Amazon A2I helps developers add human review for model predictions to new or existing applications using reviewers from Mechanical Turk, third party vendors, or their own employees. Amazon A2I makes it easier for developers to build the human review system, structure the review process, and manage the human review workforce. For example, developers could use Amazon A2I to quickly spin up and manage a workforce of humans to review and validate the accuracy of machine learning predictions for an application that extracts financial information from scanned mortgage documents or an application that uses image recognition to identify counterfeit items online, so that the quality of results improve over time. There are no upfront commitments to use Amazon A2I, and users pay only for each review needed. Today, machine learning provides highly accurate predictions (known as "inferences") for a variety of use cases, including identifying objects in images, extracting text from scanned documents, or transcribing and understanding spoken language.

G4 instances provide the industry's most cost-effective machine learning inference for applications, like adding metadata to an image, object detection, recommender systems, automated speech recognition, and language translation. G4 instances also provide a very cost-effective platform for building and running graphics-intensive applications, such as remote graphics workstations, video transcoding, photo-realistic design, and game streaming in the cloud. Machine learning involves two processes that require compute – training and inference. Training entails using labeled data to create a model that is capable of making predictions, a compute-intensive task that requires powerful processors and high-speed networking. Inference is the process of using a trained machine learning model to make predictions, which typically requires processing a lot of small compute jobs simultaneously, a task that can be most cost-effectively handled by accelerating computing with energy-efficient NVIDIA GPUs.

Machine learning involves two processes that require compute – training and inference.

Amazon Web Services has announced the general availability of Amazon Forecast, a fully managed service that uses machine learning to deliver highly accurate forecasts based on the same technology that powers Amazon.com. Amazon uses forecasting to make sure that the right product is in the right place at the right time by predicting demand for hundreds of millions of products every day. Amazon Forecast uses this same technology to build precise forecasts for virtually any business condition, including product demand and sales, infrastructure requirements, energy needs, and staffing levels – with predictions that are up to 50% more accurate than traditional methods. Amazon Forecast is easy to use and requires no machine learning experience. The service automatically provisions the necessary infrastructure, processes data, and builds custom, private machine learning models that are hosted on AWS and ready to make predictions.

Amazon uses forecasting to make sure that the right product is in the right place at the right time by predicting demand for hundreds of millions of products every day. Amazon Forecast uses this same technology to build precise forecasts for virtually any business condition, including product demand and sales, infrastructure requirements, energy needs, and staffing levels – with predictions that are up to 50% more accurate than traditional methods. Amazon Forecast is easy to use and requires no machine learning experience. The service automatically provisions the necessary infrastructure, processes data, and builds custom, private machine learning models that are hosted on AWS and ready to make predictions. To get started with Amazon Forecast, visit https://aws.amazon.com/forecast/.