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公开(公告)号：EP4280051A1
公开(公告)日：2023-11-22
申请号：EP22204121.2
申请日：2022-10-27
发明人： YUAN, Zhengxiong , CHU, Zhenfang , LI, Jinqi , HU, Mingren , WANG, Guobin , LUO, Yang , HUANG, Yue , QIAN, Zhengyu , SHI, En
摘要： The present disclosure provides an inference service deployment method and apparatus, a device and a storage medium, relating to the field of artificial intelligence technology, and in particular to the field of machine learning and inference service technology. The specific implementation scheme provides an inference service deployment method, including: obtaining (S101) performance information of a runtime environment of a deployment end; selecting (S 102) a target version of an inference service from a plurality of candidate versions of the inference service of a model according to the performance information of the runtime environment of the deployment end; and deploying (S103) the target version of the inference service to the deployment end. The present disclosure can improve deployment efficiency of the inference service.
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2.发明公开
公开(公告)号：EP4258193A1
公开(公告)日：2023-10-11
申请号：EP23163131.8
申请日：2023-03-21
发明人： LIU, Mengyue , ZHANG, Haibin , ZHAO, Penghao , LI, Shupeng , SHI, En
IPC分类号： G06Q10/0635
摘要： The present disclosure provides a method and apparatus for predicting a risk, and relates to the technical fields of knowledge graphs, machine learning, etc. A specific implementation is: determining an inherent risk probability of a to-be-tested object; building a relationship graph between the to-be-tested object and different associated objects; determining a primary conduction probability between any two directly associated objects in the relationship graph; determining, based on the primary conduction probability between any two directly associated objects in the relationship graph and the relationship graph, a multi-level conduction probability of the to-be-tested object; and determining a target risk probability of the to-be-tested object, based on the inherent risk probability and the multi-level conduction probability of the to-be-tested object. This embodiment improves an accuracy of risk prediction.
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公开(公告)号：EP4283465A1
公开(公告)日：2023-11-29
申请号：EP22206881.9
申请日：2022-11-11
发明人： WANG, Chao , LIN, Xiangyue , LIANG, Yang , SHI, En , QIAO, Shuangshuang
摘要： Provided are a data processing method and apparatus, and a storage medium. The data processing method includes: acquiring a target directed acyclic graph, DAG, corresponding to the service processing logic of a model self-taught learning service, where the service processing logic includes execution logic for acquiring service data generated by an online released service model, execution logic for training a to-be-trained service model based on the service data, and execution logic for releasing the trained service model online; and performing self-taught learning on the to-be-trained service model according to the target DAG.
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4.发明公开
公开(公告)号：EP4105775A3
公开(公告)日：2023-02-22
申请号：EP22190846.0
申请日：2022-08-17
发明人： SHI, En , XIE, Yongkang , PAN, Zihao , LI, Shupeng , CHEN, Xiaoyu , QIAN, Zhengyu , LI, Jingqiu
摘要： Disclosed are a method, a system and an apparatus for model production, and an electronic device, which relate to a field of computer technologies, and further to a field of artificial intelligence technologies. The method includes: acquiring a related operation for model production from a user interface layer of a model production system, and determining a software platform of the model production system; acquiring a model service corresponding to the related operation by invoking an application programming interface (API) corresponding to the related operation; performing the model service by invoking local resources of the software platform with a tool of the software platform adapted to the model service, to generate a target model ; and applying the target model in a target usage scene. The method for model production has a relatively good universality and expansibility.
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5.发明公开
公开(公告)号：EP4105775A2
公开(公告)日：2022-12-21
申请号：EP22190846.0
申请日：2022-08-17
发明人： SHI, En , XIE, Yongkang , PAN, Zihao , LI, Shupeng , CHEN, Xiaoyu , QIAN, Zhengyu , LI, Jingqiu
摘要： Disclosed are a method, a system and an apparatus for model production, and an electronic device, which relate to a field of computer technologies, and further to a field of artificial intelligence technologies. The method includes: acquiring a related operation for model production from a user interface layer of a model production system, and determining a software platform of the model production system; acquiring a model service corresponding to the related operation by invoking an application programming interface (API) corresponding to the related operation; performing the model service by invoking local resources of the software platform with a tool of the software platform adapted to the model service, to generate a target model ; and applying the target model in a target usage scene. The method for model production has a relatively good universality and expansibility.
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公开(公告)号：EP4060496A3
公开(公告)日：2023-01-04
申请号：EP22188822.5
申请日：2022-08-04
发明人： YUAN, Zhengxiong , QIAN, Zhengyu , SHI, En , HU, Mingren , LI, Jinqi , CHU, Zhenfang , LI, Runqing , HUANG, Yue
IPC分类号： G06F9/50
摘要： A method for running an inference service platform, includes: determining inference tasks to be allocated for the inference service platform, in which the inference service platform includes two or more inference service groups, versions of the inference service groups are different, and the inference service groups are configured to perform a same type of inference services; determining a flow weight of each of the inference service groups, in which the flow weight is configured to indicate a proportion of a number of inference tasks to which the corresponding inference service group need to be allocated in a total number of inference tasks; and allocating the corresponding number of inference tasks in the inference tasks to be allocated to each of the inference service groups based on the flow weight of each of the inference service groups; and performing the inference tasks by the inference service group.
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公开(公告)号：EP4060496A2
公开(公告)日：2022-09-21
申请号：EP22188822.5
申请日：2022-08-04
发明人： YUAN, Zhengxiong , QIAN, Zhengyu , SHI, En , HU, Mingren , LI, Jinqi , CHU, Zhenfang , LI, Runqing , HUANG, Yue
IPC分类号： G06F9/50
摘要： A method for running an inference service platform, includes: determining inference tasks to be allocated for the inference service platform, in which the inference service platform includes two or more inference service groups, versions of the inference service groups are different, and the inference service groups are configured to perform a same type of inference services; determining a flow weight of each of the inference service groups, in which the flow weight is configured to indicate a proportion of a number of inference tasks to which the corresponding inference service group need to be allocated in a total number of inference tasks; and allocating the corresponding number of inference tasks in the inference tasks to be allocated to each of the inference service groups based on the flow weight of each of the inference service groups; and performing the inference tasks by the inference service group.
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8.发明公开
公开(公告)号：EP3968145A1
公开(公告)日：2022-03-16
申请号：EP20938507.9
申请日：2020-10-28
发明人： XIE, Yongkang , MA, Ruyue , XIN, Zhou , CAO, Hao , SHI, Kuan , ZHOU, Yu , LI, Yashuai , SHI, En , WU, Zhiquan , PAN, Zihao , LI, Shupeng , HU, Mingren , WU, Tian
IPC分类号： G06F8/20
摘要： The present disclosure relates to an apparatus and a method for executing a customized production line using an artificial intelligence development platform, a computing device and a computer readable storage medium, and relates to the technologies of artificial intelligence and cloud platform. The customized production line is an additional development process that is different from a pre-defined development process of the artificial intelligence development platform and defined by a file set. The apparatus includes: a production line executor configured to generate a native form of the artificial intelligence development platform based on the file set, the native form to be sent to a client accessing the artificial intelligence development platform so as to present a native interactive page of the artificial intelligence development platform; and a standardized platform interface configured to provide an interaction channel between the production line executor and the artificial intelligence development platform. The production line executor is further configured to generate an intermediate result by executing processing logic defined in the file set and to process the intermediate result by interacting with the artificial intelligence development platform via the standardized platform interface so as to execute the additional development process.
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