#Token optimization
1788 related articles
Deep Dives·3 min
How NVIDIA AI Agents Turn Massive Video Feeds into Searchable, Real-Time Intelligence
Deep analysis of NVIDIA's latest video AI Agent solution, using multimodal LLMs and modular Skills architecture to transform massive surveillance video into searchable real-time intelligence.
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Tutorials·4 min
NVIDIA Model Optimizer Post-Training Quantization (PTQ) Practical Guide
A deep dive into NVIDIA Model Optimizer's PTQ workflow, covering INT8/INT4 quantization principles, calibration methods, RTX GPU optimization, and best practices for deploying quantized LLMs on consumer GPUs.
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Deep Dives·2 min
The MARVIS Project: A Complete Analysis of Embedded AI Agents Empowering Autonomous Space Exploration
Deep dive into how the MARVIS project deploys LLM agents on spacecraft, covering agent architecture, edge hardware token performance benchmarks, expert evaluations, and space AI benchmark planning.
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Deep Dives·3 min
AI Agent Core Principles Explained: The Decision Loop and Three-Component Architecture
Deep dive into AI Agent core principles: the Sense-Plan-Act-Observe decision loop, and how Planning, Memory, and Tools components transform LLMs into autonomous digital employees.
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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
8K Stars on GitHub: Deep Dive into the Most Comprehensive LLM Resource Repository
Deep analysis of the awesome-LLM-resources project (8200+ GitHub Stars), covering multimodal AI, Agents, MCP protocol, model training, o1 reasoning, SLMs, and more for LLM practitioners.
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Product Reviews·5 min
DeepClaude Open Source Analysis: DeepSeek + Claude Dual-Model Collaborative Code Generation
Deep dive into DeepClaude, a 2800+ Star open source project combining DeepSeek R1 reasoning with Claude 3.7 Sonnet code generation for superior AI output.
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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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Tutorials·3 min
Google AI Studio Tutorial: A Comprehensive Guide to Gemini from Beginner to Advanced
A detailed guide to Google AI Studio and Gemini's three usage methods, covering YouTube video analysis, voice generation, Imagen 4 text-to-image, Gemini Live multimodal interaction, and building apps with natural language.
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Tech Frontiers·3 min
Claude Platform Officially Launches on AWS: Complete API, IAM Authentication & EDP Credits Explained
Claude Platform is now GA on AWS, offering enterprises the complete Claude API with IAM-native auth, unified billing, and EDP committed spend credits.
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Product Reviews·4 min
GPT-OSS 120B/20B Open-Source Model In-Depth Review: Comprehensive Testing on Hallucination, Reasoning, and Code
Comprehensive review of OpenAI's open-source GPT-OSS 120B and 20B models covering hallucination testing, logical reasoning, code generation, SQL queries, and document analysis with deployment guides.
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Product Reviews·4 min
Coze vs Dify vs n8n: In-Depth Comparison of the Top 3 AI Workflow Platforms in 2025
2025 comprehensive comparison of Coze, Dify, and n8n AI workflow platforms. Choose Coze for personal use, Dify for enterprise quick deployment, n8n for deep customization. Includes node comparison table and real-world cases.
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Deep Dives·4 min
The Agentic AI Explosion: A Complete Guide to the Paradigm Shift from Generative to Agentic AI in 2026
In 2026, the AI industry shifts from generative to Agentic AI. Deep dive into GPT-5.5 agent capabilities, Claude's autonomous learning, Physical AI deployment, DeepSeek V4, inference optimization, and the global AI competition landscape.
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Tutorials·3 min
OpenAI Open-Sources GPT-OSS: Run O4-Level Models on 16GB VRAM — Complete Deployment Guide
OpenAI open-sources GPT-OSS (20B/120B) with MOE architecture and native FP4 precision. Run O3-level reasoning on a single RTX 4090. Full deployment guide for Ollama, vLLM, and more.
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Research·4 min
MEME Benchmark Reveals Critical Flaws in LLM Memory Systems: Dependency Reasoning Accuracy Below 50%
MEME benchmark first evaluates LLM memory dependency reasoning across 6 major systems—best accuracy only 42%. Deep analysis of cascade and missing task failures reveals path to next-gen AI memory.
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Research·4 min
Skills-Oriented Programming: Domain Knowledge Engineering for Efficient Code Generation by Code Agents
Alibaba Mama's Skills-Oriented Programming methodology uses three-layer Skill structures, progressive disclosure, and four-layer anti-corruption systems to achieve 90%+ code generation accuracy for Code Agents in complex enterprise codebases.
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Tutorials·4 min
Anthropic's Official Agent Building Guide: A Complete Breakdown of Workflows vs. Agents
Deep dive into Anthropic's Building effective agents guide: workflow vs. agent distinctions, the technical selection pyramid, and framework pitfalls for building efficient LLM agents.
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