From 8fa15050bca44a021a4ccc6f2e4fe9f895773c9e Mon Sep 17 00:00:00 2001
From: Patrick Kidger <33688385+patrick-kidger@users.noreply.github.com>
Date: Wed, 7 Jun 2023 15:35:14 +0100
Subject: [PATCH 1/2] Update ecosystem links.

---
 README.md | 14 +++++++++-----
 1 file changed, 9 insertions(+), 5 deletions(-)

diff --git a/README.md b/README.md
index d42554b..c7c7ab2 100644
--- a/README.md
+++ b/README.md
@@ -41,15 +41,19 @@ Available at [https://docs.kidger.site/jaxtyping](https://docs.kidger.site/jaxty
 
 ## Finally
 
-### See also: other tools in the JAX ecosystem
+### See also: other libraries in the JAX ecosystem
 
-Neural networks: [Equinox](https://github.com/patrick-kidger/equinox).
+[Equinox](https://github.com/patrick-kidger/equinox): neural networks.
 
-Numerical differential equation solvers: [Diffrax](https://github.com/patrick-kidger/diffrax).
+[Optax](https://github.com/deepmind/optax): first-order gradient (SGD, Adam, ...) optimisers.
 
-Computer vision models: [Eqxvision](https://github.com/paganpasta/eqxvision).
+[Diffrax](https://github.com/patrick-kidger/diffrax): numerical differential equation solvers.
 
-SymPy<->JAX conversion; train symbolic expressions via gradient descent: [sympy2jax](https://github.com/google/sympy2jax).
+[Lineax](https://github.com/google/lineax): linear solvers and linear least squares.
+
+[Eqxvision](https://github.com/paganpasta/eqxvision): computer vision models.
+
+[sympy2jax](https://github.com/google/sympy2jax): SymPy<->JAX conversion; train symbolic expressions via gradient descent.
 
 ### Disclaimer
 

From edc34f14f88a7c18a75513d83cbcd6a9e0b12d53 Mon Sep 17 00:00:00 2001
From: Patrick Kidger <33688385+patrick-kidger@users.noreply.github.com>
Date: Wed, 7 Jun 2023 15:35:45 +0100
Subject: [PATCH 2/2] Update ecosystem links.

---
 docs/index.md | 14 ++++++++++++++
 1 file changed, 14 insertions(+)

diff --git a/docs/index.md b/docs/index.md
index 905c426..ab33b21 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -40,3 +40,17 @@ def accepts_pytree_of_arrays(x: PyTree[Float[Array, "batch c1 c2"]]):
 ## Next steps
 
 Have a read of the [Array annotations](./api/array.md) documentation on the left-hand bar!
+
+## See also: other libraries in the JAX ecosystem
+
+[Equinox](https://github.com/patrick-kidger/equinox): neural networks.
+
+[Optax](https://github.com/deepmind/optax): first-order gradient (SGD, Adam, ...) optimisers.
+
+[Diffrax](https://github.com/patrick-kidger/diffrax): numerical differential equation solvers.
+
+[Lineax](https://github.com/google/lineax): linear solvers and linear least squares.
+
+[Eqxvision](https://github.com/paganpasta/eqxvision): computer vision models.
+
+[sympy2jax](https://github.com/google/sympy2jax): SymPy<->JAX conversion; train symbolic expressions via gradient descent.