What key processor architecture does the AIE015-AT leverage?

The system is built to utilize advanced edge AI processing architectures such as NVIDIA Jetson Thor.

What criteria are used to judge the embedded world Best in Show Awards?

Entries are evaluated by an editorial team based on design excellence, relative performance, and market impact.

Back to feed

#Robotics & Edge AI

Axiomtek Wins embedded world Best in Show Award: Design Architecture and Edge AI Deployment Considerations

Originally published as: Embedded Computing Design Announces Axiomtek Wins embedded world Best in Show Award

Embedded Computing DesignPublished 6 hours ago

AI overview

Hardware teams designing edge AI and robotics systems should evaluate award-winning modular platforms like Axiomtek's AIE015-AT to accelerate time-to-market and mitigate custom baseboard design risks.

Recognizing Excellence in Edge AI Design

Embedded Computing Design announced the winners of the embedded world North America Best in Show Awards, highlighting standout products evaluated on design excellence, relative performance, and market impact. Among the honorees, Axiomtek was recognized for its AIE015-AT embedded system, engineered specifically for next-generation robotics and physical AI applications.

The award-winning platform leverages advanced heterogeneous processing architectures—such as the NVIDIA Jetson Thor platform—to deliver dense real-time AI compute alongside comprehensive sensor and camera integration interfaces. For hardware engineering teams, leveraging pre-validated, award-winning embedded systems can significantly compress development cycles for complex edge intelligence deployments compared to custom ground-up baseboard designs.

As physical AI and autonomous systems demand higher compute throughput at the extreme edge, hardware architects must evaluate industrial computers that balance thermal dissipation, rich I/O flexibility, and strict reliability standards. Monitoring component availability and vendor integration support will be vital for teams looking to scale these advanced edge systems from prototype to volume production.

Related components

Questions & answers

Axiomtek won the award for the AIE015-AT, an embedded system built for robotics and physical AI.

Discover more

#Optics & Connectivity

Pedro Duque Named IEEE Honorary Member: Aerospace Leadership and Satellite Hardware Implications

Pedro Duque, Spain's first astronaut and current Hispasat chairman, has been named an IEEE honorary member for his contributions to space exploration and leadership. This recognition highlights the critical synergy between aerospace engineering milestones and professional technical standards.

IEEE Spectrum

#Robotics & Edge AI

Enclustra and MakarenaLabs Partner to Scale Edge AI SoM Platform Integration

Enclustra has partnered with MakarenaLabs to bring hardware-accelerated Edge AI orchestration across its SoC, MPSoC, and MLSoC portfolio via the Lira framework. This integration simplifies low-latency, cloud-free local inference for developers selecting modular embedded computing platforms.

Embedded Computing Design

#Optics & Connectivity

Canadian Startup Novigrad Solves Space-Qualification Bottlenecks for Resilient Electronics

Canadian startup Novigrad has successfully established domestic space qualification and radiation testing capabilities to support resilient electronics. This development helps hardware teams mitigate bottlenecks in radiation hardening and validation for high-reliability missions.

EE Times