101 related articles

In the age of AI-assisted programming, how do you make tools like Codex and Claude Code output more stably? This article deeply analyzes SuperPowers and GStack, covering project-level orchestration and module-level code layering to help developers master AI coding.

What is prompt engineering? This guide covers prompts, their four key functions, the 6-step engineering process, business value, and technical limitations for a complete foundation.

A political news story about British satirical candidate 'Count Binface' sparked debate in the tech community: why does AI struggle to understand sarcasm, contrast humor, and cultural context? An in-depth analysis of LLM limitations.

The same Chinese AI wins praise on Hacker News yet gets criticized at home. This article dissects three mismatches — user identity, product form, and positioning — behind the divided reviews.

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.

Explore the core features and use cases of the free Mermaid Diagram Editor. Supporting flowcharts, sequence diagrams, Gantt charts and more, it follows the 'diagrams as code' philosophy to enable version-controlled technical documentation for developers and architects.

Can a brand's "visibility" in AI answers really be quantified? This article deeply dissects the methodological flaws of AI visibility dashboards—from LLM output randomness and black-box mechanisms to vanity metric traps.

Hugging Face's open-source ml-intern autonomously reads papers, writes training scripts, and finetunes LLMs, deeply integrating the HF ecosystem and smolagents. Explore its features and impact on ML careers.

LLMs are often overconfident and prone to hallucination. How can AI learn to say "I'm not sure"? This article explains the reinforcement learning approach with metacognitive feedback and how calibrating confidence boosts LLM trustworthiness.

OpenAI launches GPT-5.6 Sol at half the price of Anthropic's Fable 5. We compare both models on HealthBench, cybersecurity and more using hard system-card data, analyzing Sol's cost-effectiveness and shifts in AI power.

A tailored large-model learning path for ordinary programmers: from prompt engineering, API calls, and LangChain, to RAG, Agents, fine-tuning, and enterprise deployment—six steps to build AI application skills fast.

Cut through the Agentic AI hype to see the real value of agentic applications. Based on Andrew Ng's course, learn why Evals and error analysis—not framework choice—separate top developers.

How benchmarking transforms dormant domain data into an AI optimization engine. From healthcare to law to manufacturing, building vertical benchmarks activates proprietary data and builds a strategic moat.

Taiganet.com is simulating the WS4000 industrial control system. This niche project preserves the engineering wisdom from before the PLC and SCADA era. A deep look at the challenges of ICS simulators, knowledge preservation, and reverse engineering in OT security research.

Prompt engineering is a core skill in the AI era. This article breaks down the essential differences between prompts and prompt engineering, the six-step workflow, four evaluation criteria, and key limitations like context limits and hallucination.

LLMs are built to predict the most probable output — making them averaging engines by design. Explore how regression to the mean quietly stifles innovation and how to fight back.

Learn how to use an AI Agent to fully automate WordPress SEO — covering image Alt tags, RankMath API integration, prompt configuration, and more.

PP-OCRv6 is PaddlePaddle's SOTA-level OCR model. This article covers Docker deployment, invoice recognition testing, and the critical font-missing pitfall causing entire regions to be skipped.
Nvidia: From Chip Supplier to the Capi…
Nvidia is more than a GPU giant — it operates as the financial backbone of the AI boom through investment and capital recycling. A deep analysis of the risks.

Redis creator runs 284B-parameter DeepSeek model on a MacBook Pro at 26 tokens/sec using a pure C engine, asymmetric quantization, and MoE architecture.