AWS Announces General Availability of Amazon Personalize
SEATTLE, WA — Amazon Web Services has announced the general availability of Amazon Personalize, bringing the same machine learning technology used by Amazon.com to AWS customers for use in their applications – with no machine learning experience required. Amazon Personalize makes it easy to develop applications with a wide array of personalization use cases, including specific product recommendations, individualized search results, and customized direct marketing. Amazon Personalize is available today in US East (Ohio), US East (N. Virginia), US West (Oregon), Asia Pacific(Tokyo), Asia Pacific (Singapore) and EU (Ireland) with additional regions coming soon.
Amazon Personalize is a fully managed service that trains, tunes, and deploys custom, private machine learning models. Amazon Personalize provisions the necessary infrastructure and manages the entire machine learning pipeline, including processing the data, identifying features, selecting algorithms, and training, optimizing, and hosting the results. Customers receive results via an Application Programming Interface (API) and only pay for what they use, with no minimum fees or upfront commitments.
Amazon has pioneered the use of machine learning for recommendation and personalization for more than 20 years. During that time, customers have asked for access to these capabilities so they could enjoy similar benefits when running their businesses. However, the technology can be challenging to deliver effectively across a variety of use cases because there isn’t a single, master personalization algorithm. Each use case – videos, music, products, or news articles – has its own specificities, which requires a unique mix of data, algorithms, and optimizations to create a result.
Today’s general availability of Amazon Personalize provides a major step toward putting the power of Amazon’s experience in machine learning into the hands of everyday application developers and data scientists at businesses of all sizes across all industries. Amazon Personalize reduces the time to build a custom model from months to days. When using Amazon Personalize, customers provide the service an activity stream from an application (e.g. page views, signups, or purchases) along with an inventory of the items to recommend (e.g. music, videos, products, or news articles), and receive recommendations via an API. Amazon Personalize does this by processing and examining the data, identifying what is meaningful, selecting from multiple advanced algorithms built and refined over years for Amazon’s retail business, and training and optimizing a personalization model customized to the data. During the whole time, all of the data is kept completely private, owned entirely by the customer.
“We are excited to share with AWS customers the expertise we’ve developed during two decades of using machine learning to deliver great experiences on Amazon.com,” said Swami Sivasubramanian, Vice President of Machine Learning, Amazon Web Services, Inc. “Customers have been asking for Amazon Personalize, and we are eager to see how they implement these services to delight their own end users. And the best part is that these artificial intelligence services, like Amazon Personalize, do not require any machine learning experience to immediately train, tune, and deploy models to meet their business demands.”