This project contains implementations of simple neural network models, including training scripts for PyTorch and Lightning frameworks. The goal is to provide a modular, easy-to-understand codebase ...

Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...

Chip designs are busting out beyond the reticle limits of lithography machines, making chiplets and high-bandwidth, in-package die-to-die interconnects inevitable. And AI training workloads are ...

AI data centers require a stable, baseload energy supply. And that makes them a great fit for SMRs. Photo courtesy Stantec This blog post was authored by Jag Singh, Regional Sector Lead of Clean ...

physics_informed_neural_network/ ├── app/ # FastAPI application │ ├── __init__.py │ ├── api/ # API endpoints │ │ ├── __init__.py ...

Abstract: Artificial intelligence (AI) continues to be transformative across various domains, integrating learning paradigms like machine learning, modular learning, and federated learning. In ...

As demand for clean electricity to run data centers increases, operators are considering nuclear energy. But the path to power has a few roadblocks. Data center power constraints and burgeoning AI ...