Abstract: The dialogue system includes a keyword acquisition unit configured to acquire an input key group containing one or a plurality of input keywords on the basis of an input of a character string, a category generation unit configured to classify the resulting sentence candidates into a plurality of categories on the basis of a comparison between the input key group acquired by the keyword acquisition unit and the storage key group contained in an FAQ database, an intra-category ranking determination unit configured to determine a priority ranking of the resulting sentence candidates within each of the categories, and a presentation unit configured to select a resulting sentence candidate of a highest priority ranking determined by the intra-category ranking determination unit from within a category of a highest priority ranking determined in advance, and present a response for prompting a user to make an additional input.

Abstract: In an embodiment, communication data including an interaction between at least two individuals in an organization is received via at least two communication platforms. Content of the interaction is extracted to produce extracted content. A frequency of interaction and a type of interaction between the at least two individuals is determined based on the extracted content. A map representative of social interaction within the organization is generated. The map includes an indication of the frequency of interaction and the type of interaction between the at least two individuals. A new frequency of the interaction and a new type of interaction for at least a first individual of the at least two individuals with another individual is determined based on the map. A signal representing the new frequency of interaction and the new type of interaction with the other individual in the organization is provided to a compute device.

Abstract: Introduced here is a computer program that is representative of a software-implemented collaboration platform that is designed to facilitate conversations in virtual environments, document those conversations, and analyze those conversations, all in real time. The collaboration platform can include or integrate tools for turning ideas—expressed through voice—into templatized, metadata-rich data structures called “knowledge objects.” Discourse throughout a conversation can be converted into a transcription (or simply “transcript”), parsed to identify topical shifts, and then segmented based on the topical shifts. Separately documenting each topic in the form of its own “knowledge object” allows the collaboration platform to not only better catalogue what was discussed in a single ideation session, but also monitor discussion of the same topic over multiple ideation sessions.

Abstract: Methods and servers for preparing a sequence for a machine processing task. The method includes acquiring: (i) a vocabulary storing tokens, (ii) a merge table indicating possible mergers between pairs of tokens, and (iii) a text sequence. For a given word from the sequence, the method includes using the vocabulary for splitting the word into an initial sequence, and iteratively merging tokens of the initial sequence to generate a final sequence for the given word. The iterative merging includes, at a given merging iteration using the merge table for identifying merges between pairs of adjacent tokens in a current sequence of the given merging iteration, excluding at least one of merge based on a pre-determined probability, and using the reduced set merges for generating a new sequence by performing at least one merge. The new sequence is to be used as a current sequence during a next merging iteration.

Abstract: The present disclosure describes methods, devices, and storage medium for generating a natural language description for a media object. The method includes respectively processing, by a device, a media object by using a plurality of natural language description models to obtain a plurality of first feature vectors corresponding to a plurality of feature types. The device includes a memory storing instructions and a processor in communication with the memory. The method also includes fusing, by the device, the plurality of first feature to obtain a second feature vector; and generating, by the device, a natural language description for the media object according to the second feature vector, the natural language description being used for expressing the media object in natural language. The present disclosure resolves the technical problem that natural language description generated for a media object can only give an insufficiently accurate description of the media object.

Abstract: The disclosure relates to an artificial intelligence (AI) system that simulates functions such as cognition and judgment of the human brain by utilizing machine learning algorithms such as deep learning and its applications. A method in which a device provides translation information of an application includes obtaining a resource file of an application through an operating system (OS) of the device; translating text to be displayed on an execution screen of the application from the obtained resource file by using an artificial intelligence model; generating the execution screen of the application by using the resource file and the translated text; and displaying the generated execution screen, wherein the translating includes translating the text of a first language into a second language by applying at least a part of data in the resource file to the artificial intelligence model trained to translate the text to be displayed on the execution screen of the application.

Abstract: A circuit includes a first full adder, a second full adder, a first half adder, a third full adder configured to receive a sum output signal of the first full adder, a sum output signal of the second full adder, and a sum output signal of the first half adder, a fourth full adder configured to receive a carry output signal of the first full adder, a carry output signal of the second full adder, and a carry output signal of the first half adder, a second half adder configured to receive a carry output signal of the third full adder and a sum output signal of the fourth full adder, and a third half adder configured to receive a carry output signal of the second half adder and a carry output signal of the fourth full adder.

