113 results about "User expectations" patented technology

The invention provides a mechanical arm control method based on a visual language model and human feedback. The method comprises the following steps: a) acquiring scene information: acquiring states of a mechanical arm and objects in a scene in real time through a camera; b) generating a control code according to the user instruction: decomposing the user instruction into a plurality of subtasks by utilizing a large language model, and combining and calling a predefined API (Application Program Interface) to generate the control code; c) verifying the generated control code: verifying the code through a visual language model, and judging that the control code completes a user instruction; d) executing the control codes: sequentially executing the control codes according to the sequence of the subtasks, and judging whether the step is successfully executed or not; and e) fault repair and man-machine interaction: feeding back reasons that tasks are not completed according to expectations, and regenerating control codes according to user feedback. According to the invention, the mechanical arm can understand and execute the natural language instruction of the user, and can communicate with the user when an abnormal condition occurs, so that the mechanical arm can complete various tasks in accordance with the expectation of the user.

Embodiments of the present application provide an operating parameter recommendation method and apparatus, used for in a big data processing scenario, recommending operating parameters for a computing device on the basis of the resource consumption under different operating parameters, without depending on historical data. The method comprises: first, on the basis of information obtained during the processing of historical tasks in a big data system, establishing a first relationship among the corresponding data information, parameters of a computing device processing the tasks, and time required to process the tasks, and a second relationship among the data information, the parameters, and resources of the computing device consumed for processing the tasks; inputting data information of a task to be processed, and the first relationship and the second relationship to a genetic algorithm, and outputting multiple sets of time values and resource values, i.e., modeling the process of the computing device executing data processing tasks, so as to fit the relationship between the time and resource consumption of the computing device and the operating parameters of the computing device; and determining operating parameters on the basis of actual available resources of the computing device or resource consumption that a user desires.

The invention discloses a big language model dialogue optimization method, device and equipment and a computer storage medium, and the method comprises the steps: responding to the entering of a current dialogue round, and obtaining configuration information corresponding to the current dialogue round based on the type of the current dialogue round; obtaining user input information corresponding to the current dialogue round; on the basis of a dialogue round switching judgment strategy corresponding to the dialogue round switching strategy configuration information, whether the current dialogue round needs to be switched or not is judged; if switching is needed, determining a next dialogue round corresponding to the current dialogue round based on a dialogue round switching strategy corresponding to the dialogue round switching strategy configuration information, and entering the next dialogue round; if switching is not needed, a reply task is generated based on a reply prompt word corresponding to the reply strategy configuration information and the user input information, the reply task is executed through a large language model, and reply information is generated; reply information is output in the current dialogue round, and user expectation is met.

The invention relates to the technical field of artificial intelligence, in particular to a verbal skill confrontation training generation method and device based on a large model, equipment and a storage medium, and the method comprises the steps: generating a simulation inquiry based on a preset user portrait, then obtaining a response of a service large model, and comprehensively evaluating the response quality; and the specific defect type of the service model in logic understanding or verbal skill expression is diagnosed through the cognitive deviation between the response and the user expectation by another evaluation model, so that a targeted optimization strategy is generated, the service model is finally driven to carry out directional reinforcement learning, and the verbal skill ability of the large service model is iteratively improved. According to the method, an adversarial sample is dynamically generated, and deep diagnosis is carried out in combination with cognitive deviation, so that a service model can understand deep intentions and emotion demands of different user groups fundamentally. Therefore, the strain capacity and the communication accuracy of the service model in a real interaction scene are remarkably improved, and the user satisfaction is effectively improved.

The invention discloses a product engineering change execution management method based on a PLM system, relates to the technical field of product management, and has the functions of acquiring changed data through a datamation technology, a development management system and an automatic series PLM system, automatically establishing tasks according to engineering, automatically providing an SOP operation instruction change application form, automatically managing overdue and the like. Platform-based, transparent and intelligent management is realized; the automatic series PLM system obtains the changed data, performs automatic modeling on the changed data, performs automatic conversion and transmission on the changed data, automatically generates task decision arrangements in different environments based on the association rule base, effectively conforms to user expectations, and improves the user experience. Trouble steps, labor cost and time delay of manually transferring the changed data are greatly reduced, efficient feature extraction is performed on the changed data, the relation between the changed data and original data is deeply sensed, generated task decision arrangement has higher robustness, and environment, cost, resources and user requirements are met in multiple aspects.

