US20250077794
2025-03-06
Physics
G06F40/40
The patent application details a system designed to generate textual responses from images using large language models (LLMs). It focuses on integrating image analysis with text generation, allowing users to receive coherent and contextually relevant text based on image inputs. This system addresses inefficiencies in traditional AI systems by combining image recognition with advanced language processing.
This innovation falls within the realm of LLMs, specifically their application in converting visual data into text. It leverages machine learning techniques to process images and generate human-like text responses, enhancing tasks such as translation and summarization.
Traditional AI systems often operate in silos, with separate models for image recognition and text generation. These systems lack integration, leading to limitations in generating natural language descriptions from visual data. The proposed system overcomes these challenges by merging image processing with natural language processing in a unified workflow.
The described system integrates multiple AI modules: one for retrieving and analyzing images, another for filtering content, and a third for generating text responses using LLMs. The process involves identifying features within an image, applying content filters to ensure appropriateness, and crafting a response that aligns with user profiles and past interactions. This seamless integration enhances the chatbot's ability to respond contextually to image inputs.
The system operates within a networked environment, comprising user devices connected via communication networks. Interaction clients communicate with server systems to exchange data and invoke functions. This architecture supports various services, such as message transmission and media processing, facilitating efficient data exchange and interaction across devices and platforms.