A system can be provided for managing data encryption during system updates. For example, the system can detect an upgrade to a component of a computing device that includes encrypted data. In response to detecting the upgrade and prior to a boot process the system can deactivate a link between a set of platform configuration register (PCR) values and a decryption key usable to decrypt the encrypted data. The system can further authorize access to the decryption key during the boot process by provisioning an alternative link between a network server and the decryption key. Additionally, subsequent to the boot process, the system can update the set of PCR values and link the updated set of PCR values and the decryption key.
Systems and methods are provided. An example method can include obtaining, by a computing system comprising one or more computing devices, first time series data indicative of a plurality of amounts of a computing resource used at a first plurality of times by a first service instance executing on a first cluster of computing devices. The example method can include obtaining, by the computing system, second time series data indicative of a plurality of amounts of the computing resource used at a second plurality of times by one or more processes executing on a second cluster of computing devices. The example method can include migrating, by the computing system based on a comparison between the first time series data and the second time series data, the first service instance to the second cluster of computing devices.
Systems and methods for zero-copy forwarding for network function virtualization (NFV). An example method comprises: receiving, by a supervisor of a host computer system, a definition of a packet filter originated by a virtual execution environment running on the host computer system; responsive to validating the packet filter, associating the packet filter with a vNIC of the virtual execution environment; receiving, by the supervisor, a network packet originated by the vNIC; and responsive to matching the network packet to a network connection specified by the packet filter, causing the packet filter to forward the network packet via the network connection.
A method, a system, and a non-transitory computer-readable storage medium are provided. The method includes detecting an access point of a cluster infrastructure. The cluster infrastructure includes an application associated with the access point and a control plane to schedule execution of the application. The method includes, responsive to detecting the access point, creating a proxy access point to intercept requests directed to the access point of the cluster infrastructure. The method includes controlling an operating state of the control plane responsive to the intercepted requests of the proxy access point.
G06F 9/48 - Program initiatingProgram switching, e.g. by interrupt
G06F 9/50 - Allocation of resources, e.g. of the central processing unit [CPU]
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
5.
Downstream destination selection for tunnel packets based on fixed header packet values
A network device driver (NDD) associated with a network interface device (NID) of a computing device processes a tunnel packet received by the NID and originating from a source device. The tunnel packet includes a tunnel packet header, a user datagram protocol (UDP) header, and a payload including a Transmission Control Protocol/Internet Protocol (TCP/IP) packet. The NDD accesses a data structure that corresponds to the NID. The NDD extracts a value from a field of the tunnel packet based on information in the tunnel packet and on information in the data structure. The NDD selects, based on the value, a first downstream destination from a plurality of downstream destinations operable to further process the tunnel packet, and causes the tunnel packet to be subsequently processed by the first downstream destination.
G06F 15/16 - Combinations of two or more digital computers each having at least an arithmetic unit, a program unit and a register, e.g. for a simultaneous processing of several programs
H04L 45/00 - Routing or path finding of packets in data switching networks
In one example, an agent of a first processing node can receive data from a data provider. The agent can determine whether the first processing node has at least a threshold amount of computing capacity. In response to determining that the first processing node has less than the threshold amount of computing capacity, the agent can receive, from a lookup service, a list of one or more processing nodes in the computing cluster that have at least the threshold amount of computing capacity. The agent them can select, from the list, a second processing node that has at least the threshold amount of computing capacity. Having selected the second processing node, the agent can cause the data to be transmitted to a second agent of the second processing node, the second agent being configured to process the data and provide the processed data to a backend server system.
A computing system comprising one or more computing devices can access a file comprising documentation that includes a textual description and a source code snippet written to comply with a programming language syntax. The computing system can identify the source code snippet. The computing system can generate an executable based on the source code snippet. The computing system can initiate a test process that accesses the executable, the test process causing the executable to cause an event. The computing system can determine that the event is a valid event or an invalid event.
A placement service can be used to determine workload placement using plugin voting. The placement service can transmit a voting request to one or more plugins to request input from the one or more plugins to determine a placement location to assign a workload. The voting request can indicate a predefined time limit by which to respond to the voting request. The placement service can receive a set of responses. Each response can be generated by a respective plugin and indicate at least one respective candidate location to execute the workload. The placement service can determine the placement location based on the set of responses received from the one or more plugins. Subsequent to determining the placement location, the placement service can assign the workload to the placement location for execution.
Some examples of the present disclosure relate to configuration validation for container deployments in a computing environment. In one particular example, a system can receive a request for a deployment of a container. A specification that is associated with the deployment can include a set of resources for running the container and an indicator for a repository storing source code associated with the container. Prior to running the container, the system can access the repository to determine a set of configuration requirements for running the container. The system can then determine a match or a mismatch between the set of resources and the set of configuration requirements. Based on the match or the mismatch, the system can perform an action.
Embodiments of the present disclosure relate to executing an automation system with a container engine. More specifically, a processing device obtains a domain-specific automation file comprising an indication of a set of tasks for automating a process. The processing device provides, via a host OS of a device, the domain-specific automation file to a container instance managed by a container engine. The processing device generates, via an automation system, a payload within the container instance based on the domain-specific automation file. The processing device outputs the payload to cause the set of tasks to be performed.
Uploaded data including an artificial intelligence (AI) model and metadata associated with the AI model may be received. A task corresponding to the AI model may be determined. A processing device may confirm the metadata includes samples predictions generated based on benchmark data associated with the task corresponding to the AI model. The AI model and the sample predictions may be stored in an AI model registry in response to confirming the metadata includes the sample predictions generated based on the benchmark data associated with the task corresponding to the AI model.
Disclosed herein is a method comprising: receiving, by a processing device of a first computing device, a first request from a second computing device to establish a first trusted execution environment (TEE) in the first computing device; establishing the first TEE in the first computing device, wherein the first TEE comprises an encrypted memory area and executable code; receiving, by the processing device, a second request to establish a second TEE in the first computing device; establishing, by the first TEE, the second TEE in the first computing device, wherein the second TEE comprises a second executable code; receiving, by the first TEE, cryptographic key data from the second computing device; validating, by the first TEE, the second TEE; providing, by the first TEE, the cryptographic key data to the second TEE; and causing, by the processing device, the second TEE to execute, using the cryptographic key data, the second executable code.
G06F 21/53 - Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems during program execution, e.g. stack integrity, buffer overflow or preventing unwanted data erasure by executing in a restricted environment, e.g. sandbox or secure virtual machine
Techniques for verifying whether vendor-provided functions that are used in application code are compliant with a safety agreement are disclosed. Code comprising a plurality of functions are received at a compiler. During compilation of the code, a plugin of the compiler may determine whether each of the plurality of functions originates from a vendor. For each function originating from the vendor, the plugin may determine if the function is listed in a profile comprising a list of safety agreement compliant functions. The plugin may identify as compliant with the safety agreement, each function originating from the vendor that is listed in the profile.
Ransomware activity in operating systems can be mitigated by monitoring from user space. For example, a computing environment can generate an affinity score indicating a likelihood of ransomware activity associated with an operating system based on a first set of system calls detected from a user space of the operating system within a first time window. The computing environment can buffer one or more write operations from the first set of system calls during a second time window based on the affinity score. The computing environment can update the affinity score based on a second set of system calls detected from the user space of the operating system within the second time window. The computing environment can block execution of the one or more write operations based on the updated affinity score exceeding a predefined threshold.
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 21/54 - Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems during program execution, e.g. stack integrity, buffer overflow or preventing unwanted data erasure by adding security routines or objects to programs
G06F 21/56 - Computer malware detection or handling, e.g. anti-virus arrangements
15.
REMOTE LOGIN RESOURCE ACCESS CONTROL USING A CONTAINER
A system can be used to control access to protected resources with respect to remote access of a computing environment. The system can execute a service file to generate a container in a host system based on user input received from a user device to initiate a login session. The service file can correspond to the user input. Subsequent to generating the container, the system can execute a user shell associated with the container to assign the user device to the container. The container can restrict the user device to access a set of predefined resources indicated in the service file. In response to detecting that the login session has ended, the system can remove the container associated with the user device from the host system.
Techniques for using a software bill of materials to determine whether an application is still in compliance with a set of policies after being updated, are disclosed. In response to a first version of an application being certified as compliant with a set of policies, a first software bill of materials (SBOM) associated with the first version of the application is generated. In response to determining that the first version of the application has been updated to a second version of the application, a second SBOM corresponding to the second version of the application is generated. The first SBOM and the second SBOM are compared to determine whether the second version of the application is still compliant with the set of policies.
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
A system and method of a proactive hosting capacity analysis and evaluation for dynamic container migration. The method includes receiving a request to analyze a performance of a containerized application executing on a host machine. The containerized application using one or more resources of the host machine to provide a quality of service. The method includes acquiring performance data associated with the containerized application by applying one or more stresses to the one or more resources. The method includes determining, based on the performance data, a likelihood for a degradation in the quality of service occurring prior to a satisfaction of one or more rules associated with a remedial action. The method includes performing, by a processing device prior to the satisfaction of the one or more rules, the remedial action to prevent the degradation in the quality of service.
Techniques for executing a software program that uses a different memory-page size than its host computing environment are described. As one example, a system can deploy a virtual machine in a host computing environment of the computing device. The host computing environment can include a host operating system that is configured to use a first memory page size. The virtual machine can be configured to use a second memory page size that is different from the first memory page size. Based on a software program being configured to use the second memory page size, the system can execute the software program in the virtual machine.
Configuration management files can be generated to refine software package installation processes. For example, a system can identify a first installation process for installing a software package in a computing environment. The first installation process can include commands. The system can also generate a set of tasks for the first installation process by relating each command to a task. The system can then generate a second installation process for the software package based on the set of tasks and based on conditions of the computing environment. The second installation process may include a subset of tasks from the set of tasks. The system can then cause the package manager to implement the second installation process for the software package by executing each task in the subset of tasks.
