97 results about "Direct execution" patented technology

The invention is suitable for the technical field of industrial design, and provides a multi-agent cooperative industrial design method and system for complex engineering, and the method comprises the following steps: constructing a large model agent set for a complex engineering design task; dividing a design task into sub-tasks which can be executed by an intelligent agent based on a task decomposition algorithm of a knowledge graph and an intention recognition mechanism; a Prompt-to-Code enhancement model is constructed, and task planning targets and constraints of multiple agents are converted into CAD modeling or CAE simulation design instructions capable of being directly executed by an industrial design tool through Prompt embedding; constructing a design version evolution tree, and designing a causal reasoning graph structure based on the interactive influence of target features; and inputting an asynchronous task planning strategy, a design instruction and a version evolution tree feedback result into a large model agent for iterative adaptive optimization. And the design efficiency and the scheme quality of a complex engineering design task can be obviously improved.

The invention discloses an unmanned aerial vehicle group task planning method based on a large language model, and the method comprises the steps: collecting and preprocessing the multi-level input information of an unmanned aerial vehicle group, transmitting the multi-level input information to a large language model in a specific coding format, and enabling the large language model to understand a natural language instruction, generating a high-level task target; performing recursive decomposition on the high-level task target by using a traditional task planner to form a task tree, and allocating sub-tasks after task decomposition to the unmanned aerial vehicle according to the capability of the unmanned aerial vehicle; and constructing an unmanned aerial vehicle action function library, understanding a task planning result generated by the traditional task planner by using a large language model, matching and calling related action functions in the unmanned aerial vehicle action function library, generating an action sequence which can be directly executed by the unmanned aerial vehicle, and checking and verifying the action sequence. According to the invention, the task planning capability of the unmanned aerial vehicle group in a dynamic environment is improved, and efficient task distribution and path planning are realized.

The invention provides an instant messaging driving type automatic service processing method and system based on a large language model and a model context protocol (MCP), and relates to the technical field of computers, and the method comprises the following steps: a user sends a message in a group of an instant messaging platform and makes a group robot to form a Webhook event; the MCP client exposes an HTTP (Hyper Text Transport Protocol) interface to receive a Webhook event, completes authentication and analyzes a message; the MCP client sends the message to a large language model, ACL permission judgment is carried out, and an MCPServer method and parameters to be called are recognized; if the permission is judged to be'unauthorized ', stopping, and then submitting permission errors to a big language model organization and description and directly executing and returning'insufficient permission'; if the permission is judged to be'authorization ', the next step is carried out; and the MCP client calls the MCP server (through HTTP + SSE or stdio) to obtain a structured result. According to the method, the unstructured chat instruction is stably converted into the standardized MCP request, and coupling of dialect type APIs of all back-end systems is eliminated.

The invention relates to the technical field of secure dialogues, and provides a financial operation secure dialogue method and system based on a verifiable intermediate code. The method comprises the steps of obtaining a natural language instruction of a user, generating V-FOC structured data based on a large language model, obtaining a question needing to be confirmed by the user, and generating a corresponding API instruction according to the generated V-FOC structured data after confirmation by the user; based on the generated API instruction, performing simulation execution by adopting a sandbox environment to obtain an expected execution result; the expected execution result is sent to the user for confirmation, and after the user confirms the expected execution result and authorizes the expected execution result, the safety API executor calls the background financial service API to complete operation. According to the invention, a transparent, controllable and verifiable'security firewall 'is established for the behavior of directly executing financial operation, so that the security of user funds is guaranteed while intelligent services are provided.

The invention discloses a quantum bit mapping algorithm based on dynamic coupling optimization, and the algorithm comprises the steps: (1) calculating a physical quantum bit distance through employing a Floyd-Warshall algorithm, constructing a directed acyclic graph (DAG) of a logic quantum circuit and an inverse graph r (DAG) of the DAG, and generating an initial mapping Pi; (2) an SABRE algorithm is used for traversing an original line and a reverse line of the original line, and initial mapping is optimized; (3) creating a buffer area B (vi) for each physical quantum bit vi, storing a single quantum bit gate to be executed, and setting a current mapping progress P (vi) of the vi; and (4) traversing the original line by using a quantum bit mapping algorithm based on dynamic coupling optimization, inserting an additional exchange operation SWAP, and generating a physical quantum line which can be directly executed on NISQ equipment. According to the quantum bit mapping algorithm based on dynamic coupling optimization, the logic equivalence is ensured, the line depth is remarkably reduced, and the parallelism degree is improved.

