LivePerson had 29 patents in artificial intelligence during Q2 2024. LivePerson Inc’s patents in Q2 2024 focus on artificial intelligence-based formatting of data for different interfaces, managing voice connections between devices and automated services, automatically establishing recording parameters and generating analytics for recorded communications, implementing dynamic-action systems in real-time data streams, and providing recommendations for improving conversations between users and agents. GlobalData’s report on LivePerson gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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LivePerson had no grants in artificial intelligence as a theme in Q2 2024.
Recent Patents
Application: Methods and systems for implementing a unified data format for artificial intelligence systems (Patent ID: US20240211477A1)
LivePerson Inc. has developed a system and method for artificial intelligence-based formatting of data into interface-specific representations. The system involves receiving datasets structured for various interfaces, training a machine-learning model using feature vectors from the datasets to generate interface-specific representations, and executing the model to respond to queries through a specific interface. The model tailors the response structure to match the interface type, ensuring accurate and efficient communication.
The patent claims detail the method and system's steps, including receiving datasets, defining feature vectors, training the machine-learning model, and facilitating responses tailored to specific interface types. The claims also cover scenarios where the dataset includes audio segments, the interface types correspond to textual communications, text messaging, or webpages, and the feature vectors capture source interface features. Additionally, the patent includes provisions for receiving input on response accuracy, generating feature vectors for model modification, and enhancing response accuracy metrics. Overall, LivePerson Inc.'s patent focuses on optimizing data presentation across different interfaces through machine learning and tailored responses, enhancing user experience and communication efficiency.
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