A system can be provided that can assign levels of trust to external identity providers and determine a security level for a software service. The system may then generate a mapping based on the security level of the software service and the levels of trust assigned to the external identity providers. The mapping may associate permitted access to the software service with a first subset of the external identity providers and associate denied access to the software service with a second subset of the external identity providers. Additionally, the system may receive authentication data from a user device using an external identity provider and may control access for the user device to the software service by using the mapping to determine that the external identity provider is in the first subset or the second subset.
A networking request is received from a first workload, within a first container, on an edge device. A determination is made that the destination of the networking request is a second workload, within a second container, on the edge device. In response to determining the destination of the networking request, the networking request is forwarded to the second application, wherein the forwarding comprises intercepting the networking request at a socket associated with the first workload and delivering the network request to a socket associated with the second workload.
H04L 43/028 - Capturing of monitoring data by filtering
H04L 67/60 - Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources
22.
AUTOMATED DETECTION AND NOTIFICATION OF PACKAGE CHANGES FOR SOFTWARE UPDATES IN A COMPUTER ENVIRONMENT
In one example, a method can detect and notify a user of package breaking changes for software in a computer environment. The method includes receiving, from a user, a request associated with upgrading a software program of a computing device from a first version to a second version of the software program, where the second version is newer than the first version. The method may then determine a package difference between the second version and a third version of the software program, with the third version of the software program being newer than the second version. The package difference may be a change to a package associated with the software program. The method then may output a notification indicating the package difference prior to the computing device being upgraded from the first version to the second version.
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
23.
TESTING AND DEPLOYMENT OF CONTAINERIZED APPLICATION USING SIDE-CAR CONTAINERS
A method includes identifying a code testing tool associated with an application within a first container, deploying the code testing tool to a second container separate from the first container, and performing a test of the application within the first container using the code testing tool deployed to the second container.
Some examples of the present disclosure relate to error code generation for software application executions. In one particular example, a system can determine an error in an execution of a software application. The system can determine, based on a decision tree representing the software application, an error code associated with the error. The error code can be a subset of a plurality of identifiers indicating a path of the execution of the software application and data associated with the path. The system can perform an action in response to the error code.
Techniques for processing change requests for software projects are disclosed. An example method includes receiving a change request describing new source code for a software project. The method also includes generating, by a processing device, a prompt comprising context information and a plugin, wherein the context information comprises source code from the software project and the plugin comprises text that describes a supplemental work product to be generated. The method also includes providing the prompt to a machine learning model, wherein the context information trains the machine learning model to provide the supplemental work product with a correct content and format. The method also includes receiving the supplemental work product from the machine learning model. The method also includes applying the supplemental work product to the software project.
Techniques for atomic live updates to operating systems are described herein. For example, a computing system can generate a first version of a binary large object (BLOB) file indicating first metadata for each file of a first version of an image for an operating system. The computing system can generate a second version of the BLOB file indicating second metadata for each file of a second version of the image. The second version can include new files associated with an update to the operating system. The computing system can execute the update to the operating system by remounting, by a file system for the operating system, the second version of the image of the operating system using the second metadata of the second version of the BLOB file.
A system can be provided for controlling software application deployment based on resource data for an associated software extension. For example, the system can extract first resource data for a software extension from a code base of the software extension. The software extension can be used to deploy a software application. The system can further install the software extension at one or more computing clusters and can detect resource requests transmitted by the software extension during installation. The system may then generate second resource data for the software extension based on the resource requests. Additionally, the system can deploy, using the software extension, the software application at a computing cluster. The computing cluster can be selected based on the first resource data and the second resource data and the computing cluster can be separate from the one or more computing clusters.
Techniques for customizing the functionality of an operating system that is common to all devices in a network with specific application functionality are provided. A base image defining functionality that is common to a plurality of devices is provided. An application required by a first device of the plurality of devices is provided as a set of layers. The base image is provided to a first device and each of the set of layers are provided to the first device separately from the base image. At the first device, the set of layers is mounted on the base image.
G06F 16/11 - File system administration, e.g. details of archiving or snapshots
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]
Systems and methods are disclosed for validating decision tables. An example method includes comparing a new version of a decision table with a previous version of the decision table to identify a changed rule among a plurality of rules of the decision table. The method also includes pruning, by a processing device, an initial list of rules to be validated in view of the changed rule to generate a reduced list of rules based on a variant map that describes differences between the plurality of rules in the previous version of the decision table. The method also includes performing a validation process for the reduced list of rules.
Systems and methods are provided. An example method can include receiving, from a first process, a first request for first data to be written to a first memory location by a second process. The example method can include providing a second request for the first process to write data to a second memory location, wherein the second process has write access to the second memory location and not the first memory location. The example method can include receiving a first notification indicating that the second process has written the first data to the second memory location. The example method can include transferring the first data from the second memory location to the first memory location. The example method can include providing a second notification to the first process indicating that the first data has been written to the first memory location.
A virtual machine (VM)-based container runtime executing on a computing device receives a request to run a container from a container image that is at least partially encrypted. The VM-based container runtime causes a VM to be initiated from a VM image, the VM image including an agent operable to, during execution, obtain a plurality of decryption keys operable to decrypt blocks of the container image. The agent is operable to set up a block remapper in the VM to be invoked by a file system mounted to the VM to request a particular container image block, send a request for the particular container image block to a block obtainer component executing outside of the VM, utilize a decryption key to decrypt a container image block received from the block obtainer component to generate a decrypted container image block, and pass the decrypted container image block to the file system.
G06F 21/62 - Protecting access to data via a platform, e.g. using keys or access control rules
G06F 21/53 - Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems during program execution, e.g. stack integrity, buffer overflow or preventing unwanted data erasure by executing in a restricted environment, e.g. sandbox or secure virtual machine
32.
Predicting and Minimizing Quantum Decoherence in Quantum Computer Systems
In one example described herein a system can receive, by a gate analysis service, a quantum assembly language (QASM) file. The QASM file can define a quantum algorithm that can include logic gates that can be executed on a quantum computer system. The system can access, by the gate analysis service, a data repository that can include an estimated amount of quantum decoherence associated with each logic gate of a plurality of logic gates that includes the logic gates. The system can determine, by the gate analysis service, a prediction of an amount of quantum decoherence associated with executing at least one logic gate of the logic gates on the quantum computer system. Additionally, the system can adjust, by the gate analysis service, the QASM file to modify the prediction associated with executing the logic gates on the quantum computer system.
G06N 10/80 - Quantum programming, e.g. interfaces, languages or software-development kits for creating or handling programs capable of running on quantum computersPlatforms for simulating or accessing quantum computers, e.g. cloud-based quantum computing
A file system of a workspace including a playbook may be monitored. A modification to the files system of the workspace may be detected. A path corresponding to the modification to the file system of the workspace may be injected, by a processing device, into a current configuration associated with the playbook to produce an updated configuration associated with the playbook. A language server may be triggered to reinitialize based on the updated configuration associated with the playbook.
Sensitive data stored in an object of a distributed computing environment can be secured. For example, a pod can be deployed in a distributed computing environment. The pod can include an initialization container. The initialization container can retrieve encrypted data from an object in the distributed computing environment and a decryption key from a key source, where both object and the key source are separate from the pod. The initialization container can decrypt the encrypted data using the decryption key to produce decrypted data. The initialization container can then overwrite the encrypted data stored in the object with the decrypted data. After deploying the initialization container, an application container can be deployed in the pod, where the application container can retrieve the decrypted data from the object and initialize one or more environment variables of the application using the decrypted data.
A computing device receives, from a client computing device, a request to access a quantum service, the request comprising a plurality of parameters associated with the quantum service, wherein a plurality of versions of the quantum service execute on a plurality of quantum computing devices. The quantum computing device identify characteristics of the plurality of versions of the quantum service. The quantum computing device identify characteristics of the plurality of quantum computing devices. The quantum computing device determine a version from among the plurality of versions of the quantum service to route the request to based on the request, the characteristics of the plurality of versions of the quantum service, and the characteristics of the plurality of quantum computing devices. The quantum computing device route the request from the client computing device to the version from among the plurality of versions of the quantum service.
G06F 16/21 - Design, administration or maintenance of databases
G06N 10/80 - Quantum programming, e.g. interfaces, languages or software-development kits for creating or handling programs capable of running on quantum computersPlatforms for simulating or accessing quantum computers, e.g. cloud-based quantum computing
36.
WORKLOAD MANAGEMENT VIA ADAPTIVE REQUEST RATE LIMITING
A determination is made that a quantity of computing resources utilized by a set of existing workloads is greater than a threshold quantity of the computing resources. Responsive to the determination, a particular rate limiting target is identified from a plurality of rate limiting targets of a rate limiting policy, wherein the rate limiting policy controls a workload management Application Programming Interface (API) that receives workload requests from requesting entities, and wherein the plurality of rate limiting targets comprises a particular workload type, a particular requesting entity, or a particular requesting entity type. The rate limiting policy is modified, wherein modifying the rate limiting policy comprises replacing an existing rate limit for the rate limiting target with a modified rate limit different than the existing rate limit.
A technique for dynamic scaling of a distributed computing system is described. In one example of the present disclosure, a system can include a base node configured to provide an access point to a distributed computing system and for servicing a first portion of requests and to generate at least one compute node based on a first load of the base node. The system can also include the at least one compute node of the distributed computing system for servicing a second portion of requests. The at least one compute node can be configured to generate an additional compute node for servicing a subset of the second portion of requests based on a second load of the at least one compute node.
