From caac6b7b6d96453c0969bdf83eb6f2bf3f4f17e5 Mon Sep 17 00:00:00 2001
From: davidastart <37092569+davidastart@users.noreply.github.com>
Date: Sun, 1 Sep 2024 16:30:07 -0400
Subject: [PATCH] Update introduction.md

---
 ai-vector-image/introduction/introduction.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ai-vector-image/introduction/introduction.md b/ai-vector-image/introduction/introduction.md
index a073b771..2591ed3c 100644
--- a/ai-vector-image/introduction/introduction.md
+++ b/ai-vector-image/introduction/introduction.md
@@ -10,7 +10,7 @@ The workflow diagram illustrates the following steps:
 
 - Image Input: Start with an image that needs to be described.
 - Description Generation: Use a model to generate a textual description or caption for the image.
-- Text Vectorization: Pass the generated description through a second model (embededd in the database) that creates vectors from the text.
+- Text Vectorization: Pass the generated description through a second model (embedded in the database) that creates vectors from the text.
 - APEX Application: Create a quick application leveraging an embedded text model and AI Vector Search
 
 This method makes the solution more versatile since the text embeddings and search occur within the database allowing any application to be developed.