diff --git a/ch06/01_main-chapter-code/ch06.ipynb b/ch06/01_main-chapter-code/ch06.ipynb
index f80a03f..8d4d9f7 100644
--- a/ch06/01_main-chapter-code/ch06.ipynb
+++ b/ch06/01_main-chapter-code/ch06.ipynb
@@ -1687,6 +1687,21 @@
    ],
    "source": [
     "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
+    "\n",
+    "# Note:\n",
+    "# Uncommenting the following lines will allow the code to run on Apple Silicon chips, if applicable,\n",
+    "# which is approximately 2x faster than on an Apple CPU (as measured on an M3 MacBook Air).\n",
+    "# As of this writing, in PyTorch 2.4, the results obtained via CPU and MPS were identical.\n",
+    "# However, in earlier versions of PyTorch, you may observe different results when using MPS.\n",
+    "\n",
+    "#if torch.cuda.is_available():\n",
+    "#    device = torch.device(\"cuda\")\n",
+    "#elif torch.backends.mps.is_available():\n",
+    "#    device = torch.device(\"mps\")\n",
+    "#else:\n",
+    "#    device = torch.device(\"cpu\")\n",
+    "#print(f\"Running on {device} device.\")\n",
+    "\n",
     "model.to(device) # no assignment model = model.to(device) necessary for nn.Module classes\n",
     "\n",
     "torch.manual_seed(123) # For reproducibility due to the shuffling in the training data loader\n",
diff --git a/ch07/01_main-chapter-code/ch07.ipynb b/ch07/01_main-chapter-code/ch07.ipynb
index 9ac4f58..1db0a3d 100644
--- a/ch07/01_main-chapter-code/ch07.ipynb
+++ b/ch07/01_main-chapter-code/ch07.ipynb
@@ -1125,13 +1125,17 @@
    "source": [
     "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
     "\n",
-    "# If you have a Mac with Apple Silicon chip, you can uncomment the next lines of code\n",
-    "# to train the model on the Mac's GPU cores. However, as of this writing, this results in\n",
-    "# larger numerical deviations from the results shown in this chapter, because Apple Silicon\n",
-    "# support in PyTorch is still experimental\n",
+    "# Note:\n",
+    "# Uncommenting the following lines will allow the code to run on Apple Silicon chips, if applicable,\n",
+    "# which is much faster than on an Apple CPU (as measured on an M3 MacBook Air).\n",
+    "# However, the resulting loss values may be slightly different.\n",
     "\n",
-    "# if torch.backends.mps.is_available():\n",
-    "#     device = torch.device(\"mps\")\n",
+    "#if torch.cuda.is_available():\n",
+    "#    device = torch.device(\"cuda\")\n",
+    "#elif torch.backends.mps.is_available():\n",
+    "#    device = torch.device(\"mps\")\n",
+    "#else:\n",
+    "#    device = torch.device(\"cpu\")\n",
     "\n",
     "print(\"Device:\", device)"
    ]
@@ -2762,7 +2766,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.6"
+   "version": "3.11.4"
   }
  },
  "nbformat": 4,