diff --git a/site/_posts/2026-01-22-lesson_28_materials_update.md b/site/_posts/2026-01-22-lesson_28_materials_update.md
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+---
+layout: post
+title: "Lesson 28 materials update"
+date: 2026-01-22
+categories: resources
+---
+
+The lesson 28 demo has been split into parts 1 & 2, both are available on the Jupyter notebooks page. Both the new tensorflow-CPU devcontainer and the tensorflow-GPU devcontainer now run TensorBoard by default on startup. They also publish port 6006 to the host system so you can access TensorBoard in you browser and include the TensorBoard VS Code extension. Links here: [tensorflow-CPU](https://github.com/gperdrizet/tensorflow-CPU), [tensorflow-GPU](https://github.com/gperdrizet/tensorflow-GPU#).
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diff --git a/site/devops_pages/tensorflow.md b/site/devops_pages/tensorflow.md
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@@ -99,7 +99,9 @@ Build cuda_12.5.r12.5/compiler.34385749_0
 
 Here is the link to the GitHub repo that will walk you through setting up docker and using the devcontainer: [gperdrizet/tensorflow-GPU](https://github.com/gperdrizet/tensorflow-GPU#).
 
-Target is NVIDIA TensorFlow release 24.06 container. This gets us:
+**Note**: there is now a CPU only version of the devcontainer which provides a similar environment for folks without an NVIDIA GPU. You can find it here: [gperdrizet/tensorflow-CPU](https://github.com/gperdrizet/tensorflow-CPU).
+
+For folks with an NVIDIA GPU, the target environment is a NVIDIA TensorFlow release 24.06 container. This gets us:
 
 - CUDA: 12.5
 - Python: 3.10