Abstract: The present disclosure discloses a processing element and a neural processing device including the processing element. The processing element includes a weight register configured to store a weight, an input activation register configured to store input activation, a flexible multiplier configured to generate result data by performing a multiplication operation of the weight and the input activation by using a first multiplier of a first precision or using both the first multiplier and a second multiplier of the first precision in response to a calculation mode signal and a saturating adder configured to generate a partial sum by using the result data.

Abstract: Some embodiments provide methods and apparatus for quantum random number generation based on a single bit or multi bit Quanta Image Sensor (QIS) providing single-photon counting over a time interval for each of an array of pixels of the QIS, wherein random number data is generated based on the number of photons counted over the time interval for each of the pixels.

Abstract: A method for supporting block coding is provided. The method includes the steps of: determining an arrangement position of a coding block selected by a user on the basis of a sentence component-specific arrangement order specified from a sentence structure of a spoken language; and providing the user with an arrangement result of the coding block specified on the basis of the arrangement position.

Abstract: A feature estimating device includes a parser identifying means for identifying a parser, the parser being contained in software, for parsing user input and executing a relevant command, a dividing means for extracting commands form a character string in the parser and clustering control flows connecting with the extracted commands as starting points to divide a code of the software for each feature, and a feature estimating means for estimating, based on a characteristic part of each divided code, a feature for each divided code.

Abstract: Techniques are presented to enable or facilitate the execution of a portion of source code, written in a high-level language (HLL), on a blockchain platform. The technique comprises receiving a portion of source code as input; and generating an output script comprising a plurality of op_codes. The op_codes are a subset of op_codes that are native to a functionally-restricted, blockchain scripting language. The outputted script is arranged and/or generated such that, when executed, the script provides, at least in part, the functionality specified in the source code. The blockchain scripting language is restricted such that it does not natively support complex control-flow constructs or recursion via jump-based loops or other recursive programming constructs.

Abstract: Systems and methods that provide a mechanism to transition static schema to dynamic schema while maintaining backwards capability. Simple removal of static schema elements, followed by replacement with dynamic schema elements, make a third-party code incompatible since the third-party code references schema entities that no longer exist. Provided is a mechanism to decrease the memory use of non-material static schema entities. Transitioning static schema to dynamic schema allows the database to avoid loading non-material schema entities, thereby decreasing overall memory usage.

Abstract: Various methods, apparatuses/systems, and media for dynamic code analysis using aspect oriented programming (AOP) are disclosed. A processor (i) creates a list of all method names associated with an application before launching the application and writes into a file; (ii) at runtime, reads the method names from the file into a hash set and using AOP load time weaving, each time a method is invoked, pointcut around the execution of the method to remove method name from the hash set in memory; (iii) periodically overwrites the file with a dump of current entries in the hash set for fault tolerance; (iv) for every subsequent restart of the application, the processor repeats from processes (ii) and (iii). After running processes (i)-(iv) for a predetermined time period (a month, a quarter etc.), the processor creates a final with methods that have not been invoked for potential deletion.

Abstract: A deployment platform, computer-readable medium, and computer-implemented method for intelligent execution of a solution on a computer network, including receiving an instruction to execute a solution in a local runtime environment on the deployment platform, the solution including solution code written in a solution language, determining, by a helper program on the deployment platform, whether the solution is executable on the deployment platform based on the solution language and either launching, by the helper program, the solution on the deployment platform when the solution is executable on the deployment platform or launching, by the helper program, the solution on a remote platform on the computer network that is configured to execute the solution when the solution is not executable on the deployment platform, the helper program being configured to communicate with the launched solution to enable the launched solution to interface with the local runtime environment on the deployment platform.

Abstract: An example computing platform is configured to (a) cause a client device associated with a user to display an interface for deploying a new data science model, where the interface presents the user with a list of deployment templates, and where each of the deployment templates includes data specifying (i) a respective executable model package and (ii) a respective set of execution instructions for the respective executable model package, (b) receive, from the client device, data indicating (i) a user selection of a given deployment template for use in deploying the new data science model and (ii) a given set of configuration parameters for use in deploying the new data science model, and (c) use the given executable model package, the given set of execution instructions, and the given set of configuration parameters to deploy the new data science model.

