When we started designing Kiwi Box 5, we had a simple list of demands. Build a computer around the Rockchip RK3588. Add everything that Edge AI Box users are always missing, and don’t turn it into an overheating toy. We looked at the market for industrial and hobbyist single-board computers and compact mini PCs. We saw users dealing with USB hubs, living with a single Ethernet port, and praying their power connector wouldn’t fall out at the worst possible moment. So we built Kiwi Box 5. This is not just another RK3588 box; this is a finished device for real tasks. Kiwi Box 5: Our new Edge AI Box At the heart of Kiwi Box 5 lies the Rockchip RK3588. If you want a deep dive into what this chip can do, we have prepared a complete RK3588 specs and performance guide. Quick facts: 8 cores: 4x Cortex-A76 at 2.2GHz plus 4x Cortex-A55 at 1.8GHz, 8nm process Mali-G610 MC4 graphics with Vulkan 1.2 and OpenCL 2.0 support Triple-core NPU delivering 6 TOPS for on-device AI, no cloud needed We did not cut corners on memory. The standard config is 8GB LPDDR4X (options for 4, 16, or 32GB) and 128GB eMMC
Last week, Radxa and DEEPX dropped AICore DX-M1M a tiny M.2 module that promises 25 TOPS of AI acceleration while sipping just 3 watts. Remember the AI accelerators that turned out to be glorified USB sticks with half-baked drivers? Yeah. But this thing? It fits in your M.2 slot, like an NVMe drive. And it claims to run YOLO, ResNet, pose estimation – the whole nine yards, without melting your motherboard. Wait, What Actually Is This Thing? DeepX is a South Korean AI chip startup, Radxa – the folks behind the ROCK series SBCs – is partnering with them to put this NPU into an M.2 package. The original AICore DX-M1 AI Module launched in late 2025. That was a bigger M.2 2280 card with PCIe Gen3 ×4, 4GB of LPDDR5, and a 3-5W power envelope. Respectable, but bulky. The new DX-M1M AI Module is different: smaller, leaner. Meaner in some ways, weaker in others. Feature DeepX DX-M1 (original) DeepX DX-M1M (new) AI Performance Up to 25 TOPS Up to 25 TOPS Form Factor M.2 2280 M.2 2242 (M + B Key) Interface PCIe Gen3 ×4 PCIe Gen3 ×2 Memory 4GB LPDDR5 1GB LPDDR4X (4266 MT/s) Storage ? 1Gbit QSPI
At the 2026 Beijing Auto Show, Rockchip introduced its new Automotive AI BOX platform together with ModelBest. The goal is simple – to bring large AI models into the car without depending too much on the network. This is not just another automotive demo; it also shows how embedded AI hardware is changing across many industries. The same ideas behind smart cockpit AI can also be used in robotics, kiosks, AI terminals, edge video systems, and embedded Linux devices. Why Automotive AI BOX Is Moving to the Edge Rockchip’s new Automotive AI BOX tries to solve this problem with a dedicated AI compute system inside the vehicle. According to the company, the platform is designed for multimodal AI workloads and local large model inference. That matters because modern in-car AI is no longer only voice commands. New systems process video, audio, driver behavior, navigation data, and even cabin monitoring at the same time. This trend is very similar to what we already see in edge AI hardware based on Rockchip RK3588 platforms. Devices powered by RK3588 are already handling local video processing, AI acceleration, and multimedia workloads without relying heavily on remote servers. Custom ODM/OEM Solutions If you’re developing an
What Is Edge AI Robotics? If you have been seeing more edge AI robotics news lately, there is a good reason. This field is moving fast, and now it is no longer just about experiments. Real robots are already working in real places. Edge AI robotics means robots can think and make decisions directly on the device (So that is cool). They do not need to send data to the cloud and wait for a response. Everything happens locally (very convenient). This makes them faster and more reliable. Edge AI Robotics Before, many robots depended on cloud systems. They would capture data, send it somewhere, wait, and then act; that works for some tasks, but not for real-time work. If a robot is moving, lifting, or interacting with people, even a small delay can cause problems. That is why edge AI is becoming the standard. It allows robots to react instantly. It also means they can keep working even if the internet is slow or completely unavailable. Latest Edge AI Robotics News: Real Industry Updates in 2026 The biggest change in recent news is simple. Robots are now being used in real jobs, not just tested
