Amazon Technologies, Inc.

Charles H Bell

Jeffrey P Bezos

Jonathan A Jenkins

Jeffrey Alan Holden

Rahul Sharma

Ian W Freed

Muneer Mirza

James Robert Blair

Vikram Madan

Joseph Minarik

Alexander Grant Douglas

Techniques for generating and utilizing machine learning based adaptive instructions for annotation are described. An annotation service can use models to identify edge case data elements predicted to elicit differing annotations from annotators, 'bad' data elements predicted to be difficult to annotate, and/or 'good' data elements predicted to elicit matching or otherwise high-quality annotations from annotators. These sets of data elements can be automatically incorporated into annotation job instructions provided to annotators, resulting in improved overall annotation results via having efficiently and effectively &#x201c;trained&#x201d; the annotators how to perform the annotation task.

Machine learning based adaptive instructions for annotation

A system configured to determine interactive elements for non-traditional computing devices is disclosed. The system receives a portion of a webpage with a first interactive element and an element identifier. The system determines that a threshold number of interactive actions are associated with a second interactive element in a data store. The threshold number of interactive actions indicates that the second interactive element is selectable to perform an action in response to an interaction by a user. The system determines that the first interactive element is similar to the second interactive element by a similarity measure. The system provides to a computer, a selectable option associated with the element identifier of the first interactive element. The selectable option is for selection by an indirect input to the computer and for causing the action associated with the first interactive element upon the selection of the selectable option.

Interactive content element presentation

A data center may predict infrastructure failures in order to perform mitigation actions at services hosted at the data center. Operational metrics for different infrastructure systems of a data center may be collected and analyzed to generate failure models. The failure models may be evaluated to predict infrastructure failure events. The predicted infrastructure failure events may be programmatically provided to the services. The services may evaluate the prediction and select mitigation actions to perform. For data centers implemented as part of a provider network with services hosted across multiple data centers, mitigation actions may be performed at multiple data centers for a service in response to a predicted failure event at one data center.

Predicting infrastructure failures in a data center for hosted service mitigation actions

A network content message placement management process is directed to the processing and management of messages in content displayed at a client computing device. A client computing device provides message placement configuration information to a network computing and storage provider. The network computing and storage transmits message placement requests to a content provider based on the message placement configuration information. The client computing device may subsequently directly or indirectly request content from the content provider. The content provided from the content provider may include one or more of the alternative messages provided in the message placement configuration information. Illustratively, the alternative messages may be included in place of other messages, such as advertisements, from third party message providers.

Network content message placement management

A computer-implemented data processing system includes tag logic for permitting a user to create an active tag. The active tag is associated with an object and includes configuration information that defines an action to be performed upon selection of the active tag. The configuration information is accessible by another user. The system also includes a user interface in communication with the tag logic for displaying the active tag.

Growing community of inventors

Redmond, WA, United States of America

Charles H Bell