09 - Scientific and electric apparatus and instruments
35 - Advertising and business services
42 - Scientific, technological and industrial services, research and design
Goods & Services
Computers; quantum computers; downloadable electronic
publications namely informational materials; computer
hardware and software for information technology analysis
and data management; computer hardware and software for
application development; computer hardware and software for
cloud computing; computer hardware and software for
cognitive computing; computer hardware and software for
artificial intelligence; computer hardware and software for
blockchain technology; computer hardware and software for
quantum computing and quantum programming; computer
hardware, namely magnetic tape units (data processing),
magnetic tapes (ribbons), printed circuits, integrated
circuits, computer keyboards, compact discs (audio-video),
optical discs, couplers (data processing), floppy disks,
magnetic data carriers; computer hardware, namely video
screens, scanners (data processing equipment), computer
printers, interfaces (data processing), readers (data
processing), computer software (recorded programs) intended
for data processing, microprocessors, modems, monitors
(hardware), computers, computer memories, computer
peripherals; computer adapters; computer components;
equipment for data processing; computer devices for data and
information management; semiconductors; machine-readable
electronic data carriers; magnetic disks; hard disk drives;
magnetic tape recorders; calculating machines; cash
registers; fax machines; video recorders; video tapes;
electric cells and electric batteries; computer chips;
wafers for integrated circuits; computer accessories,
namely, computer communications servers; carrying cases for
computers; computer interface cards; computer cables and
computer cable parts; fax-modem cards for computers;
computer accessories, namely, screen filters, computer mouse
pads, pagers, computer controllers; electrical converters,
namely, digital-to-analog, analog-to-digital and
step-by-step voltage switches; computer mouse; integrated
circuit cards and smart chip cards; integrated circuit
adapters and smart chip card adapters; readers for
integrated circuit cards and smart chip cards;
microcomputers; projectors (projection devices); remote
controls for computers; inverters, surge protectors and
uninterruptible power supplies; point-of-sale terminals
(payment terminals); computer servers; computer storage
devices, namely, high-speed storage subsystems for storing
and backing up electronic data locally or via a
telecommunications network; downloadable computer programs;
recorded computer programs; computer software platforms,
recorded or downloadable; computer software applications,
downloadable; video game software; operating system software
and programs; software for accessing a global computer
network; document management software; database management
software; software for locating, retrieving and receiving
text, electronic documents, graphic artwork and audio-visual
information on internal enterprise-wide computer networks
and on local and wide-area global computer networks;
development software and website design software and user
manuals, in electronic format, sold as a set; computer
software for controlling the operations and execution of
computer systems, programs, and computer networks; computer
software for connecting disparate computer networks and
systems, servers and storage devices; computer programs for
connecting computers to each other and enabling computer
activities across a global computer network; computer
software for systems management, existing software and
processes in an information technology environment;
interactive computer systems combining computer hardware and
software for use in data management and analysis and
instruction manuals in electronic format sold with these
products; cloud computing systems, namely communications
networks integrating computer hardware and software for
dynamic provisioning, virtualization and consumption
measurement of computer resources; recorded and downloadable
cloud computing software for deploying and managing virtual
machines on a cloud computing platform; computer systems,
namely computer hardware and computer software for the
development and integration of artificial intelligence,
namely machine learning, deep learning and natural language
processing which are capable of collecting, organizing and
analyze data; computer systems, namely computer hardware and
computer software incorporating functions of natural
language processing, computational linguistics, information
retrieval, machine learning and capable of understanding
general queries formulated by humans and formulating
responses; software for developing, building and operating
blockchain technology applications; computer hardware and
computer software for developing and testing quantum
algorithms; downloadable documentation and instruction
manuals on machine-readable electronic data carriers
relating to computers or computer programs; downloadable
electronic publications; electronic publications
downloadable on computer media, namely user manuals, guides,
brochures, information sheets, written presentations and
teaching materials in the field of computers, computer
networks, computer storage, computer operating systems,
information technology, database management, cloud
computing, artificial intelligence, blockchain technology
and quantum computing; computer hardware and software for
the implementation of generative artificial intelligence
solutions; computer hardware and software to help businesses
understand the potential of generative artificial
intelligence; computer hardware and software for the
management and expansion of generative artificial
intelligence projects for other companies; computer hardware
and software for the integration of generative artificial
intelligence into operations. Arranging and placing advertisements; sales promotion
services (for third parties); business management and
business management consultancy; provision of business
information; distribution of leaflets; distribution of
samples; newspaper subscription services for others;
accounting; reproduction of documents; systematization of
data in a central file; organization of exhibitions for
commercial or advertising purposes; business management
consultancy services and business affairs consultancy
services; commercial business development service; analysis
of market research data and statistics; electronic data
processing; computer data processing services for artificial
intelligence; computer data processing services for
cognitive computing; computer data processing services for
cloud computing; computer data processing services for
blockchain technology; computer data processing services for
information management; computer data processing services
for quantum computing and quantum programming; organizing
and conducting trade exhibitions in the field of computers,
it services, information technology, artificial
intelligence, cloud computing, blockchain technology,
quantum computing, database management and electronic
business transactions through a global computer network;
business advisory services to businesses relating to
artificial intelligence; business consulting services to
companies in the field of computer systems integrating
functions of natural language processing, computational
linguistics, documentary retrieval, machine learning and
capable of understanding general queries formulated by
humans and formulating some answers; business advisory
services to businesses relating to cloud computing; business
advisory services to businesses relating to blockchain
technology; business advisory services to businesses
relating to quantum computing, quantum programming and to
develop and test quantum algorithms; business advisory
services to businesses relating to information technology;
analysis and compilation of commercial data; systematization
of data in computer databases; commercial advice to
businesses on the use of computer equipment (hardware);
business management and consulting services for the
implementation of generative artificial intelligence
solutions; market research and analysis services to help
businesses understand the potential of generative artificial
intelligence; advertising and promotion services for
companies offering generative artificial intelligence
solutions; business administration services for managing and
expanding generative artificial intelligence projects for
other companies; consulting and advisory services and in the
field of business strategies for the integration of
generative artificial intelligence in operations. Computer programming; software as a service (SaaS) services
featuring data management software; software as a service
(SaaS) services featuring software for cloud computing;
software as a service (SaaS) services featuring software for
artificial intelligence; software as a service (SaaS)
services featuring software for cognitive computing;
software as a service (SaaS) services featuring software for
blockchain technology; software as a service (SaaS) services
featuring software for quantum computing and quantum
programming; software as a service (SaaS) services featuring
software for constructing, analyzing and executing quantum
programs and quantum algorithms; software as a service
(SaaS) services featuring software for developing and
testing quantum algorithms; computer programming and
computer consulting services for artificial intelligence;
computer programming and computer consulting services for
cognitive computing; computer programming and information
management consulting services; computer programming
services and computer consulting for data management;
computer programming and computer consulting services for
cloud computing; computer programming and computer
consulting services for blockchain technology; computer
programming and computer consulting services for quantum
computing; computer programming and IT consulting services
for software as a service (SaaS); design, installation,
updating and maintenance of software; design of computer
software and hardware for others, and professional
consultancy services in the field of computers; technical
support services, namely troubleshooting computer programs
and software; computer services, namely, design, creation
and maintenance of websites on behalf of third parties;
analysis of computer systems, integration of databases and
computer networks, programming of computers for others all
intended for commercial interactions on global computer
networks; design of computer and software interconnection
systems; namely, electronic connection of computers and
software to each other; computer program (software) and
computer hardware (quality control and technical control)
testing services; technical project studies in the field of
computer hardware and software; computer advice relating to
computer hardware, namely advice relating to computer
research and development; computer advice and assistance
relating to the use of the Internet; rental of computers and
software; scientific and industrial research, namely
research and development of new products, biological
research, research in bacteriology, research in chemistry,
research in cosmetology, research in mechanics, geological
research, technological research, pharmaceutical research,
scientific research for medical purposes; information
technology (IT) consulting; computer systems integration
services; consultancy services relating to the design,
selection, implementation and use of computer systems and
software for others; technical support services, namely,
diagnosing computer program problems; computer systems
design services for others; design of computer systems for
the interconnection of computer hardware and software,
namely, electronic interconnection of computers and
software; computer program and hardware testing services,
namely, testing of software, computers and servers to ensure
proper functioning; cloud computing services relating to
computer hardware and software services integrated into a
network for dynamic provisioning, virtualization and
metering of consumption of computer resources; providing
virtual computing systems and virtual computing environments
via cloud computing; design and development of software for
cloud data storage; cloud computing hosting provider
services; electronic data storage and data retrieval
services; data security service; IT support services
relating to software provided by IT specialists; design of
computer hardware for computer networks; computer design and
development; quantum computing; consulting services relating
to computer and Internet security and data encryption;
scientific research and development services in the field of
generative Artificial Intelligence technology; technology
consulting services for companies wishing to exploit
generative Artificial Intelligence in their activities;
software development services for the creation and
customization of generative Artificial intelligence
solutions; technical project planning and implementation
services for companies developing their capabilities in
generative artificial intelligence; design and development
of computer hardware and software for generative artificial
intelligence applications; IT services for monitoring and
detecting potential legal issues or security threats related
to the use of Generative Artificial Intelligence.
A method includes receiving a message at a network bridge from a computer system where the network bridge stores a forwarding table. The method also includes determining a type of the message. The method also includes upon a determination that the type of message is a network notification message, determining whether data within the message corresponds to an entry within the forwarding table. The method also includes upon determining that the data within the message corresponds to the entry within the forwarding table, halting a transmission of the message. The method also includes upon determining that the data within the message does not correspond to the entry in the forwarding table, transmitting the message to a device in communication with the network bridge.
A method is described including signing a concatenation of an image signature, a public key associated with the image signature, and a full disk encryption (FDE) header to obtain an image encryption service (IES) signature. The method also includes writing the IES signature to an extensible firmware interface system partition (ESP) of an encrypted confidential virtual machine (CVM) disk image.
G06F 21/53 - Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems during program execution, e.g. stack integrity, buffer overflow or preventing unwanted data erasure by executing in a restricted environment, e.g. sandbox or secure virtual machine
Migrating containers across Non-Uniform Memory Access (NUMA) nodes of a processor device is disclosed herein. In one example, a processor device identifies one or more containers each executing on one of a plurality of NUMA nodes of the processor device. For each container of the one or more containers, the processor device determines an allocation of a processing resource to the container by a source NUMA node on which the container is executing, and identifies one or more NUMA nodes of the plurality of NUMA nodes having an availability of the processing resource sufficient to execute the container. The processor device selects a target NUMA node from among the identified one or more NUMA nodes, and migrates the container from the source NUMA node to the target NUMA node.
