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README.md

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-Modula is a deep learning framework designed for graceful scaling. Neural networks written in Modula automatically transfer learning rate across scale.
+Modula will be a Python framework for fast, scalable & robust deep learning. And [the docs](https://docs.modula.systems/) will be a good place to learn the mathematics of deep learning.
 
-We are slowly writing [the Modula docs](https://docs.modula.systems/). Check them out for an accessible introduction to scaling theory and the Modula API. Also, here are some [slides](https://docs.google.com/presentation/d/1mCp6weIty9BzFFmx7LUGk2MPmNi-m-yKjigQ9wnycng/edit?usp=sharing) for a talk that Jeremy gave, that provide a more visual introduction to Modula. And here is [Modulax](https://github.com/GallagherCommaJack/modulax/) by Jack Gallagher. And here is a barebones implementation of [Modula in NumPy](https://colab.research.google.com/drive/1lKS15RJilGsstYP5JDQKSn3Z7TUUYIDQ?usp=sharing).
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-Modula is an experimental framework based on our research paper: [Scalable Optimization in the Modular Norm](https://arxiv.org/abs/2405.14813).
+More resources:
+- [slides](https://docs.google.com/presentation/d/1mCp6weIty9BzFFmx7LUGk2MPmNi-m-yKjigQ9wnycng/edit?usp=sharing) for a talk that Jeremy gave
+- [Modulax](https://github.com/GallagherCommaJack/modulax/) by Jack Gallagher
+- a barebones implementation of [Modula in NumPy](https://colab.research.google.com/drive/1lKS15RJilGsstYP5JDQKSn3Z7TUUYIDQ?usp=sharing).
 
 ## Quick start