92 results about "Artificial intelligence software" patented technology

Techniques for leveraging a large language model (LLM) in software development are described. A description of an error message associated with a software system hosted by the multi-tenant provider network is received. An LLM is prompted with an analysis prompt to generate an analysis of the error message, the analysis prompt including the description of the error message, and the analysis of the error message is received from the LLM. The LLM is prompted with a suggested resolution prompt to generate a suggested resolution to a cause of the error message, the suggested resolution prompt including the description of the error message and the analysis of the error message, and the suggested resolution is received from the LLM. A change to resolve the cause of the error message is sent to an originator of the received description, the change based at least in part on the suggested resolution.

Techniques for leveraging a large language model (LLM) in software development are described. A description of a software development task is received from a user. Data associated with the software system is obtained from a data source. An LLM is prompted to identify at least one aspect of the task which requires clarification from the user, at least partly by providing the obtained data to the LLM and asking the LLM to identify a question for the user which remains unanswered by the obtained data. The question is presented to the user. An answer to the question is received from the user. The LLM is prompted to respond to propose an implementation of the task at least partly based on the data associated with the software system and the answer received from the user. The proposed implementation is received from the LLM and caused to be displayed to the user.

Techniques for displaying a graphical user interface of a software development system are described. An initial description of an initial structure of a software system is obtained, the initial description including an identification of interconnections amongst provider network resources that form the initial structure. A modified description of a modified structure of the software system is obtained, the modified structure based on at least a change to the initial structure of the software system described in the initial description. A difference between the initial description and the modified description is determined. An electronic device is caused to display a graphical user interface including a visual depiction of the initial structure of the software system and an indication of the difference, the visual depiction based at least in part on the initial description.

A unified virtual background image is generated for multiple participants of a video conference to create an immersive conference experience based on its use within video streams of those multiple participants. Generative artificial intelligence software associated with a conferencing system obtains input associated with a video conference. The generative artificial intelligence software generates a virtual background image based on the input. The virtual background image is then for use within multiple participant video streams during the video conference

The invention discloses a credential application software testing system and method based on artificial intelligence, and relates to the technical field of computer science and software engineering. The invention discloses a credential application software testing system based on artificial intelligence. The system comprises a demand analysis module, a test case generation module, a self-adaptive test execution module, an intelligent analysis module and a continuous integration and feedback module. The demand analysis module is responsible for analyzing a software demand document; the test case generation module generates a test case according to the demand analysis result; the self-adaptive test execution module is used for testing the generated test case by using a dynamic priority adjustment method; the intelligent analysis module analyzes the test result and generates a test report; and the continuous integration and feedback module is used for integrating the whole test system into a process of artificial intelligence software development, so that intelligent feedback and continuous optimization of the test process are realized.

To reduce labor related to an update of an encryption key in response to an encryption request for the AI software specifying the third type key, encryption key leakage or the like.An information processing apparatus according to the present technology includes an encryption key creation part that creates an encryption key on a basis of a first type key stored in advance in an imaging apparatus, a second type key different from the first type key, and a third type key that is different from the first type key and the second type key and is a key multiplied with the second type key to create a combination key stored in the imaging apparatus, or is a key stored in the imaging apparatus together with the second type key, as an encryption key used by the imaging apparatus for encryption of artificial intelligence (AI) software including at least software of an artificial intelligence model, the imaging apparatus performing image recognition processing using the artificial intelligence model on a captured image obtained by capturing an image of a subject, the encryption key creation part creating, in response to specification of a key derived from new information different from original information as the third type key, a new encryption key based on the third type key derived from the new information, the first type key, and the second type key on a basis of the new information.

The invention discloses an artificial intelligence interaction method and device, a display device, a storage medium and a product, and relates to the technical field of display device.The method is applied to the display device.The method comprises the steps that in response to an awakening instruction, a preset interaction interface is displayed, and video information is obtained in real time; inputting the video information and the interaction information into preset artificial intelligence software to obtain output information of the artificial intelligence software; and displaying the output information through the interactive interface. The interactive interface is displayed in the screen through the display device, the video information is detected through the display device, after the user inputs the interactive information through the interactive interface, the AI software can comprehensively output the result based on the interactive information input by the user and the video information obtained by the display device, and the output information is obtained; and the video information is fed back to the user through the interaction interface, so that the user can interact with the AI software based on the video information acquired by the current display equipment, and a new interaction mode is introduced for the display equipment.