The invention discloses an artificial intelligence large model application method supporting vector graphic input and processing, and relates to the technical field of artificial intelligence, comprising: receiving a natural language instruction and multi-modal data of a user, the multi-modal data comprising vector graphic data selectable to input by the user; analyzing the vector graphic data, extracting a spatial relationship and a semantic attribute, constructing a structured representation of the spatial relationship and the semantic attribute, performing cross-modal semantic alignment and joint coding on the structured representation and a natural language instruction, and inputting into a multi-modal large model to generate a task execution plan comprising a plurality of steps, and scheduling the multi-mode large model and an external vector graphic processing tool to execute to obtain a processing result, and aiming at solving the technical problem that the vector graphic operation is difficult to directly execute by a general large model, the general cognitive ability of the large model and the accurate execution ability of the external professional tool are decoupled and coordinated; and the application potential of the large model in the professional field is effectively expanded.

The invention provides a policy translation and kernel protection method and system applied to a container environment, and the method relates to a control device and a host machine, the control device is in communication connection with the host machine, and the method comprises the steps: the host machine creates a target container therein, and distributes a container identifier for the target container; the control device monitors creation of a target container and obtains a target security policy for file access in the target container, and the target security policy is compiled by adopting a high-level language; according to a dynamic translation mechanism, the control equipment converts a target security policy written by adopting a high-level language into a native instruction which can be directly executed by a kernel of a host machine in real time; the native instruction is sent to the host machine, so that the host machine calls the proxy tool to inject the native instruction into a kernel of the host machine, and the native instruction autonomously runs in the host machine without depending on communication with the control equipment. Therefore, the security access protection of the file in the target container can be realized through the native instruction injected into the kernel of the host machine.

The invention provides an intelligent caching method and device based on a self-adaptive caching strategy, and the method comprises the steps: collecting an access event flow of each caching key in real time through a sensing probe embedded in a caching client, the event flow comprising Key, operation type, timestamp, request source, hit state and response time; running a streaming processing engine at a client based on an access event stream, and calculating indexes such as instantaneous QPS, continuous miss times and short-term access frequency by adopting a sliding time window; a calculation result is input into a rule engine for online matching, a decision instruction for a single Key is generated, and the decision instruction comprises distributed mutual exclusion lock addition, local TTL dynamic adjustment and read-write mode switching; a decision instruction is directly executed in a client memory through a strategy executor, and nanosecond strategy effectiveness is achieved; and finally, collecting system feedback data after strategy execution, inputting the system feedback data into a machine learning module for online learning, and dynamically optimizing a rule threshold value or recommending a new strategy.

The invention provides a large language model structured multi-mode response method and device oriented to the vertical domain, and the method comprises the steps: recognizing a task mode to which a natural language question belongs based on the natural language question inputted by a user, extracting a parameter corresponding to the task mode from a stored task mode-parameter mapping table, and storing the extracted parameter in the task mode-parameter mapping table; calculating the similarity between the natural language question and the structure label set and the high-dimensional semantic vector of each knowledge fragment in the knowledge base, and fusing to obtain a similarity score; if the maximum value of the similarity score is greater than or equal to a confidence coefficient threshold value, directly executing answer content generation, otherwise, deducing an answer to the natural language question according to a deduction rule, taking a deduction conclusion as an answer reference text, and labeling source information of the deduction conclusion; and generating answer content from the answer reference text according to the field structured template, and labeling source information. The method is higher in precision.

