AkiraOS is an open-source @ZephyrIoT-based OS that runs sandboxed WebAssembly apps on microcontrollers.
https://t.co/NmUNVfpZ8O
In some ways, it's similar to Docker, but for microcontrollers. The firmware is built specifically for a target, and the WASM apps are independent, platform-agnostic, and OTA upgradeable.
It works on ESP32 targets (ESP32-S3, ESP32-H2, ESP32-C6), nRF54L15 MCU, and several STM32 boards. There's also a simulator for x86-64 computers. A web interface and a mobile app are being developed for remote management.
@googlegemma On-board speech + vision + hardware control with Gemma locally — this is the future of edge AI.
For builders experimenting with on-device prompts, here's one I use for natural language hardware control workflows:
https://t.co/UcOEV5Nmi1
Introducing the newest Coral board, for efficient, on-device AI!
Check out the demos in the video:
- On-board speech translation
- Natural language controlling hardware
- Vision & sound generating music
If you want to become good at AI engineering (in 3 weeks), then learn these 15 concepts:
1 AI Agents: Memory, State & Consistency
→ https://t.co/v8H7O00jub
2 Machine Learning System Design 101
→ https://t.co/9MkHcLb5e0
3 Design Personal AI Chat Assistant
→ https://t.co/nNWq3onTnW
4 How RAG Works
→ https://t.co/cGmunPTUlb
5 LLM Concepts - A Deep Dive
→ https://t.co/5lCKxq2g4N
6 How to Design an AI Agent
→ https://t.co/JvnPd9773A
7 What is Reinforcement Learning
→ https://t.co/AVpl9j1oit
8 How Vector Databases Work
→ https://t.co/FVxan8xHH3
9 Context Engineering 101
→ https://t.co/OMkiZhkODL
10 AI Coding Workflow 101
→ https://t.co/paIf9ksIU9
11 LLM Evals Explained
→ https://t.co/nv3Ol8W53p
12 How AI Agents Work
→ https://t.co/tk3zkCjRvg
13 How MCP Works
→ https://t.co/wgf8gHnnkn
14 Agentic Patterns Explained
→ https://t.co/8YdBBWvTj1
15 Multi-Agent Architecture Explained
→ https://t.co/rS5QQS7Jln
What else should make this list?
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