System

A system comprising:

• circuitry configured to:
• receive, via a communication interface coupled to a packet-switched network, input data from a terminal device, determine a data type, and perform preprocessing comprising missing-value completion, normalization, and encoding to generate preprocessed data;
• input the preprocessed data to a machine learning model executed by a parallel computation device comprising a graphics processing unit, distribute computation across a plurality of threads, and perform data analysis processing comprising at least one of feature extraction, classification, prediction, or anomaly detection;
• acquire a prompt sentence from the terminal device, execute task-interpretation processing to specify a target attribute, an analysis task, and an output format, and dynamically select or configure the machine learning model or an analysis algorithm based on the task-interpretation processing;
• execute a generative neural network model comprising a transformer-based architecture using the prompt sentence, the analysis result, and metadata as inputs, and generate natural-language explanation information comprising a summary, a rationale, and a commentary;
• generate visualization data comprising at least one of list information, statistical information, graph information, region-highlighting information, or annotation information, and transmit a notification data packet comprising the visualization data and the natural-language explanation information to the terminal device;
• and
• execute information-protection processing comprising at least encryption and access control for the input data and the analysis result.

A method comprising:

• receiving, via a communication interface coupled to a packet-switched network, input data from a terminal device and storing the input data in a storage device;
• determining a data type of the input data, performing preprocessing on the input data comprising at least missing-value completion, normalization, and encoding to generate preprocessed data;
• inputting the preprocessed data to a machine learning model executed by a parallel computation device, and performing data analysis processing comprising at least one of feature extraction, classification, prediction, or anomaly detection;
• acquiring a prompt sentence in natural language from the terminal device, and executing task-interpretation processing that specifies at least one of a target attribute, an analysis task, or an output format of the data analysis processing based on contents of the prompt sentence;
• executing a generative neural network model using the prompt sentence, a result of the data analysis processing, and related metadata as inputs, and generating natural-language explanation information comprising at least a summary, a rationale, and a commentary regarding the analysis result;
• and
• generating visualization data based on the result of the data analysis processing and the natural-language explanation information, and transmitting a notification data packet comprising the visualization data to the terminal device via the communication interface.