diff --git a/docs/blog/posts/multimodal-gemini.md b/docs/blog/posts/multimodal-gemini.md
index 95d14cbca..eb7e38da8 100644
--- a/docs/blog/posts/multimodal-gemini.md
+++ b/docs/blog/posts/multimodal-gemini.md
@@ -172,12 +172,6 @@ The Gemini model analyzes the video and provides structured recommendations. Her
 9. **Kin no Kotte Ushi**: A shop specializing in Hida Wagyu Beef Sushi.
 10. **Shirakawa-go**: A World Heritage Site in Gifu Prefecture.
 
-## Conclusion
-
-This example demonstrates the power of combining multimodal AI with structured output parsing. By using Gemini with Instructor, we can extract rich, structured information from video content, opening up new possibilities for travel recommendation systems, content analysis, and more.
-
-The ability to process video inputs and generate structured data outputs can be applied to various domains beyond travel, such as education, entertainment, and market research. As multimodal AI continues to evolve, we can expect even more sophisticated applications that bridge the gap between visual content and structured data.
-
 ## Limitations, Challenges, and Future Directions
 
 While the current approach demonstrates the power of multimodal AI for video analysis, there are several limitations and challenges to consider: