219 related articles

Sysdig captured JadePuffer, the first fully autonomous LLM attack agent: exploited Langflow RCE, self-corrected in 31 seconds, laterally moved, encrypted databases, and left a ransom note — a deep-dive into weaponized AI agents.

The iFLYTEK T30 Lite learning tablet features the Spark large model and DeepSeek dual AI engines, a 12.5-inch eye-care display, and 8GB+512GB storage. This in-depth review analyzes its hardware, AI learning capabilities, and buying advice for K12 families.

In one week, OpenAI, xAI, Google, and Microsoft all cut AI prices, driving near-frontier inference costs sharply lower. Meanwhile, Microsoft Copilot's paid conversion across 450M seats is under 4.5%, exposing the monetization challenge of general AI assistants.

The viral "free GPT5.6" videos hide real risks: the model doesn't exist, and the "treasure sites" are third-party proxy mirrors carrying data privacy leaks and account bans.

Anthropic's Claude Code is accused of covert tagging via Unicode punctuation encoding, prompting Alibaba to ban its use. A deep dive into the reverse-engineering findings, distillation allegations, and the AI-era battle over compute monopoly and developers' right to know.

In-depth analysis of Tencent's open-source reasoning model Hunyuan HY3: MoE architecture, 295B total params, Apache 2.0 license, coding & front-end rivaling DeepSeek V4 Pro at 1/35 the cost.

A systematic guide to the four-stage AI Agent development path: core concepts, principle paradigms like ReAct, RL and multi-agent optimization, and real-world projects. Mastering Agent development is the true hardcore edge in today's LLM field.

The U.S. White House is considering an executive order on open-source AI, touching on national security, tech proliferation, and industry competition. A deep dive into its possible directions and impact.

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.

A complete guide to building a local AI coding agent on a 32GB Mac: Ollama for local inference, OpenCode as the agent framework, and MCP memory servers for cross-session context. Code stays on-device, no subscription fees.

DeepSeek is entering AI chip development, targeting compute autonomy. This article analyzes its motivations, software-hardware synergy, chip R&D challenges, and impact on China's AI vertical integration.

Want to build an AI Agent but don't know where to start? This guide covers the complete seven-step workflow—from requirements analysis, platform selection, prompt engineering, data storage, and UI building to testing and deployment.

Alibaba has banned Claude Code as high-risk software. Reverse engineering revealed a covert environment-identification mechanism hiding user fingerprints in punctuation via prompt steganography. A deep dive into the incident and AI tool trust.

Starting from the three limitations of LLMs, this guide systematically explains LangChain's core positioning, environment setup, API key prep, model init, and the message system. Learn init_chat_model and AIMessage/HumanMessage/SystemMessage.

The explosive expansion of AI data centers is voraciously consuming electricity, directly driving up U.S. manufacturing energy costs. This article dissects the crowding-out effect and the path forward.

Learn how to split AI reasoning tasks by act and character, run 14 concurrent streams, and cut processing time from 100s to 30s — a reusable schedule-concurrency-aggregate methodology.

An AI research engineer with 3 years of experience sent 50 applications to FAANG with zero replies. This article breaks down the hidden barriers of top-tech AI roles, the truth about LinkedIn ghost jobs, and the MLE vs. Research Engineer divide.

A clear, in-depth guide to how AI Agents work: the paradigm shift from traditional programs, the perception-decision-action loop, and the four pillars—LLMs, tool calling, memory, and RAG.

A complete AI Agent learning roadmap covering BDI theory, core components (Perception/Planning/Execution), AutoGen multi-agent frameworks, and DeepSeek RAG projects for beginners.

Deep dive into DeepSeek-V4: 1.6T-parameter MoE, CSA+HCA hybrid attention, MHC & MUON optimizer. Inference FLOPs drop to 27% of V3.2, redefining open-source LLM SOTA.