How do you safely integrate AI/ML into embedded systems where every byte, millisecond, and decision counts? In safety-critical industries like autonomous vehicles, aerospace, and healthcare, AI and machine learning promise incredible innovation—but they also introduce new regulatory, performance, and reliability challenges.
In this expert-led webinar, we explore how to safely deploy AI/ML models in embedded environments, where precision and compliance are essential. Learn about real-world strategies and tools that can help ensure AI behavior remains predictable, explainable, and certifiable—even in the most resource-constrained systems.
📌 Key topics covered:
• The evolution of embedded systems through AI/ML integration
• Safety risks and resource limitations in critical deployments
• Breakthroughs in model optimization (e.g. pruning, quantization, freezing)
• How to meet standards like ISO 26262 and IEC 62304
• Ensuring predictable AI behavior for functional safety
🎯 Whether you're building smart medical devices, automotive ADAS, or aerospace systems, this session will help you build safer, more efficient, and certifiable AI-powered products.
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About Parasoft
Parasoft helps organizations continuously deliver quality software with its market-proven, integrated suite of automated software testing tools. Supporting the embedded, enterprise, and IoT markets, Parasoft’s technologies reduce the time, effort, and cost of delivering secure, reliable, and compliant software by integrating everything from deep code analysis and unit testing to web UI and API testing, plus service virtualization and complete code coverage, into the delivery pipeline. Bringing all this together, Parasoft’s award winning reporting and analytics dashboard delivers a centralized view of quality enabling organizations to deliver with confidence and succeed in today’s most strategic ecosystems and development initiatives — security, safety-critical, Agile, DevOps, and continuous testing
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