42 - Scientific, technological and industrial services, research and design
Goods & Services
Providing online non-downloadable software for use in
processing and generating natural language queries;
providing online non-downloadable software using ai
(artificial intelligence) for the production of speech and
text; providing online non-downloadable software for
multi-modal and large machine-learning based language, text,
and speech processing software; providing temporary use of
online non-downloadable software for facilitating
interaction and communication between humans and artificial
intelligence powered technology; providing temporary use of
online non-downloadable software for facilitating
multi-modal and large natural language, speech, text, image,
video, code, and sound input; research and development
services in the fields of multi-modal computer natural
language processing, artificial intelligence, and machine
learning; providing online non-downloadable software for
extracting and retrieving information and data for others by
means of artificial intelligence; providing online
non-downloadable computer software for use as an application
programming interface (api) for use in the fields of
artificial intelligence, natural language processing, image
content analysis, speech recognition, deep learning, high
performance computing, distributed computing,
virtualization, machine learning, cluster computing,
internet of things, and container management; computer
services, namely, search engine services using artificial
intelligence; providing online non-downloadable chatbot
software for simulating conversations; providing online
non-downloadable software for advertising and promoting the
goods and services of others, comparison shopping services,
and providing special offers and online catalogs featuring a
wide variety of consumer goods of others; providing online
non-downloadable software for providing and displaying
geographic information, interactive geographic maps,
non-downloadable software for accessing satellite and aerial
images of earth and space, and ocean bathymetry using
artificial intelligence; providing online computer mapping
services using artificial intelligence; mapping services,
namely, providing online non-downloadable geographic
information system (gis) software using artificial
intelligence; providing use of non-downloadable software
using artificial intelligence for controlling home
automation systems, namely, lighting, appliances, heating
and air conditioning units, alarms and other safety
equipment, home monitoring equipment; cloud computing
featuring software using artificial intelligence for use in
creating web applications, syncing, storing, archiving and
backing-up data to cloud servers; cloud computing featuring
software featuring artificial intelligence for use in
deploying virtual machines to a cloud computing platform;
cloud computing featuring software using artificial
intelligence for use in sharing data, creating data
visualizations, data processing, and analyzing data; cloud
computing featuring software using artificial intelligence
for use in administration of computer local area networks
management of computer applications and computer hardware,
and computer application distribution; cloud computing
featuring software using artificial intelligence for use in
managing online projects, developing predictive digital
marketing models, managing and facilitating online
conferences, meetings, demonstrations, tours, presentations
and interactive discussions; providing online
non-downloadable computer software for developing,
deploying, updating, managing, monitoring, training, and
evaluating the performance of machine learning, deep
learning, artificial intelligence and large language models;
platform-as-a-service (paas), infrastructure-as-a-service
(iaas) and software-as-a-service (saas) services featuring
computer software platforms using artificial intelligence
for sharing data, creating data visualizations, data
processing, and analyzing data; platform as a service (paas)
featuring computer software for developing, deploying,
updating, managing, monitoring, training, and evaluating the
performance of machine learning, large language, deep
learning, artificial intelligence and large learning models;
platform-as-a-service (paas), infrastructure-as-a-service
(iaas) and software-as-a-service (saas) services featuring
computer software platforms using artificial intelligence
for managing online projects, developing predictive digital
marketing models, managing and facilitating online
conferences, meetings, demonstrations, tours, presentations
and interactive discussions; computer services, namely,
creating cloud-based indexes of information using artificial
intelligence; providing online non-downloadable computer
software for use as an application programming interface
(api) for use in the fields of artificial intelligence,
natural language processing, image content analysis, speech
recognition, deep learning, statistical learning,
mathematical learning, supervised learning, unsupervised
learning, high performance computing, distributed computing,
virtualization, machine learning, cluster computing,
internet of things, and container management; providing
on-line non-downloadable software featuring online storage
of documents and databases using artificial intelligence;
providing temporary use of non-downloadable computer
software using artificial intelligence for browsing,
accessing, transmitting, and displaying digital content,
computer software programs, audio works, visual works,
audiovisual works, electronic publications, books, and
movies; computer services, namely, monitoring, tracking,
optimizing, and reporting on the performance of the websites
and website traffic, e-commerce activity, customer loyalty,
and sales conversion rates, and online content of others
using artificial intelligence; providing online
non-downloadable software for tracking, managing, and
optimizing advertising and promotional campaigns, and
calculating return on investment in connection with the same
using artificial intelligence; technical support services,
namely, troubleshooting of computer hardware, computer
software, and network problems using artificial
intelligence; providing online non-downloadable computer
software for calendaring and scheduling, task management,
and personal information management using artificial
intelligence; providing online non-downloadable software for
use in personal productivity, collaboration, communication,
and publishing using artificial intelligence; providing
online non-downloadable software using artificial
intelligence for database management and word processing;
providing online non-downloadable software using artificial
intelligence for use in creating, accessing and editing
spreadsheets, emails, and presentations; providing online
non-downloadable software for language translation using
artificial intelligence; providing online non-downloadable
software for language and speech processing, generation,
understanding and analysis; providing online
non-downloadable software for creating generative models;
providing online non-downloadable software for processing
and generating speech, text, sound, code, videos, images,
and sound input; research, design and development of
computer programs and software; providing online
non-downloadable software for managing data sets and
performing safety checks in the field of artificial
intelligence; providing temporary use of online
non-downloadable software for creating an integrated
development environment for large language models; providing
non-downloadable software using ai (artificial intelligence)
for creating and generating images and video from text;
research and development services in the field of
text-to-image and text-to-video generation; software as a
service (saas) featuring software for text-to-image
generation and creation; providing online non-downloadable
software using artificial intelligence for automatic voice
and speech recognition, translation and transcription;
providing online non-downloadable software for using and
customizing foundational models, namely, large artificial
intelligence models trained on a large quantity of data;
software as a service (saas) services featuring software for
using and customizing foundational models, namely, large
artificial intelligence models trained on a large quantity
of data; software as a service (saas) services for building,
managing, updating, developing, training, evaluating, and
monitoring generative user experiences powered by machine
learning, deep learning, and artificial intelligence;
providing temporary use of online non-downloadable software
using artificial intelligence (ai), machine learning, and
deep learning for use in software development and computer
code; providing temporary use of online non-downloadable
software using artificial intelligence (ai), machine
learning, and deep learning for use in software development
and writing, editing, correcting, maintaining, translating,
checking, updating, upgrading, migrating, testing,
automating, summarizing, describing, documenting, and
tracking computer code; providing temporary use of online
non-downloadable software using artificial intelligence
(ai), machine learning, and deep learning for analyzing code
and providing computer-generated code recommendations;
application service provider featuring application
programming interface (api) software for use in software
development and writing, editing, correcting, maintaining,
translating, checking, updating, upgrading, migrating,
testing, automating, summarizing, describing, documenting,
and tracking computer code; software as a service (saas)
services featuring software using artificial intelligence
for evaluating, synthesizing, and interacting with primary
source materials, documents, and information, and for
automatically generating written material, notes, summaries,
and reports; providing use of online non-downloadable
software featuring artificial intelligence for evaluating,
synthesizing, and interacting with primary source materials,
documents, and information, and for automatically generating
written material, notes, summaries, and reports; providing
use of online non-downloadable software for facilitating
interaction and communication between humans and ai
(artificial intelligence) chatbots concerning primary source
materials, documents, and information; providing use of
online non-downloadable software featuring artificial
intelligence to assist in preparing outlines, study-guides,
taking notes on, and summarizing primary source materials,
documents and information; providing use of online
non-downloadable software featuring artificial intelligence
for assisting users in understanding and capturing insights
contained within primary source materials, documents, and
information; providing online non-downloadable artificial
intelligence software; providing online non-downloadable
software for use in the fields of artificial intelligence,
machine learning, natural language generation, statistical
learning, mathematical learning, supervised learning, and
unsupervised learning; extraction and retrieval of
information and data analysis by means of artificial
intelligence; providing online non-downloadable software for
use in the fields of artificial intelligence, machine
learning, natural language generation, statistical learning,
mathematical learning, supervised learning, and unsupervised
learning; application service provider featuring application
programming interface (api) software.
09 - Scientific and electric apparatus and instruments
10 - Medical apparatus and instruments
Goods & Services
Wearable devices for the detection, monitoring, and
management of health and physiological data, not for medical
use, namely, wearable activity and biometric data trackers,
and wearable computers in the nature of smartwatches not for
medical use. Wearable devices for the detection, monitoring, and
management of health and physiological data, namely,
wearable activity and biometric data trackers, wearable
computers in the nature of smartwatches, and medical
apparatus and instruments for monitoring vital signs, blood
properties and respiratory properties and events; all the
foregoing for medical use.
