AI MODEL OPTIMIZATION
Optimize Source Content Using
AI Model Diagnostics
Analyze validation data to understand neural network weights and biases to address AI ethical concerns and support trust.
SPEAK WITH AN EXPERTEvaluate and Modify Training Content
The topic of AI ethics with concerns of bias in neural networks has prompted the call for effective AI governance.
Accurate model diagnostics that support AI accountability within a larger AI governance framework will enable organizations to:
- Remove protected, erroneous, or low-performing content effects
- Detect performance degradation
- Identify unwanted anomalies based on set thresholds and alerts
- Pinpoint corresponding input stimulus and source training content within the data set
- Mitigate unwanted effects or output results by removal or modification from the AI model
- Continuously optimize and improve results
"Now we have the ability to correct past mistakes or the inclusion of unwarranted, undesirable, or irrelevant content effects from the AI without expensive and time-consuming removal of all subsequent training content."
John E. Derrick
CEO, Authentrics.ai
DISCOVER AI GOVERNANCE SOFTWARE
Measure, adjust, and continuously optimize AI/ML source content to deliver superior output.
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