Abstract: Computing systems, for example, multi-tenant systems deploy software artifacts in data centers created in a cloud platform using a cloud platform infrastructure language that is cloud platform independent. The system receives a declarative specification for creating a datacenter on a cloud platform. The system generates an aggregate pipeline comprising a hierarchy of pipelines. The system generates an aggregate deployment version map associating data center entities of the data center with versions of software artifacts targeted for deployment on the datacenter entities. The system collects a set of software artifacts according to the aggregate deployment version map. The system executes the aggregate pipeline in conjunction with the aggregate deployment version map to create the datacenter in accordance with the cloud platform independent declarative specification.

Abstract: Aspects of the subject disclosure may include, for example, a non-transitory machine-readable medium comprising executable instructions that, when executed by a processing system including a processor, facilitate performance of operations, the operations comprising: receiving by a selected one of a plurality of containers incoming traffic from a legacy application, the legacy application having been associated with a migrated application prior to the migrated application having been installed on a Software as a Service (SaaS) cloud infrastructure, the incoming traffic comprising a first instruction to perform a first legacy operation; mapping the first legacy operation of the legacy application to a replacement instruction for the migrated application by receiving data from the selected container and assigning the replacement instruction to replace the first instruction; and communicating with the migrated application on the SaaS cloud infrastructure, the communicating comprising sending to the migrated appli

Abstract: The present disclosure relates generally to systems and methods for providing sets of compatible firmware versions (e.g., cross-compatibility solution) for flashing (e.g., programming or re-programming) different devices of a network of devices (e.g., an industrial automation system) when using a flashing application. Providing the compatible firmware versions of such network of devices may facilitate flashing the devices with compatible firmware, based on a topology of the network of devices, to prevent functional errors in the network of devices. The present systems and methods may also be applicable to determining and providing cross-compatibility solution between different firmware, as well as software, used by different devices of a network of devices.

Abstract: A computing device can manage installation of an application program using an agent registered with an operating system. The agent can receive a notification in response to a user request to mount a disk image. The disk image can include the application program. The agent can generate metadata associated with the disk image. An action to take can be determined based on the metadata. The application program can be installed using privileges of the agent without changing privileges of an account for the current user.

Abstract: An edge device management system comprising a plurality of edge devices is shown. Each device includes a processing circuit configured to provide, via a first edge device of the plurality of edge devices, remote upgrades for an application of a second edge device of the plurality of edge devices. The processing circuit is configured to control hardware security features of the second edge device. The processing circuit is configured to configure a software update package for the second edge device, the software update package comprising a plurality of different software updates. The processing circuit is configured to deploy one or more deployment management tools to manage the application on the second edge device.

Abstract: A system for updating software installed on an electronic unit on a vehicle can include a processor and a memory. The processor can be disposed on an intermediate communications device. The intermediate communications device can be a mobile device. The memory can store an update request module and an update existence module. The update request module can include instructions that when executed by the processor cause the processor to receive, from the electronic unit on the vehicle, a request for an update of the software. The request can include: (1) an identification of a version of the software currently installed on the electronic unit and (2) a key to specifically identify the electronic unit. The update existence module can include instructions that when executed by the processor cause the processor to receive, from a device associated with development of the software, information about an existence of the update.

Abstract: There are provided systems and methods for a compute platform for machine leaning model roll-out. A service provider, such as an electronic transaction processor for digital transactions, may provide intelligent decision-making through decision services that execute machine learning models. When deploying or updating machine learning models in these engines and decision services, a model package may include multiple models, each of which may have an execution graph required for model execution. When models are tested from proper execution, the models may have non-performant compute items, such as model variables, that lead to improper execution and/or decision-making. A model deployer may determine and flag these compute items as non-performant and may cause these compute items to be skipped or excluded from execution. Further, the model deployer may utilize a pre-production computing environment to generate the execution graphs for the models prior to deployment or upgrading.

Abstract: An example operation may include one or more of receiving a software update at a transport of a subset of transports, validating the software update based on one or more of: a period of time when the software update is in use, and a number of utilizations of the software update by the subset of the transports, propagating the software update based on the validating, to a further subset of transports, wherein the further subset of the transports is larger than the subset of the transports.