09 - Scientific and electric apparatus and instruments
42 - Scientific, technological and industrial services, research and design
Goods & Services
Downloadable software for patient case management for use by
healthcare providers for the purpose of viewing and sharing
patient health information, performing healthcare data
analytics, generating patient insights, and managing patient
care. Providing temporary use of non-downloadable cloud-based
software for patient case management for use by healthcare
providers for the purpose of viewing and sharing patient
health information, performing healthcare data analytics,
generating patient insights, and managing patient care.
The present disclosure contemplates a method for synchronizing a large number of generators on an AC bus simultaneously by closing the generator breakers when the generators are rotating but de-energized. Then excitation is raised for each generator simultaneously, causing the generators to synchronize as voltage increases, without large transient current surges that can damage the machines. In order to safely maximize the rate at which excitation is raised, initial excitation can be controlled using current regulation, specifically controlling excitation current instead of voltage. Once a predetermined voltage is reached, a control scheme can be switched to a voltage regulation mode, which brings the generator to the final desired voltage.
H02P 1/56 - Arrangements for starting electric motors or dynamo-electric converters for starting dynamo-electric motors or dynamo-electric converters for starting two or more dynamo-electric motors simultaneously
H02P 5/68 - Arrangements specially adapted for regulating or controlling the speed or torque of two or more electric motors controlling two or more dc dynamo-electric motors
5.
Dynamic Participant Device Management for Hosting a Teleconference
Systems and methods for hosting a teleconference are disclosed herein. The method can include receiving, by a server, a request from a connected participant device to transition from a non-interactive slot to an interactive slot of the teleconference and moving, by the server, the connected participant device from the non-interactive slot to a buffer slot. The method can also include determining, by the server, a longest-inactive participant device among one or more participant devices currently occupying interactive slots; removing, by the server, the longest-inactive participant device from an associated interactive slot; and moving, by the server, the connected participant device from the buffer slot to the associated interactive slot.
A method includes receiving a spoken utterance that includes a plurality of words, and generating, using a neural network-based utterance classifier comprising a stack of multiple Long-Short Term Memory (LSTM) layers, a respective textual representation for each word of the of the plurality of words of the spoken utterance. The neural network-based utterance classifier trained on negative training examples of spoken utterances not directed toward an automated assistant server. The method further including determining, using the respective textual representation generated for each word of the plurality of words of the spoken utterance, that the spoken utterance is one of directed toward the automated assistant server or not directed toward the automated assistant server, and when the spoken utterance is directed toward the automated assistant server, generating instructions that cause the automated assistant server to generate a response to the spoken utterance.
A computer-implemented method for partially supervised image segmentation having improved strong mask generalization includes obtaining, by a computing system including one or more computing devices, a machine-learned segmentation model, the machine-learned segmentation model including an anchor-free detector model and a deep mask head network, the deep mask head network including an encoder-decoder structure having a plurality of layers. The computer-implemented method includes obtaining, by the computing system, input data including tensor data. The computer-implemented method includes providing, by the computing system, the input data as input to the machine-learned segmentation model. The computer-implemented method includes receiving, by the computing system, output data from the machine-learned segmentation model, the output data including a segmentation of the tensor data, the segmentation including one or more instance masks.
G06V 10/77 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
G06V 10/774 - Generating sets of training patterns; Bootstrap methods, e.g. bagging or boosting
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
8.
DECENTRALIZED LEARNING OF MACHINE LEARNING MODEL(S) THROUGH UTILIZATION OF STALE UPDATES(S) RECEIVED FROM STRAGGLER COMPUTING DEVICE(S)
During a round of decentralized learning for updating of a global machine learning (ML) model, remote processor(s) of a remote system may transmit, to a population of computing devices, primary weights for a primary version of the global ML model, and cause each of the computing devices to generate a corresponding update for the primary version of the global ML model. Further, the remote processor(s) may cause the primary version of the global ML model to be updated based on the corresponding updates that are received during the round of decentralized learning. However, the remote processor(s) may receive other corresponding updates subsequent to the round of decentralized learning. Accordingly, various techniques described herein (e.g., FARe-DUST, FeAST on MSG, and/or other techniques) enable the other corresponding updates to be utilized in achieving a final version of the global ML model.
Various arrangements involving a bidirectional pulse driver circuit are presented herein. The driver circuit can include a forward pulse trigger circuit and a forward pulse loop circuit. The forward pulse loop circuit can include a first silicon-controlled rectifier (SCR) that is activated by the forward pulse trigger circuit. The driver circuit can include a reverse pulse trigger circuit and a reverse pulse loop circuit. The reverse pulse loop circuit can include a second SCR that is activated by the reverse pulse trigger circuit. The driver circuit can also include a controller that activates the forward pulse trigger circuit and the reverse pulse trigger circuit in a first pattern to cause a current pulse to be applied to a load in a forward direction and in a second pattern to cause the current pulse to be applied to the load in a reverse direction.
H03K 3/57 - Generators characterised by the type of circuit or by the means used for producing pulses by the use of an energy-accumulating element discharged through the load by a switching device controlled by an external signal and not incorporating positive feedback the switching device being a semiconductor device
H03K 3/352 - Generators characterised by the type of circuit or by the means used for producing pulses by the use, as active elements, of bipolar semiconductor devices with more than two PN junctions, or more than three electrodes, or more than one electrode connected to the same conductivity region the devices being thyristors
10.
HEAD-WORN COMPUTING DEVICE WITH MICROPHONE BEAM STEERING
The disclosed devices and methods provide beamforming for a head-worn microphone array that can adapt to changes in the user's head position/orientation. The microphone array may be part of a head-worn computing device, which can be configured to automatically detect a direction for the beamforming based on computer-assisted recognition of a conversation with a participant. After the participant is identified, the beamforming can automatically steer the sensitivity of the microphone array towards the participant regardless of the position of the head user to improve a quality of the captured audio without constraining movement of a user. The improved audio may be used to aid in a user's hearing of the conversation, aid an augmented reality application corresponding to the conversation, and/or provide a degree of privacy by limiting sensitivity to participants in the conversation.
To provide navigation directions according to road surface types of road segments, a request for navigation directions from a starting location to a destination location is received. A set of candidate routes for navigating from the starting location to the destination location is identified. Then for each road segment within each candidate route, a road surface type for the road segment is determined. A route is selected from the set of candidate routes based at least in part on the road surface types of the road segments within the route. A set of navigation directions is provided for presentation on a client device for navigating from the starting location to the destination location via the selected route.
The technology is generally directed to a coordinated power throttling mechanism for a payload using power provided by a rack such that the rack power does not exceed a threshold amount for greater than a predetermined period of time. The coordinated power throttling mechanism includes the rack providing a power throttling signal to the payload and the payload executing the power throttling upon detection of the throttling signal. The payload may detect the throttling signal and, after a delay, execute the power throttling. The delay may ensure that all payloads within the rack have detected the power throttling signal.
An example device includes a display component that is configured to operate at a first refresh rate or a second refresh rate. The device also includes one or more processors operable to perform operations. The operations include identifying a rate change triggering event while the display component is operating at the first refresh rate. The operations further include determining a current brightness value of the display component. The operations also include determining, based on an environmental state measurement associated with an environment around the device, a threshold brightness value. The operations additionally include transitioning the display component from the first refresh rate to the second refresh rate m response to identifying the rate change triggering event if the current brightness value of the display component meets or exceeds the threshold brightness value.
G09G 3/20 - Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes for presentation of an assembly of a number of characters, e.g. a page, by composing the assembly by combination of individual elements arranged in a matrix
G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
14.
ROBOT NAVIGATION IN DEPENDENCE ON GESTURE(S) OF HUMAN(S) IN ENVIRONMENT WITH ROBOT
Training and/or utilizing a high-level neural network (NN) model, such as a sequential NN model. The high-level NN model, when trained, can be used to process a sequence of consecutive state data instances (e.g., N most recent, including a current state date instance) to generate a sequence of outputs that indicate a sequence of position deltas. The sequence of position deltas can be used to generate an intermediate target position for navigation and, optionally, an intermediate target orientation that corresponds to the intermediate target position. The intermediate target position and, optionally, the intermediate target orientation, can be provided to a low-level navigation policy, such as an MPC policy, and used by the low-level navigation policy as its goal position (and optionally goal orientation) for a plurality of iterations (e.g., until a new intermediate target position (and optionally new target orientation) is generated using the high-level NN model.
G05D 1/02 - Control of position or course in two dimensions
G06V 10/80 - Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 40/20 - Movements or behaviour, e.g. gesture recognition
15.
SYSTEMS AND METHODS FOR HANDLING MACRO COMPATIBILITY FOR DOCUMENTS AT A STORAGE SYSTEM
A document including one or more macros in a first programming language is identified. A determination is made that one or more objects of the document are referenced by a function defined by a macro of the one or more macros. The function is converted into one or more sets of operations represented in a first programming language. A user is provided with access to the one or more objects of the document based on the one or more sets of operations represented in the second programming language.