A target software architecture can be automatically evaluated for compliance with safety requirements. For example, a system can receive safety requirement data indicating an allocation of safety requirements to an external input interface of a target software architecture. The system can determine at least one failure mode associated with the external input interface. The system can determine adjusted compile-time parameters and adjusted runtime parameters based on the at least one failure mode. The system can determine at least one architectural mitigation based on the at least one failure mode, the at least one architectural mitigation being configured to reduce an effect of the at least one failure mode. The system can then apply the at least one architectural mitigation to the external input interface.
Disclosed are techniques for a temporary file system with local memory swapping capabilities. An example method includes receiving a mount request comprising a request to mount a temporary file system for a container. The mount request indicates that the temporary file system is to reside in volatile memory of the container and includes one or more local memory-swapping specifications to be applied to the container. The method also includes receiving write operations addressed to the container. The method also includes determining, by a processing device, whether to initiate local memory swapping for the container by comparing memory usage of the container with a threshold memory usage, and in response to determining to initiate local memory swapping, swapping data from the volatile memory of the container to a local swap file specified by the one or more local memory-swapping specifications included in the mount request.
A system comprises a first set of quantum hardware (QH) that includes a first set of qubits, a second set of QH that includes a second set of qubits, and a third set of QH. The first set of qubits encodes a first portion of a cryptographic key (CK). The second set of qubits encodes a second portion of the CK. In response to receiving an access request, the third set of QH receives from the first set of QH, a first transmission that encodes the first portion of the CK and a second transmission, from the second set of QH, that encodes the second portion of the CK. The third set of QH generates a first encoding of the CK that includes the first portion and the second portion of the CK. The system provides a requesting party a third transmission based on the first encoding of the CK.
A media playback system can be used to implement adaptive playback speed of a media stream based on an availability of system resources. In some aspects, the media playback system can apply a set playback speed as a rate at which the media stream is presented to a user. In response to applying the set playback speed to the media stream, the media playback system can determine that one or more interruptions of the media stream are occurring at the set playback speed. In response, the media playback system can adjust the set playback speed to a reduced playback speed to resolve the interruptions. Subsequently, the media playback system can adjust the reduced playback speed to an increased playback speed. The increased playback speed can be further adjusted based on whether the interruptions occur when the media stream is presented at the increased playback speed.
A computing system comprising one or more computing devices accesses a container build file comprising a plurality of instructions for building a container image based at least in part on an instruction file that defines an application. The computing system identifies a programming language in which the instruction file was written. The computing system determines that the programming language is a member of a set of programming languages that can be compiled into a WebAssembly (WASM) binary code format. The computing system causes the instruction file to be compiled into the WASM binary code format.
Cloud networks can be dynamically deployed for edge computing environments. For example, a control plane of a computing environment can detect a set of device identifiers and a set of priority levels for data transmitted by a set of edge devices in the computing environment. Each device identifier can correspond to an edge device in the set of edge devices. A network deployment service of the control plane can determine a network weight for the set of edge devices based on a set of device identifiers and the set of priority levels. The network deployment service can determine an adjustment to a virtual gateway based on the network weight. The virtual gateway can transmit data from the set of edge devices to a compute node in the computing environment. The network deployment service can execute the adjustment to the virtual gateway.
H04L 47/762 - Admission controlResource allocation using dynamic resource allocation, e.g. in-call renegotiation requested by the user or requested by the network in response to changing network conditions triggered by the network
H04L 47/80 - Actions related to the user profile or the type of traffic
48.
DISTRIBUTED TASK QUEUING AND PROCESSING FOR LIGHTWEIGHT EDGE DEVICES
Techniques for assigning tasks among networked devices/nodes e.g., edge devices using an automation controller are disclosed. A manager node executing the automation controller may provide a global task queue of tasks to be assigned to a plurality of execution nodes. In response to receiving a new task to be assigned, the manager node may compare resource metadata associated with the new task, a priority of the new task and device metrics for each of the plurality of execution nodes, wherein the device metrics for each of the plurality of execution nodes indicate a resource availability of the execution node and a status of a local task queue associated with the execution node. The manager node may determine, based on the comparison, a particular execution node among the plurality of execution nodes to assign the new task to.
In some examples, a targeted test suite can be executed to test a subset of a set of software packages corresponding to a compliance certification. For example, a computing system can identify one or more functions associated with the compliance certification of the set of software packages that can include one or more codebases. In response to identifying the one or more functions, the computing system can tag the one or more functions with a function identifier that can define a subset of the one or more codebases. The subset of the one or more codebases can consist of the one or more functions. The computing system can execute the targeted test suite that can be limited in scope to the subset of the one or more codebases based on the function identifier.
A cross-domain data access service enables data access across two or more computing domains, such as, for example, transient access by a public device to data held in a private cloud. In particular, the cross-domain data access service can identify a data subset from within a secure datastore of a first computing domain. The cross-domain data access service can replicate the data subset within a transient datastore that is segregated from the secured datastore. The cross-domain data access service can implement a data access policy so as to enable a client device from a second domain to access the transient datastore.
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database systemDistributed database system architectures therefor
G06F 21/62 - Protecting access to data via a platform, e.g. using keys or access control rules
51.
SIZING SERVICE FOR CLOUD MIGRATION TO PHYSICAL MACHINE
A computing device receives data related to operation of a cloud computing environment having an application comprising several services. The data related to operation of the cloud computing environment can include time-based data related to computing resource use in the cloud computing environment, such as I/O rate, processor utilization, and others. In some implementations the services that compose the application can be orchestrated through an orchestrator, and in those implementations data regarding the orchestration can also be provided to the computing device. The computing device can also request service-related information from the cloud computing environment, where the service-related information can include financial related information for operations in the cloud. The computing device can take as input the data related to operation of the application and services the orchestration, and the service and thereafter provide a recommendation of an on-premises computing infrastructure adequate to replace the cloud computing environment.
A vulnerability with respect to a file in a continuous integration (CI) pipeline can be suppressed according to some aspects described herein. For example, a computing system can determine that the vulnerability is suppressible. In response to determining the vulnerability is suppressible, the computing system can automatically adjust a status of the vulnerability from an observed state that prevents deployment of the file to a suppressed state that allows the deployment of the file. The computing system additionally can determine a security risk of deploying the file. The suppressed state of the vulnerability can exclude the vulnerability from the determination of the security risk. The computing system can deploy the file in the CI pipeline subsequent to automatically adjusting the status of the vulnerability to the suppressed state.
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
53.
UPGRADE OF DISTRIBUTED DATA GRID WITH NO STATE TRANSFER
A method of receiving an update for a first node of a cluster of compute nodes, generating a second node including the update for the first node, copying data from the first node to the second node, and in response to completion of copying the data, replacing the first node in the cluster with the second node.
A computing device accesses a source code instruction file comprising source code instructions written to comply with a predetermined programming language syntax, wherein a compiler is operable to generate an executable file based on the source code instruction file. The computing device identifies, based on the source code instruction file, an annotation that identifies object size verification instructions that, when executed and passed a reference to an object that is defined by the source code instructions, returns a memory size of the object. The computing device identifies source code instructions that access the object. The computing device injects, in the executable file, executable instructions that cause the object size verification instructions to be executed to determine the memory size of the object and condition the access to the object on a value returned by the object size verification instructions.
A quantum computing device obtains, from a first quantum instruction file (QIF) corresponding to a first quantum process, an amount of qubits required by the first quantum process. The quantum computing device creates a first namespace within a qubit registry comprising a plurality of qubit registry entries each corresponding to a qubit of a plurality of qubits, the first namespace referring to a first subset of qubits of the plurality of qubits, the first subset of qubits comprising at least the amount of qubits required by the first quantum process. The quantum computing device inserts an identifier for the first namespace into the first QIF. The quantum computing device causes the qubit registry to provide the first quantum process with access to the first namespace when the first QIF is executed.
A computing device determines that a workload of a first virtual machine is to be transferred to a second virtual machine. The computing device generates a file comprising virtual CPU (vCPU) data that describes current conditions of the first virtual machine. The computing device transmits the file from the first virtual machine to the second virtual machine. The computing device restores the current conditions of the first virtual machine on the second virtual machine based on the file. The computing device sends a signal to the first virtual machine indicating that the current conditions of the first virtual machine are restored on the second virtual machine.
Virtualization can be used to isolate drivers in monolithic operating systems. For example, a monolithic kernel can determine that a first driver has a first level of criticality to the monolithic kernel that is higher than a second level of criticality for a second driver. In response to determining that the first level is higher than the second level, the monolithic kernel can execute a first driver workload for the first driver. The monolithic kernel can also execute a virtual machine including a guest kernel. The guest kernel can execute a second driver workload for the second driver such that the second driver is isolated to the virtual machine. A communication channel can be generated between the guest kernel and the monolithic kernel such that the monolithic kernel can access the second driver workload via the communication channel.
Systems and methods for optimizing energy usage of a computing device running one or more VMs are disclosed. Energy consumption data for each of a plurality of virtual machines (VMs) executing on a computing device is monitored. A machine learning (ML) model is used to generate an energy usage prediction for each of the plurality of VMs based on the energy consumption data for each of the plurality of VMs. An allocation of resources for one or more of the plurality of VMs may be adjusted based on the energy consumption data and the set of energy usage predictions for each of the plurality of VMs to minimize an energy usage of each of the plurality of VMs.
