Jeremias Rößler, founder of ReTest, discusses his company’s open source re-check tool, how customer input was vital to the tool’s development, and shares insight on growing a start-up. Jeremias also provides resources for learning about AI that can guide you on how to apply AI into your testing strategy.
Testing artificial intelligence- and machine learning-based systems presents two key challenges. First, the same input can trigger different responses as the system learns and adapts to new conditions. Second, it tends to be difficult to determine exactly what the correct response of the system should be. Such system characteristics make test scenarios difficult to set up and reproduce and can cause us to lose confidence in test results. Yury Makedonov will explain how to test AI/ML-based systems by combining black box and white box testing techniques. His "gray box" testing approach leverages information obtained from directly accessing the AI’s internal system state. Yury will demonstrate the approach in the context of testing a simplified ML system, then discuss test data challenges for AI using pattern recognition as an example and share how data-handling techniques can be applied to testing AI.
AI is here. Will it take over your job? Is it possible to make it beneficial, not detrimental to your career? Kevin Pyles and his team jumped right into the AI universe. Untrained and inexperienced, they realized immediately that they knew nothing.
The machine learning age is well underway. Today’s software can see novel patterns that humans are unable to see and improve task performance based on experience. Learning algorithms are widely used for varied purposes, including loan approval, intrusion detection, fraud prevention, risk...