Google Inc.

Cayden Meyer

Scott James Ogden

Harold H W Kim

Nicholas Trent Caston

Ian Kilpatrick

Xudong Yang

Reuben Kan

Jennifer Delphine King

John Patterson

David Armstrong

David Lattimore

Lior Biran

Jennifer King Kilpatrick

James Watts

Eric Zhang

Sandeep Tata

Lai Kwan Wong

Alexandre Mah

Alan Green

Joshua Bergstrand

Ryan Weber

Xiaojie Jiang

Birkan Icacan

Sebastian Doerner

Julian Gibbons

Divanshu Garg

Harold Kim

Yifan Cao

Alexandrin Popescul

Joel Christopher Onofrio

Jameslevi Schmidt

Michael Smith

A navigation system can identify locations of interest at a route destination. Those locations of interest at the destination can fall within a predetermined distance of the destination or those that are responsive to a query that includes the destination as a parameter. The navigation system can receive a selection of an identified location of interest near the destination, and update a route to terminate at the identified location of interest rather than the original destination. Information identifying the origin and destination for the route can be collected at a first user device and the route can be displayed at a second user device. Additional information is then received from the first user device (such as a selection of an identified location of interest near the destination). This additional information received at the first user device is used to update the route that is displayed on the second user device.

Rerouting in a navigation system based on updated information

A method for organizing a plurality of files to be stored on a cloud file system includes receiving user data provided by a user and pertaining to an organization of a plurality of files of the user into folders on the cloud file system, identifying a first file of the plurality of files, determining that the first file is a first email attachment to a first email received by the user, automatically storing the first email attachment in a first folder, identifying a second file of the plurality of files, determining that the second file is a second email attachment to a second email received by the user, determining that the folders associated with the user account do not include a folder for the second email attachment, and causing a new folder associated to be created on the cloud file system as a destination folder for the second email attachment.

Systems and methods for automatically organizing files and folders

The techniques, methods, systems, and other mechanisms described herein include processes for determining if customized content should be generated, what information to include in the customized content, and when to provide the customized content. In general, a computing system determines that a user intends to travel to a physical venue. The computing system can determine if an entity associated with the physical venue has a web page. The computing system can determine various aspects of a predicted route of travel from the user's present location to the physical venue. The computing system can use location information indicating the user's current location and determine one or more routes of travel to the physical venue. The computing system can compare one or more determined aspects of the predicted route to threshold values to determine if customized content should be generated and presented to the user.

Systems and methods for detection of navigation to physical venue and suggestion of alternative actions

Systems and methods are disclosed herein for organizing a plurality of files to be stored on a cloud file system. A method includes identifying a file to be stored on the cloud file system, identifying features of the file, wherein the features of the file include at least three selected from a group comprising file content, keywords in the file, file name, time of creation of the file, time of modification of the file, type of the file, a set of users associated with the file, folder depth of the file, and an origination of the file, identifying a plurality of folders each including a subset of the plurality of files, wherein grouping the plurality of files into respective folders is based on assessed similarities across each subset of the plurality of files, assessing similarities between the file and each subset of the plurality of files based on the features of the file and features of each subset of the plurality of files, determining, based on the assessed similarities between the file and each subset of the plurality of files, whether any of the plurality of folders satisfies one or more destination folder criteria, and responsive to determining that none of the plurality of folders satisfies the one or more destination folder criteria, creating a new folder as a destination folder for the file to be stored on the cloud file system.

A system is described that infers that a user will need to complete a trip and selects a transportation service that the user can use to complete the trip. The system predicts a time to request a vehicle associated with the transportation service for completing the trip such that the request has sufficiently high degree of likelihood, of causing the vehicle to arrive at a future location by a final departure time; the final departure time being a latest time at which the user is predicted to need to begin traveling. Responsive to determining that a current time is within a threshold amount of time of the predicted time, the system sends, to a reservation system associated with the transportation service, a reservation request for the vehicle associated with the transportation service for completing the trip.

Automatic booking of transportation based on context of a user of a computing device

A method for editing and updating content of a collaborative document within a preview user interface is provided. The method includes a content management platform receives a request for a file stored which is stored in a third-party application format. The system causes a rendered graphical image of the file to be presented within a preview user interface. The rendered graphical image of the file represents a view of the file as if opened within a third-party application. The system receives from the preview user interface, content associated with a portion of the file. The system generates a new version of the file that includes the content associated with the portion of the file.

Managing comments on binary files preview view in a cloud-based environment

A computer-implemented method disclosed herein includes identifying, by a processor, a plurality of participants of a video conference meeting, the plurality of participants comprising a first user of a first user device and a set of scheduled attendees in addition to the first user of the first user device, wherein the first user of the first user device and the set of scheduled attendees were invited to participate in the video conference meeting via a calendar invitation. The method further includes receiving an indication that a second user of a second user device is interested in participating in the video conference meeting, wherein the second user of the second user device was not invited to participate in the video conference meeting via the calendar invitation, adding the second user of the second user device to the plurality of participants of the video conference meeting, generating meeting notes of the first user of the first user device, the meeting notes being associated with the video conference meeting, and causing access to the meeting notes to be provided to at least a subset of the plurality of participants.

System and method for automatic meeting note creation and sharing using a user's context and physical proximity

Systems and methods are disclosed herein for organizing a plurality of files on a cloud file system. In particular, the plurality of files and features of the plurality of files are identified. A machine learning model is trained on a set of inputs comprising the features of the plurality of files and a set of target outputs for the set of inputs, the set of target outputs comprising a set of destination folders to store the plurality of files. Further, the trained machine learning model is applied to features of additional files to produce predicted destination folders on the cloud file system. User inputs indicative of user requests to add the additional files to requested destination folders on the cloud file system are received, and the requested destination folders are compared to the predicted destination folders. In response to determining that the requested destination folders do not match the predicted destination folders, the trained machine learning model is updated.

Locating passenger transit vehicles by detecting interactions. Each interaction is between a transit terminal and a geolocation-enabled user device, and is characterized by data indicative of the interacting terminal, the interacting user device, and the time of interaction. For each detected interaction, a geolocation of the corresponding user device at the time of the interaction is requested; and in response to the requesting, the geolocation of the corresponding user device, the time of the geolocation, and the data indicative of the interacting terminal is received. A particular passenger transit vehicle associated with at least one interacting terminal is identified based on the user device geolocations. The location of the passenger transit vehicle is transmitted for display on user devices.

Passenger transit vehicle geolocation

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Pyrmont, Australia

Cayden Meyer