Unexpected weather events can happen. It’s vital however, that they do not negatively impact AI missions.
It is common for ML models to fail when faced with fog, rain, snow, and more. The challenge is ensuring that these models are robust against these conditions. Testing and validating models will ensure the models stand up against these adverse weather conditions.
How VESPR Validate Drives Mission Success
A variety of conditions
A series of tests are provided to benchmark your ML model’s ability to make correct predictions despite weather obstructions of varying intensities.
Built for your use case
Stakeholders can test against the conditions where the model will be deployed; not wasting time on snow when the model will be used indoors, for example.
Clear results and informed decision-making
Based on test results presented in plain language, stakeholders can decide whether to deploy the models to production.
Widespread confidence in Mission Success
Accelerate trust that models will perform against sudden weather changes, or identify the need to further retrain models in order to deploy with confidence.