17818852. Interactive Graphical User Interfaces for Deployment and Application of Neural Network Models using Cross-Device Node-Graph Pipelines simplified abstract (GOOGLE LLC)
Contents
- 1 Interactive Graphical User Interfaces for Deployment and Application of Neural Network Models using Cross-Device Node-Graph Pipelines
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 Interactive Graphical User Interfaces for Deployment and Application of Neural Network Models using Cross-Device Node-Graph Pipelines - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Original Abstract Submitted
Interactive Graphical User Interfaces for Deployment and Application of Neural Network Models using Cross-Device Node-Graph Pipelines
Organization Name
Inventor(s)
Ruofei Du of San Francisco CA (US)
Jing Jin of Mountain View CA (US)
Maria Mandlis of Vancouver (CA)
Scott Joseph Miles of American Canyon CA (US)
Interactive Graphical User Interfaces for Deployment and Application of Neural Network Models using Cross-Device Node-Graph Pipelines - A simplified explanation of the abstract
This abstract first appeared for US patent application 17818852 titled 'Interactive Graphical User Interfaces for Deployment and Application of Neural Network Models using Cross-Device Node-Graph Pipelines
Simplified Explanation
The method described in the patent application involves providing an interactive graphical user interface with menus for input options, machine learning models, and output formats. Users can select options from each menu to generate a graph that displays nodes and edges representing the selected choices. The machine learning model is then applied to the input data to produce an output in the chosen format.
- Interactive graphical user interface with menus for input options, machine learning models, and output formats
- Selection of options from each menu to generate a graph displaying nodes and edges
- Application of machine learning model to input data to generate output in chosen format
Potential Applications
- Data analysis and visualization
- Machine learning model selection and application
- Report generation and presentation
Problems Solved
- Simplifying the process of selecting and applying machine learning models
- Providing a user-friendly interface for data analysis and visualization
- Streamlining the generation of reports and outputs
Benefits
- Improved efficiency in selecting and applying machine learning models
- Enhanced user experience in data analysis and visualization
- Faster and more accurate report generation and output presentation
Original Abstract Submitted
A method includes providing an interactive graphical user interface comprising a first menu providing one or more input options, a second menu providing one or more machine learning models, and a third menu providing one or more output formats. The method also includes generating a graph in a portion of the interactive graphical user interface by detecting one or more user selections of an input option, a machine learning model, and an output format, displaying nodes corresponding to the input option, the machine learning model, the output format, and displaying edges connecting the first node to the second node, and the second node to the third node. The method additionally includes applying the machine learning model to an input associated with the input option to generate an output in the output format. The method further includes providing, by the interactive graphical user interface, the output in the output format.
