114 related articles

When GitHub Copilot, ChatGPT and other AI coding tools shift from help to burden, developers face a new kind of professional fatigue—LLM burnout. Learn its causes, symptoms, and coping strategies.

An in-depth analysis of the essentials of Andrew Ng and OpenAI's ChatGPT Prompt Engineering course. Covers the difference between base and instruction-tuned models, two core prompting principles, and how to wield LLM APIs to build apps.

IEEE launches an official LLM training course, signaling large language models are entering standardized professional education. What this means for the AI talent gap and your career.

Behind every hackathon lies a deeper story about AI innovation ecosystems. This article examines why hackathons are surging in the generative AI era, their core value, and key lessons for AI developers and founders.

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.

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.

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.

Want to switch careers into LLM development but don't know where to start? This guide breaks down a four-level skill roadmap — from basics and API calls to RAG, fine-tuning, Agent development, and multimodal — to help you build real AI career value.

As one of the world's largest car marketplaces, AutoScout24 is going AI-native with OpenAI Codex and agents. It built a CapEx agent in 48 hours, saving ~$1M/year, and explores hands-off coding.

Fable 5, an AI storytelling platform, opens to all paid users and sparks debate on Hacker News. We analyze AI creation tools' practicalization trend across product positioning, competition, and access strategy.

When "AI-powered" becomes a magic phrase for valuation premiums, are companies paying for technology or for a story? A deep analysis of AI hype cycles, the gap between narrative and reality, and how to identify genuine AI value.

Explore why non-AI news shouldn't be forced into tech articles. Learn about content screening mechanisms, topic classification models, and proper editorial gatekeeping.

Tripadvisor's AI review summaries are generating positive assessments for hotels with safety hazards while downplaying critical warnings. Deep analysis of causes and practical user protection tips.

Struggling with math and Python when learning AI from scratch? This article lays out a five-step entry path: grasp the concepts, learn Python lightly, master ML and deep learning principles, get hands-on with PyTorch, then deepen understanding through real projects.

A systematic AI Agent learning roadmap in four progressive stages: fundamentals → ReAct core paradigm → memory & tools → multi-agent collaboration. Master LangChain, AutoGen, and more, growing from beginner to practical developer in three months.

Tencent Hunyuan 3 open-sourced with 295B MoE; GPT-5.6 Sol Ultra may bring multi-subagent collaboration to Codex; Alibaba FunASR upgraded; Japan plans 10M AI robots by 2040.

In-depth look at DryFox v0.3.3's three core features: multi-role agent team collaboration, one-click reusable team templates, and block-style composable UI panels. With Stop Hook, file mailbox comms, and hot-reload plugins.

No ChatGPT account? No problem. Learn how to configure DeepSeek API with Codex++ to use Codex in China — full setup guide, API key steps, and model switching included.
Meta's Next-Gen Model Claims to Match …
Meta's Chief AI Scientist claims its next-gen LLM matches OpenAI's flagship. We break down the strategic intent, open vs. closed source dynamics, and what this means for the AI industry.

Can't make pure AI work? This guide explores the Semi-AI approach to API automation testing, covering key challenges, enterprise framework design, and how AI and frameworks work together for maximum impact.