The invention provides a method and device for making a diversified analysis chart based on a UE engine, and belongs to the technical field of charts.According to the embodiment of the invention, based on source data, a service index weight matrix conforming to a service scene can be obtained, and based on the source data and demand description information, the diversified analysis chart is made. The method comprises the following steps: obtaining a chart type weight matrix which accords with data characteristics and user expectations through a business index weight matrix and a business index weight matrix, further recommending an appropriate chart type to a user while realizing deep analysis of data by comprehensively considering the business index weight matrix and the chart type weight matrix, and further improving the user experience by converting a multi-dimensional matrix into executable parameters of a UE engine. According to the embodiment of the invention, the powerful computing power support of the cloud server and the powerful graphic rendering capability of the UE engine can be utilized to provide a more visual and comprehensive diversified analysis chart for the user, so that the display efficiency is improved, and the use experience of the user is remarkably improved.

The invention discloses a trajectory planning method and device, electronic equipment and a storage medium, and relates to the computer technology, and the method comprises the steps: determining a target region according to obtained region information, and carrying out the feature extraction of map data corresponding to the target region, and obtaining region map features; performing feature extraction on the received image information to obtain required track features; and performing feature matching according to the regional map features and the demand track features to obtain a planned track of the demand path. According to the method and the device, the pattern expected by the user is combined with the real geographical environment in a mode of performing feature matching on the regional map features and the demand track features, an accurate and feasible planning track can be generated according to conditions such as actual roads and terrains, the track planning efficiency is improved, and the user experience is improved. And the beneficial effect of improving the precision and the aesthetic degree of the planned trajectory and the pattern required by the user is further achieved.

The invention provides a model updating method, device and system, in the model updating method, computer equipment displays a first processing result obtained by processing system data of a network system according to a model, and a user can perform knowledge data input operation after seeing the first processing result. The computer device obtains target knowledge data obtained after format conversion is conducted on the knowledge data, then the computer device responds to the model updating instruction, a model is updated through the target knowledge data, an updated model is obtained, and finally system data of the network system is processed according to the updated model to obtain a second processing result. And displaying the second processing result. The user can directly participate in the model adjusting and optimizing process, and the model of the user can be updated in real time to meet changing business requirements and personalized expectation of the user.

Described is a method for instilling the haptic dimension of texture to virtual and holographic objects using mid-air ultrasonic technology. A set of features is extracted from imported images using their associated displacement maps. Textural qualities such as the micro and macro roughness are then computed and fed to a haptic mapping function together with information about the dynamic motion of the user's hands during holographic touch. Mid-air haptic textures are then synthesized and projected onto the user's bare hands. Further, mid-air haptic technology enables tactile exploration of virtual objects in digital environments. When a user's prior and current expectations and rendered tactile texture differ, user immersion can break. A study aims at mitigating this by integrating user expectations into the rendering algorithm of mid-air haptic textures and establishes a relationship between visual and mid-air haptic roughness.

The embodiment of the invention provides an alarm information processing method, device and system, and an alarm information auxiliary processing method, device and system, and the method can comprise the steps: receiving first alarm information reported by a first camera device, and the first alarm information comprises a first alarm video; performing multi-modal feature extraction on the first alarm video to generate a first multi-modal feature vector; and based on the first multi-modal feature vector and a decision matching object, generating a push decision of the first alarm information, the decision matching object being determined according to a labeled visual sample uploaded by the client, and the labeled visual sample being obtained by labeling a visual sample by a user at the client. In this way, more accurate alarm content which better conforms to the expectation of the user can be provided.

The invention discloses a space computing power network task migration method and system based on dynamic environment perception, and relates to spaceflight electronics and data processing technologies, and the method comprises the steps: determining that a user node obtains a computing resource needed by a computing power service from a satellite node in a space computing power network; calculating a task migration moment caused by satellite node movement and an alternative satellite set capable of receiving tasks according to the dynamic environment information; based on a candidate satellite set, an optimal satellite is screened out according to different user expected targets, before the migration moment arrives, a calculation task is migrated to the selected satellite in advance, and seamless continuity of services is guaranteed; and for the high-priority task, carrying out redundancy migration on the alternative scheme without computing resource intersection. According to the method, the problems of low efficiency, service interruption caused by sudden faults, multi-target optimization conflicts, resource shortage scene migration failure and the like of a traditional migration algorithm in a spatial network topology dynamic scene can be effectively solved.