G06F 8/76 - Adapting program code to run in a different environment; Porting
G06F 9/38 - Concurrent instruction execution, e.g. pipeline, look ahead
H04L 67/1097 - Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
16.
Methods and Systems for Improving Measurement of Sleep Data by Classifying Users Based on Sleeper Type
The present disclosure is directed towards systems and methods for improving analysis of sleep data by classifying users based on sleeper type. In particular, a wearable computing system can obtain a first set of motion sensor data from the motion sensor for a user during a first period. The wearable computing system can determine a sleeper type from a plurality of sleeper types for the user based on the first set of motion sensor data received from the motion sensor. The wearable computing system can select a sleep analysis model from a plurality of sleep analysis models based on the sleeper type determined for the user. The wearable computing system can use the selected sleep analysis model to analyze a second set of motion sensor data from a second period to determine one or more sleep characteristics for the user during the second period.
Provided are machine learning models that generate geometry-free neural scene representations through efficient object-centric novel-view synthesis. In particular, one example aspect of the present disclosure provides a novel framework in which an encoder model (e.g., an encoder transformer network) processes one or more RGB images (with or without pose) to produce a fully latent scene representation that can be passed to a decoder model (e.g., a decoder transformer network). Given one or more target poses, the decoder model can synthesize images in a single forward pass. In some example implementations, because transformers are used rather than convolutional or MLP networks, the encoder can learn an attention model that extracts enough 3D information about a scene from a small set of images to render novel views with correct projections, parallax, occlusions, and even semantics, without explicit geometry.
Systems and methods of the present disclosure include a method for increasing teleconferencing bandwidth efficiency via presentation of remotely accessible content. The method includes receiving a request to present content to a teleconference from a presenting participant device of the teleconference. The method includes generating a unit of software instructions that is configured to cause a participant device to access the content from an originating location that differs from the presenting participant device, and display the content within a shared content interface of the teleconference configured to display a view of the content that is consistent between each participant device of the teleconference. The method includes providing the unit of software instructions to one or more non-presenting participant devices of the teleconference.
Multiple global motion models associated with respective segments of a current frame are decoded from a compressed bitstream. Each global motion model is based on a segmentation of the current frame and represents a respective underlying motion of blocks within a respective segment. Blocks of the current frame are decoded by: for each inter-predicted block of a segment, decoding, form the compressed bitstream, an indication of whether to decode the each inter-predicted block based on a global motion model of the multiple global motion models and associated with the segment, or whether to decode the each inter-predicted block based on a motion vector that is different from the global motion model; and decoding the each inter-predicted block based on the indication.
H04N 19/517 - Processing of motion vectors by encoding
H04N 19/17 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
H04N 19/20 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using video object coding
H04N 19/54 - Motion estimation other than block-based using feature points or meshes
H04N 19/543 - Motion estimation other than block-based using regions
H04N 19/547 - Motion estimation performed in a transform domain
H04N 19/557 - Motion estimation characterised by stopping computation or iteration based on certain criteria, e.g. error magnitude being too large or early exit
H04N 19/80 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals - Details of filtering operations specially adapted for video compression, e.g. for pixel interpolation
20.
MANAGING INSTALLATION AND UPDATES OF AN APPLICATION ON A COMPUTING DEVICE
This disclosure relates to a method for managing installation of applications, where the method includes receiving, from a first computing device associated with an administrator of an organization, a pin request to attach an application, provided by an application store platform, with a version of the application, initiating, in response to the pin request, transfer of a copy of the version of the application from the application store platform to a data storage device, generating an application identifier that identifies a location of the version of the application stored in the data storage device, and transmitting installation data to a second computing device that is managed by the organization. The installation data includes the application identifier, which is used by the second computing device to install the version of the application from the data storage device.
Aspects of the disclosure provide for verifying user-generated content (UGC). When the UGC is a review of an entity of a good or service, the review is verified when a UGC verification system determines that the user authoring the review was a consumer of a good or service offered by the entity. At the time of a transaction for a good or service, the UGC verification system can receive and respond to a request by a point-of-sale (POS) system to generate a unique encoding. The POS system may be implemented on a device in communication with, but separate from, a platform implementing the UGC verification system. The UGC verification system tracks receipt of requests to access a content form for leaving a review, so as to ensure that each generated encoding is only used to access the content form once.
Systems and methods of generating voice-based software applications are provided. A system can receive, from an application developer computing device, a request to build a voice-based software application. The system can select an application template from a plurality of application templates. The selected application template can include a module that corresponds to a function of the voice-based software application. The system can provide the selected application template to the application developer computing device. The system can receive, from the application developer computing device, an input for a field of the at least one module of the selected application template. The system can generate the voice-based software application based on the selected application template and the input for the at least one field of the at least one module of the selected application template.
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
G10L 15/18 - Speech classification or search using natural language modelling
G10L 15/22 - Procedures used during a speech recognition process, e.g. man-machine dialog
G10L 15/28 - Constructional details of speech recognition systems
H04N 21/2387 - Stream processing in response to a playback request from an end-user, e.g. for trick-play
H04N 21/458 - Scheduling content for creating a personalised stream, e.g. by combining a locally stored advertisement with an incoming stream; Updating operations, e.g. for OS modules
23.
AUDIO-BASED POLLING DURING A CONFERENCE CALL DISCUSSION
One or more audio files including a recording of one or more verbal statements provided by a first participant of the conference call are obtained. A determination is made that the recorded one or more verbal statements include a question associated with audio-based polling of a set of second participants of the conference call. Response data indicating one or more responses to the question provided by at least one of the set of second participants is obtained. A report indicating one or more outcomes of the audio-based polling is generated based on at least the question and the one or more responses to the question indicated by the obtained response data.
Audio rendering devices comprising at least one audio rendering unit for playing audio streams, processing circuit and a wireless communication unit for establishing wireless links and related method are disclosed. One audio rendering device is configured to receive a remote audio stream prioritization policy comprising one or more lists of associations between audio stream attributes and priority values, update a local audio stream prioritization policy based on the remote audio stream prioritization policy, identify audio streams available via wireless links, retrieve audio stream attributes of the available audio streams, select an available audio stream to be played among the available audio streams, based on the updated local audio stream prioritization policy and based on the audio stream attributes of the available audio streams, and play the selected audio stream, by the audio rendering unit of the audio rendering device.
G10L 25/51 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium for securely attributing application (app) installations while preserving user privacy are described. In one aspect, a method includes a given digital component that can be provided and can include a reference to a software application. A user interaction with the digital component that initiates installation of the application can be detected. The software application can be installed at a client device. The following can be obtained: (i) impression data that reference the software application and (ii) interaction data that reference the software application. Attribution credits for the installation of the software application can be assigned by applying an attribution model to the presentation and interaction data. Attribution tokens can be generated that includes (i) data identifying the software application, (ii) data identifying the respective attribution credit assigned to the entity, and (iii) and an integrity token.
G06F 21/57 - Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
G06F 21/64 - Protecting data integrity, e.g. using checksums, certificates or signatures
H04L 9/32 - Arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system
26.
AUTOMATICALLY TRASITIONING A ROBOT TO AN OPERATIONAL MODE OPTIMIZED FOR PARTICULAR TERRAIN
According to one disclosed method, one or more sensors of a robot may receive data corresponding to one or more locations of the robot along a path the robot is following within an environment on a first occasion. Based on the received data, a determination may be made that one or more stairs exist in a first region of the environment. Further, when the robot is at a position along the path the robot is following on the first occasion, a determination may be made that the robot is expected to enter the first region. The robot may be controlled to operate in a first operational mode associated with traversal of stairs when it is determined that one or more stairs exist in the first region and the robot is expected to enter the first region.
27.
CONTROLLING ROBOTS USING LANGUAGE MODEL GENERATED PROGRAMS
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for controlling a robot using language model programs. A language model program is computer program generated from an output of a code generation neural network, e.g., one that has been trained on a language modeling objective on computer code data.
This document describes systems for and techniques of alternating-current (AC) power harmonic-based circuit state detection. In various aspects, a system includes a component, a bypass circuit for the component, and a controller with an AC power harmonic-based circuit state detector that can determine a state of the bypass circuit. The AC power harmonic-based circuit state detector may convert an AC voltage of the AC power to a direct current (DC) voltage, filter the DC voltage to obtain a voltage of a harmonic of the AC power, and compare the voltage of the harmonic to a threshold to determine that the bypass circuit is in a fault state (blown fuse). By so doing, the controller of the system can notify a user that the bypass circuit needs to be reset or replaced to reenable operation of the system and avoid poor user experience typically associated with a non- or mis-functioning system.