The invention discloses a robot strategy generation method and device, a computer and a storage medium, whether an initial plan generated by a VLM strategy network should be directly executed or not is judged through a confidence trigger, unnecessary reflection is achieved, task execution efficiency is improved, if the confidence is lower than a preset threshold value, an reflection stage is entered, and the task execution efficiency is improved. A plurality of candidate future trajectories guided by a plurality of candidate actions are generated, advantage evaluation is performed on each candidate future trajectory, a more accurate supervision signal is provided, decision robustness is enhanced, an evaluation result is used as feedback of a VLM strategy network, feedback information of all trajectories is aggregated by the VLM strategy network in a decoding stage to correct an initial plan, and the decision robustness is improved. According to the method, the low-quality action planning can be accurately identified and corrected, and the balance of efficiency and performance is realized.

Disclosed are various embodiments for machine learning- and artificial intelligence- based connector design and assistance. At least one computing device is directed to access a computer-generated model of an input / output (I / O) connector having a housing and at least one conductive connector, direct execution of at least one machine learning model using the computer-generated model of the I / O connector or data derived therefrom to perform at least one of a finite element analysis (FEA) that generates structural results and a signal integrity (SI) analysis that generates signal integrity results. The at least one computing device determines at least one changed design parameter as a function of at least one of the signal integrity results and the structural results and directs display of at least one user interface comprising the at least one changed design parameter. The computer-generated model can be generated and optimized automatically without human intervention.

The invention provides a heterogeneous reasoning acceleration method and system for a hybrid expert model, and the method comprises the steps: analyzing the historical activation behavior of each expert based on a representative data set of a multi-task context, constructing an expert portrait representing the relevance between the experts and tasks, and providing priori knowledge for scheduling; a cost prediction model is established for the heterogeneous computing units, and time delays of different execution paths are predicted according to input characteristics (such as data volume) during operation; in the reasoning process, an expert portrait and a cost prediction model are combined, an optimal path is selected from candidate paths (CPU execution, GPU direct execution and weight migration to GPU execution) for an activated expert, and task execution and data migration are controlled; based on real-time expert activation statistics and a system state, an expert portrait and a resident strategy of an expert in a heterogeneous environment are dynamically updated, and a feedback closed loop is formed. According to the method, adaptive optimization of the expert reasoning path is realized, and the problem of performance degradation of a traditional static distribution strategy in a complex input scene is solved.

The invention relates to the technical field of intelligent closestools, in particular to an intelligent closestool control method and system based on natural language interaction and a storage medium, and the method comprises the following steps: receiving an instruction input by a user through a natural language; determining a user identity; initializing a user mode and setting parameters; shunting natural language instructions; when it is judged that the natural language instruction is a simple instruction, the local edge layer analyzes and directly executes control operation; when it is judged that the natural language instruction is a complex instruction, the cloud large model analyzes and generates a local fixed control instruction; storing the local fixed control instruction into a corresponding user personalized mode; and executing the control instruction. According to the intelligent closestool, interaction control of natural languages is achieved, through the big language model of the cloud end, the model distillation technology is adopted, the requirement for computing power is reduced, and the use experience and the intelligent level of the intelligent closestool are overall improved.

This invention discloses a method for generating intelligent shell commands in a Linux environment, comprising: acquiring input natural language in a Linux terminal; determining whether a corresponding ready-made command exists; if it exists, directly executing the corresponding ready-made command; if it does not exist, calling a cloud model to perform semantic parsing on the natural language, identifying the user's intent based on the semantic parsing, and performing knowledge retrieval in conjunction with the context; combining the user's intent and the knowledge retrieval results, calling a large model to generate a shell command, and displaying the shell command to the user; after user confirmation, performing sandbox pre-execution; if pre-execution fails, returning the pre-execution result; if pre-execution succeeds, executing the shell command, and returning the execution result to the user after execution. This invention also discloses an intelligent shell command generation system in a Linux environment. This invention uses natural language to operate the terminal, making it convenient to use.

