FMR had one patents in social media during Q2 2024. FMR LLC has filed a patent for using AI to generate personalized visual artifacts based on user input data, which are then integrated into communication sessions on remote computing devices. GlobalData’s report on FMR gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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FMR had no grants in social media as a theme in Q2 2024.
Recent Patents
Application: Generating customized context-specific visual artifacts using artificial intelligence (Patent ID: US20240144565A1)
The patent filed by FMR LLC describes methods and apparatuses for generating customized visual artifacts using artificial intelligence (AI) in communication sessions. The system captures input data from remote computing devices associated with users, creates visual artifacts based on this data using an AI-based generator, and integrates these artifacts into the communication session. The input data can include various types of information such as text, demographic data, health data, social media data, and more, captured during an ongoing communication session. The system can analyze video and audio data from the remote devices to generate additional input data, convert the input data for the AI generator, and create visual artifacts representative of the input data characteristics.
Furthermore, the system can dynamically change the visual artifacts during the communication session based on updates to the input data, receive feedback from remote devices to modify the input data for creating additional visual artifacts, and integrate the visual artifacts into video conferencing sessions by inserting them into virtual backgrounds or combining them into aggregate visual artifacts for multiple users. The AI-based visual artifact generator can utilize techniques such as generative adversarial networks, variational autoencoders, or autoregressive models to create synthetic images depicting the input data characteristics. Overall, the system aims to enhance communication sessions by providing context-specific visual elements tailored to individual users based on captured input data.
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