H02J 1/00 - Circuit arrangements for dc mains or dc distribution networks
H02J 3/00 - Circuit arrangements for ac mains or ac distribution networks
H02J 3/01 - Arrangements for reducing harmonics or ripples
H02J 3/14 - Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load by switching loads on to, or off from, network, e.g. progressively balanced loading
G08B 3/10 - Audible signalling systems; Audible personal calling systems using electromagnetic transmission
H04N 7/18 - Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
Methods, systems, and apparatus, for an analog-to-digital converter. One system includes an MSB DAC array configured to generate respective sample values for one or more most-significant bits of an output ADC value, a first LSB DAC array configured to generate respective sample values for one or more least-significant bits of the output ADC value, a second LSB DAC array configured to generate respective sample values for the one or more least-significant bits of the output ADC value, wherein each DAC array in the first LSB DAC array and the second LSB DAC array is configured to alternate between generating an output ADC bit value and a mismatch error value for the output ADC bit value.
H03M 1/06 - Continuously compensating for, or preventing, undesired influence of physical parameters
H03M 1/46 - Analogue value compared with reference values sequentially only, e.g. successive approximation type with digital/analogue converter for supplying reference values to converter
30.
REDUCING MEMORY BANK CONFLICTS IN A HARDWARE ACCELERATOR
Methods and systems, including computer-readable media, are described for reducing or preventing memory bank conflicts in a hardware accelerator to allow for concurrent access of memory banks at a hardware accelerator. A compute tile of the hardware accelerator receives requests that are used to access a tile memory of the accelerator. For each of the requests: a logical address represented by a sequence of bits is identified in the request and a first subset of bits is obtained from the sequence. An identifier is generated based on a bank generation function that uses the first subset of bits. The identifier identifies a particular bank among physical memory banks of the tile memory. Each request is processed using the respective bank identifier that is generated for that request. Multiple distinct memory banks are accessed concurrently during the same clock cycle in response to processing the requests.
Systems and methods of the present disclosure are directed to automatic control of mute controllers for participants in videoconferences. For example, a method for automatically controlling a mute control associated with a participant during a videoconference includes obtaining communication data associated with the participant participating in the videoconference. The communication data includes audio signals associated with the participant and/or visual signals associated with the participant. The method includes processing the communication data by a gate control model to generate an output. The output is indicative of an intent of the participant to communicate with other participants of the videoconference. The method includes generating a noise gate status based at least in part on the output associated with the gate control model. The method includes automatically controlling the mute control of the participant based at least in part on the noise gate status.
Various arrangements involving a bidirectional pulse driver circuit are presented herein. The driver circuit can include a forward pulse trigger circuit and a forward pulse loop circuit. The forward pulse loop circuit can include a first silicon-controlled rectifier (SCR) that is activated by the forward pulse trigger circuit. The driver circuit can include a reverse pulse trigger circuit and a reverse pulse loop circuit. The reverse pulse loop circuit can include a second SCR that is activated by the reverse pulse trigger circuit. The driver circuit can also include a controller that activates the forward pulse trigger circuit and the reverse pulse trigger circuit in a first pattern to cause a current pulse to be applied to a load in a forward direction and in a second pattern to cause the current pulse to be applied to the load in a reverse direction.
H03K 17/73 - Bipolar semiconductor devices with more than two PN junctions, e.g. thyristors, programmable unijunction transistors, or with more than three electrodes, e.g. silicon controlled switches, or with more than one electrode connected to the same conducti for dc voltages or currents
H03K 17/66 - Switching arrangements for passing the current in either direction at will; Switching arrangements for reversing the current at will
33.
DYNAMIC QUANTIZATION PARAMETER FOR ENCODING A VIDEO FRAME
A computer-implemented method includes setting, by a computing device, a maximum quantization parameter (QP) value for encoding an input video frame to a value which is the maximum of: a first QP value corresponding to a first proportion of an application-specified maximum QP value, or a second QP value determined based on a value which is the minimum of: a third QP value determined based on an average value of QP values used to encode a plurality of video frames before the input video frame, or a fourth QP value corresponding to a second proportion of the application-specified maximum QP value. The computer-implemented method further includes using the set maximum QP value as a quality bound for encoding the input video frame.
H04N 19/172 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a picture, frame or field
H04N 19/136 - Incoming video signal characteristics or properties
H04N 19/30 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using hierarchical techniques, e.g. scalability
This document describes apparatus, devices, and methods for providing an isolation element for diversity antennas. The systems and techniques use supporting circuitry, such as wiring connectors, in a transmission device that uses diversity antennas to present a conductor connected to electrical ground to receive a portion of a transmission signal generated by at least one of the antennas to couple the signal to ground. In this manner, the isolation element helps to prevent signals from the diversity antennas from merging and thereby supports the diversity antennas' capability of successfully transmitting a signal when an obstacle may impede the signal transmitted by one of the antennas.
A computing device outputs for display a first graphical element and a second graphical element. The second, graphical element is located at an initial location relative to the first graphical element, where the initial location is at a first angular position relative to the first graphical element. The computing device receives an indication of a user input having an input point starting at the initial location. The computing device determines whether the user input corresponds to a swivel gesture. Responsive to determining that the user input corresponds to the swivel gesture, the computing device performs an action associated with the swivel gesture.
G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
G06F 3/04847 - Interaction techniques to control parameter settings, e.g. interaction with sliders or dials
G06F 3/04883 - Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures for inputting data by handwriting, e.g. gesture or text
36.
PRESENTATION OF REMOTELY ACCESSIBLE CONTENT FOR OPTIMIZING TELECONFERENCE RESOURCE UTILIZATION
Systems and methods of the present disclosure include a method for increasing teleconferencing bandwidth efficiency via presentation of remotely accessible content. The method includes receiving a request (118) to present content (120) to a teleconference from a presenting participant device (102) of the teleconference. The method includes generating a unit of software instructions (128) that is configured to cause a participant device (103) to access the content (120) from an originating location (122) that differs from the presenting participant device (102), and display the content (120) within a shared content interface of the teleconference configured to display a view of the content (120) that is consistent between each participant device (102, 103) of the teleconference. The method includes providing the unit of software instructions (128) to one or more non-presenting participant devices (103) of the teleconference.
H04L 65/401 - Support for services or applications wherein the services involve a main real-time session and one or more additional parallel real-time or time sensitive sessions, e.g. white board sharing or spawning of a subconference
H04L 65/403 - Arrangements for multi-party communication, e.g. for conferences
In a general aspect, an electronic device includes a semiconductor structure including a doped surface, a silver-based (Ag-based) layer electrically contacting at least a portion of the doped surface and a passivation layer disposed on a portion of the semiconductor structure. A portion of the passivation layer is in physical contact with the Ag-based layer. The passivation layer is a material compound including a II-Nitride material.
H01L 33/44 - SEMICONDUCTOR DEVICES NOT COVERED BY CLASS - Details thereof characterised by the coatings, e.g. passivation layer or anti-reflective coating
38.
RESTRICTING THIRD PARTY APPLICATION ACCESS TO AUDIO DATA CONTENT
Implementations relate to restricting access of an application to audio data content captured subsequent to rendering content to the user at the request of the application. An application can generate content that is to be rendered to a user with an additional request to receive audio data content from audio data captured immediately after rendering the content. The content can be processed, using a trained machine learning model that generates, as output, an indication of likelihood that providing audio data content after rendering the content from the application was improper. In instances the application improperly requested audio data content, the application can be restricted from being provided the audio data content and/or subsequent audio data content.
Implementations described herein relate to training and refining failure neural network (NN) models and robotic control policies using imitation learning techniques. A failure NN model and a robotic control policy can initially be trained based on human demonstrations of various robotic tasks. In many implementations, an instance of vision data capturing the environment of the robot can be processed using an embedding model to generate an embedding. The given embedding can be processed using the failure NN model to generate failure output indicating the likelihood of the robot failing to complete the robotic task. In various implementations, the given embedding can also be processed using the robotic control policy to generate action output for use in controlling the robot in performance of the robotic task.
Aspects of the disclosure are directed to retraining an ensemble machine learning model. The ensemble model can include a base model and an overlay model. The base model can be trained on an older dataset, validated, and manually verified. The overlay model can be trained on a newer dataset and automatically validated. A combination of base model predictions and overlay model predictions, with bias towards the base model predictions, can form ensemble model predictions. A model weight for optimizing the ensemble model can determine the bias, as well as indicate that the overlay model contributes too much or too little to the ensemble model.
A reading assistant tool implemented in a browser application facilitates the presentation of text content in a manner and format that addresses the reading and/or comprehension capabilities of individual users, while maintaining the context of the original content. The reading assistant tool outputs a reader view pane alongside a main content pane. Original content is presented in the main content pane, and simplified/reformatted content corresponding to text content extracted from the original content, is presented in the reader view pane. Scrolling of the extracted text content in the reader view pane is synchronized with scrolling of the original content in the main content pane, so that context is maintained as the user moves through the content. The concurrent presentation of the original content and the extracted text content allows the user to more easily consume the extracted text content, while also maintaining context as originally intended.