The invention provides a gray-based continuous deployment method, device and equipment, a medium and a program product, which can be applied to the technical fields of artificial intelligence and software development. The method comprises the following steps: acquiring a first deployment strategy corresponding to a first deployment task, wherein the first deployment strategy comprises the number of nodes participating in gray deployment and the proportion of nodes of different risk levels; selecting nodes from the node pools of different risk levels according to a first deployment strategy to obtain a target batch of nodes; executing the first deployment task in the target batch node; wherein the node pools with different risk levels are obtained by continuously updating according to a second trigger logic, and the updating process of the node pools with different risk levels comprises the following steps: dividing the plurality of nodes into the node pools with different risk levels based on the node features of the plurality of nodes by using a trained risk prediction model, wherein the node features of the plurality of nodes are obtained by continuously updating according to the first trigger logic.

A system and method of encoding and decoding using generative AI for compression of video stream uses the system for encoding and decoding using generative AI for compression of video stream that comprises a camera, an encoder comprising generative artificial intelligence (AI) software operative in the encoder to encode video data, a transmitter, a receiver, a processor, a decoder, and a visual display operatively in communication with the decoder. Using the system, video data obtained from the camera are provided to the encoder; the generative artificial intelligence (AI) software encodes the video data at encoder to produce a compressed data set; the compressed data set are transmitted in a kilobit per second range (kbps-range) bandwidth at a low bandwidth using transmitter and receiver and, subsequently, from the receiver to a distant site via a further data network; and the compressed data set decoded at the distant site.

Artificial intelligence software implements a data processing structure with at least one additional virtual data storage structure operating as a parallel network of vectors tracking influence factors by which owners of proprietary data can be tracked along with the influence that their respective data sources had in developing an AI model and provides a method of modifying the influence of select data sources from an AI model. Embodiments of the disclosure include tracking not only tagged sources of training data and input stimulus data, but also calculating differential values for weights, biases and other information for saving as node vector weights. These vectors can be used to determine, and modify as desired, the contributions that these data sources provided to any given snapshot or checkpoint of the neural network.

An AI-assisted document organization system includes an internet equipment, an identification equipment, a processing unit which is matched and connected to the internet equipment and the identification equipment. The processing unit includes a central processor, an artificial intelligence software and a document organization software. The document organization software includes document organization goals which include automatic document classification and identification, artificial intelligent data extraction, automatic data verification, automatic approval verification, compliance and regulatory compliance, document tracking and control, automatic reporting, and notification. The central processor drives the artificial intelligence software. The processing unit acquires document data through the identification equipment. The artificial intelligence software reads the document data and, based on the document organization goals set by the document organization software, to search relevant information via the internet equipment and intelligently calculate the best organization solution for the obtained document data. The database stores the classified and organized document data.

A system and method for improving generative artificial intelligence (AI) software application response is provided. The method includes: receiving a query directed to a generative AI software application; receiving a response to the query, the response generated by the generative AI software application; generating a first contextual value based on the received query; generating a second contextual value based on the received response; generating a verification score based on the first contextual value and the second contextual value; and initiating a mitigation action in response to detecting that the verification score is below a predetermined threshold

Various embodiments of the present disclosure include systems, methods, and / or apparatuses for executing an agentic-AI-based software modernization system. An example system may be configured to receive one or more portions of monolithic legacy code of a legacy software program product, the monolithic legacy code comprising a plurality of code segments, group the monolithic legacy code by functionally related code segments of the plurality of code segments to define a plurality of groups, generate an API for each identified group, generate modern microservice code for each identified group to define a modernized software program product, and validate the modernized software program product.

A method for secure collection of sensitive data at a computer device includes receiving a request for sensitive data. The request indicates a set of parameters and a dynamic encryption key. The dynamic encryption key is generated by an authorized data requester based on a login session identifier. The method includes creating a user interface for collecting the set of parameters by an artificial intelligence (AI) software of the computer device. The method includes providing the user interface for collecting the set of parameters. Responsive to collecting the set of parameters from the user, the method includes encrypting the set of parameters using the dynamic encryption key and an encryption algorithm associated with the authorized data requester. The method includes transmitting the encrypted set of parameters to the authorized data requester to be decrypted.

