313 related articles

A Reddit user compared FP8 and BF16 precision on the Krea2 model and found almost no difference in image quality. This article analyzes the technical reasons behind the shrinking quantization gap and its real-world impact on VRAM usage and inference speed.

A real case study: team builds AI Agent "Oogway" to auto-patrol after every job, investigate anomalies, create tickets, and update a knowledge Wiki — catching bugs before customers do.

HKUDS's open-source Vibe-Trading gained nearly 1,000 GitHub stars in a day. This deep dive covers its LLM+Tool Calling architecture, core modules, and the risks of AI-driven trading agents.

A street poll experiment at a Juneteenth celebration in South Carolina used transparent voting buckets and index cards to gauge public opinion on Kamala Harris running in 2028, revealing deep divides over female leadership in America.

A deep dive into Security Swarm's evaluation methodology: building test sets from real, recent vulnerabilities to avoid training data contamination and validate its ability to find more bugs at lower cost.
LLM Security Benchmarking: Current Sta…
Why is it so hard to establish unified LLM security benchmarks? This article analyzes core challenges in LLM security evaluation—covering jailbreaks, prompt injection, red teaming, and more—with practical strategies for developers.

AI coding tools are changing development, but Vibe Coding hides risks in code quality and maintenance. This article explores Engineered AI Programming, compares Codex and Claude Code, and reveals real enterprise development paths.

The same model scores 77% in Claude Code but jumps to 93% in Cursor—the only variable is the Harness. This article dissects how AI coding tools work in 60 lines of Python.

An exclusive look at the AI Engineer Summit dress rehearsals, decoding the paradigm shift from research to production. A deep dive into AI Engineer challenges, RAG, agent systems, and AI engineering as a distinct discipline.

Starting from a brief thank-you tweet, this article explores content co-creation in AI and open source communities—how video demos become a new dissemination medium and how creators and developers build trust networks together.

OpenAI releases the GPT-5.6 series with flagship Sol, balanced Terra, and lightweight Luna. An in-depth look at each model's positioning, use cases, pricing, and the multi-agent Ultra architecture.

A deep dive into LangChain's positioning and value—why do LLMs need a middle layer? How does LangChain serve as the 'glue' unifying multi-model interfaces and supporting Agent development? Learn its core modules and learning path.

Hands-on report on DeepSeek's open-source inference acceleration toolkit DSpec: draft model + smart scheduling delivers lossless speedup, hitting acceptance length 6 on GSM8K and reproducing official data.

Most Agent projects lack competitiveness in interviews due to missing business value and engineering depth. This article breaks down the 6 core standards of high-value Agent projects.

Google lets businesses connect their Google Business Profile to Gemini, so the AI can read operating info, reviews, and business data to offer targeted marketing advice—lowering AI barriers for SMBs.

Andrew Ng partners with JetBrains on a new course systematically teaching Spec-Driven Development. By writing high-quality specs, developers can precisely control AI coding agents, eliminate context decay, and boost intent fidelity.

Rowboat is an open-source, local-first AI desktop client positioned as a Claude Desktop alternative. Local data storage and fully transparent code help developers control privacy and workflows.

OSWorld 2.0 benchmark tests 108 long-horizon computer tasks. Claude Opus tops at only 20.6% completion, exposing critical AI weaknesses in state tracking and error self-correction.

OSWorld 2.0 benchmark tests 108 long-horizon computer tasks (median 1.6 hrs for humans). Claude Opus tops out at 20.6% completion, exposing critical AI Agent weaknesses in state maintenance and self-correction.

As next-gen Claude models arrive, traditional cybersecurity faces a systemic crisis. Explore why human-built defenses have structural blind spots against AI-native attacks — and how the industry must respond.