Research Challenges for Combined Autonomy, AI, and Real-Time Assurance
- Resource Type
- Conference
- Authors
- Abdelzaher, Tarek; Baruah, Sanjoy; Gill, Chris; Vorobeychik, Eugene; Zhang, Ning; Zhang, Xuan
- Source
- 2021 IEEE Third International Conference on Cognitive Machine Intelligence (CogMI) COGMI Cognitive Machine Intelligence (CogMI), 2021 IEEE Third International Conference on. :163-167 Dec, 2021
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Robotics and Control Systems
Conferences
Mission critical systems
Real-time systems
Timing
Safety
Artificial intelligence
Machine intelligence
autonomy
AI
ML
neural networks
real-time
- Language
Advances in machine intelligence revolutionized a broad category of safety-critical and mission-critical applications, but important challenges remain when applying these solutions at the embedded network edge, as opposed to resource-rich contexts. What challenges stem from deploying cost-sensitive applications on lower-end devices to offer AI at the point of need? We present an overview of key research challenges that must be addressed to provide assurance of timing and other safety properties for resource-constrained systems involving autonomy and artificial intelligence on-line. We then describe a vision and agenda for research targeting those challenges.