  The gigantic complexity and heterogeneity of today's advanced cyber-physical
systems and systems of systems is multiplied by the use of avant-garde
computing architectures to employ artificial intelligence based autonomy in the
system. Here, the overall system's reliability comes along with requirements
for fail-safe, fail-operational modes specific to the target applications of
the autonomous system and adopted HW architectures. The paper makes an overview
of reliability challenges for intelligence implementation in autonomous systems
enabled by HW backbones such as neuromorphic architectures, approximate
computing architectures, GPUs, tensor processing units (TPUs) and SoC FPGAs.
