Google Inc.

Microsoft Technology Licensing, LLC

Kabushiki Kaisha Toshiba

Facebook, Inc.

Rayvio Corporation

Hewlett-packard Development Company, L.p.

Larq, Inc.

Airbnb, Inc.

Apple Inc.

Applied Materials, Inc.

Amgen Inc.

Alibaba Group Holding Limited

Entit Software LLC

Amgen Fremont Inc.

Li Zhang

Douglas A Collins

Yitao Liao

Hartwig Adam

Tadashi Sakai

Aaron Michael Donsbach

Gareth Brown

Daniel Ramage

Doug Collins

Kunal Talwar

Yuhong Xiong

Tomio Ono

Gregory Matthew Marra

Carlos Hernandez Esteban

Blaise Hilary Aguera-Arcas

Krzysztof Duleba

Yuan Yu

Jon Gabriel Clapper

Yangli Hector Yee

Hugh Brendan McMahan

Navid Shiee

Mihai Budiu

Juston Payne

Andrew Nguyen

John Raff

Bernardo A Huberman

Dharma Kiritkumar Shukla

Fang Wu

Steven Maxwell Seitz

James P Cruse

Jared Ahmad Lee

Andrew Michael Chung

Gabor Szita

Maxim Gubin

Benjamin Schwarz

Matthew Chin

Yuzo Watanabe

Quetzalcoatl Bradley

Shireesh Kumar Thota

Mei-Mei Tsai

Zhuang Li

Madhan Gajendran

Raylene Kay Yung

Kevin Graham

Serkan Piantino

Raymond G Beausoleil

Cheng Kai Chen

Victor H Yin

Masahiro Kiyotoshi

Patrick Henri Dussud

Shosuke Fujii

Xiao-Chi Jia

Kiwamu Sakuma

Florence W Ow

Tetsufumi Tanamoto

Michael M Magruder

Shigeki Takahashi

Yong Zhao

Vance Palmer Morrison

William John Munro

Jaspal Singh Kang

Jingmei Liang

Tad H Hogg

Chandramohan Amyangot Thekkath

C Douglas Hodges

David A Kalinowski

Enkhamgalan Dorjgotov

Rajan Mathew Lukose

Praket Prakash Jha

Masao Shingu

Rui Liang

Takashi Yamauchi

Xiaokai Li

Varun Kacholia

Young Cheol Yang

James S Miller

Sean Edwin Trowbridge

Jiangang Liang

Gehan Anil Joseph Amaratunga

John Stephen Babcook

Kristina A Babiarz

Brian Robert Crawford

Kazuya Nakayama

Mihail Gavril Tarta

Soyoung Kim

Gary W Calfee

Wenyong Zhu

Yiu-Ming Leung

Eytan Adar

John Lawrence Hamby

Peter A Hallam

Elliot H Omiya

Victor Luzzato

Richard Oswald

Jinrui Guo

Mikhail Arkhipov

Ren Wu

Jie Zhang

Jason L Zander

James H Hogg

The present disclosure provides systems and methods that provide feedback to a user of an image capture device that includes an artificial intelligence system that analyzes incoming image frames to, for example, determine whether to automatically capture and store the incoming frames. An example system can also, in the viewfinder portion of a user interface presented on a display, a graphical intelligence feedback indicator in association with a live video stream. The graphical intelligence feedback indicator can graphically indicate, for each of a plurality of image frames as such image frame is presented within the viewfinder portion of the user interface, a respective measure of one or more attributes of the respective scene depicted by the image frame output by the artificial intelligence system.

Systems and methods for providing feedback for artificial intelligence-based image capture devices

The present disclosure is directed to processing imagery using one or more machine learning (ML) models. In particular, data describing imagery comprising a plurality of different and distinct frames can be received; and based at least in part on one or more ML models and the data describing the imagery, and for each frame of the plurality of different and distinct frames, one or more scores can be determined for the frame. Each score of the score(s) can indicate a determined measure of suitability of the frame with respect to one or more of various different and distinct uses for which the ML model(s) are configured to determine suitability of imagery.

Methods and systems for processing imagery

Methods and computer systems for storing a query plan in a cache are provided. The method can include: determining a use frequency of the query plan; determining a target storage layer for storing the query plan based on the determined use frequency, wherein the cache includes at least two storage layers and each of the storage layers is associated with a compression level of query plans; processing the query plan according to the compression level of the target storage layer; and storing the processed query plan in the target storage layer.

Method and system for storing query plans in a cache and method for querying a database system

A head-mountable device can provide passive cooling that utilizes surfaces of an optical assembly to allow heat to be managed in a manner that does not detrimentally impact the visual information displayed to the user. Lenses can be coated with a transparent and thermally conductive material, such as silver nanowire. Such a thermal layer can provide superior thermal conductivity, transmittance, flexibility, flat transmission, low cost, and angular color stability. The thermal layer can passively manage heat by increasing the surface area across which heat can be efficiently dissipated.

Heat dissipation for head-mountable device

Systems and methods for learning differentially private machine-learned models are provided. A computing system can include one or more server computing devices comprising one or more processors and one or more non-transitory computer-readable media that collectively store instructions that, when executed by the one or more processors cause the one or more server computing devices to perform operations. The operations can include selecting a subset of client computing devices from a pool of available client computing devices; providing a machine-learned model to the selected client computing devices; receiving, from each selected client computing device, a local update for the machine-learned model; determining a differentially private aggregate of the local updates; and determining an updated machine-learned model based at least in part on the data-weighted average of the local updates.

Training user-level differentially private machine-learned models

Wand for pitcher

Methods for forming a smooth ultra-thin flowable CVD film by using a surface treatment on a substrate surface before flowable CVD film deposition improves the uniformity and overall film smoothness. The flowable CVD film can be cured by any suitable curing process to form a smooth flowable CVD film.

Surface roughness for flowable CVD film

Bottle

Cap for a bottle with a ring on top

The present disclosure provides an image capture, curation, and editing system that includes a resource-efficient mobile image capture device that continuously captures images. In particular, the present disclosure provides low power frameworks for controlling image sensor mode in a mobile image capture device. On example low power frame work includes a scene analyzer that analyzes a scene depicted by a first image and, based at least in part on such analysis, causes an image sensor control signal to be provided to an image sensor to adjust at least one of the frame rate and the resolution of the image sensor.

Low power framework for controlling image sensor mode in a mobile image capture device

Systems and methods are provided for analyzing booking session data to generate a plurality of feature vectors for each booking session of the plurality of booking sessions, and generating training data comprising the plurality of feature vectors for each booking session and at least a first constraint. The systems and methods further providing for calculating a set of weights using the training data, wherein each weight is a lowest weight satisfying the most constraints possible, wherein the set of weights comprises a weight associated with each feature in the plurality of feature vectors, and computing a reservation value for each of a plurality of clients for each of a plurality of listings and for each date of a plurality of dates, based on the set of weights and the plurality of feature vectors.

Machine learning modeling for generating client reservation value

Growing community of inventors

Sunnyvale, CA, United States of America

Li Zhang