Reorder sections: coreai-opt description first, What is Core AI last; remove Links section

Author: Elizabeth Davis

docs/src/landing_page.md

@@ -1,22 +1,5 @@
 # Core AI Optimization Documentation
 
-## What is Core AI?
-
-Core AI is a set of technologies for deploying machine learning models on Apple hardware, covering the full model deployment lifecycle: from model optimization and conversion, to debugging, to app integration. Models run entirely on device on Apple silicon, with no server required.
-
-```{image} _images/core-ai-ecosystem.png
-:alt: Diagram of the Core AI ecosystem. At the top, Core AI Models provides ready-to-use models and examples. Core AI Optimization and Core AI PyTorch Extensions prepare models for deployment, producing a .aimodel file. Core AI Debugger and Xcode support integration and debugging. Core AI Framework runs models on device.
-:align: center
-```
-
-The Core AI ecosystem consists of the following components:
-
-- Convert PyTorch models to the Core AI model format (`.aimodel`) using [Core AI PyTorch Extensions](https://github.com/apple/coreai-torch)
-- Compress models with quantization, palettization, and pruning using [Core AI Optimization](https://github.com/apple/coreai-optimization)
-- Load and run models in an app with the [Core AI Framework](https://developer.apple.com/documentation/coreai)
-- Inspect, debug, and profile models using [Core AI Debugger](https://developer.apple.com/documentation/coreai/inspecting-debugging-and-profiling-core-ai-models)
-- Get popular open-source models with conversion, optimization, and Swift app integration code using [Core AI Models](https://github.com/apple/coreai-models)
-
 ## What is `coreai-opt`?
 
 `coreai-opt` is a Python library for compressing PyTorch models for deployment on Apple Silicon. It allows you to apply compression-based optimizations (such as quantization or palettization) to any PyTorch model, producing a transformed PyTorch model that can be converted to a Core AI model and run with the [Core AI](https://developer.apple.com/documentation/coreai) framework.
@@ -71,8 +54,19 @@ For an overview of the generic structure of `coreai-opt` APIs, see [How to use c
 
 For end-to-end examples on API usage and common workflows, see [MNIST examples](examples/toy_models.md) and [model examples](examples/model_examples.md).
 
-## Links to related Core AI components
+## What is Core AI?
+
+Core AI is a set of technologies for deploying machine learning models on Apple hardware, covering the full model deployment lifecycle: from model optimization and conversion, to debugging, to app integration. Models run entirely on device on Apple silicon, with no server required.
+
+```{image} _images/core-ai-ecosystem.png
+:alt: Diagram of the Core AI ecosystem. At the top, Core AI Models provides ready-to-use models and examples. Core AI Optimization and Core AI PyTorch Extensions prepare models for deployment, producing a .aimodel file. Core AI Debugger and Xcode support integration and debugging. Core AI Framework runs models on device.
+:align: center
+```
+
+The Core AI ecosystem consists of the following components:
 
-- **[coreai-torch](https://github.com/apple/coreai-torch)** — Python library for converting PyTorch models to the Core AI (`.aimodel`) format.
-- **[coreai-models](https://github.com/apple/coreai-models)** — GitHub repository with example models demonstrating how to convert, optimize, and re-author models for deployment with Core AI. Several of the LLMs in there are compressed to ~4–5 bits using `coreai-opt`. The repo also contains a number of AI skills, including some that wrap `coreai-opt` workflows.
-- **[Core AI framework](https://developer.apple.com/documentation/coreai)** — Apple's on-device AI framework that runs `.aimodel` models.
+- Convert PyTorch models to the Core AI model format (`.aimodel`) using [Core AI PyTorch Extensions](https://github.com/apple/coreai-torch)
+- Compress models with quantization, palettization, and pruning using [Core AI Optimization](https://github.com/apple/coreai-optimization)
+- Load and run models in an app with the [Core AI Framework](https://developer.apple.com/documentation/coreai)
+- Inspect, debug, and profile models using [Core AI Debugger](https://developer.apple.com/documentation/coreai/inspecting-debugging-and-profiling-core-ai-models)
+- Get popular open-source models with conversion, optimization, and Swift app integration code using [Core AI Models](https://github.com/apple/coreai-models)