Amazon AI – Bringing powerful artificial intelligence to all developers 1/3
Amazon AI services bring natural language understanding (NLU), automatic speech recognition (ASR), visual search and image recognition, text-to-speech (TTS), and machine learning (ML) technologies within the reach of every developer. Based on the same proven, highly scalable products and services built by the thousands of deep learning and machine learning experts across Amazon, Amazon AI services provide high-quality, high-accuracy AI capabilities that are scalable and cost-effective.
In addition, the AWS Deep Learning AMI provides a way for AI developers and researchers to quickly and easily begin using any of the major deep learning frameworks to train sophisticated, custom AI models; experiment with new algorithms; and learn new deep learning skills and techniques on AWS’ massive compute infrastructure.
Our approach to AI is made up of three main layers that sit on top of the AWS infrastructure:
AI Services: At the highest level, for developers who want access to AI technologies without having to train or develop their own ML models, AWS provides a collection of highly scalable pre-trained and pre-tuned managed AI Services that do not require any previous artificial intelligence or deep learning knowledge in order to get started. Amazon Rekognition for image and facial analysis, Amazon Polly for text-to-speech, and Amazon Lex for building conversational chatbots with automatic speech recognition and natural language understanding (NLU) capabilities.
AI Platforms: For customers with existing data who want to focus on building custom inference models, we provide a set of AI platforms which remove the undifferentiated heavy lifting associated with deploying and managing AI training and model hosting. The Amazon Machine Learning service allows you to train custom machine learning models using your own data, without requiring deep machine learning skills or expertise. In addition, Apache Spark on Amazon EMR includ es MLlib for scalable machine learning algorithms.
AI Frameworks: Finally, we support all major AI frameworks for researchers and data scientists who want to build sophisticated and cutting-edge intelligent systems. Frameworks such as Apache MXNet, TensorFlow, Caffe, Theano, Torch, Keras, and CNTK provide flexible programming models for training custom models at scale. The AWS Deep Learning AMI, available for both Amazon Linux and Ubuntu, provides all of these frameworks pre-installed and configured on a convenient Amazon Machine Image to help you get started quickly and easily.
AI Infrastructure: Deep learning frameworks, like Apache MXNet, use neural nets, which involve the process of multiplying a lot of matrices. Amazon EC2 P2 instances provide powerful Nvidia GPUs to substantially accelerate the time to complete these computations, so you can train your models in a fraction of the time required by traditional CPUs. After training, Amazon EC2 C4 compute-optimized and M4 general purpose instances are ideally suited for running inferences with the trained model. In addition, AWS Lambda lets you simplify your operations with serverless machine learning predictions, while AWS Greengrass lets you run AI IoT applications seamlessly across the AWS Cloud and local devices.