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Scaling Federated Learning Across Docker, Kubernetes, and Slurm with NVIDIA FLARE

Federated learning (FL) projects often begin with a straightforward setup: one server, a few clients, and one dataset at each site. As those projects grow, the...

Federated learning (FL) projects often begin with a straightforward setup: one server, a few clients, and one dataset at each site. As those projects grow, the challenge shifts from running an algorithm to operating shared infrastructure. GPUs must be allocated when jobs need them, multiple research studies must remain separated, and every participating organization must retain control of its own…

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How Many Labeled Examples Does a Text Classifier Actually Need? I Measured It.

Before reaching for an LLM API on every classification problem, it's worth knowing what a decades-old baseline can already do with the labeled data you have β€” and exactly how much more data buys you.

The post How Many Labeled Examples Does a Text Classifier Actually Need? I Measured It. appeared first on Towards Data Science.

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High-Throughput Structure Prediction with BioNeMo Inference Runtime

Biomolecular structure prediction is now often run at proteome scale, where the goal is to move an entire worklist through the pipeline efficiently. NVIDIA...

Biomolecular structure prediction is now often run at proteome scale, where the goal is to move an entire worklist through the pipeline efficiently. NVIDIA BioNeMo Inference Runtime (BioIR) helps accelerate supported biomolecular structure-prediction models on NVIDIA GPUs while keeping the familiar PyTorch workflow. It uses optimized kernels and, where applicable, CUDA Graphs to speed model…

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Introducing CUDA Rust: Two Tracks for Writing GPU Kernels

In September 2026, NVIDIA announced it is leaning into native GPU programming in Rust. CUDA C++ and CUDA Python are mature, enterprise-grade toolchains, and...

In September 2026, NVIDIA announced it is leaning into native GPU programming in Rust. CUDA C++ and CUDA Python are mature, enterprise-grade toolchains, and NVIDIA will be growing and maturing CUDA Rust into 2027 and beyond The systems layer of AI spans inference engines, serving infrastructure, drivers, and agent runtimes, and it churns constantly as models and techniques change.

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Text Watermarking in Python: Catch Whoever Copies Your Writing

AI companies quietly watermark billions of words a day. Here’s how to apply the same three families of techniques to your own writingβ€”and what real experiments reveal about which watermarks survive copy-paste, editing, and paraphrasing.

The post Text Watermarking in Python: Catch Whoever Copies Your Writing appeared first on Towards Data Science.

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The Power BI Developer's Survival Guide to Microsoft Fabric

Power BI Premium is gone. Microsoft Fabric took its place. Here's what actually changed for you, what didn't, and where to start β€” without the panic.

The post The Power BI Developer's Survival Guide to Microsoft Fabric appeared first on Towards Data Science.

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Restore LLM Inference Capacity in Seconds with Shadow Engine Recovery in NVIDIA Dynamo

Decorative image.When an LLM engine process fails, the standard recovery path involves a cold restart. This requires loading weights into HBM from storage, compiling kernels,...Decorative image.

When an LLM engine process fails, the standard recovery path involves a cold restart. This requires loading weights into HBM from storage, compiling kernels, and capturing NVIDIA CUDA graphs. For large models, initialization can take several minutes, during which surviving workers must absorb the displaced traffic. Shadow engine recovery, available as a preview feature in NVIDIA Dynamo…

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