#autoregressive model
493 related articles
Expert Opinions·2 min
The Faster AI Generates Code, the Faster Your Project Dies: Trust Engineering Is the Real Bottleneck
AI programming drives code generation cost to zero, but verifying correctness is the ultimate bottleneck. GitClear data shows 10x copy-paste surge. Developers must shift from writing to verifying code.
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Tutorials·2 min
vLLM and SGLang Local Deployment Tutorial: A Practical Guide to 3-8x Performance Gains
Complete guide to deploying vLLM and SGLang locally. Compare performance vs LM Studio, deploy in 3 steps with Docker + AI assistant. Covers SGLang vs vLLM selection, 5090 VRAM optimization, and Cherry Studio integration.
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Tech Frontiers·1 min
Qwen3.6 MTP Acceleration Benchmarked: Single GPU Inference Hits 220 token/s
Qwen3.6 experimental MTP-GGUF benchmarked: single GPU pushes 35B-A3B model to 220 token/s, 1.4x faster with zero accuracy loss. Covers MTP principles, optimal Draft Tokens strategy, and RTX 5090 results.
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Product Reviews·1 min
Qwen 3.6 MTP Real-World Test: The Secret to a 20% Speed Boost with Just Three Parameters
Real-world test of Qwen 3.6 Multi-Token Prediction (MTP): boost inference speed from 34.2 to 41 tokens/s with just three parameters in ik_llama.cpp — zero quality loss, zero extra models.
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Tech Frontiers·1 min
Claude 4 Launch: Opus and Sonnet Dual Models Explained, Coding Agent Capabilities Fully Upgraded
Anthropic launches Claude 4 Opus and Claude 4 Sonnet. Claude Code goes GA with IDE integration and SDK. MCP protocol connects directly to API. Full breakdown of coding and agent upgrades.
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Deep Dives·1 min
Harness Engineering Explained: Core Methodology and Implementation Guide for Industrializing AI Agents
Deep dive into Harness Engineering methodology: Agent=Model+Harness formula, the Prompt→Context→Harness evolution path, and a developer implementation guide.
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Tutorials·4 min
AI Agent Memory Architecture Design: Four-Layer Partitioning + Bitemporal Modeling Practical Guide
A deep dive into production-grade AI Agent memory architecture covering four-layer partitioning, bitemporal modeling, and skill extraction to eliminate hallucinations and historical amnesia.
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Tech Frontiers·3 min
DeepSeek V3.2 Released: Reasoning on Par with GPT-5, First to Integrate Deep Thinking into Tool Use
DeepSeek V3.2 is officially released and open-sourced with reasoning on par with GPT-5, second only to Gemini 3.0 Pro. First to integrate deep thinking into tool use, with top-tier agent capabilities and an IMO 2025 gold medal.
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Deep Dives·1 min
Beginner's Guide to AI Agents: Core Principles, Technical Architecture, and Application Scenarios Explained
A systematic guide to AI Agents covering core principles of perception, decision-making, and action, plus the technical stack of LLMs, tool calling, memory systems, and RAG, with real-world use cases.
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Product Reviews·2 min
GPT-5.5 In-Depth Review: Real-World Performance in Coding, Research, and Presentations
In-depth hands-on review of GPT-5.5's real-world performance in coding, data analysis, presentation generation, and visualization — with comparison to o4-mini and best-practice prompting tips.
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Tutorials·2 min
MoS-TTS-Nano Deployment Guide: Ultra-Lightweight 0.1B TTS Model That Runs on CPU
Battle-tested MoS-TTS-Nano local deployment guide. 0.1B ultra-lightweight TTS model runs on quad-core CPU without GPU. Covers Conda setup, pynini installation fixes, model download, and Gradio WebUI.
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Product Reviews·3 min
OpenAI Codex Free Design Features Tested: How Does It Compare to Claude Design?
OpenAI Codex launches free design features with GPT Image 2 for a complete design-to-code pipeline. Detailed comparison with Claude Design on text rendering, code conversion, and workflow completeness.
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Tutorials·4 min
Harness Engineering in Practice: A Three-Layer Architecture for Taming AI Agent Development
A detailed guide to Harness Engineering's three-layer architecture for controlling AI Agent code generation quality, covering the Information, Constraint, and Automation layers with practical setup and pitfall avoidance tips.
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Tech Frontiers·4 min
Step 3.5 Flash Deep Dive: How a 196B Parameter Open-Source Model Beat Gemini
Deep dive into StepFun's Step 3.5 Flash: 196B parameter MoE model activating only 11B, 350 tokens/sec coding speed, 256K context window, local deployment ready. How it beats Gemini 3 Flash.
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Tutorials·3 min
Grammar-Constrained Decoding: A Practical Guide to Generating Reliable Bash Code with Small Models
Deep dive into Grammar-Constrained Decoding (GCD) technology: applying Bash syntax constraints during inference to dramatically improve small language models' code generation correctness and executability for AI Agent edge deployment.
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Deep Dives·3 min
NVIDIA Dynamo Multi-Turn Agentic Interaction: Deep Integration of Streaming Tokens and Tool Calling
Deep dive into NVIDIA Dynamo's multi-turn agentic interaction support, covering streaming token output, structured tool calling, state management, and MoE synergy for production-grade AI agents.
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Deep Dives·3 min
The Truth About AI Writing Code: Can It Actually Program? A Complete Breakdown
Can AI really program? This article explains how LLMs generate code through massive training and pattern matching, and analyzes the true capabilities and limitations of AI coding tools.
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Product Reviews·3 min
GitHub 8K Stars: Deep Dive into the Most Comprehensive LLM Resource Repository
Deep analysis of the GitHub project awesome-LLM-resources covering multimodal generation, AI Agents, MCP protocol, model training/inference, o1 models, and SLMs—a community-verified 8200+ Star LLM learning resource hub.
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Deep Dives·5 min
Hugging Face Transformers: A Comprehensive Guide to the 160K-Star Open-Source AI Framework
Comprehensive guide to Hugging Face Transformers, the 160K-star GitHub framework—covering architecture, multimodal support, quantization, and inference optimization for loading, fine-tuning, and deploying pre-trained models.
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Product Reviews·4 min
Hugging Face Transformers: Deep Dive into the 160K-Star Open Source AI Model Framework
Deep dive into Hugging Face Transformers: architecture, multimodal support, ecosystem, and trends. Learn how this 160K-Star project became essential for AI developers.
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