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Abhijeet Goel

10 Tests for your AI/ML/DL model

CTO, testAIng.com In recent past there has been a spate of accidents involving AI and Machine learning models in practice and deployment. Much so that there is an active database of all such accidents being chronicled (https://incidentdatabase.ai/ ). At a time when AI is making strides in radical

Why current testing processes in AI/ML are not enough?

The current notions of quality assurance and testing in AI/ML pipelines is based on the idea of validation using a random set-aside set of data on which the model is tested and metrics computed thereof. Metrics like accuracy on the random set-aside data set termed ambiguously as test data,

Why we need to let go of our programming instinct in ML based AI?

Why we need to let go of our programming instinct in ML based AI?

In the modern world of software we are used to the paradigm of software engineering. The discipline of software engineering is predicated upon following a rigid regimen of quality programming, with deployment of expert coders and programmers to enable building of systems. Hence, a basic necessity often stressed is that

Why AI is required to have explainability?

In today s world of machine learning dominated Artificial Intelligence applications, there is a renewed push for the agenda of explainability. The triggers for explainability could be multifold: * A comfort feeling of knowing what you are handing over control to * A knowledge of the influence of the precise input component