Update README.md

README.md

@@ -35,7 +35,7 @@ On AWS, you can access performant infrastructure, deployment resources, data gov
 
 ## Build and Scale AI/ML on AWS
 
-AWS offers a comprehensive suite of AI/ML tools and services that cater to every stage of the machine learning lifecycle. From model development and training to deployment and inference, AWS provides cutting-edge solutions such Amazon SageMaker AI as a fully-managed service for end-to-end development and deployment of models, Amazon Bedrock for building and scaling generative AI applications with foundation models, custom AI accelerator chips such as AWS Trainium for training and AWS Inferentia for inference, and pre-configured environments to streamline your ML workflows. Additionally, you can explore the Registry of Open Data to discover, access, and utilize diverse datasets for your AI/ML projects. Whether you're working on large language models, generative AI, computer vision, time-series forecasting, or natural language processing, scaling your projects on AWS is easy.
+AWS offers a comprehensive suite of AI/ML tools and services that cater to every stage of the machine learning lifecycle. From model development and training to deployment and inference, AWS provides cutting-edge solutions such as Amazon SageMaker AI, a fully-managed service for end-to-end development and deployment of models, Amazon Bedrock for building and scaling generative AI applications with foundation models, custom AI accelerator chips such as AWS Trainium for training and AWS Inferentia for inference, and pre-configured environments to streamline your ML workflows. Additionally, you can explore the Registry of Open Data to discover, access, and utilize diverse datasets for your AI/ML projects. Whether you're working on large language models, generative AI, computer vision, time-series forecasting, or natural language processing, scaling your projects on AWS is easy.
 
 Learn more about these services and others: