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13 Interestana reports mention PyTorch, newest first. Each is summarised from the original reporting and links back to its publisher.
Researchers have developed a method to construct an end-to-end streaming robotics learning pipeline utilizing the NVIDIA Cosmos3-DROID dataset without requiring a full local download of its substantial 707 GB repository.
A comprehensive tutorial has been released detailing the creation of an end-to-end multimodal data augmentation and robustness workflow utilizing the AugLy library. This workflow is designed to handle images, text, and audio data, addressing modern dependency compatibility issues and generating…
Microsoft's Azure Kubernetes Service (AKS) engineering team has open-sourced TauGrid, a new platform designed to streamline the deployment and management of AI workloads on Kubernetes clusters equipped with GPU nodes.
NVIDIA has introduced the BioNeMo Inference Runtime (BioIR), a new Python library engineered to dramatically accelerate the performance of supported biomolecular structure prediction models when executed on NVIDIA GPUs. This development is particularly timely as the field of biomolecular structure…
NVIDIA Earth2Studio has been utilized in a tutorial to construct custom, batched ensemble weather forecasting workflows. This process involves installing the necessary Earth2Studio components, ensuring compatibility with an existing CUDA-enabled PyTorch environment within Google Colaboratory.
Gradio, a popular open-source Python library for creating user interfaces for machine learning models, has introduced a suite of updates designed to simplify the entire AI workflow, from development to deployment.
NVIDIA has released TensorRT Model Connect (TRTMC) in public preview, an open-source project designed to streamline the conversion of machine learning models into highly optimized native C++ inference engines. This new tool allows users to take supported Hugging Face…
A comprehensive tutorial has been released detailing the development of an end-to-end document intelligence pipeline utilizing the docTR library. This pipeline integrates multiple stages of document processing, including text detection, text recognition, geometry analysis, layout analysis, structured data extraction…
A comprehensive tutorial has been released detailing an end-to-end supervised fine-tuning (SFT) pipeline designed to enable large language models (LLMs) to effectively call external tools. This process leverages the XYZ-Aquila-SFT dataset, the Hugging Face Transformers library, PyTorch, and the Parameter-Efficient…
NVIDIA's NeMo team has released Molt, a new PyTorch-native framework for agentic reinforcement learning, designed to streamline the research process by reducing the complexity of algorithm modification. The framework aims to be compact enough for researchers to understand its entirety…
TileLang, a high-level Python domain-specific language (DSL) integrated with TVM, facilitates the design and compilation of performance-oriented GPU kernels. This tutorial demonstrates its capabilities by progressively implementing various computational tasks, starting with basic vector addition and moving to more complex…
A comprehensive tutorial has been released detailing NVIDIA's tile-based GPU programming, specifically focusing on the use of cuTile and Triton kernels. The guide outlines a practical workflow using Google Colab that is adaptable across various hardware configurations.
This article, the third in a series on PyTorch profiling, focuses on analyzing the performance of the attention mechanism. It outlines specific techniques and tools within PyTorch to identify bottlenecks within attention layers, which are crucial components in many modern…