The invention provides a GPU (Graphics Processing Unit) write storage system based on a Stream write instruction and a method thereof, and belongs to the technical field of calculation. According to the method, the special Stream Write instruction is provided, so that the operation of flexibly writing a small amount of data into the memory by a single instruction is realized, the method can be used for carrying out hardware acceleration on a data writing function of a common artificial intelligence software framework, a software compiler can be simplified, the instruction execution efficiency can be improved, and the support of a GPU on high-performance calculation is realized.

Software code optimization for specific computerized tasks is achieved by utilizing task-specific ML models that are trained to determine optimal sets of software code by intelligently assessing available hardware resources (i.e., specifically, processing devices, such as CPUs and GPUs) and, in some instances, SDKs for a specified task and, as a result, determining an optimal set of software codes for the specified task that is tied to one or more of the available hardware resources.

A virtual background image used with a video stream of a conference participant during a video conference is updated to visually represent one or more key points of the video conference. Generative artificial intelligence software associated with a conferencing system evaluates content of a video conference to determine one or more key points related to the video conference. The generative artificial intelligence software updates a virtual background image of a participant of the video conference to include one or more visual elements representing the one or more key points. The updated virtual background image is then output for use within a video stream of the participant during the video conference.

An artificial intelligence (AI) software product for providing scalable intelligent video surveillance for the artificial intelligence of things. The AI software product performs operations including receiving, at an edge node, a sequence of images of a target environment, where the AI software product resides in the edge node, and where the edge node is local to the target environment. The AI software product further observes one or more target objects in the sequence of images of the target environment in real time. The AI software product further detects at the edge node one or more anomalies in the target environment based on the observing of the one or more target objects in real time, where the one or more anomalies are specific to the target environment.

The application relates to the technical field of artificial intelligence assisted software engineering, and discloses a management method and system based on artificial intelligence software development, which comprises the following steps: collecting multidimensional data in development, testing and running stages, constructing a unified software development knowledge graph, establishing a cross-stage time sequence causal diagram based on the graph, extracting a defect correlation mode by combining a time sequence convolution network and a causal discovery algorithm, capturing an operation context in real time when a developer codes, submits or tests, matching a historical defect mode through two-stage retrieval, dynamically generating intelligent guidance information, finally recording a developer adoption behavior and a subsequent verification effect, and continuously iterating model parameters and guidance generation strategies through a double-channel feedback optimization mechanism. The application associates development, testing and running stage data in real time, intelligently pushes an interpretable early warning and correction guidance, forms a closed-loop optimization system, and significantly improves the quality and efficiency of software development.

The invention relates to a solar-panelled wind turbine (100) which combines wind and solar energy, which are renewable energy sources, in a single body instead of using them separately, and wherein the data from the sun sensor (191 ), wind direction sensor (192) and wind speed sensor (193) thereon is interpreted by means of an electronic control unit (182) (ECU) containing an artificial intelligence software, and after this interpretation, the most appropriate direction for the support system (140) and solar-panelled blades (110) is selected and electrical energy generation from both the sun and the wind is achieved.

The present application relates to the technical field of display devices, and discloses an artificial intelligence interaction method and apparatus, a display device, a storage medium, and a product. The method is applied to a display device. The method comprises: in response to a wake-up instruction, displaying a preset interaction interface, and acquiring video information in real time; inputting the video information and interaction information into preset artificial intelligence software so as to obtain output information of the artificial intelligence software; and displaying the output information by means of the interaction interface.

The invention relates to the technical field of artificial intelligence and software engineering, and discloses a small sample individual fairness testing method based on a domain adaptive flow model. Aiming at the problems of difficulty in obtaining target model training set data, low discrimination sample generation efficiency, insufficient sensitive attribute decoupling and the like in the existing black box fairness test, the invention provides the following technical scheme: firstly, constructing a gating residual domain adaptive flow model, and performing dynamic fusion on a frozen source domain projection matrix and a trainable low-rank adapter to obtain an adaptive flow model; domain adaptation of the flow model is realized under the condition of not depending on a target model training set; secondly, a two-stage anti-fact generation strategy is adopted, a seed sample set is constructed by utilizing a dynamic radius attenuation mechanism, and discriminated samples are efficiently expanded in combination with triple disturbance; finally, gradient orthogonal constraint is applied to the hidden space of the flow model, and decoupling control over the sensitive attributes and the semantic features is achieved. The black box fairness testing method can be used for black box fairness testing of classification models such as tables, texts and images, and has good practical significance and actual effect.