Abstract: A method to improve the updating of firmware in a firmware updating system, uses serially-sent data packets containing the update and data. The firmware updating system includes storage, including an expander/switch, a baseboard manager controller (BMC), and a storage interface. A universal asynchronous receiver/transmitter (UART) for serial communication in the expander/switch is initialized and firmware updating instruction is sent to the expander/switch by the BMC. The firmware data packets are sent to the expander/switch by the BMC. A serial instruction to reset is sent to the expander/switch by the BMC and the BMC ends a communication with the UART serial. A firmware updating system applying the method is also provided.

Abstract: Shader source code performance prediction is described. In accordance with the described techniques, an update to shader source code for implementing a shader is received. A prediction of performance of the shader on a processing unit is generated based on the update to the shader source code. Feedback about the update is output. The feedback includes the prediction of performance of the shader. In one or more implementations, generating the prediction of performance of the shader includes compiling the shader source code with the update to generate a representation of the shader, inputting the representation of the shader to one or more machine learning models, and receiving the prediction of performance of the shader as an output from the one or more machine learning models.

Abstract: A vehicle controller includes: an execution unit configured to execute a control program for controlling a vehicle; a storage unit having a first program storage area to store the control program and a second program storage area to store an update program that is an updated version of the control program and created based on update data acquired from a device located outside the vehicle through a network; and an update unit that stores the update program in the second program storage area based on the update data, regardless of whether the execution unit is executing the control program.

Abstract: A controller device manages a plurality of network devices. The controller device includes one or more processing units configured to receive an upgrade request; obtain a redundancy model indicating network device redundancies or service redundancies; determine, based on the upgrade request and the redundancy model, an update graph having nodes each representing one of the network devices or one of the services, the update graph also having at least one edge that connects two of the nodes and that indicates the network redundancy or the service redundancy; determine, based on the update graph including the at least one edge, an update schedule for performing an update of software for the network devices that ensures availability for the first network device or second network device or availability for the service; and update the software of each of the network devices according to the update schedule.

Abstract: A method for authenticating and updating an eUICC firmware version includes: receiving first information from a terminal device, where the first information includes a target identifier; searching a currently stored event record for a target event record, where a group event identifier in the target event record matches the target identifier in the first information; sending the target event record to the terminal device, where the target event record is used to enable the terminal device to download an eUICC firmware version update package; and updating a firmware version of an eUICC of the terminal device based on the eUICC firmware version update package.

Abstract: A method for implementing LINUX kernel hot patch, an electronic device and a computer readable medium, the method includes: modifying header instruction code of a patched function in an atomic operation mode, and jumping directly or indirectly from a patched function address to a patching function address to activate a patching function. The method for implementing LINUX kernel hot patch can achieve the activation of the patching function without restarting the LINUX system.

Abstract: An example operation may include one or more of sending, by a master transport, a first portion of a software update to a transport of a first subset of transports, sending, by a master transport, a second portion of the software update to a transport of a further subset of transports, when a first transport of the subset of the transports and a second transport of the further subset of the transports are in proximity, causing the first transport to send the first portion of the software update to the second transport, and causing the second transport to send the second portion of the software update to the first transport.

Abstract: In a computer-implemented method for automatically presenting a visualization of information within a terminal for interfacing with a distributed version control system, an input is received at a command line interface of a terminal for interfacing with a distributed version control system, the input including an operation to be performed by the distributed version control system. The operation to be performed by the distributed version control system is identified based on the input. The operation is executed to generate output of the operation. The output is displayed within the command line interface. A graphical visualization of the output is automatically displayed within a visualization pane of the terminal, wherein the graphical visualization is interactive.

Abstract: This disclosure relates to method and system for identifying duplicate Cascading Style Sheets (CSS) selector declarations in CSS code bases. The method includes receiving at least one updated CSS code file in a CSS code base from a user. For each of the plurality of selector declarations, the method further includes identifying one or more locations associated with a selector declaration in each of the plurality of CSS code files of the CSS code base in real time. For each of the plurality of selector declarations, the method further includes generating a set of selector locations in each of the plurality of CSS code files. For each of the plurality of selector declarations, the method further includes determining a number of elements in the set of selector locations corresponding to the selector declaration.

