236 related articles

NVIDIA TensorRT now supports multi-device inference via pipeline and tensor parallelism, distributing large models across multiple GPUs to break through single-card memory limits.

Cognition's Agentic MapReduce architecture combines classic distributed computing with autonomous agents to break LLM context window limits, enabling multi-Agent parallel reasoning across entire codebases.

OpenAI releases GPT-5.6 preview with three models: flagship Soul, balanced Tara, and lightweight Luna. Based on real KingBench 3 testing, this article breaks down each model's performance on math, front-end, and agentic tasks, and compares them with Anthropic Fable.

The Reddit meme "did you or Claude build it" struck a chord with developers. This article explores how AI coding assistants reshape workflows, where the boundary of human-AI contribution lies, and how programmers can find irreplaceable value in the AI era.

ManagedAgents.sh is a model-agnostic managed agent platform from OpenComputer, supporting Claude, Pi, and Codex runtimes with Slack and GitHub integration.

A Reddit hobbyist builds a four-wheel skid-steer off-road robot using hoverboard hub motors, ODrive boards, and a Raspberry Pi 5. A deep dive into hardware, 4G teleop, ground friction challenges, and the road to ROS2 autonomous navigation.

A systematic breakdown of the complete AI Agent learning roadmap, covering prompt engineering, the ReAct paradigm, memory mechanisms, and multi-agent collaboration, with hands-on project advice.

Learn automation testing from scratch! This article breaks down a three-stage path: Selenium/Appium tools, Requests+PyTest API testing, performance testing and CI/CD, with real projects—build a complete skill set in 21 days.

An in-depth breakdown of LangChain 1.3's core concepts, covering the three major limitations of LLMs, Agent architecture, memory management, and a complete learning path. Master LangChain and LangGraph to quickly build AI development skills.

Tencent Hunyuan and Tsinghua jointly release DiscoBench, the first benchmark evaluating search agents' dynamic ambiguity clarification. Covering 463 ambiguity instances across 11 domains, it reveals real weaknesses of mainstream LLMs.

Are AI companies really losing money? This article deconstructs the fundamental differences between training and inference costs, revealing why pure AI inference services have structural profitability.

Unsloth v0.1.481-beta adds full DeepSeek-V4-Flash support, NVFP4/FP8/imatrix GGUF quantized export, 1.3x faster GRPO, 3-5x faster MoE training, and an OpenAI-compatible API service in Studio.

Want to become an Agent engineer? This article systematically covers three core skill tracks—LLM fundamentals, LangChain architecture development, and enterprise deployment—to help you avoid detours.

The Fi Ultra is the first pet tracker to connect to Starlink satellites, with automatic failover across GPS, LTE, and T-Satellite for nationwide tracking even in dead zones. This in-depth review covers its technology, battery limits, and subscription costs.

A detailed guide to deploying the Dify agent platform locally: from Docker setup and integrating Ollama + DeepSeek local LLMs to workflow orchestration and RAG knowledge base construction.

A detailed guide to Dify, the open-source LLM app development platform, covering its core features and full local deployment via VMware + Ubuntu + aaPanel + Docker. Supports 100+ models like DeepSeek and ChatGPT to build enterprise AI apps fast.

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.

Xiaomi XiaoAI 10.1-inch Smart Control Panel features AI LLM Q&A, WeChat calling, and whole-home Mi IoT control. Priced at 839 yuan, ~679 yuan after national subsidy. An in-depth review of AI capabilities, screen experience, and smart home integration.

A deep dive into LangChain's positioning and value—why do LLMs need a middle layer? How does LangChain serve as the 'glue' unifying multi-model interfaces and supporting Agent development? Learn its core modules and learning path.

From Prompt Engineering to Harness Engineering, a deep dive into the core challenge of truly deploying AI Agents in enterprises. This article breaks down the six-layer architecture and shares real-world Hermes Agent practice.