DEEP-LEARNING

Go beyond simple imports by building a functional machine learning framework from scratch. Learn how TinyTorch demystifies tensors, autograd, and transformer architectures.

An in-depth look at how pediatric hospitals leverage NVIDIA open-source AI frameworks to improve cardiac imaging, diagnostics, and patient outcomes.

Explore how the University of Manchester utilizes NVIDIA Earth-2 digital twin technology and generative AI surrogate models to transform UK air pollution forecasting, overcoming legacy atmospheric chemistry bottlenecks.

An in-depth technical analysis of PyTorch Conference North America 2026, covering TorchDynamo graph capture, TorchInductor codegen, cross-hardware Triton DSL kernels, FSDP2, torchao quantization, and high-performance LLM serving.

A deep dive into the fundamental logic behind the Transformer architecture, exploring the 'why' before the 'how' of Queries, Keys, and Values.

Master the art of performance optimization in PyTorch using the native torch.profiler tool. Learn how to identify bottlenecks, visualize execution traces, and optimize your deep learning models for maximum efficiency.

An in-depth technical analysis of Timer-XL, a decoder-only Transformer foundation model designed to handle extreme context lengths in time-series forecasting, and how it outperforms traditional architectures.

While the world focuses on Nvidia's H100 and Blackwell GPUs, the real secret to their trillion-dollar dominance lies in CUDA. This deep dive explores how software, not just silicon, created an unassailable moat for AI development.

An in-depth technical analysis of the EMO framework, exploring how Mixture of Experts (MoE) models can achieve true modularity through specialized pretraining techniques and the implications for the future of efficient LLM scaling.

Explore Andrej Karpathy's revolutionary autoresearch project, which shifts the AI development paradigm from manual coding to autonomous agent-driven experimentation.

An exhaustive technical breakdown of Andrej Karpathy's microGPT, exploring character-level tokenization, the custom Value autograd engine, and the structural implementation of Transformer blocks without modern libraries.

NVIDIA has released its Earth-2 open models on Hugging Face, offering a comprehensive suite of AI-driven weather forecasting tools from global predictions to high-resolution regional downscaling.