#constrained decoding
95 related articles
·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
From Enter to First Token: Decrypting the Full LLM Inference Pipeline (Autoregression, KV Cache & Decoding Strategies)
From pressing Enter to the first character appearing, what happens inside an LLM? This article breaks down autoregressive generation, KV cache acceleration, and decoding strategies like temperature, Top-k, and Top-p.
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·3 min
CPU-Native Language Models: Breaking Through Inference Bottlenecks with Memory Bandwidth Co-Design
SiliconLLM builds a CPU-native LLM architecture from scratch, combining selective SSM, ternary (1.58-bit) LUT MLP, and granular MoE, co-designed around the L3 cache bandwidth cliff. Ternary kernels show 4-5x speedup over fp32.
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·6 min
The Eight-Step Method for Agent Development: A Practical Path from Pitfalls to Production
Many enterprises fail at AI Agents due to choosing the wrong tools and lacking methodology. This article outlines an eight-step Agent development method—from cognitive foundations, scenario selection, hand-writing ReAct, and structured output to Tool Use, RAG, evaluation sets, and production fallback.
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·5 min
OpenAI GPT-Live Full-Duplex Voice Model: Reshaping the Human-Computer Interaction Gateway
OpenAI unveils GPT-Live, a full-duplex voice model with real-time interruption, tiered compute routing, and dynamic UI rendering—surpassing Siri and targeting the OS-level voice gateway.
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·7 min
Building AI Agents in Rust: The GAIA Benchmark Reveals the Capability Ceiling of Large Models
A Rust-based AI Agent evaluation framework uses the GAIA benchmark to compare GPT, Claude, DeepSeek and other models with no tools. Results show pure LLMs cap at ~25% accuracy, revealing why tool use is decisive for Agents.
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·5 min
GPT-5.6 Triple Launch: Understanding the Positioning and Key Differences of Sol, Terra, and Luna
OpenAI released three GPT-5.6 models—Sol, Terra, and Luna—covering everything from flagship reasoning to lightweight speed. A deep dive into their positioning, performance differences, pricing, and industry signals.
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·4 min
meshoptimizer: A Deep Dive into This Open-Source 3D Mesh Compression and Rendering Optimization Library
meshoptimizer is a lightweight C++ open-source library offering vertex cache optimization, overdraw reduction, mesh compression, quantization, and LOD simplification for game engines, WebGL, and glTF pipelines.
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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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·4 min
GPT-5.6 Sol vs Grok 4.5: Same $20 Subscription — Which One Is Actually Worth It?
GPT-5.6 Sol or Grok 4.5 — both at $20/month, but which delivers more value? We break down use cases, intelligence benchmarks, and ecosystem tradeoffs to help you decide.
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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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·6 min
Why Is Qwen3 27B So Slow on a 4090? A Hands-On Guide to Local Inference Performance Optimization
RTX 4090 taking over 400 seconds to run Qwen3 27B inference? This article analyzes the core causes—VRAM overflow and CPU offloading drag—and offers targeted fixes.
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·4 min
8-Step AI Agent Development Guide: From Zero to Production
Demo works but production fails? This guide covers the full AI Agent development path: when to use Agents, hand-writing ReAct loops, tool schemas, RAG, eval sets, and production fallback strategies.
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·7 min
GPT-5.6 In-Depth Hands-On Review: How Do Soul, Tara, and Luna Really Perform?
OpenAI releases GPT-5.6 preview with three models: flagship Soul, balanced Tara, and lightweight Luna. Based on real KingBench 3 testing, this article breaks down each model's performance on math, front-end, and agentic tasks, and compares them with Anthropic Fable.
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·7 min
Complete Guide to Training Small Models on Kaggle's Free Compute: GPU Quotas and Practical Tips
In-depth guide to Kaggle's free-tier compute: P100/T4 GPU with 30 hours/week quota, 12-hour sessions, suitable models like CNN and BERT fine-tuning, plus tips like mixed precision and checkpointing to start deep learning at zero cost.
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·6 min
MIRA: An Analysis of a Multiplayer Interactive World Model Built on Rocket League
MIRA is an interactive world model project for the multiplayer competitive game Rocket League, exploring how neural networks simulate multi-agent interaction and complex physics. An in-depth look at its significance, challenges, and prospects.
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·5 min
Ideogram 4 Local Deployment in Practice: One-Click Image Generation with a Fully Automated ComfyUI Workflow
Deep dive into Ideogram 4's core strengths: realistic photographic quality, powerful text generation, and Chinese prompt support. Learn to skip complex JSON prompts with a fully automated ComfyUI workflow + Qwen3—input your idea, get an image instantly, deployable locally at just 8GB.
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·5 min
Is AI Inference Really Profitable? Deconstructing the Cost Economics of Inference vs. Training
Are AI companies really losing money? This article deconstructs the fundamental differences between training and inference costs, revealing why pure AI inference services have structural profitability.
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·7 min
Sakana Fugu vs GLM 5.2 Hands-On Test: Who Can Truly Challenge Top-Tier AI Models?
A head-to-head hands-on test of Sakana Fugu vs GLM 5.2 based on real Hermes agent workflows. Covering tool calling, frontend generation, and code improvement to reveal each model's true performance, speed, and value.
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