diff --git a/README.md b/README.md
index d61fdee644..578c3cce8b 100644
--- a/README.md
+++ b/README.md
@@ -197,7 +197,7 @@ openai.api_key = "sk-..."  # supply your API key however you choose
 text_string = "sample text"
 
 # choose an embedding
-model_id = "text-similarity-davinci-001"
+model_id = "text-embedding-ada-002"
 
 # compute the embedding of the text
 embedding = openai.Embedding.create(input=text_string, model=model_id)['data'][0]['embedding']
diff --git a/openai/embeddings_utils.py b/openai/embeddings_utils.py
index f1d438c9c0..ca30545826 100644
--- a/openai/embeddings_utils.py
+++ b/openai/embeddings_utils.py
@@ -15,7 +15,7 @@
 
 
 @retry(wait=wait_random_exponential(min=1, max=20), stop=stop_after_attempt(6))
-def get_embedding(text: str, engine="text-similarity-davinci-001", **kwargs) -> List[float]:
+def get_embedding(text: str, engine="text-embedding-ada-002", **kwargs) -> List[float]:
 
     # replace newlines, which can negatively affect performance.
     text = text.replace("\n", " ")
@@ -25,7 +25,7 @@ def get_embedding(text: str, engine="text-similarity-davinci-001", **kwargs) ->
 
 @retry(wait=wait_random_exponential(min=1, max=20), stop=stop_after_attempt(6))
 async def aget_embedding(
-    text: str, engine="text-similarity-davinci-001", **kwargs
+    text: str, engine="text-embedding-ada-002", **kwargs
 ) -> List[float]:
 
     # replace newlines, which can negatively affect performance.