Embedded World 2023: VDC’s “Embeddy” Award Winnersby Dan Mandell...

Embedded World 2023: VDC’s “Embeddy” Award Winners

by Dan Mandell & Chris Rommel | 3/28/2023

Last week, VDC Research attended the Embedded World 2023 conference in Nuremberg, Germany and held dozens of face-to-face meetings with exhibitors. Following a barren 2020 and relatively muted attendance last year, Embedded World 2023 was a clear indication that this industry is a small step away from back to normal conference and tradeshow attendance and activities. The halls were packed and bustling like times of old, with everyone sharing a sense of relief and rejuvenated appreciation for in-person events, meetings, and connections.
VDC created and named the Embeddy Awards to highlight companies announcing important advances in the IoT and embedded software, hardware, and services industries. The Embeddy is awarded for the most cutting-edge product or service available to embedded software developers and system engineers. Nominees were judged across specific criteria including corporate, technological, and industry significance, as well as the most cutting-edge hardware and software solutions or services.
The 2023 Embeddy Award Winners include:

• IP: BrainChip Akida 2nd Generation
• HARDWARE: Eurotech ReliaCOR Secure Edge AI
• SOFTWARE: 1NCE OS

Embeddy IP Winner: BrainChip
Akida 2nd Generation: Leading up to Embedded World 2023, BrainChip, a commercial producer of ultra-low power neuromorphic AI IP, launched the 2nd generation of its Akida platform to drive provide direct support for the embedded AI processor market, which is rapidly growing, particularly at the far edge. More complex networks like RESNET-50 can be processed by Akida without CPU intervention and the platform supports 8-bit weights to go with existing 4,2,1 bit support. Akida also adds an efficient vision transformer implementation for acceleration and can also handle 3D data for applications like video object detection and target tracking as well as 1D time series data for streaming data on devices with limited memory, battery, and compute resources. Akida features separable spatial temporal convolutions called Temporal Event Based Neural Nets that allow for simpler and efficient AI processing solutions.