1125 related articles

A deep dive into Kimi Delta Attention (KDA): tracing the evolution from quadratic Softmax attention through linear attention, Delta rules, and gated decay mechanisms, with insights on associative memory and hardware optimization.

Analyzing whether LLMs can identify 16 cards through 45 yes/no questions from an information theory perspective. Exploring AI reasoning capabilities in constraint-based multi-turn tasks.

Segue is an AI context migration tool that uses short handles to seamlessly transfer conversation context across ChatGPT, Claude, and other AI platforms, solving the context-reset problem when switching tools.

Segue is an AI context migration tool that uses short handles to seamlessly transfer conversation context across ChatGPT, Claude, and other AI platforms, solving the cross-platform context reset problem.

A deep dive into HuggingFace's speech-to-speech open-source project, covering its modular VAD, STT, LLM, and TTS pipeline architecture and the advantages of local deployment for privacy, cost, and latency.

book-to-skill is an open-source GitHub project with over 10K stars that converts technical book PDFs into Claude Code Skills, enabling AI coding assistants to directly leverage book knowledge.

Real-world comparison of Kimi K3 vs Claude flagship across e-commerce pages, 3D fighting games, and flight simulators. Kimi K3 delivers 90% output quality at 1/8 the price with faster speeds and local deployment support.

Moonshot AI launches Kimi K3 with 2.8 trillion parameters and 1M token context. Google delays Gemini 3.5 Pro, AI coding tools upgrade collectively as competition shifts to coding and Agent capabilities.

July 24 AI news: Black Forest Labs launches Flux 3 multimodal model, Kimi K3 lags in US-UK gov tests, Alibaba Qwen tops TTS rankings, Etched raises $300M, AMD unveils MI430X.

Moonshot AI releases Kimi K3, a 2.8 trillion parameter open-source model using MoE architecture that tops the global frontend coding arena at under $1 per task, beating GPT and Claude.

Loop Engineering is a paradigm shift in AI usage. Learn how to build automated loops where agents explore, execute, and verify tasks autonomously, with a hands-on e-commerce case study.

An open-source STEM education robot using Edge Impulse edge AI for local object detection, teaching kids computer vision and ML through an engaging ball-fetching game with anthropomorphic design.

A systematic breakdown of the AI LLM learning roadmap covering prompt engineering, AI Agent development, RAG knowledge bases, model fine-tuning, and hands-on projects for beginners.

A systematic guide to AI Agent development from beginner to deployment, covering task planning, tool calling, memory management, learning paths, and realistic commercial monetization considerations.

How to learn AI Agent development from scratch? This article outlines a clear 3-step path: Python crash course, LLM theory & practice, and LangChain framework project implementation.

Complete guide for backend developers transitioning to AI/LLM engineering. Covers the 4 core skills—Python, RAG, Fine-tuning, and Agents—with a phased learning roadmap and practical project advice.

A deep dive into enterprise RAG from setup to production, covering document chunking, vector search, query rewrite, reranking, and quality evaluation frameworks.

Build an enterprise RAG knowledge base Q&A system using Spring AI 2.0, Cursor AI programming, Ollama local deployment, and Redis vector storage. Runs on just 4GB VRAM.

Deep dive into Kimi K3: the largest open-weight model at 3 trillion parameters, surpassing Opus-level models in Agentic coding with 896-expert MoE architecture, 1M token context, at Sonnet pricing.

Colibri uses MoE hot-cold separation and 4-bit quantization to run 744B-parameter models like GLM 5.2 on consumer hardware. Learn about its three-tier memory architecture and speculative decoding.