Abstract: 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 are provided. The apparatus includes: a production line executor configured to generate a native form of the artificial intelligence development platform based on a 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.

Abstract: Methods, systems, and devices for memory system logical unit number (LUN) procedures are described. A memory system may receive an indication to convert a LUN for storing LBAs associated with an application from a first type to a second type, where the second type is associated with a higher performance defragmentation process than the first type. The memory system may perform defragmentation on data associated with the LUN based on converting the LUN to the second type. The memory system may determine whether the LBAs stored in the LUN are ordered based on the defragmentation, and the memory system may operate (e.g., execute) the application based on the LBAs being ordered.

Abstract: The present disclosure provides a human-machine interactive method based on artificial intelligence and a human-machine interactive device based on artificial intelligence. The method includes: receiving a query from a user; processing the query based on a pre-generated model, and obtaining an answer with a human conversation style corresponding to the query, wherein the model is generated based on a human conversation corpus; and feeding back the answer to the user.

Abstract: A method of recommending data, a device, and a medium, which relate to a field of an artificial intelligence technology, in particular to fields of deep learning, natural language processing and intelligent recommendation technologies. The method of recommending the data includes: acquiring operation data of an operation object, and the operation data is associated with first content data and first target object data; determining an operation object feature, a content feature and a target object feature based on the operation data; determining a fusion feature based on the operation object feature and the content feature; and recommending second content data and second target object data in an associated manner based on the fusion feature and the target object feature.

Abstract: 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 are provided. The apparatus includes: a production line executor configured to generate a native form of the artificial intelligence development platform based on a 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.

Abstract: The present disclosure provides a translation processing method, a translation processing device, and a device. The first speech signal of the first language is obtained, and the speech feature vector of the first speech signal is extracted based on the preset algorithm. Further, the speech feature vector is input into the pre-trained end-to-end translation model for conversion from the first language speech to the second language text for processing, and the text information of the second language corresponding to the first speech signal is obtained. Moreover, speech synthesis is performed on the text information of the second language, and the corresponding second speech signal is obtained and played.

Abstract: Embodiments of the present disclosure disclose a text translation method, a text translation apparatus, a device and a storage medium. The method includes: obtaining a source language text; and translating the source language text with a modified translation model to obtain a target language text corresponding to the source language text, the modified translation model being obtained by modifying an original translation model based on a text evaluation result of one or more translated texts for training, the translated text for training being an output result after translating through the original translation model, and the text evaluation result for evaluating a contextual semantic relation in the translated text for training.

Abstract: Embodiments of the present disclosure disclose a text translation method, a text translation apparatus, a device and a storage medium. The method includes: obtaining a source language text; and translating the source language text with a modified translation model to obtain a target language text corresponding to the source language text, the modified translation model being obtained by modifying an original translation model based on a text evaluation result of one or more translated texts for training, the translated text for training being an output result after translating through the original translation model, and the text evaluation result for evaluating a contextual semantic relation in the translated text for training.

Abstract: The present disclosure provides a translation processing method, a translation processing device, and a device. The first speech signal of the first language is obtained, and the speech feature vector of the first speech signal is extracted based on the preset algorithm. Further, the speech feature vector is input into the pre-trained end-to-end translation model for conversion from the first language speech to the second language text for processing, and the text information of the second language corresponding to the first speech signal is obtained. Moreover, speech synthesis is performed on the text information of the second language, and the corresponding second speech signal is obtained and played.

Abstract: The present disclosure provides a human-machine interactive method based on artificial intelligence and a human-machine interactive device based on artificial intelligence. The method includes: receiving a query from a user; processing the query based on a pre-generated model, and obtaining an answer with a human conversation style corresponding to the query, wherein the model is generated based on a human conversation corpus; and feeding back the answer to the user.

Abstract: Proposed are a method and device for constructing an event knowledge. The method comprises: identifying text to obtain an event mining candidate sentence; dividing the event mining candidate sentence into syntax fragments; generating an event knowledge instance according to the syntax fragments and a preset event knowledge construction, in which the number of the event knowledge instances is equal to the number of verb-object fragments and subject-predicate fragments in the syntax fragments; obtaining an event mining target sentence according to the verb-object fragments and the subject-predicate fragments in the syntax fragments, dividing the event mining target sentence, and writing divided members into an event knowledge instance correspondingly, so as to accomplish construction of the event knowledge base.

Abstract: The present disclosure provides a human-computer intelligence chatting method and device. The method includes: receiving a multimodal input signal, the multimodal input signal comprising at least one of a speech signal, an image signal, a sensor signal and an event driving signal; processing the multimodal input signal to obtain text data, and obtaining an intention of a user according to the text data; obtaining an answer corresponding to the intention of the user, and converting the answer to a multimodal output signal; and outputting the multimodal output signal.

Abstract: Proposed are a method and device for constructing an event knowledge. The method comprises: identifying text to obtain an event mining candidate sentence; dividing the event mining candidate sentence into syntax fragments; generating an event knowledge instance according to the syntax fragments and a preset event knowledge construction, in which the number of the event knowledge instances is equal to the number of verb-object fragments and subject-predicate fragments in the syntax fragments; obtaining an event mining target sentence according to the verb-object fragments and the subject-predicate fragments in the syntax fragments, dividing the event mining target sentence, and writing divided members into an event knowledge instance correspondingly, so as to accomplish construction of the event knowledge base.

Abstract: This invention relates to a method of regulating apoptosis and/or proliferation in a cell, the method including the step of altering the expression and/or function in the cell of polypeptides based on Apoptosis Related Basic Protein.