ADOBE had 214 patents in artificial intelligence during Q4 2023. ADOBE Inc’s patents filed in Q4 2023 cover a range of technologies including user representation generation, text processing, font recommendation, node embeddings for multiple roles in graphs, and image search and modification processes. These patents showcase ADOBE‘s innovation in machine learning, natural language processing, and image processing technologies. GlobalData’s report on ADOBE gives a 360-degreee view of the company including its patenting strategy. Buy the report here.
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ADOBE grant share with artificial intelligence as a theme is 45% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Generating concise and common user representations for edge systems from event sequence data stored on hub systems (Patent ID: US20230419339A1)
The patent filed by ADOBE Inc. describes a system that includes a representation generator subsystem capable of generating a user representation by executing a user representation model and a task prediction model. This user representation is a vector of a predetermined size that represents user event sequence data, such as user interactions with the system, and is stored in a data store with a lower storage requirement than the original event sequence data. The system can utilize different types of learning models, such as task-specific, multitask, or task-agnostic models, to generate these user representations efficiently.
Furthermore, the patent includes claims for a system, a non-transitory computer-readable medium, and a method for executing the user representation model, generating user representations, and storing them in user profiles. The claims cover various aspects of the system, including the use of specific learning models like task-specific or multitask models, the structure of the user representation model (e.g., two-layered LSTM network or autoencoder network), and the types of user interactions considered for generating the user representations. Overall, the patent focuses on optimizing storage space requirements by generating compact user representations while maintaining the necessary information from user event sequence data.
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