The embodiment of the invention provides a tensor instruction optimization method, tensor instruction optimization equipment and a storage medium, and relates to the technical field of artificial intelligence chips, the method comprises the following steps: sequentially traversing N tensor instructions in a target basic block, and if a target instruction on which the current traversed tensor instruction depends exists and L intermediate instructions exist between the tensor instruction and the target instruction, determining that the tensor instruction depends on the target instruction; if yes, obtaining the total extra time based on the respective extra execution time of the L intermediate instructions; if the total out-of-total time is greater than the unit execution time of the currently traversed tensor instruction, it is indicated that when the assembly line executes the currently traversed tensor instruction, a target instruction on which the currently traversed tensor instruction depends is inevitably executed, so that a dependency descriptor of the currently traversed tensor instruction is set as a first descriptor to represent a dependency-free relationship; therefore, the assembly line can directly execute the tensor instruction without waiting, so that the probability that the assembly line is blocked is reduced, idle running of hardware resources in the assembly line is reduced, and the utilization rate of the hardware resources is improved.

Embodiments of the present application provide a tensor instruction optimization method and device and a storage medium, and relate to the technical field of artificial intelligence chips. The method comprises: sequentially traversing N tensor instructions in a target basic block; if there is a target instruction on which a currently traversed tensor instruction depends, and there are L intermediate instructions between the tensor instruction and the target instruction, obtaining total additional time based on the additional execution time of each of the L intermediate instructions; and if the total additional time is greater than the unit execution time of the currently traversed tensor instruction, it is indicated that the target instruction on which the currently traversed tensor instruction depends has been executed when the pipeline executes the currently traversed tensor instruction, so the dependency descriptor of the currently traversed tensor instruction is set to a first descriptor to represent no dependency relationship. In this way, the pipeline can directly execute the tensor instruction without waiting, thereby reducing the probability of pipeline blocking, reducing the idling of hardware resources in the pipeline, and improving the utilization rate of hardware resources.

This application discloses a method and apparatus for updating a boot program. The method is applied to a storage medium including a first bank and a second bank, wherein the first bank is an active, running bank, and the second bank is an inactive, non-running bank. The method first responds to a boot program update command and queries the burning flag bit of the storage medium. This update command instructs the target boot program to be burned to each bank of the storage medium. Subsequently, when the burning flag bit indicates that the program should be burned to the inactive bank, the target boot program is burned to the second bank. Finally, after the target boot program is successfully burned to the second bank, it is copied to the first bank, thus completing the boot program update. By using the burning flag bit as the execution basis, the target boot program is prioritized for burning to the inactive, non-running second bank. After successful burning, the target boot program is copied to the first bank. The entire process does not require direct burning operations on the active bank, avoiding interference with the currently running boot program during the update process.

The present application provides a voice control method, system and storage medium for a virtual platform. The method includes: performing noise reduction and start / end point recognition on the acquired initial voice command to obtain a processed voice command; mapping the text converted from the processed voice command to a predefined atomic operation instruction set to obtain an initialization instruction; generating an atomic operation instruction or an atomic operation instruction sequence according to the complexity of the initialization instruction; the atomic operation instruction and the atomic operation instruction sequence are respectively instructions that can be directly executed; combining the content currently virtualized by the virtual platform and the natural law to verify the rationality of the atomic operation instruction or the atomic operation instruction sequence; and executing the verified atomic operation instruction or atomic operation instruction sequence. This method can solve the problem that the commonly used voice control methods at present cannot balance the response speed and complex instruction processing, thereby improving the efficiency of voice control of the virtual platform.

This application provides a method and apparatus for processing an interaction event. The method may be performed by a unified interaction framework. Behavior identification of the interaction event is performed by the unified interaction framework, and a widget may directly execute the interaction behavior identified by the unified interaction framework. The widget does not need to adapt to an interactive device. When a software system needs to adapt to a newly added interactive device, a developer can perform adaptation development on the unified interaction framework once to adapt the newly added interactive device for a plurality of widgets.

Approaches are described for a decentralized computing platform that enables dynamic execution of distributed services through a hybrid on-chain and off-chain architecture. The platform consists of a network of nodes, each running a virtual machine to host and execute service instances. A sequencer component records, sequences, and notarizes function calls to maintain a consistent service-level state across the network. Computation takes place off-chain on nodes that participate dynamically in specific services based on resource availability. A persistent virtual memory structure manages both service-level and instance-level state. The service-level state is synchronized across nodes participating in the same service, while the instance-level state is isolated to individual nodes for independent operations. The memory system is non-volatile, retaining state across function calls and enabling direct execution from memory. A universal procedure call (UPC) framework facilitates decentralized communication through multicast-enabled operations with customizable fault tolerance and supports applications from finance to high-performance computing.