The application provides an intelligent grading and early warning system for intraoperative bleeding of a medical endoscope based on artificial intelligence and a working method thereof, and has the characteristics that the system comprises a medical endoscope catheter, a medical endoscope image processor, a medical lavage pump, a medical high-definition highlight liquid crystal display and end-side artificial intelligence software; the working method comprises real-time image recognition, bleeding point monitoring and early warning, automatic regulation of lavage and negative pressure suction; and the bleeding can be monitored in real time, intelligently and efficiently during surgery, and innovative medical technology support is provided for the surgery.The application has the advantages of convenient, intelligent and reliable surgical treatment effect.

The invention discloses a credibility evaluation method for artificial intelligence software. The credibility evaluation method comprises the steps of 1, full-life-cycle data acquisition and preprocessing, 2, multi-dimensional collaborative evaluation, 3, scenarized rule adaptation, 4, comprehensive credibility analysis and early warning and 5, visual output of evaluation results. According to the method, traditional dimensions, a large model and multi-mode special evaluation are integrated, the credibility verification problem of an emerging AI technology is solved, and real-time monitoring and collaborative verification of credibility are achieved through full-life-cycle data collection and cross-dimension linkage logic.

A system and method comprising a computer system and database configured using artificial intelligence software for storing historical histograms derived from images of particular biological features of different patients. The stored histograms are each associated with a transfer function that can be used in a 3D model of the biological features to allow users of the model to better observe particular features of the model. The system will automatically determine a transfer function for a new scan(s) by deriving a current histogram of the new scan, comparing this current histogram with the historical histograms stored in the database, and selecting the histogram that is closest to the current histogram based on certain features. The transfer function associated with the closest histogram is then used to obtain a new transfer function for the current histogram for use in a 3D model of the new scan(s).

An artificial intelligence (AI) software product for providing scalable intelligent video surveillance for the artificial intelligence of things. The AI software product performs operations including receiving, at an edge node, a sequence of images of a target environment, where the AI software product resides in the edge node, and where the edge node is local to the target environment. The AI software product further observes one or more target objects in the sequence of images of the target environment in real time. The AI software product further detects at the edge node one or more anomalies in the target environment based on the observing of the one or more target objects in real time, where the one or more anomalies are specific to the target environment.

A system and method that takes as input streamed and real-time data from the electric vehicle, from the charging station, from vehicle routes and scheduling systems, weather, traffic, and terrain from appropriate data streams, and uses Artificial Intelligence software using Machine Learning Technology on the Internet Cloud to manage electric vehicle charging, dispatch operations, and yard management for electric fleets is provided which combines data-driven decision making, deep learning, optimization, and statistical methods.

A method is provided for reducing energy consumption and / or demand of an edge device appliance involves receiving conditioning data pertaining to a thermostatic or other control output of the edge device appliance for a conditioned space or other load, processing the conditioning data using artificial intelligence (Al) software to create an optimized thermostatic or other control signal for the edge device appliance in the conditioned space or other load, and controlling the edge device appliance for the conditioned space or other load based on the optimized thermostatic or other control signal. The method can further include receiving an energy consumption and / or demand modification command. Power consumption data can be received to determine real-time energy consumption and demand data of the edge device appliance. An energy consumption and / or demand modification signal can be generated using the Al software and used to control the edge device appliance.

This invention relates to a method (100) for transferring emotional state and facial texture between two human face photographs using optimization techniques, without requiring any dataset. It can be utilized in forensic investigations, the entertainment and social media sectors, pre-procedural studies in medical aesthetics, synthetic dataset generation for 0 artificial intelligence software, and identity anonymization in images.

A system, computer program product, and method comprising the steps of tracking a work or school performance and an interaction at work or participation in an educational program at an educational institution with at least one tracking module; learning a physical movement or interaction, with at least one self-learning and analytics module, derived from the work or school performance and interaction at work or participation in an educational program at an educational institution; identifying a behavioral anomaly pattern, with an AI software module, founded on the physical movement or interaction; associating a predetermined movement value as measure to the behavioral anomaly pattern; generating a digital work or school performance review by the AI software module; generating a digital resume, with a resume module, based at least on one of, the digital work or school performance review, a work or school history and a place of employment or educational institution.