refactor README introduction

Author: BerndDoser

README.md

@@ -4,8 +4,15 @@
 
 # Spherinator
 
-`Spherinator` and `HiPSter` are tools to provide much needed explorative access and visualization for multimodal data from extremely large astrophysical datasets, ranging from exascale cosmological simulations to multi-billion object observational galaxy surveys. `Spherinator` uses dimensionality reduction to learn a low-dimensional representation of galaxy structure, and `HiPSter` creates a interactive hierarchical spherical vizualization of the entire dataset. They currently support multichannel maps or images as input. `Spherinator` uses [PyTorch Lightning](https://lightning.ai/docs/pytorch/stable/) to implement a convolutional neural network (CNN) based variational autoencoder (VAE) with a spherical latent space.
-`HiPSter` creates HiPS tilings and a catalog which can be visualized interactively on the surface of a sphere using [Aladin Lite](https://github.com/cds-astro/aladin-lite).
+[Spherinator](https://github.com/HITS-AIN/Spherinator) and
+[HiPSter](https://github.com/HITS-AIN/HiPSter) are tools that provide explorative access
+and visualization for multimodal data from extremely large astrophysical datasets, ranging from
+exascale cosmological simulations to multi-billion object observational galaxy surveys.
+
+A variational autoencoder (VAE) will be trained using
+[PyTorch Lightning](https://lightning.ai/docs/pytorch/stable/)
+to compress the structural data into a low-dimensional spherical latent space.
+
 
 <p align="center">
   <img src="docs/assets/P404_f2.png" width="400" height="400">