Automotive SoCs: What compute architectures are best suited for handling high-bandwidth sensor fusion in real-time autonomous driving?

AI Accelerators & NPUs: How can NPUs and AI accelerators improve latency and power efficiency for deep-learning models in autonomous perception?

Memory & Storage: How can high-speed, non-volatile storage solutions keep up with the massive data logging requirements of autonomous vehicle fleets?

Zonal Controllers & Networking: What networking protocols and architectures enable deterministic, low-latency communication between zonal controllers and central compute units?

AI Accelerators & NPUs + Power Management: How can AI model compression and specialized compute units reduce power consumption without compromising real-time inference accuracy?

Zonal Controllers & Networking: What are the biggest integration challenges when transitioning from a distributed ECU architecture to a zonal E/E architecture?

Safety-Critical Compute: How do hardware and software co-design approaches impact the reliability and certification of safety-critical autonomous driving systems?

Safety-Critical Compute: How can fail-operational safety architectures be implemented to ensure ASIL-D compliance in centralized compute systems?

Sensors (LiDAR, Radar, Cameras): What are the key trade-offs between LiDAR, radar, and camera-based perception for Level 4 and Level 5 autonomy?