A computing system may provide a model of a robot. The model may be configured to determine simulated motions of the robot based on sets of control parameters. The computing system may also operate the model with multiple sets of control parameters to simulate respective motions of the robot. The computing system may further determine respective scores for each respective simulated motion of the robot, wherein the respective scores are based on constraints associated with each limb of the robot and a goal. The constraints include actuator constraints and joint constraints for limbs of the robot. Additionally, the computing system may select, based on the respective scores, a set of control parameters associated with a particular score. Further, the computing system may modify a behavior of the robot based on the selected set of control parameters to perform a coordinated exertion of forces by actuators of the robot.
B62D 57/032 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted feet or skid
A robot leg assembly including a hip joint and an upper leg member. A proximal end portion of the upper leg member rotatably coupled to the hip joint. The robot leg assembly including a knee joint rotatably coupled to a distal end portion of the upper leg member, a lower leg member rotatably coupled to the knee joint, a linear actuator disposed on the upper leg member and defining a motion axis, and a motor coupled to the linear actuator and a linkage coupled to the translation stage and to the lower leg member. The linear actuator includes a translation stage moveable along the motion axis to translate rotational motion of the motor to linear motion of the translation stage along the motion axis, which moves the linkage to rotate the lower leg member relative to the upper leg member at the knee joint.
B62D 57/032 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted feet or skid
44.
Systems and Methods for Communication Efficient Distributed Mean Estimation
The present disclosure provides systems and methods for communication efficient distributed mean estimation. In particular, aspects of the present disclosure can be implemented by a system in which a number of vectors reside on a number of different clients, and a centralized server device seeks to estimate the mean of such vectors. According to one aspect of the present disclosure, a client computing device can rotate a vector by a random rotation matrix and then subsequently perform probabilistic quantization on the rotated vector. According to another aspect of the present disclosure, subsequent to quantization but prior to transmission, the client computing can encode the quantized vector according to a variable length coding scheme (e.g., by computing variable length codes).
A method for decaying speech processing includes receiving, at a voice-enabled device, an indication of a microphone trigger event indicating a possible interaction with the device through speech where the device has a microphone that, when open, is configured to capture speech for speech recognition. In response to receiving the indication of the microphone trigger event, the method also includes instructing the microphone to open or remain open for a duration window to capture an audio stream in an environment of the device and providing the audio stream captured by the open microphone to a speech recognition system. During the duration window, the method further includes decaying a level of the speech recognition processing based on a function of the duration window and instructing the speech recognition system to use the decayed level of speech recognition processing over the audio stream captured by the open microphone.
Systems and methods of the present disclosure are directed to automatic control of mute controllers for participants in videoconferences. For example, a method for automatically controlling a mute control associated with a participant during a videoconference includes obtaining communication data associated with the participant participating in the videoconference. The communication data includes audio signals associated with the participant and/or visual signals associated with the participant. The method includes processing the communication data by a gate control model to generate an output. The output is indicative of an intent of the participant to communicate with other participants of the videoconference. The method includes generating a noise gate status based at least in part on the output associated with the gate control model. The method includes automatically controlling the mute control of the participant based at least in part on the noise gate status.
G10L 25/57 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for processing of video signals
H04N 5/232 - Devices for controlling television cameras, e.g. remote control
In a computer system where multiple client computers share use of a storage device, submission priorities for input-output commands from the computers are adjusted when one or more of the client computers exceeds its quota of usage. The submission priorities for the client computers which are exceeding their quota are reduced relative to submission priorities for client computers which are not exceeding their quotas. This allows up to full usage of the processing capacity of the storage device, while minimizing effects such as unfairness and latency experienced by the other client computers.
Methods, systems and apparatus for implementing a quantum gate on a quantum system comprising a second qubit coupled to a first qubit and a third qubit. In one aspect, a method includes evolving a state of the quantum system for a predetermined time, wherein during evolving: the ground and first excited state of the second qubit are separated by a first energy gap ω; the first and second excited state of the second qubit are separated by a second energy gap equal to a first multiple of ω minus qubit anharmoniticity η; the ground and first excited state of the first qubit and third qubit are separated by a third energy gap equal to ω−η; and the first and second excited state of the first qubit and third qubit are separated by a fourth energy gap equal to the first multiple of the ω minus a second multiple of η.
A first image is rendered on an active area of an OLED display panel with a first refresh rate that is below a threshold refresh rate and, subsequent to rendering the first image with the first refresh rate, a second image that is different from the first image is rendered on the active area, where the rendering of the second image includes rendering a number of initial frames of the second image at a second refresh rate that is at or above the threshold refresh rate. After rendering the number of initial frames of the second image at the second refresh rate, additional frames of the second image on the active area are rendered with the first refresh rate, where the number of initial frames is greater than 1.
G09G 3/3233 - Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes for presentation of an assembly of a number of characters, e.g. a page, by composing the assembly by combination of individual elements arranged in a matrix using controlled light sources using electroluminescent panels semiconductive, e.g. using light-emitting diodes [LED] organic, e.g. using organic light-emitting diodes [OLED] using an active matrix with pixel circuitry controlling the current through the light-emitting element
50.
Socket To Support High Performance Multi-die ASICs
A microelectronic system may include a microelectronic component having electrically conductive elements exposed at a first surface thereof, a socket mounted to a first surface of the microelectronic component and including a substrate embedded therein, one or more microelectronic elements each having active semiconductor devices therein and each having element contacts exposed at a front face thereof, and a plurality of socket pins mounted to and extending above the substrate, the socket pins being ground shielded coaxial socket pins. The one or more microelectronic elements may be disposed at least partially within a recess defined within the socket. The socket may have a land grid array comprising top surfaces of the plurality of the socket pins or electrically conductive pads mounted to corresponding ones of the socket pins, and the element contacts of the one or more microelectronic elements may be pressed into contact with the land grid array.
H01L 25/10 - Assemblies consisting of a plurality of individual semiconductor or other solid state devices all the devices being of a type provided for in the same subgroup of groups , or in a single subclass of , , e.g. assemblies of rectifier diodes the devices having separate containers
H01L 23/538 - Arrangements for conducting electric current within the device in operation from one component to another the interconnection structure between a plurality of semiconductor chips being formed on, or in, insulating substrates
H01L 25/00 - Assemblies consisting of a plurality of individual semiconductor or other solid state devices
51.
METHODS, SYSTEMS, AND MEDIA FOR PROVIDING AUTOMATED ASSISTANCE DURING A VIDEO RECORDING SESSION
Methods, systems, and media for providing automated assistance during a video recording session are provided. In some embodiments, the method comprises: receiving, at a first user device, user input to initiate a video recording session, wherein a video recording session comprises a plurality of segments of recorded video, wherein at least one segment of recorded video is non-contiguous with a second segment of recorded video; executing a machine learning model on the first user device that monitors the video recording session and that analyzes audio content and video content of the recorded video to determine segment metadata and segment quality metrics for each segment of the plurality of segments of recorded video; associating each segment of the plurality of segments of recorded video with the segment metadata and the segment quality metrics determined using the machine learning model, wherein the segment metadata and the segment quality metrics for each segment of the plurality of segments is presented when editing the recorded video from the video recording session; receiving a remote input during the video recording session, wherein the remote input comprises at least one of a voice command, a gesture command, and a remote control command; determining, using the machine learning model executing on the first user device, a video recording command associated with the remote input; and causing the video recording session to execute an action associated with the video recording command.
Dynamically adapting provision of notification output to reduce distractions and/or to mitigate usage of computational resources. In some implementations, an automated assistant application predicts a level of engagement for a user and determines, based on the predicted level of engagement (and optionally future predicted level(s) of engagement), provisioning (e.g., whether, when, and/or how) of output that is based on a received notification. For example, the automated assistant application can, based on predicted level(s) of engagement, determine whether to provide any output based on a received notification, determine whether to suppress provision of output that is based on the received notification (e.g., until a later time with a decreased predicted level of engagement), determine whether to provide output that is a condensed version of the received notification, determine whether to automatically respond to the notification, and/or select an output modality for providing output that is based on the received notification.
H04W 68/02 - Arrangements for increasing efficiency of notification or paging channel
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
H04W 4/46 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for vehicle-to-vehicle communication [V2V]
A system and method for updating and correcting facts that receives proposed values for facts from users and determines a correctness score which is used to automatically accept or reject the proposed values.
Methods and systems are provided for ranking search results and generating a presentation. In some implementations, a search system generates a presentation based on a search query. In some implementations, a search system ranks search results based on data stored in a knowledge graph. In some implementations, a search system identifies a modifying concept such as a superlative in a received search query, and determines ranking properties based on the modifying concept.