A current resource utilization value of a computing resource used by an application executing on a computing device is accessed, the current resource utilization value quantifying a utilization of the computing resource, the application having a priority application designation and being one of a plurality of applications executing on the computing device, at least one of the plurality of applications lacking the priority application designation. An application profile that identifies a resource utilization trigger condition that corresponds to the computing resource is accessed. It is determined, based on the current resource utilization value of the computing resource and the resource utilization trigger condition that corresponds to the computing resource, that the application is in a non-preferred state. In response to determining that the application is in the non-preferred state, an additional quantity of the computing resource is caused to be available to the application.
A system and method of a state machine mechanism for targeted container creation. The method includes maintaining, in a database, a pool of available image layers and a plurality of compatibility profiles, each compatibility profile of the plurality of compatibility profiles indicates whether a respective available image layer of the pool of available image layers is compatible with other available image layers of the pool of available image layers. The method includes receiving, from a client device, a request to modify a container image including a base layer and one or more image layers. The method includes generating, based on the pool of available image layers and the plurality of compatibility profiles, a state machine for evaluating image layer compatibility for the container image. The method includes generating, by a processing device based on the state machine, a container image file that defines a modified version of the container image.
A kernel monitor can be used to mitigate ransomware activity of a host system. In some aspects, a computing system can use the kernel monitor to monitor a set of system calls generated by the host system within a time window to perform a functionality. The kernel monitor can include a respective kernel program monitoring each system call in the set of system calls. The set of system calls can be filtered by the kernel monitor to identify a subset of system calls associated with encrypting a filesystem of the host system. The computing system can determine that the subset of system calls is indicative of ransomware activity associated with the host system based on the subset of system calls exceeding a predefined threshold. Subsequently, the computing system can perform a mitigation operation to mitigate the ransomware activity.
An example method may include booting, by a host computer system, an operating system (OS) kernel; locking, by a security service running on the host computer system, a plurality of physical pages in a memory of the host computer system, wherein the plurality of physical pages is designated for use by the OS kernel, wherein the plurality of physical pages, upon locking, are unmodifiable by the OS kernel, and wherein the security service is associated with a privilege level higher than a privilege level of the OS kernel; performing, by the security service, a cryptographic measurement on the plurality of the physical pages; and generating, by the host computer system, a measurement report based on the cryptographic measurement.
Techniques that provide source metadata associated with code recommendations generated by an automation controller are described. A training data set comprising queries, code recommendations and source metadata associated with each of the code recommendations may be stripped of the source metadata and encoded by an NLP model to generate vector representations of each code recommendation. Each vector representation is stored in an index in association with the source metadata corresponding to the underlying code recommendation. In response to receiving a query, the query is processed using an inference model to generate a second code recommendation, which is encoded using the NLP model to generate a second vector representing the second code recommendation. The second vector is compared to the index to identify the source metadata corresponding to the second code recommendation. The second code recommendation and corresponding source metadata are provided via an interface of the automation controller.
Embodiments of the present disclosure relate to managing or controlling an update of a unikernel. An update to a first unikernel may be obtained. A second unikernel is created from the update. Application state is transferred from the first unikernel to the second unikernel.
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
65.
MANAGING COMPUTING RESOURCE CONSUMPTION OF SOFTWARE APPLICATIONS USING CONTROL GROUPS TO FACILITATE SAFETY COMPLIANCE
A system can be provided for managing computing resource consumption of user loaded software applications using control groups to facilitate safety compliance. For example, the system can detect an interference event between a user application executing within safety management system and a functional safety application executing within the safety management system. In response to detecting the interference event, the system can generate a control group for the user application. The control group can specify a portion of system resources of the safety management system to allocate to the user application. The system can then migrate the user application to the control group to allocate the portion of the system resources to the user application. In doing so, reoccurrence of the interference event can be prevented.
Qubit allocation service is disclosed. A qubit allocation service determines that a first quantum service requires a qubit for execution. A qubit registry that maintains information about a plurality of qubits on a quantum computing system is accessed to identify a first qubit of the plurality of qubits that is available for allocation. Information indicating that the first qubit is allocated to the first quantum service is stored. The first quantum service is provided qubit information via which the first quantum service can determine that the first qubit is allocated to the first quantum service.
G06N 10/80 - Quantum programming, e.g. interfaces, languages or software-development kits for creating or handling programs capable of running on quantum computersPlatforms for simulating or accessing quantum computers, e.g. cloud-based quantum computing
A system and method of a distributed and partitioned state machine for mesh devices. The method includes obtaining a first capability dataset indicating capabilities of a first mesh node of a first mesh network system to provide a first service for a first object. The method includes obtaining a second capability dataset indicating capabilities of a second mesh node of a second mesh network system to provide a second service to a second object. The method includes generating a set of NFSM models for the first object and the second object, each NFSM model to provide the first service for the first object or the second object. The method includes providing the set of NFSM models and a partition dataset to cause a first gateway device and a second gateway device to use a single NFSM model to provide the first service to the second object.
A system and method of using wireless charging to redistribute power resources within a mesh network. The method includes monitoring, by a processing device of a control node of the mesh network, a plurality of nodes of the mesh network to obtain a power distribution (PD) report comprising a plurality of battery levels associated with the plurality of nodes. The method includes identifying a first node of the mesh network having a first battery in a first deficit power state based on the PD report. The method includes identifying a second node of the mesh network having a second battery in a second surplus power state based on the PD report. The method includes transmitting a message to the second node of the mesh network to cause the second node to wirelessly charge the first battery of the first node.
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
H02J 7/00 - Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
H02J 7/02 - Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries for charging batteries from AC mains by converters
Page table entries for a maximum number of virtual functions configurable by a physical function of a single root input-output virtualization (SR-IOV) device can be pre-allocated to provide access for nested virtual machines and containers. For example, a computing device can allocate, by an input-output memory management unit (IOMMU), a page table comprising page table entries to a physical function executed by an SR-IOV device. The number of page table entries can be the maximum number of virtual functions that are configurable by the physical function. A virtual IOMMU executing in a virtual machine deployed by the computing device can map a virtual page table comprising virtual page table entries to the page table comprising page table entries. The virtual machine can assign a virtual function using a virtual page table entry. The virtual page table entry can include a function number and a virtual memory address.
A computing device accesses a plurality of datasets, each dataset comprising an input of a first plurality of inputs to a computer program, a first output of a plurality of outputs of the computer program, and a value identifying an importance of the input to the first output and produced by an explanation service. The computing device trains a machine-learned model to predict values based on the plurality of dataset. The computing device executes the computer program with a second plurality of inputs to produce a second output. The computing device inserts the second plurality of inputs and the second output into the machine-learned model, and the machine-learned model produces values for the second plurality of inputs based on the second plurality of inputs and the second output.
Techniques for booting a computing device are disclosed. An example method includes, in response to powering on or rebooting a computing device, performing a pre-boot process comprising loading an Operating System (OS) installer into storage of the computing device and executing the OS installer. The method also includes entering, by a processing device executing the OS installer, a standby state after performing the pre-boot process. The method also includes in response to receiving an activation instruction, exiting the standby state and installing an operating system of the computing device.
The technology disclosed herein receives a test suite, identifies one or more parameter values for each test case of the test suite, obtains a plurality of Infrastructure as Code (IaC) variables for a respective test case based on the one or more parameter values, generates a corresponding IaC module for each IaC variable of the plurality of IaC variables, and instantiates a corresponding testing environment to execute the respective test case based on each IaC module associated with a respective IaC variable.
A system can execute a first container and a second container on a first node, transmit configuration data associated with the first container to the second container, and initiate a migration of the second container from the first node to a second node. The second node has a different computer architecture than the first node. The second node can be configured to modify the functioning of a third container based on the second container storing the configuration data.
Embodiments of the present disclosure relate to managing or controlling a warm-start of an application. A shutdown notification may be received for a first virtualization environment. Application state information associated with an application executing on the first virtualization environment may be obtained, the application state information divided into chunks. The obtained application state information may be sent to a warm-start service to be delivered to a second virtualization environment.
A rules engine that is running a rules-based application executing on a computing device comprising a processor device receives a first transaction that includes a plurality of data fields, at least some of the data fields including data to be evaluated by a plurality of rules identified in the rules-based application, the first transaction including encrypted data in a first encrypted data field of the plurality of data fields that has been encrypted with a symmetric key in accordance with a structured encrypted algorithm. The rules engine queries the encrypted data using a first query token generated using the symmetric key to determine if the encrypted data includes a value used in a first condition identified in the plurality of rules. The rules engine takes an action based at least in part on querying the encrypted data.
Systems, methods, and apparatuses for maintaining safety standard compliance in virtualized automotive computing systems are provided herein. An example method comprises monitoring an automotive computing environment executing a plurality of virtual machines, responsive to a request to instantiate a new virtual machine, inspecting a configuration file of the new virtual machine, responsive to a configuration parameter of the configuration file violating a first predefined safety rule, modifying the configuration parameter, monitoring communications to and from a virtual machine of the plurality of virtual machines, the monitored communications including a first communication, and responsive to the first communication violating a second predefined safety rule, modifying a parameter of the automotive computing environment, or intercepting the first communication and modifying a content of the first communication.
A method includes generating an optimized version of an inference serverless function using a graph compiler. The method further includes replacing a storage volume in an init container of the inference serverless function with a new storage volume comprising the optimized version of the inference serverless function.
Techniques described herein relate to generating dynamic troubleshooting information for distributed computing systems. For example, a computer-implemented method can involve receiving a support request for an issue with respect to a computing environment. The support request can include a diagnostic file for the computing environment. In response, troubleshooting information associated with the issue or the computing environment can be identified in a support information database. A diagnostic software tool associated with the issue or the computing environment can be embedded within the troubleshooting information. Then, a graphical user interface displaying the troubleshooting information and including an interface element displaying a result generated by applying the diagnostic software tool to the diagnostic file can be output for use in resolving the issue.
