Update semantic_operators.ipynb

Rename semantic operator to AI operator in the introduction.

notebooks/experimental/semantic_operators.ipynb

@@ -25,18 +25,18 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# BigQuery DataFrames Semantic Operator Demo"
+    "# BigQuery DataFrames AI (semantic) Operator Demo"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The BigQuery DataFrames team implements semantics operators as described in the \"Lotus\" paper: https://arxiv.org/pdf/2407.11418.\n",
+    "The BigQuery DataFrames team implements AI operators inspired by the \"Lotus\" paper: https://arxiv.org/pdf/2407.11418.\n",
     "\n",
-    "This notebook gives you a hands-on preview of semantic operator APIs powered by LLM. You can open this notebook on Google Colab [here](https://colab.research.google.com/github/googleapis/python-bigquery-dataframes/blob/main/notebooks/experimental/semantic_operators.ipynb). \n",
+    "This notebook gives you a hands-on preview of AI operator APIs powered by LLM. You can open this notebook on Google Colab [here](https://colab.research.google.com/github/googleapis/python-bigquery-dataframes/blob/main/notebooks/experimental/semantic_operators.ipynb). \n",
     "\n",
-    "The notebook has two sections. The first section introduces the API syntax with examples, with the aim to get you familiar with how semantic operators work. The second section applies semantic operators on a large real-world dataset. You will also find some performance statistics there."
+    "The notebook has two sections. The first section introduces the API syntax with examples, with the aim to get you familiar with how AI operators work. The second section applies AI operators on a large real-world dataset. You will also find some performance statistics there."
    ]
   },
   {