updated README

README.md

@@ -96,7 +96,7 @@ We hope that you find `AutonomySim` enjoyable to use and develop. Unlike other p
 
 ## Professional Services
 
-Robotics companies interested in having [Nervosys](https://nervosys.ai/) model their hardware/software and develop related AI models in `AutonomySim` can reach us directly via [e-mail](mailto:info@nervosys.ai). We would be delighted to offer our services, so that we may continue to support and improve this essential open-source robotics project.
+Robotics companies interested in having [Nervosys](https://nervosys.ai/) model their hardware/software and develop related AI models in `AutonomySim` can reach us directly at opensource@nervosys.ai. We are delighted to offer our services, so that we may continue to support and improve this essential open-source robotics project for the benefit of the community.
 
 ## Supported Operating Systems
 
@@ -125,8 +125,14 @@ Robotics companies interested in having [Nervosys](https://nervosys.ai/) model t
 - macOS 13 (Ventura)
 - macOS 14 (Sonoma)
 
+## Installation
+
+Coming soon. In the meantime, please see our GitHub Workflows for how to build the project.
+
 ## Getting Started
 
+Below are explanations and examples to help you get started.
+
 - [Project structure](https://nervosys.github.io/AutonomySim/project_structure.html)
 - [Development workflow](https://nervosys.github.io/AutonomySim/development_workflow.html)
 - [Settings](https://nervosys.github.io/AutonomySim/settings.html)
@@ -145,11 +151,13 @@ Robotics companies interested in having [Nervosys](https://nervosys.ai/) model t
 
 ## Documentation
 
+Project documentation and autogenerated API documentation:
+
 - [Main documentation](https://nervosys.github.io/AutonomySim/)
 - [C++ API documentation](https://nervosys.github.io/AutonomySim/api/cpp/html/index.html)
 - [Python API documentation](https://nervosys.github.io/AutonomySim/api/python/html/index.html)
 
-Figure 1 below provides an overview of the simulation architecture:
+Overview of the `AutonomySim` architecture:
 
 <p align="center">
   <img src="./media/images/shah2018_architecture.png" width="80%" alt="architecture">
@@ -159,6 +167,8 @@ Figure 1 below provides an overview of the simulation architecture:
 
 ## Tutorials
 
+Based on `AirSim`, the predecessor to `AutonomySim`.
+
 ### Videos
 
 - [Setting up AirSim with Pixhawk Tutorial](https://youtu.be/1oY8Qu5maQQ) by Chris Lovett
@@ -282,53 +292,31 @@ Unreal Engine includes built-in support.
 
 ## Machine Learning Applications
 
-### Learning Perception, Communication, Planning, and Control Models
-
-Coming soon.
-
-### Imitation or Apprenticeship Learning
-
-Coming soon. An example of recording control inputs and vehicle state for learning control systems.
-
-### Neural Radiance Fields
-
-Coming soon. Learning compressed 3-D radiative transfer models.
-
-### Large Language Models
-
-Coming soon. An example of using a large language model (LLM) to parse text commands into planning and control inputs for robotic systems. See [Eureka](https://eureka-research.github.io/).
-
-### Learning Surrogate Models or Emulators
-
-Coming soon.
-
-### Learning World Models
-
-Coming soon.
+- Learning Perception, Communication, Planning, and Control Models
+- Imitation or Apprenticeship Learning
+  - An example of recording control inputs and vehicle state for learning control systems.
+- Neural Radiance Fields
+  - Learning compressed 3-D radiative transfer models.
+- Large Language Models
+  - An example of using a large language model (LLM) to parse text commands into planning and control inputs for robotic systems. See [Eureka](https://eureka-research.github.io/).
+- Robotics Foundation Models
+- Learning Surrogate Models or Emulators
+- Learning World Models
 
 ## Other Applications
 
-### Sensor System Development
-
-Coming soon.
-
-### Locomotion System Development
-
-Coming soon. An example of learning structure, actuator, and locomotion models. This is useful, for example, for developing robotic systems that are robust to major structural failures, such as the loss of motors or legs.
-
-### Communication System Development
-
-Coming soon.
-
-### Data Randomization via Procedural Modeling
-
-Coming soon. A class of data augmentation to generate large amounts of diverse training data.
+- Sensor System Development
+- Locomotion System Development
+  - An example of learning structure, actuator, and locomotion models. This is useful, for example, for developing robotic systems that are robust to major structural failures, such as the loss of motors or legs.
+- Communication System Development
+- Data Randomization via Procedural Modeling
+  - A class of data augmentation to generate large amounts of diverse training data.
 
 ## Join the Community
 
 For updates or answers to your questions, join our GitHub Discussion group [here](https://github.com/nervosys/AutonomySim/discussions) or our Discord channel [here](https://discord.gg/Mu97ucWa). 
 
-For information on becoming a contributor, see the following section.
+For information on becoming a contributor, see the below section.
 
 ## Contributing