diff --git a/gemini/grounding/intro-grounding-gemini.ipynb b/gemini/grounding/intro-grounding-gemini.ipynb
index 0b820f37d3..a2613dfcd9 100644
--- a/gemini/grounding/intro-grounding-gemini.ipynb
+++ b/gemini/grounding/intro-grounding-gemini.ipynb
@@ -376,79 +376,25 @@
    "source": [
     "### Text generation grounded in Google Search results\n",
     "\n",
-    "Now you can add the `tools` keyword arg with a grounding tool of `grounding.GoogleSearchRetrieval()` to instruct the LLM to first perform a Google Search with the prompt, then construct an answer based on the web search results:"
+    "Now you can add the `tools` keyword arg with a grounding tool of `grounding.GoogleSearchRetrieval()` to instruct the LLM to first perform a Google Search with the prompt, then construct an answer based on the web search results.\n",
+    "\n",
+    "**Note:** Before running the sample below, you will need to opt-in for Grounding with Google Search using [this form](https://docs.google.com/forms/d/e/1FAIpQLSfj7SJNAqXOe7vB9Re-WtwJedTWjHkBKZ6OHaLoGoXRG93ymg/viewform). If you use this service in a production application, you will also need to [use a Google Search entry point](https://cloud.google.com/vertex-ai/generative-ai/docs/multimodal/grounding-search-entry-points)."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "metadata": {},
    "outputs": [
     {
-     "data": {
-      "text/markdown": [
-       "- Price: Starting from USD 499\n",
-       "- Storage size options: 128 GB and 256 GB\n",
-       "- Available colors: Porcelain, Rose, and Hazel"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "candidates {\n",
-       "  content {\n",
-       "    role: \"model\"\n",
-       "    parts {\n",
-       "      text: \"- Price: Starting from USD 499\\n- Storage size options: 128 GB and 256 GB\\n- Available colors: Porcelain, Rose, and Hazel\"\n",
-       "    }\n",
-       "  }\n",
-       "  finish_reason: STOP\n",
-       "  safety_ratings {\n",
-       "    category: HARM_CATEGORY_HATE_SPEECH\n",
-       "    probability: NEGLIGIBLE\n",
-       "  }\n",
-       "  safety_ratings {\n",
-       "    category: HARM_CATEGORY_DANGEROUS_CONTENT\n",
-       "    probability: NEGLIGIBLE\n",
-       "  }\n",
-       "  safety_ratings {\n",
-       "    category: HARM_CATEGORY_HARASSMENT\n",
-       "    probability: NEGLIGIBLE\n",
-       "  }\n",
-       "  safety_ratings {\n",
-       "    category: HARM_CATEGORY_SEXUALLY_EXPLICIT\n",
-       "    probability: NEGLIGIBLE\n",
-       "  }\n",
-       "  grounding_metadata {\n",
-       "    web_search_queries: \"Pixel Tablet price, colors, and storage size options?\"\n",
-       "    grounding_attributions {\n",
-       "      web {\n",
-       "        uri: \"https://store.google.com/product/pixel_tablet_specs\"\n",
-       "        title: \"Pixel Tablet Technical Specs - Google Store\"\n",
-       "      }\n",
-       "      segment {\n",
-       "        end_index: 119\n",
-       "      }\n",
-       "      confidence_score: 0.778106511\n",
-       "    }\n",
-       "  }\n",
-       "}\n",
-       "usage_metadata {\n",
-       "  prompt_token_count: 17\n",
-       "  candidates_token_count: 38\n",
-       "  total_token_count: 55\n",
-       "}"
-      ]
-     },
-     "execution_count": 25,
-     "metadata": {},
-     "output_type": "execute_result"
+     "ename": "",
+     "evalue": "",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31mRunning cells with 'Python 3.12.2' requires the ipykernel package.\n",
+      "\u001b[1;31mRun the following command to install 'ipykernel' into the Python environment. \n",
+      "\u001b[1;31mCommand: '/opt/homebrew/bin/python3 -m pip install ipykernel -U --user --force-reinstall'"
+     ]
     }
    ],
    "source": [