Systems and methods are provided for multimodal input collection. More particularly, the present disclosure relates to efficient and intuitive multimodal input collection for mobile devices. As an example, a mobile computing system (e.g., a smartphone, a tablet, a wearable device, etc.) can display a lock screen interface at a display device associated with the mobile computing system (e.g., an initial interface that requests interaction and/or authentication from the user before granting access to applications, etc.).
G06F 3/0488 - Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures
G06F 21/32 - User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
The technology is generally directed to a method of mapping fiber networks. The fiber networks may include a plurality of cables, such as fiber optic cables. The cable may be divided into segments. Each cable has a first end segment and a second end segment, each with a known location. When there is a perturbation that causes the cable to vibrate, each segment of the cable may experience an associated strain at a different time. Based on the known location of the perturbation sources, the known location of the end segments, and the relative time that the perturbation is detected at each cable segment, the location of each segment and, therefore, the entire cable may be determined.
A computerized method features operations conducted by a security analyzer device to process incoming information to ascertain a presence of cybersecurity threats based on a top threat list provided to the security analyzer device. The top threat list includes a plurality of cybersecurity threats prioritized for an enterprise that is subscribing to a threat management system and protected by the security analyzer device. The computerized method further conducts analytics of incoming information to determine a level of correlation between at least a portion of the incoming information and any of the plurality of cybersecurity threats within the top threat lists content, and upon determining the level of correlation between the portion of the incoming information and a cybersecurity threat of the plurality of cybersecurity threats exceeding a first threshold, may conduct operations to neutralize or mitigate the cybersecurity threat.
A threat management system features a recommendation engine and an action engine. The recommendation engine is configured to (i) conduct analytics on content from the threat catalog and content from the enterprise profile to generate results that identify a plurality of threats directed to the enterprise and (ii) generate a top threat list based on the analytic results. The action engine is communicatively coupled to the recommendation engine. The action engine is configured to receive the top threat list and generate a plurality of actions corresponding to each threat of the top threat list, where each action of the plurality of actions includes information directed to operations to mitigate or neutralize a risk associated with a threat of the top threat list.
Image coding using guided machine learning restoration may include obtaining reconstructed frame data by decoding, obtaining a restored frame by restoring the reconstructed frame, and outputting the restored frame. Obtaining the restored frame may include obtaining a reconstructed block, obtaining guide parameter values, obtaining a restored block, and including the restored block in the restored frame. Obtaining the restored block may include inputting the reconstructed block to an input layer of a trained guided convolutional neural network, wherein the neural network is constrained such that an output layer has a defined cardinality of channels, obtaining, from the output layer, neural network output channel predictions, obtaining a guided neural network prediction as a linear combination of the guide parameter values and the neural network output channel predictions, and generating the restored block using the guided neural network prediction.
H04N 19/176 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a block, e.g. a macroblock
H04N 19/30 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using hierarchical techniques, e.g. scalability
A voltage supervisor (VS) or voltage sensing circuitry or architecture that can detect fast voltage transients. To detect fast voltage transients, a dedicated differential pair is routed between a point of load, such as a die or other chip, processor, etc., and the circuitry of the voltage supervisor. By connecting the differential pair at the point of load, fast voltage transients may be detected at the load level (e.g., at the point of load) and thereafter used to enable, disable, and/or restart an electronic device, such as a die, chip, processor, or other electronic component or system.
The present disclosure provides for dynamically deactivating rectifiers to force remaining rectifiers to operate at or near their peak power efficiency. Rectifiers, for example rectifiers on racks of a data center, may operate according to an efficiency curve, based on its current load. Instead of distributing an AC power load across more rectifiers that operate sub-optimally on their efficiency curve, aspects of the disclosure provide for automatically deactivating some rectifiers by lowering voltage set-points. As power load to a rack decreases, the voltage of the current to a rectifier with a reduced voltage set-point falls below the set-point and turns off. Power is automatically redistributed to the remaining active rectifiers. The redistribution increases the power load onto the remaining rectifiers, allowing the rectifiers to perform more efficiently in converting AC power to DC power.
A method includes training a first differentially private (DP) model using a private training set, the private training set including a plurality of training samples, the first DP model satisfying a differential privacy budget, the differential privacy budget defining an amount of information about individual training samples of the private training set that may be revealed by the first DP model. The method also includes, while training the first DP model, generating a plurality of intermediate checkpoints, each intermediate checkpoint of the plurality of intermediate checkpoints representing a different intermediate state of the first DP model, each of the intermediate checkpoints satisfying the same differential privacy budget. The method further includes determining an aggregate of the first DP model and the plurality of intermediate checkpoints, and determining, using the aggregate, a second DP model, the second DP model satisfying the same differential privacy budget.
The present disclosure provides an assay device for determining a concentration of hemoglobin in a sample. The device includes a separation membrane containing a cell lysing reagent that is present on the separation membrane in an amount greater than 200 micrograms/square centimeter to less than 675 micrograms/square centimeter. Further, the device includes a downstream detection membrane configured to elicit a quantifiable response in the presence of hemoglobin. The detection membrane includes an asymmetric membrane having a first plurality of pores located towards an upstream side of the detection membrane and a second plurality of pores located towards a downstream side of the detection membrane. The first plurality of pores are larger than the second plurality of pores. The present disclosure also provides methods for using a vertical flow assay device to lyse the red blood cells in the sample to quantify the level of hemoglobin present via reflectance spectroscopy.
Systems and techniques are described for robust radar-based gesture-recognition. A radar system detects radar-based gestures on behalf of application subscribers. A state machine transitions between multiple states based on inertial sensor data. A no-gating state enables the radar system to output radar-based gestures to application subscribers. The state machine also includes a soft-gating state that prevents the radar system from outputting the radar-based gestures to the application subscribers. A hard-gating state prevents the radar system from detecting radar-based gestures altogether. The techniques and systems enable the radar system to determine when not to perform gesture-recognition, enabling user equipment to automatically reconfigure the radar system to meet user demand. By so doing, the techniques conserve power, improve accuracy, or reduce latency relative to many common techniques and systems for radar-based gesture-recognition.
Aspects of the disclosure are directed to automatically determining floor planning in chips, which factors in memory macro alignment. A deep reinforcement learning (RL) agent can be trained to determine optimal placements for the memory macros, where memory macro alignment can be included as a regularization cost to be added to the placement objective as a RL reward. Tradeoffs between the placement objective and alignment of macros can be controlled by a tunable alignment parameter.
G06F 30/27 - Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
G06F 30/392 - Floor-planning or layout, e.g. partitioning or placement
66.
System And Method For Exercise Type Recognition Using Wearables
The present disclosure provides for using multiple inertial measurement units (IMUs) to recognize particular user activity, such as particular types of exercises and repetitions of such exercises. The IMUs may be located in consumer products, such as smartwatches and earbuds. Each IMU may include an accelerometer and a gyroscope, each with three axes of measurement, for a total of 12 raw measurement streams. A training image includes a plurality of subplots or tiles, each depicting a separate data stream. The training image is then used to train a machine learning model to recognize IMU data as corresponding to a particular type of exercise.
G06V 40/20 - Movements or behaviour, e.g. gesture recognition
G06V 10/778 - Active pattern-learning, e.g. online learning of image or video features
G06V 10/80 - Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
This document describes methods, devices, systems, and means for determining a joint-codebook for wireless communication with a user equipment, UE, by a base station in an active coordination set, ACS, in which a base station receives capability information from one or more other base stations in the ACS. The base station generates a joint-codebook for the ACS based on the received capability information and sends the joint-codebook to the one or more other base stations in the ACS. The base station and the other base stations in the ACS jointly-transmit the joint-codebook to the UE and receive Precoding Matrix Indicator, PMI, feedback from the UE. The base station and the other base stations in the ACS jointly-process downlink data for the UE using the PMI feedback and the joint-codebook and jointly-transmit the downlink data to the UE.
H04B 7/0456 - Selection of precoding matrices or codebooks, e.g. using matrices for antenna weighting
H04B 7/06 - Diversity systems; Multi-antenna systems, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
H04L 25/03 - Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
68.
Mesh Network Range Extension and Reliability Enhancement Through Lower Order MIMO Spatial Streams
This document describes improvements in range and reliability for wireless mesh networks implementing IEEE 802.11 networking technologies. Reducing the number of spatial streams, N, to a lower value at middle and far distance ranges using an optimized rate control algorithm, preemptively trades off a lower throughput limit for a higher link budget. This higher link budget provides longer range and higher RF link reliability by using an N×N spatial diversity of MIMO RF channels for maximizing link budget instead of network throughput.
