In the last couple of years, AWS has shown a serious commitment to take their offerings in machine-learning/artificial intelligence space to a completely different levels. During its annual developer conference (AWS re:Invent) in 2017, AWS made some big announcements on its ML/AI offerings, which have also gained immense popularity since then. The following are some of the services, which are key from AWS' ML/AI portfolio perspective:

• Amazon SageMaker: This enables data scientists and developers to quickly and easily build, train, and deploy machine learning models with high-performance machine learning algorithms, broad framework support, and one-click training, tuning, and inference. Amazon SageMaker has a modular architecture so that you can use any or all of its capabilities in your existing machine learning workflows. For more information, you can refer to https://aws.amazon.com/sagemaker/.
• Amazon Rekognition: This is a service that makes it easy to add powerful visual analysis to your applications. Rekognition Image lets you easily build powerful applications to search, verify, and organize millions of images. Rekognition Video lets you extract motion-based context from stored or live stream videos and helps you analyze them. For more information, you can refer to https://aws.amazon.com/rekognition.
• Amazon Lex: This is a service for building conversational interfaces using voice and text. Powered by the same conversational engine as Alexa, Amazon Lex provides high quality speech recognition and language understanding capabilities, enabling an addition of sophisticated, natural language chatbots to new and existing applications. For more information, you can refer to https://aws.amazon.com/lex.
• Amazon Polly: This is a service that turns text into life-like speech. It enables existing applications to speak as a first-class feature and creates the opportunity for entirely new categories of speech-enabled products, from mobile apps and cars, to devices and appliances. For more information, you can refer to https://aws.amazon.com/polly.

Other than the preceding services, AWS also supports many of the popular machine learning frameworks and libraries, which are used by data scientists and developers on a regular basis, including Apache MXNet, TensorFlow, PyTorch, the Microsoft Cognitive Toolkit (CNTK), Caffe, Caffe2, Theano, Torch, Gluon, and Keras. These are offered as an Amazon Machine Image (AMI), so it is pretty easy to get started with just a few clicks. This clubbed with the GPU compute instances and instances with field programmable gate arrays (FPGAs) make the processing of complex algorithms and models much faster and easier, thereby ensuring that the overall platform is comprehensive to address any kind of ML/AI use cases.