Abstract: A computer-implemented runtime system is operable of providing a continuous product execution runtime environment for an application via a healthcare network. The system includes a focus machine and an action plan repository, to provide an autonomous runtime environment by at least: monitoring a running use case of at least one application on at least one device; taking over responsibility of a running use case of the at least one application, upon an error state being detected for the monitored running use case; analyzing the error state of the running use case detected; obtaining at least one suitable substitution action out of a plurality of actions deposited in the action plan repository, based on the error state of the running use case analyzed; and terminating and completing at least a part of the running use case, by employing the at least one substitution actions obtained, on the at least one application.

Abstract: A method for facilitating identification of secrets in source code by using machine learning is provided. The method includes retrieving a plurality of files from a repository, each of the plurality of files including a source code file; parsing the source code file to identify a training feature; associating a predetermined label with the training feature, the predetermined label corresponding to a secret label and a non-secret label; training a model by using the training feature and the corresponding predetermined label; receiving, via a graphical user interface, a test file, the test file including a set of source codes; parsing the set of source codes to identify a feature; and determining, by using the model, a first characteristic of the feature.

Abstract: Deployments of microservices executing in a cloud are automatically managed. Some microservices are deployed on dedicated nodes, others in serverless configurations. Rates of invocation and runtime data of microservices are monitored. Responsive to the monitored rate of invocation of a microservice running serverless exceeding a given threshold, the microservice is automatically redeployed to a dedicated node. A microservice executing on a dedicated node may be redeployed serverless if the infrequency with which it is called is sufficient. Microservices can be automatically redeployed between different dedicated nodes with different capacities based on monitored usage. The underlying cloud service provider may be automatically monitored for changes in serverless support functionality. Responsive to these changes, the thresholds at which microservices are redeployed can be automatically adjusted.

Abstract: Embodiments detailed herein relate to arithmetic operations of float-point values. An exemplary processor includes decoding circuitry to decode an instruction, where the instruction specifies locations of a plurality of operands, values of which being in a floating-point format. The exemplary processor further includes execution circuitry to execute the decoded instruction, where the execution includes to: convert the values for each operand, each value being converted into a plurality of lower precision values, where an exponent is to be stored for each operand; perform arithmetic operations among lower precision values converted from values for the plurality of the operands; and generate a floating-point value by converting a resulting value from the arithmetic operations into the floating-point format and store the floating-point value.

Abstract: A system and method which allows the basic checkpoint-reverse-mode AD strategy (of recursively decomposing the computation to reduce storage requirements of reverse-mode AD) to be applied to arbitrary programs: not just programs consisting of loops, but programs with arbitrarily complex control flow. The method comprises (a) transforming the program into a formalism that allows convenient manipulation by formal tools, and (b) introducing a set of operators to allow computations to be decomposed by running them for a given period of time then pausing them, while treating the paused program as a value subject to manipulation.

Abstract: Heterogeneous memory management and services. A memory metadata service obtains memory configuration information that identifies one or more sharable load-store memory segments available on each of a plurality of computing devices. The memory metadata service generates a memory metadata repository that comprises memory metadata that identifies, for each computing device of the plurality of computing devices, the one or more sharable load-store memory segments available on the computing device and, for each sharable load-store memory segment, a memory size of the sharable load-store memory segment and at least one memory attribute. The memory metadata service receives, from a first requesting computing device, a first memory allocation request that requests a first quantity of load-store memory. The memory metadata service sends, to the first requesting computing device, memory allocation information that identifies a first sharable load-store memory segment based on the memory metadata repository.

Abstract: A system, processor, programming product and/or method including: an instruction dispatch unit configured to dispatch instructions of a compare immediate-conditional branch instruction sequence; and a compare register having at least one entry to hold information in a plurality of fields. Operations include: writing information from a first instruction of the compare immediate-conditional branch instruction sequence into one or more of the plurality of fields in an entry in the compare register; writing an immediate field and the ITAG of a compare immediate instruction into the entry in the compare register; writing, in response to dispatching a conditional branch instruction, an inferred compare result value into the entry in the compare register; comparing a computed compare result value to the inferred compare result value stored in the entry in the compare register; and not execute the compare immediate instruction or the conditional branch instruction.

Abstract: A processor with fault generating circuitry responsive to detecting a processor write is to a stack location that is write protected, such as for storing a return address at the stack location.

