Add Intelligent Application section (#149)

* Add Intelligent Application section

* Update spiceaidocs/docs/index.md

Co-authored-by: Phillip LeBlanc <[email protected]>

* Update spiceaidocs/docs/index.md

Co-authored-by: Phillip LeBlanc <[email protected]>

* Update spiceaidocs/docs/intelligent-applications/index.md

Co-authored-by: Phillip LeBlanc <[email protected]>

* Tweak order

---------

Co-authored-by: Phillip LeBlanc <[email protected]>

spiceaidocs/docs/index.md

@@ -16,7 +16,7 @@ The Spice runtime is written in Rust and leverages industry leading technologies
 
 ## Why Spice?
 
-Spice makes querying data by SQL across one or more data sources simple and fast. Easily co-locate a managed working set of your data with your application or ML, locally accelerated in-memory, with DuckDB, or with an attached database like PostgreSQL for high-performance, low-latency queries.
+Spice makes querying data by SQL across one or more data sources simple and fast. Easily co-locate a managed working set of your data with your application or ML, locally accelerated in-memory with Arrow, with SQLite/DuckDB, or with an attached database like PostgreSQL for high-performance, low-latency queries.
 
 ### Before Spice
 
@@ -30,14 +30,20 @@ Spice makes querying data by SQL across one or more data sources simple and fast
 
 **1. Faster applications and frontends.** Accelerate and co-locate datasets with applications and frontends, to serve more concurrent queries and users with faster page loads and data updates.
 
-**2. Faster analytics and BI.** Faster, more responsive dashboards without massive compute costs.
+**2. Faster dashboards, analytics, and BI.** Faster, more responsive dashboards without massive compute costs.
 
 **3. Faster data pipelines, machine learning training and inferencing.** Co-locate datasets in pipelines where the data is needed to minimize data-movement and improve query performance.
 
+**4. Easily query many data sources.** Federated SQL query across databases, data warehouses, and data lakes using [Data Connectors](./data-connectors/index.md).
+
 :::warning[DEVELOPER PREVIEW]
 Spice is under active **alpha** stage development and is not intended to be used in production until its **1.0-stable** release. If you are interested in running Spice in production, please get in touch below so we can support you.
 :::
 
+### Intelligent Applications
+
+Spice enables developers to build both data _and_ AI-driven applications by co-locating data _and_ ML models with applications. Read more about the vision to enable the development of [intelligent AI-driven applications](./intelligent-applications/index.md).
+
 ### Connect with us
 
 We greatly appreciate and value your support! You can help Spice in a number of ways:

spiceaidocs/docs/intelligent-applications/index.md

@@ -0,0 +1,16 @@
+---
+title: 'Intelligent Applications'
+sidebar_label: 'Intelligent Applications'
+sidebar_position: 5
+description: 'Building intelligent data and AI-driven applications with Spice.ai'
+---
+
+As described in the blog post [Making Apps That Learn and Adapt](https://blog.spiceai.org/posts/2021/11/05/making-apps-that-learn-and-adapt/) the long-term vision for Spice.ai is to enable developers to easily build, deploy, and operate intelligent data and AI-driven applications.
+
+With Spice.ai OSS, federated data and ML models are colocated with applications, creating lightweight, high-performance, AI-copilot sidecars.
+
+<img src="https://user-images.githubusercontent.com/80174/140449760-97974f3c-8a78-4ea2-9ec5-843dc3cff5b6.png" alt="A Spice.ai Intelligent Application" />
+
+## The Intelligent Application Workflow
+
+Dataset definitions and ML Models are packaged as Spicepods and can be published and distributed through the [Spicerack.org](https://spicerack.org) Spicepod registry. Federated datasets are locally materialized, accelerated, and provided to colocated Models. Applications call high-performance, low-latency ML inference APIs for AI generation, insights, recommendations, and forecasts ultimately to make intelligent, AI-driven decisions. Contextual application and environmental data is ingested and replicated back to cloud-scale compute clusters where improved versions of Models are trained and fined-tuned. New versioned Models are automatically deployed to the runtime and are A/B tested and flighted by the application in realtime.

spiceaidocs/docs/machine-learning/index.md

@@ -2,11 +2,11 @@
 title: 'Machine Learning'
 sidebar_label: 'Machine Learning'
 description: ''
-sidebar_position: 5
+sidebar_position: 6
 ---
 
 :::warning[Early Preview]
 
 The Spice ML runtime is in its early preview phase and is subject to modifications.
 
-:::
+:::