Google Inc.

X Development LLC

Sully.ai

Chaitanya Gharpure

Ryan Michael Hickman

James Joseph Kuffner

Anthony Gerald Francis, Jr

Thor Lewis

Arshan Poursohi

James Robert Bruce

Eric Hc Liu

Evan Jarman Fisher

Victoria Fang

Peng Yang

Emily Hou

Charles L Chen

Tiruvilwamalai Venkatraman Raman

Ahmed Nasser

Ahmed Omar

T V Raman

Peter Elving Anderson-Sprecher

Damon Kohler

Tiruvilwamalai Venkatram Raman

Won S Chun

Rachel Shearer

In some aspects, an artificial intelligence (AI) performs an analysis of a conversation between a doctor and a patient, determines a first trigger phrase in the conversation, and determines a template of a patient visit note based on the first trigger phrase. The AI determines a second trigger phrase in the conversation, determines a particular treatment plan from a plurality of treatment plans based on the second trigger phrase, and adds the particular treatment plan to the template. A first instance of the AI adds a first portion of the conversation to the template and a second instance of the AI, in parallel with the first portion of the conversation being added to the template, adds a second portion of the conversation to the template. The AI provides the template of the patient visit note to a device associated with the doctor.

Artificial intelligence (AI) to create a patient visit note based on a conversation between a doctor and a patient

The disclosure provides technology for enhancing the ability of a computing device to detect when a user has discontinued reading a text source. An example method includes receiving audio data comprising a spoken word associated with a text source, comparing the audio data with data of the text source, determining, based on the comparing, whether a segment of the audio data corresponds to a location of the text source, and responsive to determining that the segment of the audio data does not correspond to a location of the text source, transmitting a signal indicating that a user has discontinued reading the text source, the signal causing to cease the comparing of the audio data with the data of the text source.

Algorithmic determination of a story readers discontinuation of reading

In some aspects, orchestration logic is configured to receive, from a multi-modal interface, an upstream conversation between a doctor and a patient, provide, to at least one large language model (LLM), the upstream conversation and the patient's medical history, and cause the LLM to generate raw decision support insights. The LLM generates the raw decision support insights based at least in part on the upstream conversation and the patient's medical history. Real-time decision support logic is configured to: transform the raw decision support insights into prioritized, conversation-responsive decision support insights. The prioritized, conversation-responsive decision support insights are prioritized based on medical urgency. Presentation of the prioritized, conversation-responsive decision support insights to the doctor is responsive to downstream conversation between the patient and the doctor. The prioritized, conversation-responsive decision support insights are delivered to the multi-modal interface for presentation to the doctor.

Artificial intelligence (AI) to provide decision support insights including while a doctor is engaged in conversation with a patient

The disclosure provides technology for enhancing the ability of a computing device to detect when a user has discontinued reading a text source. An example method includes receiving audio data comprising a spoken word associated with a text source, wherein the audio data comprises a first duration and a second duration; comparing the audio data with data of the text source, wherein the first duration of the audio data corresponds with the data of the text source; calculating, by a processing device, a correspondence measure between the second duration of the audio data and the data of the text source; and responsive to determining the correspondence measure satisfies a threshold, transmitting a signal to cease comparing audio data with the data of the text source.

The disclosure provides technology for enhancing the ability of a computing device to conserve computing resources while providing special effects that are aligned with a text source being read aloud. An example method includes identifying effects data for a text source, wherein the effects data correlates a physical effect with an audible action of a user; receiving audio data comprising a plurality of audible actions, wherein at least one of the plurality of audible actions comprises a spoken word of the text source; determining, by a processing device, that a triggering condition pertaining to the effects data and the text source is satisfied; loading content for the physical effect prior to an occurrence of the audible action, and providing the physical effect to modify an environment of the user.

Detection of story reader progress for pre-caching special effects

An example method for identifying a reading location in a text source as a user reads the text source aloud includes determining phoneme data of the text source, the text source comprising a sequence of words; receiving audio data comprising a spoken word associated with the text source; comparing, by a processing device, the phoneme data of the text source and phoneme data of the audio data; and identifying a location in the sequence of words based on the comparing phoneme data.

Reading progress estimation based on phonetic fuzzy matching and confidence interval

The disclosure provides technology for enabling a computing device to provide context sensitive special effects that supplement a text source as it is read aloud. An example method includes receiving, by a processing device, audio data comprising a spoken word of a user, analyzing contextual data associated with the user, determining a match between the audio data and data of a text source; and initiating a physical effect in response to the determining the match, wherein the physical effect corresponds to the text source and is based on the contextual data.

