AWS Announces Three New Amazon AI Services
Amazon Lex, the technology that powers Amazon Alexa, enables any developer to build rich, conversational user experiences for web, mobile, and connected device apps; preview starts today
Amazon Polly transforms text into lifelike speech, enabling apps to talk with 47 lifelike voices in 24 languages
Amazon Rekognition makes it easy to add image analysis to applications, using powerful deep learning-based image and face recognition
Until now, very few developers have been able to build, deploy, and broadly scale apps with AI capabilities because doing so required access to vast amounts of data, and specialized expertise in machine learning and neural networks. Effectively applying AI involves extensive manual effort to develop and tune many different types of machine learning and deep learning algorithms (e.g. automatic speech recognition, natural language understanding, image classification), collect and clean the training data, and train and tune the machine learning models. And this process must be repeated for every object, face, voice, and language feature in an application. Amazon AI services eliminate all of this heavy lifting, making AI broadly accessible to all app developers by offering Amazon’s powerful and proven deep learning algorithms and technologies as fully managed services that any developer can access through an API call or a few clicks in the AWS Management Console. Amazon AI services make the full power of Amazon’s natural language understanding, speech recognition, text-to-speech, and image analysis technologies available at any scale, for any app, on any device, anywhere.
“The combination of better algorithms and broad access to massive amounts of data and cost-effective computing power provided by the cloud is making AI a reality for application developers. AWS is home to some of the most innovative and creative AI applications in use today,” said
Intelligent conversations with Amazon Lex
Amazon Lex is a new service for building conversational interfaces using voice and text that is built on the same automatic speech recognition (ASR) technology and natural language understanding (NLU) that powers Amazon Alexa. Amazon Lex makes it easy to bring sophisticated, natural language capabilities to virtually any app. Developers can build and test bots (conversational apps that perform automated tasks like checking the weather or booking flights) directly from the AWS Management Console by typing in a few sample phrases (e.g., “find a flight,” or “book a flight”) along with instructions for getting the required parameters to complete task (e.g., travel date and destination) and the corresponding clarifying questions to ask the user (e.g., “when do you want to travel?” and “where do you want to go?”). Amazon Lex takes care of the rest, building the language model and asking the follow-up questions needed to complete the task. Because Amazon Lex is integrated with AWS Lambda, developers can configure Amazon Lex to invoke the appropriate backend service (e.g., the flight booking service) through an AWS Lambda function. Developers can also use pre-built enterprise connectors that execute AWS Lambda functions to answer questions like “what are my top 10 accounts in Salesforce.com,” by fetching data from enterprise systems like Salesforce,
Bots built using Amazon Lex can be used anywhere: from web applications, to chat and messenger apps like Slack and Facebook Messenger, or through voice in apps on mobile or connected devices. Amazon Lex handles the authentication required by different platforms and simplifies the user interface design by not requiring developers to write custom code for each platform. Moreover, developers do not have to worry about scaling their infrastructure as Amazon Lex scales automatically as traffic to a bot increases, and developers pay only for the calls made to the
OhioHealth is a nationally recognized healthcare organization with a network of 11+ hospitals in 47 counties. “We are excited about utilizing evolving speech recognition and natural language processing technology to enhance the lives of our customers. Amazon Lex represents a great opportunity for us to deliver a new experience to our patients,” said
Intelligent Speech with Amazon Polly
Amazon Polly makes it easy for developers to add natural-sounding speech capabilities to existing applications like newsreaders and e-learning platforms, or create entirely new categories of speech-enabled products – from mobile apps to devices and appliances. Amazon Polly is easy to use; developers can send text to Amazon Polly using the SDK or from within the AWS Management Console and Polly immediately returns an audio stream that can be played directly or stored in a standard audio file format. With 47 lifelike voices and support for 24 languages, developers can choose from both male and female voices with a variety of accents to make applications for users around the globe. And Amazon Polly’s fluid pronunciation of text content means applications deliver high-quality voice output across a wide variety of text formats. Amazon Polly is scalable, returning high-quality speech fast, even when converting large volumes of text to speech. With Amazon Polly, developers pay only for the text they convert, and they can cache generated speech and replay it as many times as they like with no restrictions.
GoAnimate is a cloud-based, animated video creation platform, designed to allow business people with no background in animation to quickly and easily create animated videos. “Amazon Polly gives GoAnimate users the ability to immediately give voice to the characters they animate using our platform. This is especially helpful in scenarios where live voiceover is either resource or time prohibitive, such as when developing a video in many languages, or within pre-production to speed the approval process,” said
Intelligent Image Analysis with Amazon Rekognition
Amazon Rekognition enables developers to quickly and easily build applications that analyze images, and recognize faces, objects, and scenes. Amazon Rekognition uses deep learning technologies to automatically identify objects and scenes, such as vehicles, pets, or furniture, and provides a confidence score that lets developers tag images so that application users can search for specific images using key words. Amazon Rekognition can locate faces within images and detect attributes, such as whether or not the face is smiling or the eyes are open. Amazon Rekognition also supports advanced facial analysis functionalities such as face comparison and facial search. Using Rekognition, developers can build an application that measures the likelihood that faces in two images are of the same person, thereby being able to verify a user against a reference photo in near real-time. Similarly, developers can create collections of millions of faces (detected in images) and can search for a face similar to their reference image in the collection. Amazon Rekognition removes the complexity and overhead required to develop and manage expensive image processing pipelines by making comprehensive image classification, detection, and management capabilities available in a simple, cost-effective, and reliable AWS service. There are no upfront costs for Amazon Rekognition, developers pay only for the images they analyze and the facial feature vectors they store.
Redfin is a full-service brokerage that uses modern technology to help people buy and sell houses. “Redfin users love to browse images of properties on our site and mobile apps, and we want to make it easier for our users to sift through hundreds of millions of listing and images,” says
SmugMug is a safe and beautiful home for photos that stores billions of beautiful photos for millions of amazing customers every day. “SmugMug customers want to spend their time making more memories, not manually managing their photo collection,” said
Deep Learning and AI on AWS
Amazon Polly is available today in US East (N.
In addition to these services, AWS recently announced it is investing significantly in MXNet, an open source distributed deep learning framework, initially developed by
AWS also makes it easy for developers to run their own deep learning and machine learning workloads to build their own AI platform on top of AWS. Amazon Elastic Compute Cloud (Amazon EC2), with its broad set of instance types and GPUs with large amounts of memory, is ideal for deep learning training. P2 instances, launched in
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