Theme:
Edge AI & Intelligent Systems
In 15 minutes from training to inference on the edge
Run the same AI workload on two architectures: a conventional MCU and a neuromorphic processor. Measure energy per inference, latency, and idle consumption under identical conditions.
Power traces must be recorded and compared transparently.
How to win the challenge?
• Lowest energy per inference
• Best performance-per-watt ratio
• Clear, validated power measurements
Bonus: Demonstrate advantage under event-driven workloads.
Participants:
Deadline: August 31st