Update README.md

libs/ai-endpoints/README.md

@@ -1,10 +1,10 @@
-# NVIDIA NIMs
+# NVIDIA NIM Microservices
 
 The `langchain-nvidia-ai-endpoints` package contains LangChain integrations for chat models and embeddings powered by [NVIDIA AI Foundation Models](https://www.nvidia.com/en-us/ai-data-science/foundation-models/), and hosted on [NVIDIA API Catalog.](https://build.nvidia.com/)
 
-NVIDIA AI Foundation models are community and NVIDIA-built models and are NVIDIA-optimized to deliver the best performance on NVIDIA accelerated infrastructure.  Using the API, you can query live endpoints available on the NVIDIA API Catalog to get quick results from a DGX-hosted cloud compute environment. All models are source-accessible and can be deployed on your own compute cluster using NVIDIA NIM which is part of NVIDIA AI Enterprise.
+NVIDIA AI Foundation models are community and NVIDIA-built models and are NVIDIA-optimized to deliver the best performance on NVIDIA accelerated infrastructure.  Using the API, you can query live endpoints available on the NVIDIA API Catalog to get quick results from a DGX-hosted cloud compute environment. All models are source-accessible and can be deployed on your own compute cluster using NVIDIA NIM™ microservices which is part of NVIDIA AI Enterprise.
 
-Models can be exported from NVIDIA’s API catalog with NVIDIA NIM, which is included with the NVIDIA AI Enterprise license, and run them on-premises, giving Enterprises ownership of their customizations and full control of their IP and AI application. NIMs are packaged as container images on a per model/model family basis and are distributed as NGC container images through the NVIDIA NGC Catalog. At their core, NIMs are containers that provide interactive APIs for running inference on an AI Model. 
+Models can be exported from NVIDIA’s API catalog with NVIDIA NIM, which is included with the NVIDIA AI Enterprise license, and run them on-premises, giving Enterprises ownership of their customizations and full control of their IP and AI application. NIM microservices are packaged as container images on a per model/model family basis and are distributed as NGC container images through the NVIDIA NGC Catalog. At their core, NIM microservices are containers that provide interactive APIs for running inference on an AI Model. 
 
 Below is an example on how to use some common functionality surrounding text-generative and embedding models.
 
@@ -42,10 +42,10 @@ result = llm.invoke("Write a ballad about LangChain.")
 print(result.content)
 ```
 
-## Working with NVIDIA NIMs
+## Working with NVIDIA NIM Microservices
 When ready to deploy, you can self-host models with NVIDIA NIM—which is included with the NVIDIA AI Enterprise software license—and run them anywhere, giving you ownership of your customizations and full control of your intellectual property (IP) and AI applications.
 
-[Learn more about NIMs](https://developer.nvidia.com/blog/nvidia-nim-offers-optimized-inference-microservices-for-deploying-ai-models-at-scale/)
+[Learn more about NIM microservices](https://developer.nvidia.com/blog/nvidia-nim-offers-optimized-inference-microservices-for-deploying-ai-models-at-scale/)
 
 ```python
 from langchain_nvidia_ai_endpoints import ChatNVIDIA, NVIDIAEmbeddings, NVIDIARerank