The present disclosure contemplates a method for synchronizing a large number of generators on an AC bus by synchronizing each generator's output to a nominal output that is generated from a common external source. For example, each generator, using a high speed communication signal, can synchronize to a nominal output provided by a master generator, or centralized command module. In another example, each generator can generate its own nominal output referenced to a common external time signal, such as a global positioning system (GPS) signal, or other reference. By synchronizing independently of bus voltage and frequency, the generators are able to synchronize in parallel, instead of serially.
This document describes apparatuses and techniques for providing a flexible connector between a secondary circuit board and a main logic board with a permeability shield to increase impedance of the flexible connector to reduce antenna loss from an antenna via the flexible connector to the main logic board. For example, an apparatus includes a secondary circuit board supporting one or more control pads and an antenna. A flexible connector includes a plurality of conductive traces configured to electrically couple the one or more control pads of the secondary circuit board to a coupling on a main logic board. A permeability shield is configured to be disposed along one or more portions of the flexible connector. The permeability shield is configured to increase impedance of the flexible connector to reduce antenna loss of the antenna via the control pads and the flexible connector to the main logic board.
Implementations relate to processing media content, and/or associated metadata, to classify the media content into a first category, of a plurality of predefined categories. Versions of those implementations further relate to extracting target content from the media content; generating, based on the extracted target content, an action that corresponds to an application; and generating, based on the generated action, a selectable suggestion including a textual portion that describes the action. Some of those versions further relate to causing the selectable suggestion to be displayed at a display of a client device, along with rendering of the media content. The selectable suggestion, when selected, causes the application to perform the action. The target content can be extracted based on the first category and can be extracted based on the first category in response to the media content being classified into the first category.
A method of monitoring an internal body temperature of a patient includes detecting a skin temperature of the patient using a temperature sensor in a body-mountable temperature monitor attached to the patient; calculating, using the temperature sensor, a heat flux associated with the body-mountable temperature monitor based on selectively activating a heater in the body-mountable temperature monitor; and determining the internal body temperature of the patient using the skin temperature and the heat flux.
G01K 13/20 - Clinical contact thermometers for use with humans or animals
G01K 1/14 - Supports; Fastening devices; Arrangements for mounting thermometers in particular locations
G01K 1/143 - Supports; Fastening devices; Arrangements for mounting thermometers in particular locations for measuring surface temperatures
G01K 1/20 - Compensating for effects of temperature changes other than those to be measured, e.g. changes in ambient temperature
G01K 7/22 - Measuring temperature based on the use of electric or magnetic elements directly sensitive to heat using resistive elements the element being a non-linear resistance, e.g. thermistor
73.
VISUAL PROMPT TUNING FOR GENERATIVE TRANSFER LEARNING
Systems and methods for training and using a prompt token generator to generate a set of prompt tokens which, when fed into a pretrained generative image transformer (e.g., an autoregressive transformer, continuous diffusion model, non-autoregressive transformer, or discrete diffusion model), may bias the generative image transformer's output towards a particular domain (e.g., towards a particular class of images, towards a particular training instance, etc.). In some examples, the prompt token generator may be used to generate a set of different prompt token sequences, which may then be fed sequentially to a pretrained non-autoregressive generative image transformer as it iteratively generates each image in each time-step in order to introduce more diversity into the transformer's final output.
A wearable computing device is provided. The wearable computing device includes a housing; a base plate coupled to the housing, the base plate defining a bottom surface of the housing, the base plate configured to contact an extremity of a user wearing the wearable computing device; a display; a biometric sensor disposed on the base plate or within the housing, the biometric sensor configured to transmit a biometric signal; and a processor. The processor is configured to obtain the biometric signal; determine a signal strength of the biometric signal does not satisfy a threshold signal strength; and responsive to determining the signal strength of the biometric signal does not satisfy the threshold signal strength, triggering a control routing comprising one or more control actions for altering the signal strength of the biometric signal. Methods for improving biometric sensor function are also provided.
A method includes receiving an input image. The method includes predicting, by an image transformation model, a transformed version of the input image, the image transformation model having been trained to remove image degradations associated with the input image, the training having comprised (1) training of a plurality of intermediate machine learning models to remove the image degradations, each intermediate machine learning model of the plurality of intermediate machine learning models having been trained on a respective training dataset of a plurality of training datasets corresponding to a respective plurality of degradation factors, each training dataset having comprised a plurality of pairs of sharp images and corresponding synthetically degraded versions of the sharp images, and (2) the image transformation model having been trained on an additional training dataset of real images, and having learned from the plurality of intermediate machine learning models. The method includes providing the predicted transformed version.
A threat management system features a recommendation engine and an action engine. The recommendation engine is configured to (i) conduct analytics on content from the threat catalog and content from the enterprise profile to generate results that identify a plurality of threats directed to the enterprise and (ii) generate a top threat list based on the analytic results. The action engine is communicatively coupled to the recommendation engine. The action engine is configured to receive the top threat list and generate a plurality of actions corresponding to each threat of the top threat list, where each action of the plurality of actions includes information directed to operations to mitigate or neutralize a risk associated with a threat of the top threat list.
G06F 21/57 - Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
77.
SPATIAL ALIASING REDUCTION FOR MULTI-SPEAKER CHANNELS
Various arrangements for reducing auditory spatial aliasing for a user are detailed herein. A first delay filter may be set that delays output of a first same audio signal by a first duration to a speaker of a first set of multiple speakers of a device compared to a second speaker of the first set of multiple speakers. A second delay filter may also be set that delays output of a second same audio signal by a second duration to a speaker of a second set of multiple speakers of the device compared to a second speaker of the second set of multiple speakers. The first same audio signal can be output using the first set of multiple speakers and the second same audio signal can be output using the second set of multiple speakers.
A computerized method features operations conducted by a security analyzer device to process incoming information to ascertain a presence of cybersecurity threats based on a top threat list provided to the security analyzer device. The top threat list includes a plurality of cybersecurity threats prioritized for an enterprise that is subscribing to a threat management system and protected by the security analyzer device. The computerized method further conducts analytics of incoming information to determine a level of correlation between at least a portion of the incoming information and any of the plurality of cybersecurity threats within the top threat lists content, and upon determining the level of correlation between the portion of the incoming information and a cybersecurity threat of the plurality of cybersecurity threats exceeding a first threshold, may conduct operations to neutralize or mitigate the cybersecurity threat.
G06F 21/55 - Detecting local intrusion or implementing counter-measures
G06F 21/57 - Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
Aspects of the disclosure are directed to systems, method, and computer-readable mediums for reducing the number of false positive alerts generated by a SIEM system by adjusting the set of rules the SIEM system uses to analyze attributes of the network traffic and/or system activities based on feedback from a SOAR system. Alert feedback may be received for a set of alerts generated in response to attributes triggering one or more rules. The alert feedback may indicate, for each alert of the set of alerts, whether the alert was a true positive alert or false positive alert. One or more conditions of the at least one rule may be adjusted based on the feedback.
A cache includes multiple sets with each set having multiple respective ways, and replacement logic configured to implement a two-stage least recently used (LRU) replacement computation. The two-stage LRU replacement computation causes the cache to perform a first stage during which the cache computes an LRU way for a set, and a second stage during which the cache updates an LRU data structure with information of a transaction accessed way.
G06F 12/123 - Replacement control using replacement algorithms with age lists, e.g. queue, most recently used [MRU] list or least recently used [LRU] list
G06F 12/0864 - Addressing of a memory level in which the access to the desired data or data block requires associative addressing means, e.g. caches using pseudo-associative means, e.g. set-associative or hashing
G06F 12/128 - Replacement control using replacement algorithms adapted to multidimensional cache systems, e.g. set-associative, multicache, multiset or multilevel
G06F 12/126 - Replacement control using replacement algorithms with special data handling, e.g. priority of data or instructions, handling errors or pinning
Embodiments disclosed variously address the etendue limit on incoupling, e.g., in an augmented or mixed reality display waveguide combiner, by trading polarization state purity for reduced space-bandwidth product using a combination of optical elements, thereby improving system efficiency, reducing power constraints, and thus enabling longer battery life and/or smaller battery size. Efficiency of optical systems such as head mounted display devices can thus be increased to allow for lighter weight devices and/or devices that require fewer charges between uses.
Systems and methods for hosting a teleconference are disclosed herein. The method can include receiving, by a server, a request from a connected participant device to transition from a non-interactive slot to an interactive slot of the teleconference and moving, by the server, the connected participant device from the non-interactive slot to a buffer slot. The method can also include determining, by the server, a longest-inactive participant device among one or more participant devices currently occupying interactive slots; removing, by the server, the longest-inactive participant device from an associated interactive slote; and moving, by the server, the connected participant device from the buffer slot to the associated interactive slot.
