Abstract: For the online distributed estimation problem of time-varying parameters, we study a linear regression model with measurement noises over time-varying random graphs. We propose a distributed ...

Transformation in contact has fundamentally changed the Army. The new mobile brigade combat team (MBCT) is more lethal, agile, and technologically enabled than ever before, but it is also logistically ...

Effective task allocation has become a critical challenge for multi-robot systems operating in dynamic environments like search and rescue. Traditional methods, often based on static data and ...

Forbes contributors publish independent expert analyses and insights. Originally developed by Anyscale, Ray is an open source distributed computing framework for AI workloads, including data ...

Meta has open-sourced CTran, the tech giant’s custom transport stack used to perform in-house optimizations. Detailed in a PyTorch blog post, first picked up by SemiAnalysis, CTran contains multiple ...

When splitting a simple model that contains an nn.Embedding layer into pipeline stages with the torch.distributed.pipelining.pipeline API, the pipeline representation incorrectly calls the embedding ...

We are trying to run distributed training with Torchtitan on a GB200 NVL72 cluster but using more than 10 trays (40 GPUs) fails with a NCCL segmentation fault. Using 10 and less trays works fine. We ...

In this tutorial, we guide you through the development of an advanced Graph Agent framework, powered by the Google Gemini API. Our goal is to build intelligent, multi-step agents that execute tasks ...

Reinforcement learning has emerged as a powerful approach to fine-tune large language models (LLMs) for more intelligent behavior. These models are already capable of performing a wide range of tasks, ...

NVIDIA and Meta's PyTorch team introduce federated learning to mobile devices through NVIDIA FLARE and ExecuTorch. This collaboration ensures privacy-preserving AI model training across distributed ...