EMBEDDED TECHNOLOGY
drones, robotics, smart cameras and other physical AI systems where performance, thermal control and space effi ciency are equally critical.
CUBE-Lite for lower-power implementations
Alongside CUBE, Winbond is also developing CUBE-Lite, extending the same edge AI vision to lower-power endpoint devices. While CUBE is designed for applications requiring ultra-high bandwidth, CUBE-Lite is optimised for TinyML and battery-powered AI SoCs, where low power consumption, simplifi ed integration and effi cient on-device inference are prioritised over peak throughput. This makes CUBE-Lite well suited for wearables, AI glasses, smart cameras and other always-on intelligent edge devices.
Together, CUBE and CUBE-Lite represent a broader memory strategy for edge AI: one platform tailored for bandwidth-intensive intelligent systems, and another designed for compact, power-sensitive endpoints. In both cases, the shared objective is clear— to enable practical, effi cient and local AI processing in real-world devices.
Secure Flash protects system integrity
System behaviour depends on the integrity of stored code and AI model data, particularly in devices deployed outside controlled environments where physical access cannot be prevented.
The TrustME W77Q Secure Flash family provides hardware-based protection at the storage level and is compatible with the W25Q SPI NOR Flash footprint, allowing it to be introduced without changes to PCB layout or power design.
The devices support secure boot, root-of-
trust validation, authenticated over-the-air updates and rollback protection, ensuring that only verifi ed fi rmware and model data are executed and that updates cannot be used to introduce unauthorised changes. Support for LMS-OTS signatures provides a path towards post-quantum readiness, while alignment with Common Criteria EAL2+, SESIP Level 2 and ISO 21434, along with FIPS 140-3 (CAVP) in progress, refl ects compliance with current security requirements. Interface behaviour remains consistent with standard SPI NOR Flash, supporting SPI through QPI modes at up to 166MHz.
Combining performance and integrity
These solve different problems in AI edge systems. Increasing bandwidth without protecting stored code introduces risk, while securing the system without addressing data movement limits restricts AI performance. CUBE supports higher throughput where the interface is the constraint, CUBE-Lite supports designs where power and integration limits
dominate, and W77Q ensures that the system starts and runs from a verifi ed state. Used together, they allow AI edge systems to scale without shifting the limitation elsewhere.
Conclusion
Performance in AI edge systems is constrained by how data moves and whether the system can be trusted. Increasing bandwidth alone does not fi x the problem, since power, thermal behaviour and fi rmware integrity all limit what AI workloads can sustain and do not fail independently. CUBE increases available throughput when the interface is the constraint; CUBE-Lite applies the same approach when power and integration limits dominate; and W77Q ensures that the system starts and runs from a verifi ed state.
Taken together, they allow AI edge systems to scale without simply moving the limitation somewhere else.
JUNE 2026 | ELECTRONICS FOR ENGINEERS 39
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45 |
Page 46 |
Page 47 |
Page 48 |
Page 49 |
Page 50
