108 related articles

What exactly is the Cloud Coding Agent Silicon Valley is hyping? This article breaks down the core concept across three axes—where it runs, who watches, where tasks start—and gives users in China practical advice on local alternatives.

How did Ollama grow from a niche open-source project into developers' default choice for running local LLMs? This article breaks down its rise across product design, technical strategy, and ecosystem building.

Step-by-step guide to deploying Dify locally: Docker setup, Docker Compose installation, source code configuration, .env file setup, and container startup for Windows, macOS, and Linux.

In-depth guide to Kaggle's free-tier compute: P100/T4 GPU with 30 hours/week quota, 12-hour sessions, suitable models like CNN and BERT fine-tuning, plus tips like mixed precision and checkpointing to start deep learning at zero cost.

An open-source project uses HDMI capture for screen vision and USB HID to simulate touch input, enabling root-free, app-free hardware-level phone AI Agent control. Explore the principles, advantages, and limitations.

Databricks open-sources Omnigent, a Meta-Harness for orchestrating Claude Code, Codex, and more AI coding assistants together—with built-in guardrails, cross-model workflows, and real-time collaboration. Get started in 10 minutes.

Unsloth v0.1.463-beta fixes a Studio crash caused by access-denied errors during llama-server service discovery. Improves stability for multi-user servers and Windows environments.

After weeks of hands-on time with the Steam Machine, it still carves out a unique niche thanks to its living-room-and-desk flexibility—even alongside a PS5 and Xbox Series X. Mature SteamOS, strong Proton compatibility.

OpenAI launches GPT-5.6 Sol/Terra/Luna, SenseNova open-sources its full multimodal training stack, Gemini adds free Study Notebooks, Apple M7 brings on-device AI to mainstream — a roundup of today's AI updates.

A systematic guide to Dify's three deployment methods (Docker/source/online), five application types, and hands-on workflow nodes—covering LLM integration, MySQL config, and app publishing.

Master LangChain from scratch: the three limitations of LLMs, init_chat_model unified interface config, the Message type system, and the path from LLM calls to Agent development.

AMD officially unveils the Ryzen AI Halo local AI dev kit, priced around $4,000 with 128GB unified memory, capable of running 70B LLMs locally. An in-depth look at its specs, pricing, and market competition.

LangChain's LangSmith Engine is an intelligent agent tool for tracking Agent failures, prioritizing issues, and auto-drafting fixes. Deep dive into its core capabilities, sandbox isolation, sub-Agent architecture, and continuous evaluation challenges.

Unsloth v0.1.48-beta released, adding NVFP4/FP8 quantization export, OpenAI-compatible API hot-swapping, 3-5x faster MoE training, and 1.3x faster GRPO, covering the full LLM fine-tuning, quantization, and local deployment pipeline.

In-depth analysis of GPT-5.6 Ultra's sub-agent collaborative reasoning, the global rise of Chinese AI models, world-model evaluation gaps, and AI's real-world deployment challenges and bubble warnings.

Struggling with Windows pop-ups and rogue software? This in-depth review of Wukong Security reveals how AI antivirus breaks past traditional virus-database limits, blocking ads and bundleware in real time, plus a comparison of five repair shops.

Unsloth v0.1.461-beta fixes local GGUF vision model loading on llama-server in Studio, adds variant directory companion file lookup for stable multimodal deployment.

Deep analysis of a complete mobile exploit chain: how attackers start from Firefox, escape the sandbox, exploit kernel vulnerabilities, and achieve Android Root. Security insights for developers.

Master OpenAI Codex fast, even from scratch! Learn Codex vs ChatGPT differences, four versions, interface tips, plugins & skills, browser automation, plus six best practices.

Local AI faces a triple threat from tightening regulation, hardware lock-downs, and commercial pressure. A deep analysis of why running open-source LLMs on your own device is a digital right worth defending.