diff --git a/examples/Search_augmented_by_query_generation_and_embeddings_reranking.ipynb b/examples/Search_augmented_by_query_generation_and_embeddings_reranking.ipynb
index b75af15..48e3470 100644
--- a/examples/Search_augmented_by_query_generation_and_embeddings_reranking.ipynb
+++ b/examples/Search_augmented_by_query_generation_and_embeddings_reranking.ipynb
@@ -7,7 +7,7 @@
    "source": [
     "# Search augmented by query generation and embeddings reranking\n",
     "\n",
-    "Searching for relevant information can sometimes be like looking for a needle in a haystack, but don’t despair, GPTs can actually do a lot of this work for us. In this guide we explore a way to augment existing search systems with various AI techniques, helping us sift through the noise.\n",
+    "Searching for relevant information can sometimes feel like looking for a needle in a haystack, but don’t despair, GPTs can actually do a lot of this work for us. In this guide we explore a way to augment existing search systems with various AI techniques, helping us sift through the noise.\n",
     "\n",
     "There are two prominent approaches to using language models for information retrieval:\n",
     "\n",