Tagged "iot-ai"
7 articles tagged iot-ai, 26 February 2026 to 16 April 2026. Newest first.
-
Bonsai 1.7B in the Browser: A 290MB 1-bit LLM on WebGPU
Bonsai, a 1.7B parameter model quantized to 1-bit, now runs directly in web browsers via WebGPU at just 290MB. This breakthrough demonstrates extreme quantization techniques making capable language models viable for edge inference without server infrastructure.
-
Xiaomi 12 Pro Converted Into 24/7 Headless AI Server With Ollama and Gemma4
A developer successfully converted a Snapdragon 8 Gen 1 smartphone into a dedicated local LLM inference node by flashing LineageOS and configuring Ollama, achieving 24/7 uptime for edge AI workloads with 9GB RAM available for compute.
-
Lenovo Korea Launches AI-Powered Industrial Edge Solutions
Lenovo Korea has introduced artificial intelligence-based industrial edge solutions targeting manufacturing and enterprise environments. The products enable real-time AI inference at the edge without cloud connectivity dependencies.
-
Running AI on a Raspberry Pi, Part 2: Running AI on a Pi in Under 5 minutes
A practical guide demonstrating how to deploy and run AI models on Raspberry Pi hardware in minimal time, making edge inference accessible to developers and hobbyists.
-
ESP32-S31: 320MHz 2-Core Microcontroller with 512KB SRAM and Networking
Espressif announces the ESP32-S31, a new microcontroller featuring dual cores, 512KB SRAM, Gigabit Ethernet, and 802.11ax WiFi, opening new possibilities for extreme edge LLM inference on IoT devices.
-
How to Run High-Performance LLMs Locally on the Arduino UNO Q
A practical guide demonstrating how to deploy and run efficient LLMs directly on Arduino UNO Q microcontroller hardware, enabling true edge inference on resource-constrained embedded devices.
-
Running LLMs on Raspberry Pi and Edge Devices: A Practical Guide
A practical guide for deploying language models on resource-constrained edge devices like Raspberry Pi, including optimization techniques and real-world deployment patterns. Critical for understanding the limits and possibilities of truly local inference.