Autonomous Multi‑Agent Scenario Generation: Leveraging specialized AI evaluators, the system generates diverse, context‑rich test scenarios automatically, enabling wide coverage of conversational ...

Cloud-based virtualization, real-time data synchronization, and scalable AI/ML deployment can modernize the testing landscape ...

Analytical AI ranks risk, flags anomalies and analyzes test failures for automation stability and defect triage, while GenAI ...

As AI transforms hardware and network infrastructures, one small thing at a time, an equally profound change is taking place in test and measurement ...

Ripple is rolling out an AI-driven security strategy for the XRP Ledger that embeds machine learning tools across the entire development lifecycle, from code review to adversarial ...

Japan’s Rakuten Mobile and Intel extended their long-standing virtualized radio access network (vRAN) work to now include AI integration, propelling ongoing work toward using AI to help manage ...

Traditional software testing can't catch AI's unpredictable failures. Here's why humans are non-negotiable.

As artificial intelligence has continued to rapidly evolve in recent years, many government agencies have started to address and deploy the tech, both at the policy level and by testing use cases with ...

The company’s Red Team simulates attacks to uncover risks before bad actors do. As soon as new AI products are released, ...

Ever wonder why your firm’s AI initiatives don’t seem to be going anywhere? Your firm might not have the right people, ...