GIGAIPC, the industrial arm under GIGABYTE, maps out a clear edge-AI stack from ultra-compact mini PCs to ruggedized industrial systems. The BRIX GB-BRU7-255H anchors the small-form-factor tier with Intel Core Ultra 7 255H, an Intel AI Boost NPU rated up to 13 TOPS, and I/O that spans 2.5 GbE, Wi-Fi 7, and multi-display via HDMI/DP for CAD/creative workloads and on-prem inference at low power envelopes. In parallel, GIGAIPC’s ATX-Q670A/B motherboards bring DDR4/DDR5, multiple PCIe lanes for accelerators, and extensive serial/GPIO for brownfield integration in industrial PCs. https://www.gigaipc.com/en/
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For scaled deployments, the QBiX family covers DIN-rail systems for cabinet installs and the QBiX “Jumbo” chassis that accepts discrete GPUs, targeting machine-vision pipelines, factory automation, and multi-stream RTSP analytics. DIN-rail SKUs based on Intel Atom x7433RE and Celeron J6412 prioritize deterministic I/O and fanless thermals, while Jumbo systems pair 12th–14th Gen Intel Core on Q670E with full-length PCIe slots for add-in GPUs or frame-grabbers to run edge inference and high-throughput fieldbus gateways with reliability.
On the embedded boards side, GIGAIPC’s ATX and uATX lines expose plentiful COM ports (RS-232/422/485), SATA, M.2, and dual 2.5 GbE for surveillance NVRs and industrial HMIs, while newer 3.5-inch and Mini-ITX boards with Core Ultra CPUs shift AI workloads from the cloud to the line side. The practical theme is consistent: pair Intel’s integrated NPU for low-latency, low-watt operators with GPU/CPU headroom when parallelism or higher-precision tensors are required in a single, serviceable box.
Road-mapped for 2026, the team hints at next-gen “Ultra” platforms aligned with Intel’s forthcoming client CPU cadence, keeping an eye on higher on-die NPU TOPS and faster media blocks for real-time multimodal inference. That trajectory positions BRIX for desk-side dev and pilot rollouts, QBiX DIN-rail for OT cabinets, and QBiX Jumbo as the field-deployable workstation that swallows full-size accelerators without abandoning industrial I/O or lifecycle support.
This interview was filmed at Embedded World North America, where demand centered on edge-resilient AI—CCTV analytics, machine vision, and creative workstation-class tasks consolidated into compact x86 boxes that speak both IT and OT. The portfolio breadth suggests a build-once, deploy-many approach that shortens time-to-pilot while preserving the option to scale compute with discrete GPUs when the workload grows in scope.
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