diff --git a/mjx/mujoco/mjx/test_data/barkour_v0/README.md b/mjx/mujoco/mjx/test_data/barkour_v0/README.md
index b7cfdcef..4f5d970d 100644
--- a/mjx/mujoco/mjx/test_data/barkour_v0/README.md
+++ b/mjx/mujoco/mjx/test_data/barkour_v0/README.md
@@ -1,14 +1,4 @@
-# Google Barkour v0 Joystick Policy
-
-## Overview
-
-This folder contains a training script for a flat-terrain joystick policy for the [Barkour v0 Quadruped](https://ai.googleblog.com/2023/05/barkour-benchmarking-animal-level.html) which demonstrates sim2real transfer.
-
-`barkour_joystick.py` contains the environment definition, while the [colab](https://colab.research.google.com/github/google/brax/blob/main/experimental/barkour_v0/barkour_v0_joystick.ipynb) shows how to train the policy.
-
-<p float="left">
-  <img src="assets/joystick.gif" width="400">
-</p>
+# Google Barkour v0
 
 ## MJCF Instructions
 
diff --git a/mjx/mujoco/mjx/test_data/barkour_v0/assets/joystick.gif b/mjx/mujoco/mjx/test_data/barkour_v0/assets/joystick.gif
deleted file mode 100644
index b07f1afe..00000000
Binary files a/mjx/mujoco/mjx/test_data/barkour_v0/assets/joystick.gif and /dev/null differ
diff --git a/mjx/tutorial.ipynb b/mjx/tutorial.ipynb
index c6056318..befc6b3b 100644
--- a/mjx/tutorial.ipynb
+++ b/mjx/tutorial.ipynb
@@ -606,7 +606,7 @@
       "source": [
         "## Train Humanoid Policy\n",
         "\n",
-        "Let's now train a policy with PPO to make the Humanoid run forwards. Training takes about 8-9 minutes on a Tesla A100 GPU."
+        "Let's now train a policy with PPO to make the Humanoid run forwards. Training takes about 6 minutes on a Tesla A100 GPU."
       ]
     },
     {
@@ -1312,7 +1312,7 @@
       "source": [
         "## Train Policy\n",
         "\n",
-        "To train a policy with domain randomization, we pass in the domain randomization function into the brax train function; brax will call the domain randomization function when rolling out episodes. Training the quadruped takes  8-9 minutes on a Tesla A100 GPU."
+        "To train a policy with domain randomization, we pass in the domain randomization function into the brax train function; brax will call the domain randomization function when rolling out episodes. Training the quadruped takes 6 minutes on a Tesla A100 GPU."
       ]
     },
     {
@@ -1448,7 +1448,7 @@
       },
       "outputs": [],
       "source": [
-        "HTML(html.render(eval_env.sys, rollout))"
+        "HTML(html.render(eval_env.sys.replace(dt=eval_env.dt), rollout))"
       ]
     }
   ],