The invention relates to the technical field of network security, and discloses a non-killing PE program generation method based on Shellcode encryption, which comprises the following steps of: converting an original PE program into a position-independent Shellcode, respectively encrypting the Shellcode and a key loading parameter, and writing the Shellcode and the key loading parameter into a loader configuration file; a loader configuration file and a Shellcode loader main program file used for decrypting and executing a Shellcode are compiled through a compiling tool, and a non-killing PE program is generated, so that the PE program can bypass static feature analysis and a conventional file detection mechanism on the basis of not modifying a source code; meanwhile, the Shellcode loader directly executes the Shellcode in a system call (syscale) mode, and behavior characteristic monitoring caused by a common API call path is avoided. According to the method, the PE program effectively avoids a traditional antivirus engine and a terminal detection system, the concealment and reliability of the antivirus-free PE program sample are remarkably improved, and then the generalization of an existing malicious program detection system is improved.

This disclosure provides a data manipulation method, system, storage medium, and computer program product, relating to the field of computer technology. In this disclosure, a corresponding handling method is provided for situations where front-end operation instructions involve multiple syntax types. Therefore, users do not need to use a fixed syntax type during instruction input. When a user wants to perform a first operation, they can choose a first syntax type to write the instruction, which defines instructions that can directly execute the first operation. When the user wants to perform a second operation, if the first syntax type does not define instructions that can directly execute the second operation, the user can choose a second syntax type to write the instruction, which defines instructions that can directly execute the second operation. Thus, for the operation the user wants to perform, the user does not need to break the operation into multiple steps and input multiple instructions, thereby improving the user's operational efficiency.

The present invention provides a method, apparatus, device and medium for enhancing workflow, the method comprising: encapsulating the entire process of the workflow into a DAG directed acyclic graph structure on the front-end page of Dify, and submitting the DAG directed acyclic graph structure of the workflow to the back-end; modifying the method used by the back-end to obtain the next executable node to obtain all next nodes from the DAG directed acyclic graph structure of the workflow according to the current node; when the back-end executes the workflow, after executing the current node, if there is only one next node, the next node is directly executed; if there are at least two next nodes, each next node is regarded as a sub-workflow, and a thread is opened for each sub-workflow for asynchronous execution. The advantages of the present invention are: on the one hand, it can make the definition of the workflow more flexible; on the other hand, it can effectively improve the execution efficiency of the workflow and meet the needs of more application scenarios; it can also better support streaming output.

The application relates to an adaptive wavefront control method and system based on parameter identification and active disturbance rejection. The method comprises a digital architecture adopting PC data processing and FPGA control. The PC data processing module is used to perform complex calculations such as variable forgetting factor recursive least squares, is responsible for dimensionality reduction decoupling and high-precision estimation of disordered data, and utilizes the high-speed parallel processing capability of the FPGA control system to directly execute an active disturbance rejection control algorithm at the bottom layer to offset external interference. The hardware-software collaborative design effectively combines the accuracy of the complex algorithm and the real-time performance of the bottom-layer hardware, thereby significantly enhancing the anti-interference capability and response bandwidth of the system.

The invention relates to an online debugging method of an application program, a computer program product, equipment and a medium, and the method comprises the steps: responding to the starting of the application program, and introducing a Spring application context; acquiring Bean of the application program based on the application context; the method comprises the following steps of: registering Bean in a Binding of a Grouping; and in response to the test request received by the configured service endpoint, analyzing the Grouping test script in the test request, and accessing the Bean through Binding in the execution process to obtain a test result. According to the method, the application context of Spring is introduced when the application program is started, all Bean of the application program is obtained through the application context, and the Bean is registered in the Binding of the Grouping, so that the Grouping test script can be received and directly executed through the configured service endpoint under the condition that the application program is not shut down or restarted, and the test efficiency of the Grouping test script is improved. The online debugging efficiency is improved while resource consumption during debugging is reduced, the method is suitable for various complex network environments, large-batch concurrent access support can be achieved, and subsequent fine-grained permission control is facilitated.