Abstract: Methods of encoding and decoding are described which use a variable number of instruction words to encode instructions from an instruction set, such that different instructions within the instruction set may be encoded using different numbers of instruction words. To encode an instruction, the bits within the instruction are re-ordered and formed into instruction words based upon their variance as determined using empirical or simulation data. The bits in the instruction words are compared to corresponding predicted values and some or all of the instruction words that match the predicted values are omitted from the encoded instruction.

Abstract: A coprocessor may include a memory configured to store a plurality of Very Long Data Words, each as a test Very Long Data Word (VLDW) having a length in the range of about one thousand bits to one million or more bits and containing encoded information that is distributed across the length of the VLDW. A processor generates search terms and a processing logic unit receives a test VLDW from the memory, receives a search term from the processor, and computes a Boolean inner product between the search term and the test VLDW read from memory indicative of the measure of similarity between the test VLDW and the search term. Optionally, buffers within logic circuits of processing pipelines may receive the test VLDWs.

Abstract: Processor-guided execution of offloaded instructions using fixed function operations is disclosed. Instructions designated for remote execution by a target device are received by a processor. Each instruction includes, as an operand, a target register in the target device. The target register may be an architected virtual register. For each of the plurality of instructions, the processor transmits an offload request in the order that the instructions are received. The offload request includes the instruction designated for remote execution. The target device may be, for example, a processing-in-memory device or an accelerator coupled to a memory.

Abstract: Compacted addressing for transaction layer packets, including: determining, for a first epoch, one or more low entropy address bits in a plurality of first transaction layer packets; removing, from one or more memory addresses of one or more second transaction layer packets, the one or more low entropy address bits; and sending the one or more second transaction layer packets.

Abstract: Aspects of the invention include a computer-implemented method of updating metadata prediction tables. The computer-implemented method includes establishing, in the metadata prediction tables, a prediction of how a set of instructions will resolve and identifying that the set of instructions is completed. The computer-implemented method also includes determining, upon completion of the set of instructions, whether prediction update queues (PUQs) associated with the set of instructions indicate that the set of instructions resolved in one of a plurality of prescribed manners relative to the prediction and deciding that the metadata predictions tables are candidates to be updated based on the PUQs indicating that the set of instructions resolved in one of the plurality of prescribed manners.

Abstract: An electronic device that includes a central processor and a coprocessor coupled to the central processor. The central processor includes a plurality of registers and is configured to decode a first set of instructions. The first set of instructions includes a command instruction and an identity of a destination register. The coprocessor is configured to receive the command instruction from the central processor, execute the command instruction, and write a result of the command instruction in the destination register. The central processor is further configured to set a register tag for the destination register at the time the central processor decodes the first set of instructions and to clear the register tag at the time the result is written in the destination register.

Abstract: In one embodiment, a method includes accessing a loaded but paused source process executable and disassembling the source process executable to identify a system call to be instrumented and an adjacent relocatable instruction. Instrumenting the system call includes building a trampoline for the system call that includes a check flag instruction at or near an entry point to the trampoline and two areas of the trampoline that are selectively executed according to results of the check flag instruction. Building a first area of the trampoline includes providing instructions to execute a relocated copy of the adjacent relocatable instruction and return flow to an address immediately following the adjacent relocatable instruction. Building a second area of the trampoline includes providing instructions to invoke at least one handler associated with executing a relocated copy of the system call and return flow to an address immediately following the system call.

Abstract: Methods and systems are disclosed using an execution pipeline on a multi-processor platform for deep learning network execution. In one example, a network workload analyzer receives a workload, analyzes a computation distribution of the workload, and groups the network nodes into groups. A network executor assigns each group to a processing core of the multi-core platform so that the respective processing core handle computation tasks of the received workload for the respective group.

Abstract: Disclosed are a method of underlying drive forwarding and a multi-core system implemented based on a UEFI, which can increase a running speed of the multi-core system implemented based on a UEFI. The underlying drive forwarding method is configured for underlying drive forwarding of a multi-core system. The multi-core system is implemented based on a UEFI and includes an application processor and a bootstrap processor. The bootstrap processor is provided with an execution interface configured to call underlying hardware. The application processor is configured with an instruction interface corresponding to the execution interface.