Artificial intelligence is driving an unprecedented increase in sensor data, pushing today’s electrical interconnects toward their physical limits. As intelligent systems evolve from distributed architectures to centralized AI compute platforms, efficiently moving data between sensors, memory, and processors is becoming as critical as compute performance itself.
This presentation explores why sensor-to-core connectivity is emerging as a key bottleneck for next-generation software-defined vehicles and other Physical AI applications. It examines the architectural challenges created by increasing bandwidth demands, power constraints, latency requirements, and system scalability, and discusses why incremental improvements to conventional electrical interfaces may no longer be sufficient.
Attendees will gain a system-level perspective on the evolving data fabric requirements of AI-driven platforms and the role that next-generation interconnect technologies can play in enabling scalable, energy-efficient, and high-bandwidth communication for future sensing and computing architectures.
