The Industry-GPT 2.0 is a cutting-edge large model product, pretrained on an extensive corpus of industry knowledge encompassing both text and images. Industry-GPT 2.0 is designed to revolutionize the industrial landscape by offering a suite of advanced functions. The Agent function synergizes with SMore ViMo, enabling the automatic completion of model selection and training processes via conversation, streamlining operations and enhancing efficiency. The Multi-Modal Conversation feature facilitates seamless interactions, including image description and generation, fostering intuitive communication and problem-solving. Additionally, Industry-GPT 2.0 boasts capabilities for controlling equipment like robotic arms to perform complex tasks, driving automation to new heights.
By leveraging Industry-GPT 2.0, industries can rapidly implement comprehensive model training, software integration, and production line deployment without requiring the expertise of professional algorithm personnel. This significantly lowers the barrier to adopting intelligent applications in the manufacturing sector, providing robust, inclusive, and intelligent capabilities that empower the entire industry ecosystem.
ViMo Agent, leveraging our proprietary IndustryGPT, drives the ViMo platform to analyze image defects, create corresponding algorithm solutions, and dynamically adjust parameters based on user-defined criteria.
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Scenario 1: Automated Defect Analysis and Algorithm Creation
ViMo Agent uses IndustryGPT's multimodal capabilities to analyze defects in images and generate corresponding algorithm solutions. For instance, in a consumer electronics quality inspection, ViMo Agent can inspect images of USB ports for scratches or improper connections.
By understanding the image context and correlating visual data with potential defects, ViMo Agent creates precise algorithms and selects suitable models, enhancing accuracy and reducing development time.
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Scenario 2: Dynamic Algorithm Parameter Tuning
ViMo Agent dynamically adjusts algorithm parameters based on user-defined criteria such as detection metrics, hardware constraints, and cycle time requirements.
In an automotive parts inspection, users set specific detection metrics, and ViMo Agent will iteratively adjust parameters to meet these criteria. This real-time optimization ensures the inspection process is efficient and accurate, saving users from manual tuning.
