Amazon Technologies, Inc.

Tao Hu

Vishwanathan Swaminathan

Umair Bashir

Yi Liu

Josiah P Olivieri

Jian Liu

Xiao Yu

Houssam Nassif

Sriram Srinivasan

Daniel Hill

Faisal Masud

Anand Mahadeva Iyer

Stacy Saal

Paul D Ohlhaut

An optimal combination of content items may be determined and served to increase the likelihood of a predefined user interaction. A user can request content which may include an entity (such as a web page, document, advertisement, and the like) that has multiple components through which content items may be provided. For example, a web page may include multiple slots where content items may be displayed on the web page. Each component may be associated with multiple possible content items, resulting in many combinations of layouts for an entity. A content server may determine which layout to provide using a content selection model that is weighted based on a likelihood of groupings of content items resulting in a user interaction that satisfies a success condition (e.g., selecting a hyperlink, selecting a content item, initiating a transaction, etc.).

Artificial intelligence system for optimizing network-accessible content

Disclosed are various embodiments for optimizing prices of items using current offers. Numerous current offers to sell an item are determined from a subset of sellers in an electronic marketplace. Each one of the subset of sellers is associated with a respective reputational score that meets a minimum threshold. A competitive price is generated for the item based at least in part on an average marketplace price determined from the current offers.

Price optimization using current offers

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Seattle, WA, United States of America

Tao Hu