In my recent projects, I've extensively used AWS for deploying and scaling AI models. For instance, I utilized AWS EC2 instances to host machine learning models, which allowed for flexible scaling based on demand. I also leveraged AWS S3 for storing large datasets, ensuring efficient data retrieval during model training and inference. To manage and automate deployments, I used AWS Lambda and AWS Elastic Beanstalk, which streamlined the process and reduced manual intervention. Additionally, I implemented AWS CloudWatch to monitor performance and set up alerts for any anomalies, ensuring the models remained reliable and responsive. This approach not only enhanced the scalability of the models but also improved their overall efficiency and reliability.