Add features to README

README.md

@@ -15,12 +15,20 @@ cases where the *Nature* paper differs from the source, we always defer to the
 latter. 
 
 OpenFold is built to support inference with AlphaFold's original JAX weights.
-Try it out with our [Colab notebook](https://colab.research.google.com/github/aqlaboratory/openfold/blob/main/notebooks/OpenFold.ipynb).
+It's also faster than the official code on GPU. Try it out for yourself with 
+our [Colab notebook](https://colab.research.google.com/github/aqlaboratory/openfold/blob/main/notebooks/OpenFold.ipynb).
 
 Unlike DeepMind's public code, OpenFold is also trainable. It can be trained 
 with [DeepSpeed](https://github.com/microsoft/deepspeed) and with either `fp16`
 or `bfloat16` half-precision.
 
+OpenFold is equipped with an implementation of low-memory attention 
+(Rabe & Staats 2021), which makes possible inference on extremely long chains.
+
+We also make available efficient scripts for generating alignments. We've
+used them to generate millions of alignments that will be released alongside
+original OpenFold weights, trained from scratch using our code (more on that soon).
+
 ## Installation (Linux)
 
 All Python dependencies are specified in `environment.yml`. For producing sequence