Update README.md

Author: LukeWood

README.md

@@ -6,9 +6,9 @@
 
 # Mission
 
-KerasCV is a layered repository consisting of core components and modeling components.  The library is targeted at solving object detection, segmentation, and classification problems for auto-driving, robotics and on device applications.
+KerasCV is a layered repository consisting of core components and modeling components.
 
-On the core components, it is made of modular building blocks (ops, functions, layers, metrics, losses, callbacks) that standardizes APIs for computer vision concepts such as data-augmentation pipeline, bounding boxes, keypoints, point clouds, feature pyramid network, etc, so applied computer vision engineers can leverage to quickly assemble production-grade, state-of-the-art
+On the core components, it is made of modular building blocks (functions, layers, metrics, losses, callbacks) that standardizes APIs for computer vision concepts such as data-augmentation pipeline, bounding boxes, keypoints, point clouds, feature pyramid network, etc, so applied computer vision engineers can leverage to quickly assemble production-grade, state-of-the-art
 training and inference pipelines for common tasks such as image classification, object detection and segmentation, image data augmentation, etc.
 
 On the modeling components, it provides the most widely used models for each task such as ResNet family, MobileNet family, transformer-based models, anchor-based and anchor-free meta architectures, unet models, that are built on top of core components, highly composable and compatible with the Keras trainer (`model.fit`). It aims to provide pre-built models that are mixed-precision compatible, QAT compatible, and xla compilable during training, and generic model optimization tools for deployment on devices such as onboard GPUs, mobile, edge chips.