The invention relates to the technical field of advertisement design, and discloses an AI virtual human interaction method and system, and the method comprises the steps: receiving original demand data inputted by a user, generating a brand feature vector, and generating first virtual human data, first line data and first product model data based on the brand feature vector; and performing cooperative adjustment based on the ith interaction instruction to generate a virtual human image. By implementing the method and the system, the functions of full-process intelligent design, data processing, collaborative generation, interactive response, scene adaptation and the like are improved, an efficient and complete virtual human image customization scheme is formed, and the problem that multi-source heterogeneous data are difficult to comprehensively analyze when user requirements are processed by a traditional method is solved. The problems of large deviation between generated content and user expectation and poor scene adaptability caused by lack of a collaborative adjustment mechanism of a virtual human image, lines and a product model, low processing efficiency of a modification instruction and incapability of ensuring cross-modal consistency in the prior art are solved.

The invention belongs to the technical field of big data processing, and discloses an operation and maintenance data management platform based on generative artificial intelligence, which comprises an operation and maintenance data storage unit, an interaction unit, a display unit, an external field working efficiency evaluation unit and a contract operation and maintenance evaluation unit, according to the method, the user intention is analyzed through the generative model and the thinking chain, and the data source through which the user demand needs to be answered is judged, so that the problems of overlong reply time, overlarge calculation amount and excessive system resource consumption caused by searching a large amount of invalid reference data are avoided; and a more specific and accurate information retrieval result and a final reply result conforming to the expectation of the user are obtained. According to the embodiment, the stability and the operation efficiency of the system are greatly improved.

The invention provides an adaptive test case generation method and system based on a large model, and the method comprises the steps: calling a pre-constructed cue word generation agent in response to an instruction for generating a test case, and generating a matched target cue word and a recommended target test case generation model based on data input by a user; generating a first test case based on the target cue word by using the target test case generation model; displaying the first test case, and obtaining a first label input by a user for the displayed first test case; the target test case generation model is called, a second test case is generated in combination with the user intention and the first test case, and the matching degree of the second test case and the test case expected by the user is higher than the matching degree of the first test case and the test case expected by the user.

The present disclosure relates generally to systems and methods for updating an input prompt for a generative AI model (e.g., an LLM) based on feedback that is provided in connection with an output from the generative AI model that is unsatisfactory. For example, where a user indicated that an output from the generative AI model is incorrect, inaccurate, or is an otherwise unsatisfactory response to an input prompt, this disclosure describes models to facilitate generation of feedback hints and / or additional information that can be included within an updated prompt that, when provided as an input to the generative AI model, has an improved likelihood to return an output that is in-line with user expectations. Indeed, features of the systems and methods described herein provide a framework for improving outputs of generative AI models that are more accurate or otherwise responsive to the input prompts.

The embodiment of the invention provides a text generation method and device, equipment, a medium and a program product. The method comprises the following steps: displaying an original text and a first control in a first page; in response to a trigger operation of the first control, displaying a second page, the second page comprising at least one candidate title corresponding to the original text; in response to a trigger operation of a target title in the at least one candidate title, displaying content key points of at least one hierarchy of the target title, the content key points of the at least one hierarchy representing nodes of different depths of a hierarchical stacking structure corresponding to the target title; and in response to a selection operation of the candidate titles and the content key points, generating a target text based on the selected candidate titles and the selected content key points. According to the embodiment of the invention, the text meeting the expectation of the user can be efficiently and accurately generated, and the problem that the text meeting the expectation is difficult to accurately generate based on creative inspiration is solved.

The invention relates to the field of vehicles, and provides a vehicle-mounted man-machine interaction method, a vehicle-mounted man-machine interaction device and electronic equipment aiming at the problem of how to enable a vehicle-mounted terminal to accurately respond to the intention of a user and realize an application function expected by the user. The method comprises the steps that any one or a combination of more of vehicle data, driver data and environment and context data serves as a data source, a semantic text sequence is obtained according to the data source, and the semantic text sequence comprises one or more feature texts; the feature text is used for describing any one or a combination of more of a vehicle feature, a driver feature, an environment feature and a context feature, and the feature text is a text character string described by referring to a natural language; taking the semantic text sequence as the input of an intelligent model, and obtaining a prediction result output by the intelligent model; and calling the corresponding application service according to the prediction result. According to the method provided by the embodiment of the invention, the prediction accuracy of the intelligent model can be improved, and the user experience of man-machine interaction is improved.

