#PyTorch
415 related articles
Expert Opinions·2 min
Karpathy on the Future of Programmers in the AI Era: Outsource Thinking, But Not Understanding
OpenAI co-founder Karpathy explains why taste, judgment, and deep understanding remain irreplaceable for programmers in the AI era, plus startup opportunities in agent-native infrastructure.
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Industry Insights·2 min
Anthropic Acquires Stainless API: A Strategic Play for SDK and MCP Ecosystem Dominance
Anthropic acquires SDK platform Stainless API, internalizing core developer tools. Analysis of the strategic logic: controlling developer experience, strengthening MCP ecosystem, and the AI vertical integration trend.
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Tutorials·2 min
Deep Learning Beginner Tutorial: From Neural Network Fundamentals to Image Recognition in Three Days
A systematic review of a three-day deep learning crash course covering neural network math, gradient descent, backpropagation, TensorFlow, CNNs, and transfer learning with practical tips.
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Tutorials·2 min
The Truth About Making Money with Python as a Side Hustle: A Complete 2025 Analysis of Barriers, Income & Market Competition
In-depth analysis of Python side hustle realities in 2025: learning barriers, freelance pricing, market competition, and new AI-era opportunities from scraping to LLM app development.
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Tutorials·2 min
LangChain Unified Interface in Practice: init_chat_model Usage & DeepSeek Troubleshooting Guide
Guide to LangChain's init_chat_model unified interface vs model classes, with DeepSeek V4 Pro thinking mode fix, multi-provider switching tips, and AI Agent integration practices.
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Tutorials·2 min
FastEmbed Tutorial: Installation and Practical Guide for a Lightweight Local Vector Embedding Library
A detailed guide to FastEmbed, a lightweight Python embedding library covering installation, text and image embedding usage, and seamless Qdrant vector database integration for building local AI apps without GPU.
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Tutorials·2 min
Senior Developers Transitioning to AI: A 2025 Pitfall-Avoidance Guide & Practical Roadmap
How can 30+ programmers efficiently transition to AI? Practical advice on learning strategy, project experience, and interview techniques to break into AI.
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Tutorials·2 min
Docker Model Runner Tutorial: Run AI Models Locally with a Single Command
Learn how to install, configure, and use Docker Model Runner to run AI models locally with Docker Compose integration, OpenAI API compatibility, and zero-config LLM deployment.
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Tutorials·1 min
HuggingFace Transformers Beginner's Guide: Model Download, Pipeline Inference, Training & Saving
Learn HuggingFace Transformers core usage: pretrained model download, Pipeline API for sentiment analysis, Tokenizer principles, model inference with Softmax, and saving workflows with Python examples.
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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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Expert Opinions·2 min
The AI Power Struggle: Should Superintelligence Be Monopolized or Decentralized for All?
Control of AI superintelligence is becoming a defining issue of our time. This article analyzes centralization risks, the open-source movement, and a balanced third path for AI governance.
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Product Reviews·2 min
LightningRAG: A Full-Stack RAG Framework in Go, Built with Vue + Gin for High-Performance Retrieval-Augmented Generation
LightningRAG is an open-source full-stack RAG framework built with Vue and Gin, supporting knowledge base management, vector search, and multi-model integration. A deep dive into its architecture and comparison with LangChain and Dify.
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Product Reviews·2 min
iNaturalist AI Species Identification in Practice: A PyCon Developer's Birdwatching Record on the Los Angeles River
A Python developer goes birdwatching on the LA River after PyCon US, using iNaturalist's AI species identification to record four waterbirds. Exploring how citizen science, computer vision, and urban ecology converge.
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Expert Opinions·2 min
In the Age of AI Coding, Is It Still Worth Learning to Program?
When AI writes code faster than most engineers, should ordinary people still learn to program? A veteran developer analyzes how coding skills become the lever for harnessing AI productivity.
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Tutorials·1 min
Python Learning Roadmap for Beginners: 9 Weeks, 16 Hands-On Projects from Zero to Computational Thinking
A teaching-proven Python beginner roadmap: 9 weeks, 3 phases, 16 hands-on projects. From ten lines of code to computational thinking mastery.
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Tutorials·2 min
Getting Started with Physical AI Robot Full-Stack Development: A Complete Tech Stack Guide from Hardware to ROS2
A beginner's guide to physical AI robot development covering the complete tech stack from GPU hardware, Linux, Python, deep learning, computer vision to ROS2, with a clear learning roadmap.
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Tutorials·2 min
NCCL Multi-GPU Communication Optimization in Practice: A Guide to Scaling HPC High-Performance Computing
Deep dive into NVIDIA NCCL multi-GPU communication library principles and optimization strategies, covering AllReduce, NVLink, and GPUDirect RDMA to help HPC and AI developers master scaling from single-node to massive clusters.
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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·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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Product Reviews·4 min
Cube Studio Deep Dive: Tencent's Open-Source One-Stop MLOps Platform
Deep dive into Cube Studio, Tencent Music's open-source one-stop AI platform, covering architecture design, distributed training, large model fine-tuning and inference, and domestic chip adaptation.
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