Adds introductory README.md content.
-# TensorFlow Federated
+<!-- Please keep the content of this file in sync with docs/_index.yaml -->
-**TensorFlow Federated** is a framework for implementing federated learning
-algorithms and other computations on privacy-sensitive decentralized data.
+# TensorFlow Federated
-TODO(b/112658581): Add TFF high level overview.
+TensorFlow Federated (TFF) is an open-source framework for collaborative
+computations on distributed data that does not require collecting data at a
+centralized location.
+
+The framework has initially been developed to facilitate open
+research and experimentation with [Federated Learning]
+(https://ai.googleblog.com/2017/04/federated-learning-collaborative.html),
+a technology that enables devices owned by end users to collaboratively
+learn a shared prediction model while keeping potentially sensitive training
+data on the devices, thus decoupling the ability to do machine learning from
+the need to collect and store the data in the cloud.
+
+With the interfaces provided by TFF, developers can test existing federated learning
+algorithms on their models and data, or design new experimental algorithms and
+run them on existing models and data, all within the same open source
+environment. The framework has been designed with compositionality in mind, and
+can be used to combine independently-developed techniques and components that
+offer complementary capabilities into larger systems.
+
+Beyond this, TFF also provides a set of building blocks that can be used to
+implement a variety of custom non-learning algorithms, such as analytics over
+sensitive distributed on-device data.
## Installation