A Rete decision tree that identifies a plurality of nodes that correspond to conditions identified in a rules-based application and a plurality of paths through subsets of the nodes in accordance with logic of the rules-based application is accessed. The Rete decision tree is partitioned into at least two partitions, a first partition comprising a first plurality of nodes and a corresponding first set of the plurality of paths, and a second partition comprising a second plurality of nodes and a corresponding second set of the plurality of paths, wherein at least one of the nodes in the second partition comprises a copy of a node in the first partition. A first service that implements the first partition is caused to be initiated on a first compute instance and a second service that implements the second partition is caused to be initiated on a second compute instance.
Service disruption avoidance techniques are provided based on deployment metadata associated with a cluster. The cluster includes one or more nodes. A plurality of applications are installed on the cluster. Prior to a maintenance activity to the one or more nodes of the cluster, a processor receives a request to determine a state of maintenance availability of an application. The processor retrieves deployment metadata for the plurality of applications installed on the cluster, in response to receiving the request. The processor parses the deployment metadata to identify one or more installation rules associated with the plurality of applications. The processor determines a set of conflicts for the first application, and determines the state of maintenance availability of the first application based on the set of conflicts.
A quantum computing system determines that a quantum process seeks access to a quantum resource implemented by the quantum computing system. It is determined that a particular contract of a plurality of contracts governs access to the quantum resource, the contract identifying a condition of the quantum computing system that is to be met prior to granting access to the quantum resource. Information is sent to a plurality of computing devices indicating that the quantum process seeks access to the quantum resource. Condition determinations are received from the computing devices, each condition determination indicating whether the condition is met. Access to the quantum resource is granted or denied based at least in part on the plurality of condition determinations.
Some examples of the present disclosure relate to risk analysis of test failures that occurred during a testing phase of a continuous integration pipeline. In one particular example, a system can detect a failure of a test during a testing phase of a continuous integration pipeline. The testing phase can involve executing a group of tests in a plurality of configurations prior to merging an update to source code into a code base of a software application. Based on detecting the failure of the test during the testing phase, the system can access historical data associated with prior executions of the test, determine a risk score associated with the failure of the test based on the historical data, and perform an action associated with the source code based on the risk score.
Systems and methods for runtime loading of a non-native module to a virtual machine. An example method may include running, by a processing device, a virtual machine; loading, in the virtual machine, a first bytecode module comprising a first bytecode of a first bytecode type, wherein the first bytecode type is not supported by the virtual machine; validating the first bytecode module according to a first validation policy based on a status of the virtual machine; generating a second bytecode module by translating the first bytecode to a second bytecode of a second bytecode type, wherein the second bytecode type is supported by the virtual machine; and executing the second bytecode module by the virtual machine.
Container workloads can be transferred (e.g., migrated) between nodes of a distributed computing environment based on energy consumption. For example, a system may generate an energy consumption estimate for a container executing on a first node. The system can further determine that the energy consumption estimate of the container exceeds an energy consumption threshold. In response, the system may implement a multi-objective optimization algorithm to identify a second node usable to execute the container. The multi-objective optimization algorithm may identify the second node based on current workloads of a group of nodes that includes the second node and the energy consumption estimate of the container. The system may then deploy the container at the second node.
A rules engine accesses a rules-based application that identifies a plurality of rules, each rule identifying a condition and an action that may be taken based on an evaluation of the condition. The rules engine generates, from the rules-based application, a plurality of processing nodes, some of the processing nodes corresponding to conditions identified in a rule and others of the processing nodes corresponding to actions to be taken. Processing node information is input into a constraint solver that identifies the processing nodes and interrelationships between the processing nodes and a cost function that identifies a processing preference. A solution is received from the constraint solver that identifies a first set of processing nodes of the plurality of processing nodes to be implemented on a first computing device, and a second set of processing nodes of the plurality of processing nodes to be implemented on a second computing device.
Generating quantum service definitions from executing quantum services is disclosed. In one example, a processor device of a quantum computing system executes a quantum service comprise one or more qubits. The processor device (e.g., by executing a quantum analysis service (QAS)) receives a request to profile the quantum service. Based on the request, the processor device obtains service metadata corresponding to the quantum service. A quantum service definition that defines one or more features of the quantum service is then generated based on the service metadata, and the quantum service definition is stored on a persistent data store. In this manner, quantum service definitions may be partially or wholly reverse-engineered for quantum services for which original quantum services definitions are unavailable or inaccessible.
H04L 41/5054 - Automatic deployment of services triggered by the service manager, e.g. service implementation by automatic configuration of network components
09 - Scientific and electric apparatus and instruments
35 - Advertising and business services
42 - Scientific, technological and industrial services, research and design
45 - Legal and security services; personal services for individuals.
Goods & Services
Computers; quantum computers; downloadable electronic
publications namely informational materials; computer
hardware and software for information technology analysis
and data management; computer hardware and software for
application development; computer hardware and software for
cloud computing; computer hardware and software for
cognitive computing; computer hardware and software for
artificial intelligence; computer hardware and software for
blockchain technology; computer hardware and software for
quantum computing and quantum programming; computer
hardware, namely magnetic tape units (data processing),
magnetic tapes (ribbons), printed circuits, integrated
circuits, computer keyboards, compact discs (audio-video),
optical discs, couplers (data processing), floppy disks,
magnetic data carriers; computer hardware, namely video
screens, scanners (data processing equipment), computer
printers, interfaces (data processing), readers (data
processing), computer software (recorded programs) intended
for data processing, microprocessors, modems, monitors
(hardware), computers, computer memories, computer
peripherals; computer adapters; computer components;
equipment for data processing; computer devices for data and
information management; semiconductors; machine-readable
electronic data carriers; magnetic disks; hard disk drives;
magnetic tape recorders; calculating machines; cash
registers; fax machines; video recorders; video tapes;
electric cells and electric batteries; computer chips;
wafers for integrated circuits; computer accessories,
namely, computer communications servers; carrying cases for
computers; computer interface cards; computer cables and
computer cable parts; fax-modem cards for computers;
computer accessories, namely, screen filters, computer mouse
pads, pagers, computer controllers; electrical converters,
namely, digital-to-analog, analog-to-digital and
step-by-step voltage switches; computer mouse; integrated
circuit cards and smart chip cards, integrated circuit
adapters and smart chip card adapters; readers for
integrated circuit cards and smart chip cards;
microcomputers; electrical power appliances; projectors
(projection devices); remote controls for computers;
inverters, surge protectors and uninterruptible power
supplies; point-of-sale terminals (payment terminals);
computer servers; computer storage devices, namely,
high-speed storage subsystems for storing and backing up
electronic data locally or via a telecommunications network;
downloadable computer programs; recorded computer programs;
computer software platforms, recorded or downloadable;
computer software applications, downloadable; video game
software; operating system software and programs; software
for accessing a global computer network; document management
software; database management software; software for
locating, retrieving and receiving text, electronic
documents, graphic artwork and audio-visual information on
internal enterprise-wide computer networks and on local and
wide-area global computer networks; development software and
website design software and user manuals, in electronic
format, sold as a set; computer software for controlling the
operations and execution of computer systems, programs, and
computer networks; computer software for connecting
disparate computer networks and systems, servers and storage
devices; computer programs for connecting computers to each
other and enabling computer activities across a global
computer network; computer software for systems management,
existing software and processes in an information technology
environment; interactive computer systems combining computer
hardware and software for use in data management and
analysis and instruction manuals in electronic format sold
with these products; cloud computing systems, namely
communications networks integrating computer hardware and
software for dynamic provisioning, virtualization and
consumption measurement of computer resources; recorded and
downloadable cloud computing software for deploying and
managing virtual machines on a cloud computing platform;
computer systems, namely computer hardware and computer
software for the development and integration of artificial
intelligence, namely machine learning, deep learning and
natural language processing which are capable of collecting,
organizing and analyze data; computer systems, namely
computer hardware and computer software incorporating
functions of natural language processing, computational
linguistics, information retrieval, machine learning and
capable of understanding general queries formulated by
humans and formulating responses; software for developing,
building and operating blockchain technology applications;
computer hardware and computer software for developing and
testing quantum algorithms; downloadable documentation and
instruction manuals on machine-readable electronic data
carriers relating to computers or computer programs;
downloadable electronic publications; electronic
publications downloadable on computer media, namely user
manuals, guides, brochures, information sheets, written
presentations and teaching materials in the field of
computers, computer networks, computer storage, computer
operating systems, information technology, database
management, cloud computing, artificial intelligence,
blockchain technology and quantum computing; computer
hardware and software for the implementation of generative
artificial Intelligence solutions; computer hardware and
software to help businesses understand the potential of
generative Artificial Intelligence; computer hardware and
software for the management and expansion of Generative
Artificial Intelligence projects for other companies;
computer hardware and software for the integration of
generative Artificial Intelligence into operations. Arranging and placing of advertisements; sales promotion
services (for third parties); business management and
business management consultancy; provision of business
information; distribution of leaflets; distribution of
samples; newspaper subscription services for others;
accounting; reproduction of documents; systematization of
data in a central file; organization of exhibitions for
commercial or advertising purposes; business management
consultancy services and business affairs consultancy
services; commercial business development service; analysis
of market research data and statistics; electronic data
processing; computer data processing services for artificial
intelligence; computer data processing services for
cognitive computing; computer data processing services for
cloud computing; computer data processing services for
blockchain technology; computer data processing services for
information management; computer data processing services
for quantum computing and quantum programming; organising
and conducting trade exhibitions in the field of computers,
IT services, information technology, artificial
intelligence, cloud computing, blockchain technology,
quantum computing, database management and electronic
business transactions through a global computer network;
business advisory services to businesses relating to
artificial intelligence; business consulting services to
companies in the field of computer systems integrating
functions of natural language processing, computational
linguistics, documentary retrieval, machine learning and
capable of understanding general queries formulated by
humans and formulating some answers; business advisory
services to businesses relating to cloud computing; business
advisory services to businesses relating to blockchain
technology; business advisory services to businesses
relating to quantum computing, quantum programming and to
develop and test quantum algorithms; business advisory
services to businesses relating to information technology;
analysis and compilation of commercial data; systematization
of data in computer databases; commercial advice to
businesses on the use of computer equipment (hardware);
