Monitoring LLM behavior: Drift, retries, and refusal patterns

The offline pipeline's primary objective is regression testing — identifying failures, drift, and latency before production.
XDA Developers on MSN

Local LLMs work best when you're not loyal to just one

The best thing about self-hosted LLMs is that you can choose from hundreds of models ...
Android Authority

Here's why I run DeepSeek locally and how you can do it

It’s safe to say that AI is permeating all aspects of computing. From deep integration into smartphones to CoPilot in your favorite apps — and, of course, the obvious giant in the room, ChatGPT.
Digi Times

Kneron targets offline LLM applications with new AI chip device

After announcing a new AI chip in August, Kneron has now developed a new software-hardware integrated device that supports offline GPT model applications. The company believes that there are several ...
CNX Software

Espressif Systems ESP-Claw framework builds local AI agents for ESP32 devices

We had already seen OpenClaw-like AI agents for ESP32 targets such as Mimiclaw and PycoClaw, but Espressif Systems has ...

LLM-As-A-Judge: What To Expect From Using AI To Evaluate AI

LLM-as-a-judge is exactly what it sounds like: using one language model to evaluate the outputs of another. Your first ...
Digi Times

OpenClaw development and market status

OpenClaw craze accelerates personalized edge AI agent applications, driving demand for VPS and personal workstations. Abstract The OpenClaw frenzy is accelerating the adoption of AI agents in personal ...