearScape Analytics](https://www.teradata.com/platform/clearscape-analytics?) functions with your large-scale datasets.
 
 - [Create your first project](/docs/explore-and-analyze-data/create-first-project.md)
 - See the [project lifecycle](/docs/explore-and-analyze-data/project-lifecycle.md), at a glance

diff --git a/docs/install-ai-unlimited/index.md b/docs/install-ai-unlimited/index.md
@@ -13,15 +13,15 @@ import TabItem from '@theme/TabItem';
 
 # Get started
 
-***MEM: Does this content pick up from the right context? What is the user thinking, feeling, and doing when they first arrive here? How did they get here?***
+***MEM: To keep in mind: Does this content pick up from the right context? What is the user thinking, feeling, and doing when they first arrive here? How did they get here?***
 
 AI Unlimited is a self-service, on-demand platform that enables you to deploy Teradata's compute engine on your cloud service provider (CSP) and connect it to your data lake. You deploy the engine only as needed for your analytics projects.
 
-In a JupyterLab notebook, you use Teradata's [ClearScape Analytics](https://www.teradata.com/platform/clearscape-analytics?) functions to explore and analyze your large-scale datasets. You can suspend your project, then resume it, whenever you want and pay only for the compute resources you use.
+In a JupyterLab notebook, you use Teradata's [ClearScape Analytics](https://www.teradata.com/platform/clearscape-analytics?) functions to explore your large-scale datasets and experiment with analytics. You can suspend your project, then resume it, whenever you want and pay only for the compute resources you use.
 
 AI Unlimited has these elements:
 - The engine, on your cloud service provider (CSP)&mdash;AWS or Azure
-- Jupyter notebooks, with the AI Unlimited Jupyter Kernel, for running analytic workloads
+- Jupyter notebooks, with the AI Unlimited Jupyter Kernel, for running your workloads
 - Your object storage, on your CSP
 - Your GitHub or GitLab repository, for user authentication and storing project information
 - A web-based user interface where the administrator user monitors projects and all users copy their API key for connecting to the engine ***The purpose of the UI will rapidly evolve. Future-proof this bullet or be specific to PPP?***

diff --git a/docs/install-ai-unlimited/production/index.md b/docs/install-ai-unlimited/production/index.md
@@ -4,7 +4,7 @@ sidebar_position: 3
 
 # Production installation
 
-Are you ready to scale? Use the production installation to be ready for enterprise use. 
+Are you ready to scale? Use the production installation to be ready for enterprise use. ***MEM: Roadshow slide says "individuals and small teams." So how about "Is your team ready for AI Unlimited? Use the production installation."***
 
 This puts AI Unlimited on your cloud service provider (CSP) on a server instance without JupyterLab, which simplifies security and sizing. For the JupyterLab location, you have these options: