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53 related articles
·4 min
Spring AI 2.0 in Practice: Building an Enterprise RAG Knowledge Base Q&A System with Cursor
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.
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·4 min
Kimi K3 Deep Dive: 2.8 Trillion Parameter Open-Source Model Closes the Gap with Closed-Source Frontier for the First Time
Moonshot AI releases Kimi K3 open-weight model with 2.8T parameters and 1M token context. Our deep dive covers coding, 3D dev, agent capabilities, and safety concerns.
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·3 min
Apple Silicon LLM Inference Speed Benchmarks: A Complete Guide to Local Large Model Performance on Mac
In-depth analysis of Apple Silicon local LLM inference speed benchmarks covering M-series memory bandwidth, model quantization, MLX framework optimization, and Mac configuration guidance.
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·4 min
Building a High-Performance Lock-Free Queue from Scratch: A Modern C++ Practical Guide
A deep dive into building high-performance lock-free queues with modern C++, covering CAS atomic operations, memory ordering, Michael-Scott algorithm, ring buffers, ABA problem solutions, and memory reclamation mechanisms.
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·3 min
Ideogram 4.0 Turbo Workflow: An AI Image Generation Solution Balancing Speed and Quality
Detailed look at the Ideogram 4.0 mixed turbo workflow: RTX 4090 inference in just 15 seconds, rivaling Krea2 speed, with stable output up to 8K resolution.
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·3 min
Laguna S 2.1: The Open-Source Coding Model That's 14x Smaller Yet Stronger
Poolside releases Laguna S 2.1, an open-source agentic coding model: 118B total params with only 8B active, scoring 40.4% on DeepSWE — ~4.5x DeepSeek V4 Pro Max. Supports 1M-token context, deployable on a single workstation.
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·7 min
Context Engineering: A Systematic Approach to Stop AI Agents from 'Talking Nonsense'
Context engineering is the core methodology for building efficient AI Agents, covering query enhancement, RAG retrieval, prompt design, memory management, and tool invocation. Master Write, Select, Compress, and Isolate to solve LLM hallucination at its root.
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·4 min
DSpark Open Source: DeepSeek's Inference Acceleration Tech That Doubles LLM Speed
DeepSeek and Peking University open-source DSpark, an inference acceleration technology using semi-autoregressive architecture and dynamic scheduling to boost LLM speed by 50%+ and double GPU concurrency without quality loss.
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·2 min
15-Year-Old Trains 200M MoE Language Model from Scratch: Full Architecture & Hands-On Breakdown
A 15-year-old trained Tiny-MoE, a 200M-parameter MoE language model from scratch using free Kaggle GPUs, featuring MLA attention, RoPE+YaRN, and native PyTorch.
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·3 min
The Rise of Diffusion Language Models: DiffusionGemma Crushes Autoregressive Models in Speed Tests
Diffusion language model DiffusionGemma dramatically outpaces autoregressive Deepseek Flash in speed tests. Explore the tech behind diffusion vs. autoregressive models and their challenges.
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·4 min
Zhipu GLM-5.2 Released: China's First Open-Source Model to Cross the 'Primary Model' Threshold
Zhipu releases GLM-5.2 with 1M token context, matching GPT-5.x and Claude. Zcode 3.0 offers 3M free daily calls with one-click migration from Claude Code and Codex.
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·7 min
Breaking Down the Core Skills of an AI Application Engineer: From Beginner to Industrial-Grade Deployment
Knowing how to call an API doesn't make you an AI engineer. This article breaks down the complete skill structure of an AI application engineer, covering Python fundamentals, LLM fine-tuning, Agent development, and enterprise projects.
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·4 min
Gemini Omni Hands-On: A Deep Dive into Google's Omni-Modal Video Generation Capabilities
An in-depth hands-on review of Google's Gemini Omni omni-modal AI model, covering video generation workflows, prompting tips, visual quality, and comparisons with Sora and other competitors.
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·4 min
LingBot-World 2.0 Meets SGLang: A Deep Dive into the Evolution of Real-Time Interactive World Models
SGLang-Diffusion now officially supports LingBot-World 2.0, delivering leaps in resolution and temporal consistency. With live sessions, chunked streaming, and camera control, world models achieve low-latency controllable interaction.
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·3 min
Designing MPMC Queues: Balancing Bounded Waiting and High-Performance Concurrency
An in-depth look at the core design challenges of MPMC queues: bounded waiting, lock-free mechanisms, sequence-number slots, dual-path strategies, and helping. Helping engineers balance throughput, fairness, and latency.
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·4 min
Is Computer Science Still Worth Learning in the AI Era? An Honest Answer for CS Students
When AI can write code and fix bugs, is learning CS still meaningful? This article breaks down the core value of CS study in the AI era: AI replaces execution, while judgment and systems thinking are what truly matters.
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·7 min
GPT-5.6 and Grok 4.5 Launch Simultaneously, Meta Unveils Agent-Based Image Model
OpenAI GPT-5.6 expands its preview, xAI Grok 4.5 opens access at the same time, Meta releases the Agent-based Muse Image model and Muse Video model, while Apple and DeepSeek launch in-house AI inference chip programs. A quick look at the week's five biggest AI stories.
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·4 min
Hands-On Test of GPT Real-Time Voice: A Comprehensive Review of Dialect Recognition, Emotional Expression, and Role-Play
An in-depth hands-on test of GPT's real-time voice feature, covering Cantonese and Sichuanese dialect recognition, emotional tone switching, complex role-play, and cross-voice contextual memory—objectively presenting the true level and remaining gaps of AI voice interaction.
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·7 min
Grok 4.5 Launch: Coding AI Market Reshuffle, Anthropic Claims Half the Territory
Grok 4.5 launches at just $0.49 per task, 90% cheaper than rivals. Anthropic's Claude Code claims 50% of the AI coding market. SambaNova raises $1B. Read the latest AI market shifts.
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·6 min
GPT Live Full-Duplex, Grok 4.5 Coding, Seedream 5.0 Images: AI Accelerates Across Three Tracks Simultaneously
OpenAI's GPT Live full-duplex voice model, Grok 4.5 coding model with Cursor, and ByteDance's Seedream 5.0 Pro image generation launched together. A deep dive into three AI releases.
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