Amazon Web Services on Wednesday introduced a new set of tools that bring cloud customers the same AI capabilities that power Amaon.com, in the form of an API. Amazon Personalization is a real-time personalization recommendation service, while Amazon Forecast offers time-series forecasting.
"This top layer is for companies and builders who don't want to mess with the models at all," AWS CEO Andy Jassy said.
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For Amazon Personalize, customers give Amazon a set of variables related to their customers, such as page views, conversion rates or demographic information. Amazon sets up an EMR cluster and inspects the data. Amazon selects from up to six algorithms originally built for its retail business, and it sets up parameters to train the data, and it hosts the models. From there, Amazon Personalize effectively spits out a recommendation via an API.
"These are private models, they're only yours," Jassy said.
Personalize is similar to Sagemaker, Amazon's fully managed machine learning service, Jassy explained - but at this level of the stack, customers only have to submit the inputs.
Similarly, Amazon Forecast uses time series forecasting built for Amazon.com.
"The problem in forecasting is it's not usually one or two data points that impact the forecast," Jassy said. In retail, there can be hundreds of variables to analyze, like weather, shipping times, and customer reviews.
Forecasting works very much in the same way Personalize does. A customer gives Amazon historical data