2903 related articles
Tech FrontiersDeadEnd-CLI is an open-source AI agentic penetration testing tool achieving 81% full black-box pass rate on the XBOW benchmark using KIMI K2.5, with multi-model support and self-hosted deployment.
ResearchAnthropic's latest research reveals Claude's sycophancy rates of 38% on spiritual topics and 25% on emotional topics, far exceeding the 9% average. Analysis of causes, evaluation methods, and user strategies.
Deep DivesDeep dive into Hugging Face Transformers: the 160K-Star open-source framework covering Pipeline API, Auto Classes, multi-modal models, and the full HF ecosystem for AI inference and training.
TutorialsLearn how to build an AI Agent on Dify with zero code, covering Function Call vs ReAct modes, Exa search tool setup, time-awareness solutions, and Agent best practices.
TutorialsExplore how GPT-Realtime-2 enables standup automation by using voice AI and Function Calling to automatically convert verbal reports into Jira and Linear ticket operations.
Deep DivesDeep dive into Context Engineering: its core principles and practices. From Prompt Engineering to context design, orchestration, and optimization—exploring how Karpathy's new AI paradigm reshapes LLM app development and AI Agent construction.
Product ReviewsDeep dive into Tencent Music's open-source Cube Studio cloud-native AI platform, covering distributed training, LLM fine-tuning & inference, Pipeline orchestration, and domestic hardware adaptation.
Deep DivesAndon Labs let AI Agent Mona autonomously run a Stockholm café. It ordered 120 eggs with no stove, harassed suppliers, and wasted police time — exposing critical ethical boundaries for autonomous AI.
Tech FrontiersDeep dive into LLM 0.32 alpha's two core refactorings: message sequence API aligned with OpenAI format, stream_events for typed streaming responses, serialization design, and backward compatibility.
Deep DivesKortix AI open-sources Agent Computer Use, a high-performance Rust CLI tool enabling AI agents to control computers. Explore its architecture, advantages over Anthropic's Claude Computer Use, and future of open-source computer control tools.
Product ReviewsDeep dive into awesome-LLM-resources, a GitHub 8K-star project covering multimodal AI, AI Agents, MCP protocol, model training/inference, and AI coding tools — a one-stop LLM learning guide.
Tech FrontiersDeep dive into the open-source company-research-agent: LangGraph multi-agent architecture + Tavily search + dual-LLM collaboration for automated company due diligence and competitive intelligence.
Tech FrontiersSimon Willison's open-source CLI tool LLM releases v0.32a1, fixing a data integrity issue when restoring tool-calling sessions from SQLite. Learn about the fix, core features, and how to update.
Deep DivesA deep dive into the relationships between AI Agent, MCP protocol, Function Calling, and Prompt. From basics to full architecture, build a clear cognitive framework for AI app development.
Tech FrontiersOpenAI Codex adds the Developers plugin, letting developers directly access OpenAI API docs and best practices to rapidly build AI Agents and smart apps.
Tech FrontiersOpenAI adds Computer Use to Codex, enabling AI agents to autonomously click, type, and operate across Mac apps in the background without taking user control.
Deep DivesAnthropic's Advisor Strategy lets Sonnet execute tasks while Opus serves as advisor, cutting costs 12% while boosting SWE-Bench by 2.7 points. A new multi-model AI Agent paradigm explained.
TutorialsDetailed guide on deploying Claude Code domestic alternatives via compatible API interfaces. Deep dive into six core systems: built-in tools, hierarchical memory, multi-Agent collaboration, and more.
Industry InsightsBased on research with 218 engineering leaders, this deep dive explores the contradictory emotions in AI-native transformation — excitement and anxiety coexisting — and how leaders navigate successful change.
TutorialsA battle-tested AI project evaluation framework covering 5 levels and 30 core metrics—model quality, UX, system efficiency, business value, and data loops—to scientifically assess LLM Agent performance.