#data model
7808 related articles
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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Tutorials·3 min
LangGraph Multi-Agent in Practice: Building a Medical Agent System from Scratch
A deep dive into LangGraph multi-agent architecture for healthcare, covering LangChain, RAG, and MCP integration, from requirements analysis to Agent orchestration.
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Tutorials·2 min
Beginner's Guide to AI Large Language Models: GPU Requirements & Core Tech Stack Explained
2025 complete guide to AI LLMs: local deployment GPU/VRAM requirements (RTX 4090/24GB) and core tech stack including Prompt Engineering, Agents, MCP, LangGraph, and WorkFlow orchestration.
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Tutorials·4 min
Google AI Studio Tutorial: A Complete Guide to Building AI Apps with Zero Code
Complete guide to Google AI Studio: interface layout, Gemini model selection, parameter tuning, and building zero-code AI apps with Build. Covers image, video, and music generation with practical examples.
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Deep Dives·3 min
AI Model Deployment Pipeline Friction: How TensorRT Systematically Eliminates Inference Optimization Bottlenecks
Deep dive into pipeline friction in AI model deployment from training to production, covering TensorRT automated optimization, ONNX export, and Triton Inference Server best practices.
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Deep Dives·3 min
NVIDIA Vera Rubin Platform Deep Dive: Solving the Scalability Challenge of Agentic AI Inference
Deep dive into NVIDIA's Vera Rubin platform Pod-level architecture and next-gen NVLink, revealing how it solves Agentic AI inference scalability bottlenecks and the industry shift from training-first to inference-first.
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Deep Dives·3 min
NVIDIA Fleet Intelligence Explained: Real-Time Monitoring and Intelligent Optimization for GPU Clusters
Deep dive into NVIDIA Fleet Intelligence for GPU clusters: real-time visualization, AI anomaly detection, utilization optimization, and energy management to boost large-scale GPU infrastructure efficiency.
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Tech Frontiers·2 min
OpenClaw's Six Rename History: Tracing an Open Source Project's Naming Evolution Through Git Commit Records
OpenClaw went through six renames from Warelay to its final name. Simon Willison used a Python script to reconstruct this complete naming evolution from Git commit history.
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Tech Frontiers·2 min
Google's AI Triple Launch: A Complete Breakdown of AI Studio, Gemini Desktop, and Colab MCP
Deep dive into Google's three latest AI updates: AI Studio's Anti-Gravity agent with Firebase full-stack development, Gemini's native macOS desktop app, and Colab MCP Server enabling AI agents to execute Python code directly.
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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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Tech Frontiers·3 min
Snap, YouTube, and TikTok Reach First-Ever School Addiction Lawsuit Settlement
Snap, YouTube, and TikTok settle the first-ever lawsuit alleging social media addiction caused financial harm to a U.S. school district, potentially triggering nationwide litigation and stricter youth protection regulations.
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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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Product Reviews·2 min
Firecrawl: The AI Web Scraping Powerhouse with 120K Stars — Essential for RAG Development
Deep dive into Firecrawl: an open-source web search, scraping, and data cleaning tool designed for AI Agents. Supports JS rendering, smart content extraction, and Markdown output — core infrastructure for RAG systems and AI automation.
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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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Tech Frontiers·3 min
The Sony AI Camera Assistant Controversy Explained: Suggestions Only, No Photo Manipulation — Xperia's Imaging Philosophy Stays the Course
Sony responds to the Xperia 1 XIII AI Camera Assistant controversy, clarifying the AI only offers shooting suggestions — not photo edits. Full breakdown of how it works and industry implications.
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Tutorials·3 min
Claude Code Advanced Tutorial: Subagent Parallel Processing, MCP Tool Integration & Skills Automation
Deep dive into three advanced Claude Code features: Subagent parallel processing, MCP protocol for external tools like Playwright, and Skills for workflow automation. Includes practical examples.
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Tutorials·3 min
Veo 3.1 Free Without Watermark: Two Methods to Generate Cinema-Quality AI Videos
Two free methods to use Google Veo 3.1 for watermark-free cinema-quality AI videos via Google AI Studio and Google Vids, with full steps and daily limit workarounds.
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Expert Opinions·4 min
Claude Code vs Cursor Deep Dive: The AI Coding Tool Landscape Is Being Disrupted
Deep analysis of why Claude Code is replacing Cursor and Windsurf, covering tool calling mechanisms, model optimization advantages, real-world cases, and optimal workflow configurations.
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