STAREAST 2020 - ML | TechWell

STAREAST Virtual+ 2020 - ML

Thursday, May 7

Lauren Pehnke
Aquent
T9

QA for ML: Testing around the AI Black Box

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Thursday, May 7, 2020 - 11:15am to 12:15pm

There's been a lot of discussion around leveraging AI and machine learning (ML) for testing software, but seemingly less on how to test and provide QA for an AI- or ML-driven application. But Lauren Pehnke was faced with doing just that for a product that would combine natural language processing, computer vision, and image classification to drive ranked search results. She will outline the research on AI and ML she did before taking on this role, including basic vocabulary for the variants of AI involved and interesting AI "failures" to better inform what areas of the process would...

Rajni Singh
nagarro
T15

Testing Uncertainty for a Conversational AI

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Thursday, May 7, 2020 - 1:30pm to 2:30pm

Uncertainty has always been a key challenge for testers. But testing a chatbot adds a completely new level of uncertainty. There are a lot of platforms and tools available for chatbot development, but what we lack is a standardized chatbot testing strategy. The way testing is performed on chatbots differs a lot from "traditional" testing (like for an app or web portal) due to the apparent randomness of a conversation with a chatbot. From testing numerous clients' chatbots. Rajni Singh has experienced that it is impossible to anticipate all the situations that can happen during a...

Daniel Widing
ProdPerfect
T21

A Seismic Shift in Software Testing: Rise of the Machines

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Thursday, May 7, 2020 - 3:00pm to 4:00pm

Even sophisticated businesses struggle with software testing. End-to-end (E2E) testing, though vital, has remained a costly and inconsistent method of catching bugs. But there’s a light at the end of this tunnel. Advances in machine learning (ML) have increased test execution speed and stability. Now, technologies are emerging that allow machines to analyze live user traffic to produce test cases—using data to focus E2E testing on what users care about. In time, these technologies will be stitched together to allow machines to own the entire E2E testing process. This seismic shift...