AI Model Insight Interface for Non-Technical Feature Optimization
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Solution Overview
Problem
Current systems and software solutions fail to efficiently and effectively inform users about the operations of AI/ML models, requiring complex programming and high processing power to optimize results or generate alternative scenarios, which is inefficient and inaccessible to non-technical users.
Innovation Solution
Developing user-friendly applications that allow users to optimize model features and generate alternative scenarios without coding knowledge, using a data processing system to deploy models, present features, and generate predicted datasets based on user inputs, with error handling, ranking, filtering, and graphical indicators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If users use existing systems to understand AI/ML model operations, then they can access model information, but they require complex programming knowledge and high processing power, making the system difficult to operate and inaccessible to non-technical users
Solution Approach 1:
The patent introduces a user-friendly interface as an intermediary layer between non-technical users and complex AI/ML models. This interface translates complex model operations into simple visual interactions, allowing users to query model behavior, optimize parameters, and generate scenarios without requiring programming knowledge or high processing power.
2Adaptability or versatility
If users execute models with revised input data to generate alternative scenarios, then they can explore different outcomes, but the process is highly inefficient and requires high processing power
Solution Approach 1:
The patent pre-computes and stores alternative scenarios and model responses in advance during model deployment. When users query for alternative scenarios, the system retrieves pre-computed results rather than executing the model repeatedly with revised input data, dramatically improving efficiency while maintaining scenario generation capability.
3Ease of manufacture
If users perform complex programming to generate customized code for model insight, then they can optimize model attributes, but the complexity increases the barrier to entry and reduces ease of use
Solution Approach 1:
The patent enables users to perform model customization and optimization through self-service interactions with a user-friendly interface. Users can define their own optimization criteria, select parameters to adjust, and generate customized scenarios without writing code. The system automatically handles the complex programming tasks behind the scenes, making customization accessible to non-technical users.
Data Source
AI summary
Presented herein are methods and systems for generating and executing applications that provide insights to a model's operation without requiring the user to have knowledge of coding, computer programming, or artificial intelligence machine-learning methodologies. An exemplary method includes deploying a model using input data to generate a predicted dataset; presenting indications for a plurality of applications associated with the deployed model including an configured to generate new scenarios and another application configured to optimize at least one feature; presenting a plurality of features analyzed by the model; and in response to receiving a selection of a feature of the plurality of features and a new value for the feature, executing the first application to generate a second predicted dataset using the new value.