Edge AIEdge AI
The Mainline NPU Driver on RK3588, and What It Cannot Do Yet
The mainline NPU driver for RK3588 is real, in drivers/accel since Linux 6.18. What it does, what it does not, and where…
RB Aug 19 · 7 min
Embedded Linux on Edge-AI 23rd Sept 2026 enrollingLinux kernel & Device drivers starts on 24th Oct 2026 enrollingCorporate on-site training - Submit proposal Pick your modulesSharpen your kernel skills: deep dives, drivers, Yocto, CVEs, careers — updated daily. Read the blog →Embedded Linux fast track starts 23rd sept 2026 enrollingEmbedded Linux Mastery track starts 23rd sept 2026 enrollingLinux systems engineering starts 23rd sept 2026 enrolling
~/ blog
Edge AI
On-device and edge AI for embedded Linux engineers: accelerators and NPUs, model runtimes and quantization, federated learning, and the systems engineering behind deploying AI at the edge.
Edge AI
Edge AIEdge AI
Speculative Decoding: Faster On-Device LLMs
Speculative decoding speeds up on-device LLM inference by amortizing the memory-bandwidth cost of decoding. Here is how it works and where it…
RB Aug 5 · 8 min
Edge AIEdge AI
Self-Learning Edge AI: Where the Technology Stands
Self-learning edge AI comes in three technical forms. How each one works, and where each stands today.
RB Jul 29 · 9 min
Edge AIEdge AI
Edge AI in Automotive and Industrial Systems
Edge AI in automotive and industrial systems runs beside a deterministic, safety-critical control loop. How real-time Linux, TSN and mixed criticality help.
RB Jul 22 · 9 min
Edge AIEdge AI
TinyML vs Edge AI on Linux: How to Choose the Right Machine
TinyML vs Edge AI on Linux is not a TOPS comparison. It is a choice of machine. A decision guide, the measured…
RB Jul 20 · 14 min
Edge AIEdge AI
4-Bit Weight Quantization: Why the Memory System Decides
Why 4-bit weight quantization is a memory-system problem: DRAM bandwidth, unified memory on Jetson, kernel fusion, and the real accuracy and speed…
RB Jul 15 · 11 min
Edge AIEdge AI
LLM Inference From Flash: Running Models Larger Than Your DRAM
LLM inference from flash: how to run a model larger than your DRAM by streaming weights from storage, explained for embedded engineers.
RB Jul 10 · 10 min
Edge AIEdge AI
Edge AI in the Next 10 Years: The Long Horizon
Where edge AI heads by 2035: AI-native 6G networks, neuromorphic silicon, the EU AI Act, and a ten-year roadmap for embedded Linux…
RB Jul 3 · 10 min
Edge AIEdge AI
Edge AI in the Next 10 Years: The Stack and the Fleet
The embedded Linux stack for edge AI — Yocto, runtimes, secure OTA — and federated learning with Flower to improve models across…
RB Jul 2 · 10 min
Edge AIEdge AI
Edge AI in the Next 10 Years: The Silicon Shift
Edge AI in 2026: where the market and silicon stand — NPUs and TOPS tiers, quantization, and the power spectrum, for embedded…
RB Jul 1 · 10 min
The fortnightly digest
One email every two weeks — the best of our kernel & embedded writing, plus a hand-picked link or two. No spam.
// 1,200+ embedded engineers already read it
We email occasionally and never share your address.