business management and consulting services for the
implementation of generative Artificial Intelligence
solutions; market research and analysis services to help
businesses understand the potential of Generative Artificial
Intelligence; advertising and promotion services for
companies offering generative Artificial Intelligence
solutions; business administration services for managing and
expanding Generative Artificial Intelligence projects for
other companies; consulting and advisory services and in the
field of business strategies for the integration of
Generative Artificial Intelligence in operations, and data
retrieval services. Computer programming; software as a service (SaaS) services
featuring data management software; software as a service
(SaaS) services featuring software for cloud computing;
software as a service (SaaS) services featuring software for
artificial intelligence; software as a service (SaaS)
services featuring software for cognitive computing;
software as a service (SaaS) services featuring software for
blockchain technology; software as a service (SaaS) services
featuring software for quantum computing and quantum
programming; software as a service (SaaS) services featuring
software for constructing, analyzing and executing quantum
programs and quantum algorithms; software as a service
(SaaS) services featuring software for developing and
testing quantum algorithms; computer programming and
computer consulting services for artificial intelligence;
computer programming and computer consulting services for
cognitive computing; computer programming and information
management consulting services; computer programming
services and computer consulting for data management;
computer programming and computer consulting services for
cloud computing; computer programming and computer
consulting services for blockchain technology; computer
programming and computer consulting services for quantum
computing; computer programming and IT consulting services
for software as a service (SaaS); design, installation,
updating and maintenance of software; design of computer
software and hardware for others, and professional
consultancy services in the field of computers; technical
support services, namely troubleshooting computer programs
and software; computer services, namely, design, creation
and maintenance of websites on behalf of third parties;
analysis of computer systems, integration of databases and
computer networks, programming of computers for others all
intended for commercial interactions on global computer
networks; design of computer and software interconnection
systems, namely, electronic connection of computers and
software to each other; computer program (software) and
computer hardware (quality control and technical control)
testing services; technical project studies in the field of
computer hardware and software; computer advice relating to
computer hardware, namely advice relating to computer
research and development; computer advice and assistance
relating to the use of the Internet; rental of computers and
software; scientific and industrial research, namely
research and development of new products, biological
research, research in bacteriology, research in chemistry,
research in cosmetology, research in mechanics, geological
research, technological research, pharmaceutical research,
scientific research for medical purposes; information
technology (IT) consulting; computer systems integration
services; consultancy services relating to the design,
selection, implementation and use of computer systems and
software for others; technical support services, namely,
diagnosing computer program problems; computer systems
design services for others; design of computer systems for
the interconnection of computer hardware and software,
namely, electronic interconnection of computers and
software; computer program and hardware testing services,
namely, testing of software, computers and servers to ensure
proper functioning; cloud computing services relating to
computer hardware and software services integrated into a
network for dynamic provisioning, virtualization and
metering of consumption of computer resources; providing
virtual computing systems and virtual computing environments
via cloud computing; design and development of software for
cloud data storage; cloud computing hosting provider
services; electronic data storage; data security service; IT
support services relating to software provided by IT
specialists; design of computer hardware for computer
networks; computer design and development; quantum
computing; consulting services relating to computer and
Internet security and data encryption; scientific research
and development services in the field of generative
Artificial Intelligence technology; technology consulting
services for companies wishing to exploit generative
Artificial Intelligence in their activities; software
development services for the creation and customization of
generative Artificial Intelligence solutions; technical
project planning and implementation services for companies
developing their capabilities in generative artificial
intelligence; design and development of computer hardware
and software for generative artificial intelligence
applications; IT services for monitoring and detecting
potential legal issues or security threats related to the
use of Generative Artificial Intelligence. Licensing and compliance services for companies offering
Generative Artificial Intelligence solutions, in compliance
with legal requirements.
88.
INHERITANCE OPERATOR FOR MANAGING A PLURALITY OF SERVICE VERSIONS WITHIN A CLUSTER
Systems and methods for managing a set of service versions by utilizing a parent operator with a set of child operators that each provide functionality corresponding to the incremental capability of a corresponding service version are disclosed. A processing device determines a lowest service version among a plurality of different service versions and generates a parent operator based on the lowest service version. For each subsequent service version of the plurality of service versions: an incremental capability of the subsequent service version is determined and a corresponding child operator is generated based on the incremental capability. The corresponding child operator includes logic and code paths corresponding to the incremental capability. Upon receiving a request identifying a particular subsequent service version, a first child operator corresponding to the particular subsequent service version is identified. The first child operator is integrated into the parent operator to respond to the request.
A quantum computing device initiates a first quantum algorithm comprising a test method implemented as a quantum oracle, the first quantum algorithm receiving an input of a first quantum register comprising one or more qubits and a second quantum register comprising one qubit, each qubit in the first quantum register corresponding to a test case for the test method. The quantum computing device receives an output of the first quantum algorithm. The quantum computing device initiates a second quantum algorithm, the second quantum algorithm receiving an input of a third quantum register and the output of the first quantum algorithm. The quantum computing device performs a measurement on the first quantum register and a measurement on the third quantum register. The quantum computing device determines, based on the measurement on the first quantum register and the measurement on the third quantum register, that the test method passed or failed.
Systems and methods for cloud-based keyless entry are generally described. In some examples, a first number is received from a vehicle. A first computing device of the vehicle may be configured to control an electronic door lock. A first unlock code may be generated using the first number. In some examples, a notification is sent to a remote entry device associated with the vehicle. A response to the notification may be received from the remote entry device. In some examples, the first number may be retrieved from a messaging service based at least in part on the receiving the response to the notification. A second unlock code may be generated using the first number. A determination may be made that the first unlock code matches the second unlock code. An instruction may be sent to the first computing device, the instruction effective to cause unlock of the electronic door lock.
B60R 25/24 - Means to switch the anti-theft system on or off using electronic identifiers containing a code not memorised by the user
B60R 25/01 - Fittings or systems for preventing or indicating unauthorised use or theft of vehicles operating on vehicle systems or fittings, e.g. on doors, seats or windscreens
B60R 25/33 - Detection related to theft or to other events relevant to anti-theft systems of global position, e.g. by providing GPS coordinates
G07C 9/00 - Individual registration on entry or exit
H04L 9/32 - Arrangements for secret or secure communicationsNetwork security protocols including means for verifying the identity or authority of a user of the system
91.
EXECUTION OF REMOTE CONFIGURATION FILES AT CONTROL NODES
Control nodes can execute configuration files from remote locations according to some examples described herein. For example, a control node may receive an input indicating a remote location, which can include configuration files. In response to receiving the input, the control node may retrieve a configuration file from the remote location. The configuration file can be used by the control node to deploy a software entity at one or more nodes. The control node may analyze the configuration file to detect one or more references indicating one or more resources associated with the configuration file. The control node can then generate an executable version of the configuration file by retrieving each of the resources. The control node can further execute the executable version of the configuration file to deploy the software entity at each of the nodes.
Access to a physical device associated with a computing system can be shared with multiple virtual machines by delegating control of the physical device to a primary virtual machine (PVM). In some aspects, a virtual machine monitor (VMM) of the computing system can generate a hardware description that describes the physical device. The VMM can initiate the PVM, which can use the hardware description to acquire control of the physical device from a host kernel of the computing system. The VMM can delegate control of the physical device from the host kernel to the PVM. After control of the physical device is delegated to the PVM, the PVM is configured to perform a device sharing process to share access to the physical device with the SVM.
Execution of software applications can be controlled based on application profiles to facilitate safety compliance. For example, a system can execute a test suite to identify a function call of a software application that is associated with a functional safety standard issued by a standard-setting organization. In response to identifying the function call, the system can generate a risk score for the function call. The risk score can indicate a likelihood of the function call causing non-compliance with the functional safety standard. The system can further generate an application profile including a permission for the software application based on the risk score. The permission may disable the function call of the software application. The system may then execute the software application based on the application profile. As a result, execution of the software application can comply with the functional safety standard.
G06F 11/36 - Prevention of errors by analysis, debugging or testing of software
G06F 21/53 - Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems during program execution, e.g. stack integrity, buffer overflow or preventing unwanted data erasure by executing in a restricted environment, e.g. sandbox or secure virtual machine
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
94.
KERNEL PRESENTATION OF CAMERA IMAGERY DURING THE KERNEL BOOT PROCESS
A kernel of an operating system executing on a computing device is notified that the kernel is to provide network packets received by the kernel via a network interface to an eBPF program executing in an eBPF environment of the kernel. The eBPF program receives, from the kernel, a camera network packet originating from a camera. The eBPF program causes information derived from the camera network packet to be copied to an image buffer of a display device driver for presentation on a display device.
A computing device receives a container image from a container registry, the container image comprising a plurality of layers. The computing device extracts, from the container image, a plurality of files into a filesystem of the computing device, each file of the plurality of files corresponding to one of the layers of the plurality of layers. The computing device generates a metadata file that describes a directory structure of the plurality of files in the filesystem. The computing device mounts the metadata file to a location in the filesystem, wherein mounting the metadata file causes a digest of the metadata file to be generated and the metadata file and the plurality of files in the filesystem to be read-only.
Tracing data including a plurality of traces for a plurality of operations performed by a distributed computing system on behalf of a plurality of users of a distributed computing system during a period of time is identified. Each trace having latencies for a plurality of segments of a corresponding operation. A set of overall latencies comprising an overall latency for each segment is determined. A set of user latencies including a latency for each segment is determined for each of the plurality of users. A set of energy usage estimates including an energy usage estimate for one or more of the plurality of users is generated, by a processing device, based on the set of overall latencies and the set of user latencies using a machine learning (ML) model.
A method of improving continuous integration, continuous build (CI/CD) pipelines includes receiving an indication of a failure of a CI/CD pipeline of a plurality of CI/CD pipelines. The method further includes processing build status information by a rule engine, the build status information indicative of builds executed within the plurality of CI/CD pipelines. The method further includes applying a set of rules to the build status information to select a subset of the plurality of CI/CD pipelines, wherein the set of rules includes one or more of a resource availability rule or a failure type rule. The method further includes executing the subset of CI/CD pipelines selected by the rule engine.
