AWS has the broadest and deepest set of machine learning and AI services for your business.
Latest about AI and Machine Learning on AWS
Amazon has a long history in AI, from personalization and recommendation engines to robotics in fulfillment centers. Amazon Go, Amazon Alexa, and Amazon Prime Air are also examples.
Watch this session and learn more about the latest machine learning services from AWS, and hear from customers who are partnering with AWS for innovative AI.
Get an Executive Summary of an IDC White Paper, titled Streamlining the Development of Deep Learning Applications in an AI-enabled World sponsored by AWS, January 2019. It provides an overview on machine learning (ML) and deep learning (DL), an emerging area of technology. According to the Worldwide Semiannual Cognitive Artificial Intelligence Systems Spending Guide, IDC projects spending on ML and DL in Asia will rise from US$3.6 billion in 2018 to US$15.5 billion in 2022 with a compound annual growth rate of over 49%. It also highlights how data scientists and developers, with the help of AWS Machine Learning and AI Services, can quickly and easily build, train and deploy models to deliver significant impact to the business.
Read the full White Paper* for a deep dive into how machine learning and deep learning are helping businesses to increase sales, reduce costs, streamline business processes and driving new innovations in an AI-enabled world.
From the world's largest enterprises to emerging start-ups, more machine learning is built on AWS than anywhere else.
AWS customers use machine learning to improve the quality of healthcare, fight human trafficking, provide better customer service, and protect you from fraud. With the broadest and deepest set of machine learning and AI services, they are creating new insights, enabling new efficiencies, and making more accurate predictions. That's why more than 10,000 customers have chosen to use AWS for machine learning.
Intuit uses Machine Learning on AWS to automatically identify new tax deductions for their customers, saving each an average of $4,300.
Formula One uses Amazon SageMaker to analyze race data in real time, then shares the insights with television viewers.
GE Healthcare uses Deep Learning on AWS to improve the accuracy of x-ray imaging procedures while also lowering readmission rates.
Marinus Analytics uses Amazon Rekognition to find human trafficking victims who may have changed their appearance, then help to prosecute the traffickers.
Capital One enhances fraud detection with Machine Learning on AWS.
Policybazaar.com, an India insurance marketplace adopts Amazon Polly to enhance efficiency and customer experience.
Sunday Insurance uses machine learning algorithms to provide customers with a broader range of insurance policies, covering properties and possessions, and highly customized premiums that deliver greater value to customers.
BGL brings Deep Learning to Super Funds with AWS. The financial sector is adopting artificial intelligence personal assistants. More than 80% of queries against 300 million transactions were returned in less than 10 seconds.
Haptik uses Amazon Polly to power a virtual personal assistant, and delivers 80 percent reduction in IT management time.
Hear how Airtasker combined multiple AWS AI services to create "Carl" who learned everything he knows from Wikipedia.
Stackla, a social media content marketing platform uses AWS AI/ML services to enable user-generated content to generate key marketing outcomes.
Build & Deploy ML Models Quickly & Easily with Amazon SageMaker, featuring 21st Century Fox
Amazon SageMaker is a fully managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. Amazon SageMaker takes away the heavy lifting of machine learning, thus removing the typical barriers associated with machine learning. This session dives deep into the technical details of each of the modules of Amazon SageMaker to showcase the capabilities of the platform. We also discuss the practical deployments of Amazon SageMaker through real-world customer examples.
Deep Learning for Developers: Introduction, featuring Samsung SDS
Artificial intelligence (AI) is rapidly evolving, and much of the advancement is driven by deep learning, a machine learning technique inspired by the inner workings of the human brain. This session explains what deep learning is and how you can use it in your applications to unlock new and exciting capabilities for your customers and business. Also hear from Samsung SDS about how it developed a deep-learning model for cardiac arrhythmia detection using Apache MXNet, an open-source deep-learning framework. By the end of the session, understand how to leverage deep learning in your applications and get started with it.
