ai技术

NVIDIA Isaac Sim正成为机器人与智能制造领域首选的物理仿真平台。其开源、多平台扩展、深度AI集成等优势，为研发团队带来高保真物理/视觉仿真、合成数据自动化与大规模测试能力。高度兼容ROS...

The Gaussian distribution (also known as the normal distribution) is the most fundamental and widely used probability model in statistics and data science. Its "bell curve" describes the distribution patterns of numerous natural phenomena and social data. This article, from the perspective of in-depth news reporting, systematically analyzes the basic principles, mathematical formulas, and classic applications of the Gaussian distribution...

The Swin Transformer, an innovative architecture that integrates the hierarchical design of Transformers with convolutional heuristics, became a mainstream model in computer vision in 2025. It boasts state-of-the-art performance, excellent hardware compatibility, and multi-size adaptability...

This article, from a news reporting perspective, focuses on five key techniques used by AI platforms and enterprises in model compression and inference acceleration: quantization, pruning, knowledge distillation, lightweight architecture design, compilers, and hardware acceleration. The content covers mainstream methodologies...

2024年，NVIDIA CUDA 11.8 依然是AI开发与深度学习主流平台。本文以新闻报导形式，结合最新官方文档和案例，全面拆解CUDA 11.8的安装与配置要点，深度分析新手常踩的“坑”，如驱动...

MGX is NVIDIA's modular AI server architecture, poised to revolutionize the AI industry in 2025. The MGX platform employs a modular design philosophy, supporting various GPUs, CPUs, and cooling methods, providing enterprises and research institutions with a flexible foundation for AI computing power. This article provides an in-depth analysis of MGX...

Human-feedback-based reinforcement learning (RLHF) is poised to become an indispensable core technology for large-scale model training and intelligent upgrades in the AI field by 2025. This article comprehensively reviews the fundamental principles of RLHF, its differences from traditional RL, key training processes, and mainstream application tools, and delves into data bottlenecks, reward models, etc.

Overfitting is a core challenge in machine learning, referring to a model's excessive fit to training data, which reduces its predictive ability for new data. As AI becomes increasingly prevalent in industries such as healthcare, finance, and e-commerce, overfitting not only affects decision accuracy but can also pose significant risks. This….

本文专业解析DETR（Detection Transformer）目标检测框架的技术原理、主流结构与2025年前沿迭代，并对比传统检测器优势，涵盖Deformable DETR、DINO、RT-DET...