Samsung Electronics Co., Ltd.

Microsoft Technology Licensing, LLC

Apple Inc.

Jonathan James Currey

Max Muller

Jason Robert Suitts

Justin C Martineau

Christopher John Rossbach

Michael Isard

Bo Li

Vijayan Prabhakaran

Kunal Talwar

Yin Zhou

Xiaolong Wang

Ehud Wieder

James Felix Black

One embodiment provides a method comprising receiving a piece of content and salient moments data for the piece of content. The method further comprises, based on the salient moments data, determining a first path for a viewport for the piece of content. The method further comprises displaying the viewport on a display device. Movement of the viewport is based on the first path during playback of the piece of content. The method further comprises generating an augmentation for a salient moment occurring in the piece of content, and presenting the augmentation in the viewport during a portion of the playback. The augmentation comprises an interactive hint for guiding the viewport to the salient moment.

Content navigation

One embodiment provides a method comprising receiving a first input image and a second input image. Each input image comprises a facial image of an individual. For each input image, a first set of facial regions of the facial image is distinguished from a second set of facial regions of the facial image based on a learning based model. The first set of facial regions comprises age-invariant facial features, and the second set of facial regions comprises age-sensitive facial features. The method further comprises determining whether the first input image and the second input images comprise facial images of the same individual by performing face verification based on the first set of facial regions of each input image.

Learning model for salient facial region detection

One embodiment provides a method comprising receiving an input, and classifying the input utilizing a learned linear combination of multi-dimensional filters. Each multi-dimensional filter identifies a multi-dimensional pattern of a homogenous feature. The method further comprises generating an output indicative of a classification of the input.

Learning combinations of homogenous feature arrangements

An application programming interface is provided that allows programmers to encapsulate snippets of executable code of a program into accelerator tasks. A graph is generated with a node corresponding to each of the accelerator tasks with edges that represent the data flow and data dependencies between the accelerator tasks. The generated graph is used by a scheduler to schedule the execution of the accelerator tasks across multiple accelerators. The application programming interface further provides an abstraction of the various memories of the accelerators called a datablock. The programmer can store and use data stored on the datablocks without knowing where on the accelerators the data is stored. The application programming interface can further schedule the execution of accelerator tasks to minimize the amount of data that is copied to and from the accelerators based on the datablocks and the generated graph.

Scheduling accelerator tasks on accelerators using graphs

Various embodiments provide techniques and constructs to improve execution speed of distributed iterative computation using heterogeneous specialized resources including, for example, processors and accelerators. Iteration over an arbitrary sub-graph without loop unrolling including for algorithms with data-dependent loop termination and large iteration counts, including as a result of nested iteration, are supported in a resource-efficient manner without adding vertices to a dataflow graph to represent iteration constructs. Instead, some or all of the existing vertices within the sub-graph that is to be iterated upon based on having additional and/or modified ports and channels associated with them.

Iteration support in a heterogeneous dataflow engine

Providing digital media content is disclosed. A metadata file and a plurality of data files are received. The metadata file is used to process the plurality of data files. The processing of the plurality of data files using the metadata file is performed without human intervention to provide a downloadable digital media content asset.

Metadata for providing media content

The disclosed embodiments relate generally to the submission of media content to a media distribution system and the generation of media items from the media content. The media items may include, for example, audio, video, image, or podcast data. In accordance with one embodiment, a package for use in generating a downloadable digital media content asset includes metadata content that describes how the media content in a plurality of data files including media content can be processed to generate a downloadable digital media content asset, where the package includes information identifying the plurality of data files.

Media package format for submission to a media distribution system

A job scheduler may schedule concurrent distributed jobs in a computer cluster by assigning tasks from the running jobs to compute nodes while balancing fairness with efficiency. Determining which tasks to assign to the compute nodes may be performed using a network flow graph. The weights on at least some of the edges of the graph encode data locality, and the capacities provide constraints that ensure fairness. A min-cost flow technique may be used to perform an assignment of the tasks represented by the network flow graph. Thus, online task scheduling with locality may be mapped onto a network flow graph, which in turn may be used to determine a scheduling assignment using min-cost flow techniques. The costs may encode data locality, fairness, and starvation-freedom.

Scheduling ready tasks by generating network flow graph using information receive from root task having affinities between ready task and computers for execution

Growing community of inventors

San Francisco, CA, United States of America

Jonathan James Currey