The invention provides a perceptual engineering-based vehicle body selection design method. The perceptual engineering-based vehicle body selection design method comprises the following steps of: acquiring vehicle body data and comment information of a whole vehicle from data permitted to be accessed; analyzing and sorting the obtained comment text data by using a natural language processing technology to form a database; collecting user expectations, and performing semantic reasoning and analysis on the collected user expectations based on the formed database to obtain product performance semantic weights of the user expectations; and performing quantitative matching on the obtained product performance semantic weight expected by the user and the obtained vehicle body data by using the perceptual engineering model, and determining the vehicle body data corresponding to the vehicle model most conforming to the user expectation. And finally, the product with the highest customer expectation score is determined to correspondingly obtain the target product, the designed optimal product scheme is determined, and the vehicle body design efficiency and reliability are improved.

This application provides a model training method, training system, and related equipment. The method includes the following steps: acquiring positive sample data, wherein the positive sample data includes input samples and positive labels, the input samples include questions, and the positive labels include the answers corresponding to the questions; inputting the input samples into a first large model to be fine-tuned, obtaining the first negative label corresponding to the input sample; determining the first score of the first negative label based on the relevance of the first negative label to the question and the quality of the response to the first negative label based on a scoring model; inputting the input samples into the first large model; and fine-tuning the first large model based on a loss function to obtain a second large model. The loss function is used to guide the first large model to improve the prediction probability of positive labels and the prediction probability of negative labels with scores greater than a threshold, so that the model can not only learn standard answers that meet user expectations, but also generate more diverse answers, thereby improving the fine-tuning effect of the large model.

Disclosed are an online talk game method and system in which a plurality of users interacts and match composition rates by sharing opinions. A server unit announces a talk topic and receives and announces opinions of the users. The server unit receives the user's answer to the question and the expecting rate, calculates the composition rate of the answer, and determines that the smaller a difference between the composition rate and the user's expecting rate, the more advantageous it is, and the larger the difference, the more disadvantageous it is. This talk game can provide an interactive game that allows users to become immersed when a large number of users participate in the talk game, and prevent many ties, prevent collusion between the users, and reduce user confusion.

The invention relates to the field of terminals, in particular to a video generation method, electronic equipment and a computer readable storage medium. The method comprises the steps that when a user instruction is monitored, first character information contained in the user instruction is recognized; obtaining a confidence coefficient corresponding to the first character information, wherein the confidence coefficient is used for representing a credibility degree of an identified character; if it is determined that a figure confirmation process is executed according to the confidence coefficient corresponding to the first figure information, confirming a figure corresponding to the first figure information to obtain a confirmation result; and generating a video according to the confirmation result. Through the method, the problem that the generated video does not conform to user expectation due to inaccurate material acquisition in the prior art is solved.

The invention discloses an LLM Agent task execution method and device and electronic equipment. The method comprises the following steps: S1, identifying a user role; s2, task planning and interaction point configuration; s3, performing active interaction execution; and S4, dynamically adjusting the execution path. According to the method, interaction can be actively initiated at key nodes, an execution strategy is dynamically optimized, personalized interaction experience is provided, task execution efficiency is effectively improved, the risk that an execution result deviates from user expectation is reduced, and system availability and user satisfaction are improved.

The invention relates to a man-machine interaction method and device, computer equipment, a storage medium and a computer program product. Relates to the technical field of cloud computing. The method comprises the steps of receiving a current interaction task input by a user, and obtaining historical interaction information of the user; detecting the similarity between the current interaction task and each historical interaction task of the user; if a target historical interaction task of which the similarity is greater than or equal to a preset threshold value is detected, obtaining a target tool calling list of the target historical interaction task; inputting the current interaction task, the target tool calling list and the user information into a large language model to obtain a first tool calling list for executing the current interaction task; according to the input parameters and the calling sequence of all the tools in the first tool calling list, tool calling operation is executed, and a response result of the current interaction task is obtained. By adopting the method, the targeted content matched with the user expectation can be generated.

The invention provides a driving style configuration method, a model training method, a data processing method, devices and equipment. Relates to the technical field of intelligent driving. The method comprises: acquiring style configuration information of the autonomous mobile device (S201), acquiring a target driving style based on the style configuration information (S202), and configuring the driving style of the autonomous mobile device based on the target driving style (S203). According to the method, the preference and demand of the user can be identified through the style configuration information, so that the driving style meeting the expectation of the user is configured, and the user experience is improved.

