Building GeneSign: Synthetic DNA Watermarking and Biosecurity Firewall with NVIDIA Nemotron

Nvidia projected a doubling of semiconductor shipment volume next year alongside a 70 percent revenue increase. In an industry facing four-year transformer backlogs and extended utility interconnection queues, shipping twice as much silico…

Nvidia shipped two native Rust tracks for writing CUDA kernels — cuda-oxide and cutile-rs. No FFI, no wrapper, compiler-enforced memory safety on the GPU. Here's what it does, what it doesn't, and why the moat conversation just changed.

-- Executive Summary -- The evolution of Extract, Transform, Load (ETL) processes is...

On September 3, NVIDIA confirmed it is buying Hugging Face for $12.93 billion. The platform that...

Almost every AI lab now hands out a free tier. Google, Groq, Cerebras, Mistral, Cohere, NVIDIA,...

Does Jalapeño beat NVIDIA? On the benchmark OpenAI published, yes. Does that make it a better chip...

NVIDIA 发布教程，讲解在 Jetson 上部署新一代开放推理模型的方法，以 Nemotron 3.5 Lightning 和 Qwen3.8-27B 为例。

本教程演示如何用 NVIDIA SkillSpector 评估 AI 技能的安全态势，构建包含干净、风险、恶意及 MCP 示例的合成技能市场，并通过 LangGraph 检查流水线扫描每个技能。

该教程基于 NVIDIA cuTile Python 实现了分块 GPU 内核编程工作流，在 Colab 环境中配置 GPU、驱动、CUDA 及 cuTile 可用性后，分别构建了 tiled 向量加法、矩阵加法和矩阵乘法核函数，并以 PyTorch 作为回退保持 notebook 可执行。每一步均通过 PyTorch 验证结果正确性，并基准测试了各阶段的中位运行时间。

本文是 PyTorch profiling 系列的开篇，从最简单的矩阵乘法加偏置操作出发，逐步讲解如何使用 `torch.profiler` 进行性能分析。涵盖 profiler 设置、导出统计表格与 Chrome trace、解读 CPU 和 GPU 活动的时序关系，以及 `torch.compile` 对底层 CUDA kernel 调用链的影响。实验基于 NVIDIA A100-SXM4-80GB GPU 运行，面向基本掌握 PyTorch 但缺乏 profiling…