Artificial intelligence (AI) informed by compromised data can lead soldiers into contested territory, flag an innocent civilian as dangerous or prevent a passenger jet from landing safely. Machine learning at the edge requires big data processing and actionable, real-time intelligence, but data in the field can be lost, stolen or exploited. Mercury Systems and Intel are working together to design secure AI edge solutions to protect data and machine learning in the field.
Join us to discover more about:
- The importance of data and model quality
- Types of data bias and why data integrity is critical
- Model and data security techniques for learning assurance
- Strengthening edge cybersecurity with built-in hardware security
- Solutions that enable certification of Intel multi-core processors