The application discloses an intelligent AI marketing data management system based on a global member system, relates to the technical field of data management, and comprises a historical information collection module, a marketing group correlation module, a portrait deviation prediction module and a marketing real-time pushing module. The historical information collection module is used for generating corresponding marketing logs, collecting characteristic data generated by users and obtaining user portraits. The marketing group correlation module is used for analyzing the correlation between different user groups, analyzing the marketing data differences of different marketing logs and obtaining the correlation between different marketing types. The portrait deviation prediction module is used for analyzing the portrait deviation of users, making predictive adjustment and obtaining expected user portraits. The marketing real-time pushing module is used for generating corresponding real-time marketing logs in real time, making real-time prediction on the expected demands of users and providing corresponding personalized marketing recommendations for users.

This application relates to the field of vehicle-related technology and discloses a parking method, apparatus, device, and vehicle based on voice interaction. The method includes: responding to a user's voice parking command and extracting parking constraints; the parking constraints include at least one of parking area, parking location attribute features, and parking method, each parking constraint including positive and / or negative requirements; while the vehicle is driving in the parking lot, sensing environmental information around the vehicle and obtaining multi-dimensional environmental features of available parking spaces; the multi-dimensional environmental features include at least the area and location attribute features; filtering available parking spaces based on the multi-dimensional environmental features according to the priority of the parking constraints, and controlling the vehicle to park in the available parking space when a parking space that meets the parking constraints is selected. Applying the solution of this application can solve the problems of existing automatic parking systems failing to understand users' personalized parking needs and resulting in parking results that do not meet user expectations.

The application relates to the technical field of screen display, and discloses a menu option display method and device for a smart electric meter, which comprises the following steps: based on a first keyword set input by a user, determining a number identification code and a first display item code; generating a first request based on the number identification code and the first display item code and sending the first request to the smart electric meter; when a second keyword set input by the user is received, determining a second display item code based on the second keyword set; and generating a second request based on the second display item code and a preset instruction code and sending the second request to the smart electric meter. The display item code is determined based on the keyword set input by the user, and then a request is generated, so that the request is sent to the smart electric meter to make the displayed menu options consistent with the user's expectation, the adjustment of the menu options displayed by the smart electric meter is realized, the personalized demand of the user for the menu options is met, and a large amount of manpower and material resources are saved.

The present disclosure provides a method for optimizing large language model conversation, including: in response to entering a current conversation turn, acquiring configuration information corresponding to the current conversation turn based on a type of the current conversation turn; acquiring user input information corresponding to the current conversation turn; determining whether the current conversation turn needs to be switched based on a conversation turn switching determination strategy corresponding to the conversation turn switching strategy configuration information; when the current conversation turn needs to be switched, determining a next conversation turn corresponding to the current conversation turn, and entering the next conversation turn; when the current conversation turn does not need to be switched, generating a response task, and performing the response task calling a large language model to generate a response message; and outputting the response message in the current conversation turn, to meet user expectations.

The present invention discloses an intelligent industrial design measurement and control device and method of application. The key points of the technical solution include the construction and application of an AIGC agile industrial design model, a human-machine collaborative design process, the construction of an application paradigm for industrial product generation scenarios, model optimization decisions based on cognitive analysis, and application case studies and verification. The AIGC model significantly improves design efficiency and innovation by rapidly generating and optimizing design solutions. Through precise demand analysis and optimization decisions, it ensures that the design solution is highly consistent with user expectations, thereby improving user satisfaction. Agile design methods and multiple iterative optimizations ensure that the design process is efficient and accurate, and improve design quality and reliability. Rapid generation and optimization of design solutions effectively shortens the product development cycle, thereby improving the company's market response speed and competitiveness.

This application provides a voice control method, apparatus, device, system, storage medium, and program product. On one hand, voice control based on user expectations offers a novel voice control mode. Users can express their personalized needs by conveying their expected physical or emotional feelings, thereby enabling automatic device control. This achieves intelligent and flexible voice control, embodies a technological feel, and satisfies users' personalized needs. On the other hand, after generating control commands based on voice data including information related to the user's expected feelings, the accuracy of the control commands is determined. If the commands are accurate, home appliances are controlled according to the commands. This significantly reduces the possibility of misoperation, ensures the alignment of executed control commands with the user's actual intentions, and further guarantees a superior user experience.