A head-worn device may be configured with a curved window-element that can generate distortion in images captured by a camera of the head-worn device. Window extrinsics describing the shape, orientation, and/or position of the curved window-element may be used as a calibration to reduce the distortion. An online calibration process may be run at times during use so that the window extrinsics can be updated to accurately represent the curved window-element after changes in the shape, orientation, and/or position of the curved window-element occur.
A method of manufacturing a stacked material for a point-of-care (POC) testing system includes providing a first membrane comprising a first set of assay reagents and providing a second membrane. The method also includes coating the second membrane with a second set of assay reagents and a polymer coating solution. Further, the method includes arranging the first and second membranes in a stacked configuration, wherein the polymer coating solution adheres the first and second membranes together. Thus, the method also includes at least partially drying the stacked configuration to form the stacked material for the POC testing system.
Systems and methods for detecting deformation of a frame of a head mounted wearable device, and for estimating an amount of deformation of the frame, are provided. One or more fiducial markers are provided on a lens of the head mounted wearable device. Positions of fiducial marker(s) may be detected by an image sensor of the head mounted wearable device. Changes in positions of the fiducial markers(s) may be correlated with a corresponding adjustment to be made in an eye/gaze tracking algorithm implemented by a gaze tracking device of the head mounted wearable device, to maintain accuracy of the eye/gaze tracking performed by the gaze tracking device.
A device may determine, using first sensor data, that a head mounted wearable device is in a non-resting state. A device may increase an activation state of a second sensor to an increased activation level in response to determining that the head mounted wearable device is in the non-resting state. A device may receive second sensor data from the second sensor at the increased activation level. A device may determine, using the second sensor data, that the head mounted wearable device is in a head-mounted state. A device may in response to determining that the head mounted wearable device is in the head-mounted state, increasing an operational mode of the head mounted wearable device to an increased operational mode, wherein determining that the head mounted wearable device is in a first of the non-resting state or the head-mounted state includes executing a model.
Some implementations relate to generating, based on processing captured vision data instances throughout an environment: regions of interest, and an estimated map location and region embedding(s) for each region of interest. Some implementations additionally or alternatively relate to determining, based on (1) a free form (FF) natural language (NL) instruction for a robot to perform a task and (2) generated region embedding(s) for identified regions of interest in an environment: object descriptors that describe objects that are relevant to performing the task and that are likely present in the environment. Some implementations additionally or alternatively relate to utilizing a subset of object descriptor(s), determined to be descriptive of object(s) that are relevant to performing the task of an FF NL instruction and likely included in the environment, in determining robotic skill(s) for robot(s) to implement in performing the task specified in the FF NL instruction.
Systems, devices, computer-implemented methods, and non-transitory computer-readable media that facilitate health-based predictions for a patient using a single time point biological sample of the patient are provided. A regularization component can be integrated into a triplet-based objective function associated with a triplet-based machine learning model to create a modified triplet-based objective function. The regularization component can operate to regularize distances between pairs of positive data values and negative data values in triplet tuples of a dataset with respect to anchor values in the triplet tuples. A triplet-based machine learning model can be trained using the dataset and the modified triplet-based objective function to create a trained triplet-based machine learning model. The trained triplet-based machine learning model can be implemented to output one or more health-based predictions for a patient based at least in part on a single time point biological sample of the patient.
G06N 3/084 - Backpropagation, e.g. using gradient descent
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
89.
CHAT VIEW MODIFICATION BASED ON USER IDENTIFICATION OR USER MOVEMENT
According an embodiment, a computing device can: identify, in a chat view associated with a video chat session, a first authorized participant and a second authorized participant of the video chat session; render, in the chat view, first visual data indicative of the first authorized participant and second visual data indicative of the second authorized participant based at least in part on identification of the first authorized participant and the second authorized participant, respectively; define, in the chat view, a chat zone indicative of a reference location of the first authorized participant; determine that the first authorized participant moved outside the chat zone; and/or conceal, in the chat view, the first visual data indicative of the first authorized participant based at least in part on determination that the first authorized participant moved outside the chat zone.
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for detecting glare in an image. In one aspect, a system comprises a glare detection machine learning model, the glare detection machine learning model comprising: a glare segmentation neural network that generates, from data derived from the image, a glare map that identifies one or more glare areas of the image; a feature extraction model that extracts localized image feature information corresponding to the one or more glare areas of the image; a glare scoring neural network that processes the image to generate a glare detection score representing a likelihood that the image has glare; and a glare classification model that uses at least the extracted localized image feature information and the glare score to generate a classification output that specifies whether the image has glare.
G06F 18/2413 - Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on distances to training or reference patterns
G06V 10/40 - Extraction of image or video features
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
A computer-implemented method includes setting, by a participant computing device participating in a videoconference, a maximum quantization parameter (QP) value for encoding a predetermined type of video frame to a value which is the lesser of: a first QP value determined based on an average value of QP values used to encode video frames before the predetermined type of video frame, or a second QP value corresponding to an application-specified maximum QP value. The computer-implemented method further includes encoding the predetermined type of video frame using the set maximum QP value.
H04N 19/136 - Incoming video signal characteristics or properties
H04N 19/15 - Data rate or code amount at the encoder output by monitoring actual compressed data size at the memory before deciding storage at the transmission buffer
H04N 19/172 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a picture, frame or field
H04N 19/176 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a block, e.g. a macroblock
92.
Integrating applications in a surgeon console user interface of a robotic surgical system
One example method for improving the efficiency of robotic surgical procedures by integrating applications into the surgeon console user interface is presented. The method includes generating a surgeon console user interface for displaying at a surgeon console associated with a robotic surgical device during a robotic surgical procedure. The surgeon console user interface includes a main region configured for displaying a video signal of the robotic surgical procedure, a left side region for displaying data related to the surgical tools controlled by a left hand controller; and a right side region for displaying data related to the surgical tools controlled by a right hand controller. The method further includes displaying the graphical user interface on a display device of the surgeon console and integrating applications into the surgeon console user interface in response to determining that the surgeon console switches to an application mode.
G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
An electronic document associated with users of a collaborative document platform is identified. The electronic document is associated with an approval data structure including entries that correspond to approval requests. A portion of an approval data structure is included within the content of the electronic document for presentation to a first user. A first user updates a first entry of the portion of the approval data structure included within the content of the electronic is detected. The update to the first entry corresponds to a first approval request for a second user to approve a portion of the electronic document. A first notification is transmitted to a second client device associated with the second user. The first notification indicates the first approval request. The approval data structure is updated to include data of the first entry.
Individual-specific changes in health conditions are detected using a latent space mapping generated from baseline physiological data collected in a longitudinal study of the individual. Historical baseline data in an n-dimensional input space is modeled into a k-dimensional latent space, where k
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G06N 3/088 - Non-supervised learning, e.g. competitive learning
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
G16H 50/80 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for detecting, monitoring or modelling epidemics or pandemics, e.g. flu
09 - Scientific and electric apparatus and instruments
10 - Medical apparatus and instruments
42 - Scientific, technological and industrial services, research and design
44 - Medical, veterinary, hygienic and cosmetic services; agriculture, horticulture and forestry services
Goods & Services
Computer hardware for scientific research, namely, for
collecting, processing, and taking anatomical and tissue
images in connection with scientific and medical research;
computer hardware for capturing, transmitting and displaying
images of the eye. Retinal imaging camera for medical screening and medical
diagnostic purposes. Image-based screening services in the field of diabetic
retinopathy for medical research purposes; image-based
screening, grading and characterization services in the
field of pathology for medical research purposes; providing
diagnostic research services not for medical purposes in the
field of diabetic retinopathy research; providing
image-based diagnostic research services not for medical
purposes in the field of diabetic retinopathy research;
genetic screening for research purposes; immunophenotyping
services for research purposes; drug screening for research
services; pharmaceutical drug development services. Medical diagnostic testing, namely, image-based screening
and diagnostic services in the field of diabetic
retinopathy; medical diagnostic testing, namely, image-based
screening, diagnostic, grading and characterization services
in the field of pathology.
100.
FREQUENCY PATTERN FOR REDUCING PARASITIC INTERACTIONS IN A QUBIT GRID
Methods, systems, and apparatus for operating a system of qubits. In one aspect, a method includes operating a first qubit from a first plurality of qubits at a first qubit frequency from a first qubit frequency region, and operating a second qubit from the first plurality of qubits at a second qubit frequency from a second first qubit frequency region, the second qubit frequency and the second first qubit frequency region being different to the first qubit frequency and the first qubit frequency region, respectively, wherein the second qubit is diagonal to the first qubit in a two-dimensional grid of qubits.
G06N 10/70 - Quantum error correction, detection or prevention, e.g. surface codes or magic state distillation
G06F 15/80 - Architectures of general purpose stored program computers comprising an array of processing units with common control, e.g. single instruction multiple data processors
G06N 10/20 - Models of quantum computing, e.g. quantum circuits or universal quantum computers