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EMNLP 2026 introduces AI-generated reviews in ACL Rolling Review, exploring LLM-assisted academic peer review. Analysis of the experiment's background, mechanics, controversies, and implications.

Awesome Free AI Books is an open-source repo with 30+ legally free AI & ML classic textbooks covering deep learning, reinforcement learning, NLP, LLMs, and more — all linking to official sources with weekly automated link checks.

Veteran AI practitioner Remy breaks down the leap from chat models to AI agents: how agents work, the three pillars of context, tools, and skills, MCP connections, and hands-on architecture to make you a 100x employee.

China's Commerce Ministry weighs restricting overseas access to top open-weight AI models from Alibaba, ByteDance, and DeepSeek, while DeepSeek develops its own inference chip amid a US-China AI export standoff.

China's Ministry of Commerce is weighing restrictions on overseas access to top open-weight AI models from Alibaba, ByteDance, and DeepSeek. Meanwhile, DeepSeek is quietly building its own inference chip and raising ~$7B in first external funding.

OpenAI launches GPT-5.6 with three tiered models—Sol, Terra, and Luna—Ultra multi-agent parallel collaboration, Codex integrated into ChatGPT desktop, and an upgraded Computer Use.

Why do chatbots fail at long-horizon workflows? We compare Manus, Perplexity Comet, Claude, ChatGPT and more across task type, total cost, and automation level.

A complete guide to Java AI development: Spring AI, LangChain4j, Spring AI Alibaba, and AgentScope4j — framework comparisons, selection tips, and a clear learning path.

Why do AI results vary so dramatically? LangChain V1.3 reveals the answer: engineering mindset. Covers LangGraph, Deep Agent, RAG, Time Travel, and more.

OpenAI's GPT-5.6 and Codex integration tested: 3 prompts to edit a 15-min video in just 20 minutes. Full breakdown of performance, Token costs, GPT Work automation, and Chat Card real-world results.

A curated open-source repo of 500+ active AI research tools covers the full workflow—literature review, code reproduction, paper writing, and LaTeX formatting—potentially saving 80% of research time.

How can frontend engineers transition into AI development? This guide covers four agent development directions: RAG, workflow agents, vertical agents, and general-purpose agents — with framework picks like LangChain.js.

MiniMax M3-powered AR assistant M-Code automates the full content creation pipeline through four specialized agents: planning, recording, drafting, and review.

Beijing is reportedly consulting with Alibaba, ByteDance, and Z.AI on tiered AI export controls that could affect open-weight models, while DeepSeek quietly builds its own inference chips.

A deep dive into AI Agent concepts, working principles, and real products. Covers OpenAI Deep Research, Manus, Chensi, the perceive–decide–act loop, and core agent engineering logic.

Microsoft CEO Satya Nadella warns enterprises are paying for AI twice: with money and with proprietary knowledge. A deep dive into cloud AI data risks and why self-hosting is becoming a strategic choice.

LLM JSON output unstable in your Agent? This guide covers 6 engineering layers: constrained decoding, validation retry, fake tool calls, Logit Masking, Schema contracts, and anti-pattern locking.

A deep dive into LangChain's four core modules: LangChain components, LangGraph orchestration, Deep Agents, and LangSmith. Build your first Agent from scratch.

An in-depth analysis of AI agent development based on Langchain.js—comparing workflow agents and Agent Loops, deconstructing the TypeScript implementation path of an OpenClaw-like engine, covering structured output, MCP, and LangGraph.

Many enterprises fail at AI Agents due to choosing the wrong tools and lacking methodology. This article outlines an eight-step Agent development method—from cognitive foundations, scenario selection, hand-writing ReAct, and structured output to Tool Use, RAG, evaluation sets, and production fallback.