Dynamic adjustment of story time special effects based on contextual data

The disclosure provides technology for enhancing the ability of a computing device to conserve computing resources while providing special effects that are aligned with a text source being read aloud. An example method includes identifying effects data for a text source, wherein the effects data correlates a physical effect with an audible action of a user; receiving audio data comprising a plurality of audible actions, wherein at least one of the plurality of audible actions comprises a spoken word of the text source; determining, by a processing device, a triggering condition based on the effects data and the text source; responsive to satisfying the triggering condition, loading content for the physical effect, wherein the triggering condition is satisfied prior to the occurrence of the audible action; and providing the physical effect to modify an environment of the user.

The present application discloses systems and methods for inventorying objects. In one embodiment, a robot detects an object and sends identification data and location data associated with the detected object to a cloud computing system. The identification data may include an image of the object and/or information from a tag, code, or beacon associated with the object. In response to receiving the identification data and the location data, the cloud computing system identifies the object. The cloud computing system may also determine or create a first map associated with the identified object and a second map associated with the identified object. The first map may be associated with the current location of the object and the second map may correspond to a past location of the object. The cloud computing server may compare the first and second maps, and then send instructions to the robot based on the comparison.

Systems and methods for inventorying objects

Multirobotic management can involve communications between a command or leader robot and one or more client or follower robots through a cloud computing system. In an example implementation, a leader robot can receive first sensory data captured by a first follower robot and second sensory data captured by a second follower robot, determine a command function based on at least one of the first sensory data and the second sensory data, and communicate with at least one of the first follower robot and the second follower robot based on the command function.

Methods and systems for multirobotic management

A system and method for updating and correcting the location of geospatial entities, the method comprising receiving at a server from a mobile device operated by a first user, a proposed location for a geospatial entity, the proposed location determined by a wireless location system, and based upon a current location of the mobile device; providing information about the proposed location for the geospatial entity to a first plurality of other users; receiving votes from the first plurality of users as to whether the proposed location is correct and responsive to the received votes, determining whether to update the location information for the geospatial entity.

Trusted maps: updating map locations using trust-based social graphs

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for providing virtual artifacts using mobile devices. In one aspect, methods include receiving a signal indicating user input to a touchscreen display of a mobile computing device, detecting motion of the mobile computing device, the motion mimicking motion associated with a physical artifact, identifying a function based on the user input and the motion, the function corresponding to a function that can be physically performed using the physical artifact, executing the function on the mobile device, and generating feedback to a user of the mobile device, the feedback indicating execution of the function.

Virtual artifacts using mobile devices

A method and system for video encoding assets for swivel/360-degree spinners is disclosed. Still images of a 3D object from different perspectives about the 3D object may be stacked and then video encoded to generate video frames of the object from the different perspectives. The video-encoded assets may be stored on a server or other network-connected device, and later retrieved by a connected client device for display processing by a swivel/360-degree spinner on the client device. The swivel/360-degree spinner may utilize native video processing capabilities of the client device and/or of a browser running on the client device to display video motion of the object moving through different angular orientations in response to movement of an interactive cursor.

Using video to encode assets for swivel/360-degree spinners

Method for providing augmented user interface (AUI). AUI is provided in response to a request. AUI configuration information is received, stored in preference file, and sent to remote server. Remote server receives request from computer to login user. Remote server authenticates user, retrieves and sends preference file to computer. Preference file contains information that allows computer to implement and configure AUI by directing output to AUI component. Remote server sends computer web-based API to enable browser to interface with an AUI application. API can include target callable by event handler to respond to HTML document browsing event by invoking AUI application. Remote server can send computer web-based, native, or browser plug-in AUI application. Computer can provide content rich navigation via API, AUI application and content navigation rules that define plural navigation paths through HTML document. Navigation paths providing AUI functionality to particular type of special needs user or user task.

Cloud-based user interface augmentation

Methods and systems for providing a preloader animation for image viewers is provided. An example method includes receiving an image of an object, determining an edge gradient value for pixels of the image, and selecting pixels representative of the object that have a respective edge gradient value above a threshold. The example method also includes determining a model of the object including an approximate outline of the object and structures internal to the outline that are oriented based on the selected pixels being coupling points between the structures, and providing instructions to display the model in an incremental manner so as to render given structures of the model over time.

Growing community of inventors

Sunnyvale, CA, United States of America

Chaitanya Gharpure