BCM Advanced Research walks through how industrial x86 platforms are becoming “edge AI appliances”: a voice-driven customer-service agent that answers questions about the company website using retrieval-augmented generation (RAG), running locally on a booth PC rather than a cloud-only endpoint. The discussion also touches the shift toward Intel SoC designs where CPU + integrated GPU + NPU can host meaningful on-device models without a discrete GPU, cutting latency and simplifying the overall system cost.
https://www.bcmcom.com/
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The demo is a good reality check on what matters in the field: far-field microphones, ambient noise, and the need for reliable speech-to-text, dialog management, and guardrails before the LLM response ever reaches a user. BCM mentions adding “talker” awareness and presence recognition so the kiosk can focus on the person in front of the screen, a pattern that fits with camera-based user detection, wake-word gating, and on-prem governance policy.
On the vision side, BCM shows a low-power embedded system paired with Intel RealSense depth cameras for depth-aware perception and identification, quoted at around 12 W for always-on sensing. For many deployments, this kind of constrained, deterministic edge compute is the point: stable thermals, predictable latency, and continuous operation for retail analytics, industrial automation, and medical edge work.
The rest of the booth tour connects form factors to deployment options: mini-ITX through micro-ATX/ATX and up to E-ATX, plus integrated systems and rackmount builds that can be configured with high I/O and even double-wide GPU support. BCM also references medically certified box PCs (IEC/EN 60601 and related safety/EMC scope) to shorten regulatory paths, and a server roadmap spanning Emerald Rapids today and Intel Xeon 6 “Granite Rapids” motherboards (including Made-in-USA variants) for datacenter, government, and long-life embedded duty at Embedded World North America 2025.
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