Facebook, Inc.

Microsoft Technology Licensing, LLC

Dan Zhang

Shiyang Liu

Chin Lung Fong

Maria Angelidou

Harshit Agarwal

Xiongjun Liang

Steven Karl Reinhardt

Jeremy Halden Fowers

Yi-Wei Wu

Yuan Liang

Hongji Yang

Ethan Lubka

Mohammadmahdi Ghandi

Lingfei He

Yin Kam Hung

Michael Thomas Gofron

Joseph Anthony Mayer, Ii

Yuji Wang

Ren Lu

Amber Muck

Neural network processors including a window expander circuit and related methods are provided. The window expander circuit may include a first logic circuit configured to store a set of data elements, corresponding to at least a subset of the input data, into a Q number of logical memories, where each of a P number of data elements of the set of the data elements is stored in each of the Q number of logical memories. The window expander circuit may further include a second logic circuit configured to receive the first set of data elements and additional data elements corresponding to the at least the subset of the input data from the Q number of logical memories and expand the at least the subset of the input data until the at least the subset of the input data is expanded based on a predetermined factor.

Neural network processor with a window expander circuit

An online system stores online documents, where each online document has a layout. The system creates augmented online documents by combining the online documents with one or more content items. The system stores client interactions with the content items, responsive to presenting the augmented online documents via a client device. The system receives a new online document. The system creates new augmented online documents by combining the new online document with one or more new content items. For each new augmented online document, the system generates a score based on one or more features describing the layout of the new augmented online document. The system selects a new augmented online document based on the generated scores and sends the selected new augmented online document for presentation via a client device.

Automatic placement of electronic media content items within an online document

A computing system is described herein that expedites deep neural network (DNN) operations or other processing operations using a hardware accelerator. The hardware accelerator, in turn, includes a tensor-processing engine that works in conjunction with a scalar-processing unit (SPU). The tensor-processing engine handles various kinds of tensor-based operations required by the DNN, such as multiplying vectors by matrices, combining vectors with other vectors, transforming individual vectors, etc. The SPU performs scalar-based operations, such as forming the reciprocal of a scalar, generating the square root of a scalar, etc. According to one illustrative implementation, the computing system uses the same vector-based programmatic interface to interact with both the tensor-processing engine and the SPU.

Tensor-based hardware accelerator including a scalar-processing unit

Systems, methods, and non-transitory computer-readable media can obtain a media item. The media item is positioned in a content item. A plurality of histograms are generated based on colors of a first portion and a second portion of the media item. A custom background for the media item in the content item is generated based on the plurality of histograms.

Systems and methods for providing content

Growing community of inventors

Foster City, CA, United States of America

Dan Zhang