Amazon Boosts its Artificial Intelligence
Amazon.com is boosting its artificial-intelligence chops.
The world’s largest retailer by market capitalization is rolling out its sophisticated big-data-crunching platform for developers in Europe, and is also hiring scientists for its research teams in New York and Berlin who specialize in getting machines to do things like make sales predictions and predict fraud.
Machine learning is a field of artificial-intelligence computing in which algorithms are trained to make predictions from large sets of data without having to be reprogrammed on each new set of data.
Amazon already uses machine learning to automatically predict prices for millions of products and for forecasting recommendations in search.
“Machine-learning software predicts what a customer is likely to do in the next five seconds or in the next five weeks. It’s pattern recognition at scale,” said Ralf Herbrich, European Union director of machine learning at Amazon and managing director of the Amazon Development Center in Germany. Herbrich previously worked at Microsoft Research and Facebook, showing how AI experts are in high demand at global tech firms.
The machine-learning platform that companies can use, with or without being customers of Amazon’s cloud service, is a set of visualization tools and wizards that allow nontechnical users to create predictions based on their businesses’ historical data.
Each row in an Excel spreadsheet, for instance, would generate one prediction. A row could be: 300 shoes sold in Moscow in 2014. One prediction would then be: How many shoes will be sold in 2015? Amazon will charge users 10 cents per 1,000 predictions.
Amazon already has several machine-learning research groups, in cities such as Bangalore, Seattle, Palo Alto, Calif., and Berlin. It also has a speech-recognition team in Aachen, Germany.
Amazon’s move brings it in line with other tech giants like Microsoft and Facebook, who also have AI research labs in New York.
In Berlin, Amazon currently employs around 150 software engineers and scientists who primarily specialize in machine learning and big data.
The scientists at the New York unit will focus on demand forecasting, predicting how likely it is that a customer will select a product that is shown in a search query, and how likely that customer is to then click on a related link or purchase a product, Herbrich said.
The forecasting is expected to focus at first on fashion—apparel and shoes—a highly seasonal market segment that is hard to predict based on historical data. Styles of clothes may differ widely from season to season and year to year, and fashion shows in one year largely determine what retailers will sell in the next year’s seasons.
One of the new hires in New York is Dean Foster, a statistics professor and expert on machine learning and natural-language processing currently on leave from the Wharton School of the University of Pennsylvania. He declined to comment.