09 - Scientific and electric apparatus and instruments
35 - Advertising and business services
42 - Scientific, technological and industrial services, research and design
Goods & Services
(1) Computers; quantum computers; downloadable electronic publications namely informational materials; computer hardware and software for information technology analysis and data management; computer hardware and software for application development; computer hardware and software for cloud computing; computer hardware and software for cognitive computing; computer hardware and software for artificial intelligence; computer hardware and software for blockchain technology; computer hardware and software for quantum computing and quantum programming; computer hardware, namely magnetic tape units (data processing), magnetic tapes (ribbons), printed circuits, integrated circuits, computer keyboards, compact discs (audio-video), optical discs, couplers (data processing), floppy disks, magnetic data carriers; computer hardware, namely video screens, scanners (data processing equipment), computer printers, interfaces (data processing), readers (data processing), computer software (recorded programs) intended for data processing, microprocessors, modems, monitors (hardware), computers, computer memories, computer peripherals; computer adapters; computer components; equipment for data processing; computer devices for data and information management; semiconductors; machine-readable electronic data carriers; magnetic disks; hard disk drives; magnetic tape recorders; calculating machines; cash registers; fax machines; video recorders; video tapes; electric cells and electric batteries; computer chips; wafers for integrated circuits; computer accessories, namely, computer communications servers; carrying cases for computers; computer interface cards; computer cables and computer cable parts; fax-modem cards for computers; computer accessories, namely, screen filters, computer mouse pads, pagers, computer controllers; electrical converters, namely, digital-to-analog, analog-to-digital and step-by-step voltage switches; computer mouse; integrated circuit cards and smart chip cards; integrated circuit adapters and smart chip card adapters; readers for integrated circuit cards and smart chip cards; microcomputers; projectors (projection devices); remote controls for computers; inverters, surge protectors and uninterruptible power supplies; point-of-sale terminals (payment terminals); computer servers; computer storage devices, namely, high-speed storage subsystems for storing and backing up electronic data locally or via a telecommunications network; downloadable computer programs; recorded computer programs; computer software platforms, recorded or downloadable; computer software applications, downloadable; video game software; operating system software and programs; software for accessing a global computer network; document management software; database management software; software for locating, retrieving and receiving text, electronic documents, graphic artwork and audio-visual information on internal enterprise-wide computer networks and on local and wide-area global computer networks; development software and website design software and user manuals, in electronic format, sold as a set; computer software for controlling the operations and execution of computer systems, programs, and computer networks; computer software for connecting disparate computer networks and systems, servers and storage devices; computer programs for connecting computers to each other and enabling computer activities across a global computer network; computer software for systems management, existing software and processes in an information technology environment; interactive computer systems combining computer hardware and software for use in data management and analysis and instruction manuals in electronic format sold with these products; cloud computing systems, namely communications networks integrating computer hardware and software for dynamic provisioning, virtualization and consumption measurement of computer resources; recorded and downloadable cloud computing software for deploying and managing virtual machines on a cloud computing platform; computer systems, namely computer hardware and computer software for the development and integration of artificial intelligence, namely machine learning, deep learning and natural language processing which are capable of collecting, organizing and analyze data; computer systems, namely computer hardware and computer software incorporating functions of natural language processing, computational linguistics, information retrieval, machine learning and capable of understanding general queries formulated by humans and formulating responses; software for developing, building and operating blockchain technology applications; computer hardware and computer software for developing and testing quantum algorithms; downloadable documentation and instruction manuals on machine-readable electronic data carriers relating to computers or computer programs; downloadable electronic publications; electronic publications downloadable on computer media, namely user manuals, guides, brochures, information sheets, written presentations and teaching materials in the field of computers, computer networks, computer storage, computer operating systems, information technology, database management, cloud computing, artificial intelligence, blockchain technology and quantum computing; computer hardware and software for the implementation of generative artificial intelligence solutions; computer hardware and software to help businesses understand the potential of generative artificial intelligence; computer hardware and software for the management and expansion of generative artificial intelligence projects for other companies; computer hardware and software for the integration of generative artificial intelligence into operations. (1) Arranging and placing advertisements; sales promotion services (for third parties); business management and business management consultancy; provision of business information; distribution of leaflets; distribution of samples; newspaper subscription services for others; accounting; reproduction of documents; systematization of data in a central file; organization of exhibitions for commercial or advertising purposes; business management consultancy services and business affairs consultancy services; commercial business development service; analysis of market research data and statistics; electronic data processing; computer data processing services for artificial intelligence; computer data processing services for cognitive computing; computer data processing services for cloud computing; computer data processing services for blockchain technology; computer data processing services for information management; computer data processing services for quantum computing and quantum programming; organizing and conducting trade exhibitions in the field of computers, it services, information technology, artificial intelligence, cloud computing, blockchain technology, quantum computing, database management and electronic business transactions through a global computer network; business advisory services to businesses relating to artificial intelligence; business consulting services to companies in the field of computer systems integrating functions of natural language processing, computational linguistics, documentary retrieval, machine learning and capable of understanding general queries formulated by humans and formulating some answers; business advisory services to businesses relating to cloud computing; business advisory services to businesses relating to blockchain technology; business advisory services to businesses relating to quantum computing, quantum programming and to develop and test quantum algorithms; business advisory services to businesses relating to information technology; analysis and compilation of commercial data; systematization of data in computer databases; commercial advice to businesses on the use of computer equipment (hardware); business management and consulting services for the implementation of generative artificial intelligence solutions; market research and analysis services to help businesses understand the potential of generative artificial intelligence; advertising and promotion services for companies offering generative artificial intelligence solutions; business administration services for managing and expanding generative artificial intelligence projects for other companies; consulting and advisory services and in the field of business strategies for the integration of generative artificial intelligence in operations.
(2) Computer programming; software as a service (SaaS) services featuring data management software; software as a service (SaaS) services featuring software for cloud computing; software as a service (SaaS) services featuring software for artificial intelligence; software as a service (SaaS) services featuring software for cognitive computing; software as a service (SaaS) services featuring software for blockchain technology; software as a service (SaaS) services featuring software for quantum computing and quantum programming; software as a service (SaaS) services featuring software for constructing, analyzing and executing quantum programs and quantum algorithms; software as a service (SaaS) services featuring software for developing and testing quantum algorithms; computer programming and computer consulting services for artificial intelligence; computer programming and computer consulting services for cognitive computing; computer programming and information management consulting services; computer programming services and computer consulting for data management; computer programming and computer consulting services for cloud computing; computer programming and computer consulting services for blockchain technology; computer programming and computer consulting services for quantum computing; computer programming and IT consulting services for software as a service (SaaS); design, installation, updating and maintenance of software; design of computer software and hardware for others, and professional consultancy services in the field of computers; technical support services, namely troubleshooting computer programs and software; computer services, namely, design, creation and maintenance of websites on behalf of third parties; analysis of computer systems, integration of databases and computer networks, programming of computers for others all intended for commercial interactions on global computer networks; design of computer and software interconnection systems; namely, electronic connection of computers and software to each other; computer program (software) and computer hardware (quality control and technical control) testing services; technical project studies in the field of computer hardware and software; computer advice relating to computer hardware, namely advice relating to computer research and development; computer advice and assistance relating to the use of the Internet; rental of computers and software; scientific and industrial research, namely research and development of new products, biological research, research in bacteriology, research in chemistry, research in cosmetology, research in mechanics, geological research, technological research, pharmaceutical research, scientific research for medical purposes; information technology (IT) consulting; computer systems integration services; consultancy services relating to the design, selection, implementation and use of computer systems and software for others; technical support services, namely, diagnosing computer program problems; computer systems design services for others; design of computer systems for the interconnection of computer hardware and software, namely, electronic interconnection of computers and software; computer program and hardware testing services, namely, testing of software, computers and servers to ensure proper functioning; cloud computing services relating to computer hardware and software services integrated into a network for dynamic provisioning, virtualization and metering of consumption of computer resources; providing virtual computing systems and virtual computing environments via cloud computing; design and development of software for cloud data storage; cloud computing hosting provider services; electronic data storage and data retrieval services; data security service; IT support services relating to software provided by IT specialists; design of computer hardware for computer networks; computer design and development; quantum computing; consulting services relating to computer and Internet security and data encryption; scientific research and development services in the field of generative Artificial Intelligence technology; technology consulting services for companies wishing to exploit generative Artificial Intelligence in their activities; software development services for the creation and customization of generative Artificial intelligence solutions; technical project planning and implementation services for companies developing their capabilities in generative artificial intelligence; design and development of computer hardware and software for generative artificial intelligence applications; IT services for monitoring and detecting potential legal issues or security threats related to the use of Generative Artificial Intelligence.
99.
CLAIM CHECK MECHANISM FOR A MESSAGE PAYLOAD IN AN ENTERPRISE MESSAGING SYSTEM
A method includes storing, by a processing device of an enterprise messaging system comprising a plurality of nodes, a message payload in a data store, wherein the data store is shared by the plurality of nodes, wherein the message payload is extracted from a message; sending, to a first node of the plurality of nodes, a metadata item associated with the message; responsive to determining that a key corresponding to the message payload has been used by the first node to retrieve the message payload, decrementing a removal counter associated with the key; and responsive to determining that the removal counter satisfies a removal threshold criterion, removing the message payload from the data store.
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]
Systems and methods of the disclosure include: identifying, by a destination host computer system, a first memory page residing in a memory of the destination host computer system; transmitting, by the destination host computer system, at least a part of the first memory page to a source host computer system; receiving, by the destination host computer system, a confirmation from the source host computer system that the first memory page matches a second memory page associated with a virtual machine to be migrated from the source host computer system to the destination host computer system; and associating, by the destination host computer system, the first memory page with the virtual machine.