This invention relates to the field of information security technology, specifically to a secure computation method for medical privacy data based on CKKS homomorphic encryption. The method involves initializing a polynomial multiplication module and a CKKS module; the user end collects medical data, performs CKKS encoding and encryption, and uploads the ciphertext to the cloud; the server end deploys a disease risk prediction model, performs homomorphic inference analysis based on the ciphertext, and obtains the ciphertext result; the user end decrypts and decodes the ciphertext result, outputs a disease risk score, and obtains health data. This method makes the computation process more compatible with the GPU hardware architecture and scheduling mechanism, directly manipulates registers using assembly language to improve bit reversal efficiency, and designs a resource pool so that threads can place data into the resource pool after processing the current stage. Idle threads can find the data needed for the next stage in the resource pool without waiting and can directly execute the next stage's computation, reducing synchronization time.

A system comprises a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory, wherein the computer executable components comprise: an execution component that directs execution of a time dependent quantum algorithm at a quantum processor of a quantum system, wherein the quantum algorithm comprises propagating a wave packet in time under a determined Hamiltonian, resulting in a measurable output at the quantum system, and an evaluation component that determines an expectation value based on the output and corresponding to a vibrationally resolved electronic spectrum of a molecule.

The present invention discloses an embedded device and a method for repairing a ROM program. The method comprises the following steps: after an address comparison circuit captures that the address of any breakpoint interrupt register is the same as that of a PC register, a control circuit is triggered to send an interrupt to a CPU to prevent the repaired program pointed to by the current address in the PC register from being directly executed; after receiving the interrupt, the CPU updates and writes the address of the breakpoint interrupt program into the PC register to start executing the breakpoint interrupt program; the breakpoint interrupt program is executed by the CPU by searching the address in the breakpoint interrupt register that triggers the control circuit from a repaired program address list as the current repaired program address, allocating a first number of breakpoint interrupt registers from a breakpoint interrupt register group to a first program group to which the current repaired program address belongs, and allocating breakpoint interrupt registers to a plurality of second program groups respectively; and the address of the repair program is written into the PC register so that the repair program is executed by the CPU.

The present application relates to the technical field of computers. Disclosed are an exception handling method and apparatus, and a computing device. The method is applied to a processor, wherein the processor communicates with a first device, and the first device is a peripheral device of the processor. The method comprises: a processor acquiring first information, wherein the first information includes a status code, and the status code is used for representing whether an exception occurs in the process of a first device executing a first instruction issued by the processor, and / or representing the type of exception that occurred; if the status code indicates that an exception has occurred, the processor executing, on the basis of an exception handling program, exception handling corresponding to an exception type represented by the status code, wherein the exception handling program runs on the processor. A processor can directly execute, on the basis of an exception handling program, exception handling corresponding to an exception type represented by a status code, without needing to acquire, from a first device, specific information concerning an exception, thereby reducing the overhead of exception handling, and significantly improving the efficiency of exception handling.

The invention provides a risk control rule visualized configuration method and system, and the method comprises the steps: receiving a calculation function selected by a business analyst in a visualized editing interface, and enabling the calculation function to serve as a root node of an n-way tree; the calculation function has a plurality of parameter input bits, and for each parameter input bit, receiving a binding operation on a business data field or a sub-function to form a sub-node; constructing a complete n-way tree structure based on the root node and each child node, wherein the n-way tree structure represents an expression y = f (x1, x2,..., xn); receiving a selection of a risk disposal strategy associated based on the calculation result of the expression; combining the n-way tree structure with the selected strategy to generate a complete risk control rule; and converting the risk control rule into an expression which can be directly executed by the rule engine according to a script language supported by the target rule engine. According to the invention, the problems of high communication cost, long development period, low business participation degree, poor rule confidentiality and the like in a traditional risk control system are solved.