How NVIDIA Uses XML

Training a speech AI model to correctly recognize or synthesize clinical terminology is surprisingly difficult. Drug names like Acetaminophen, Amlodipine…

An agentic exchange must preserve a structured interaction: assistant turns interleave reasoning with one or more tool calls, and subsequent user turns return…

The article discusses how Amdocs is leveraging NVIDIA NIM to enhance generative AI performance while reducing operational costs in telecommunications.

The article discusses the collaboration between NVIDIA and the Alliance for OpenUSD (AOUSD) to standardize material interchange in 3D environments using OpenUSD, MaterialX, and OpenPBR.

The article discusses the security vulnerabilities found in machine learning research code, particularly focusing on the analysis of the Meta Kaggle for Code dataset.

This article discusses the integration of Universal Scene Description (USD) into Polyphony Digital's game development pipeline, particularly for Gran Turismo 7.

This article discusses the importance of data acquisition for businesses and introduces web scraping as a technique for collecting data from real estate websites using the Scrapy framework.

This article serves as a comprehensive guide to essential terms and concepts in the field of Speech AI, detailing its relationship with AI, Machine Learning (ML), and Deep Learning (DL).

The article discusses how to prepare state-of-the-art models for classification and object detection using the NVIDIA TAO Toolkit.

The U. S. Library of Congress has digitized over 16 million pages of historic American newspapers using a GPU-accelerated deep learning model.

The article discusses the integration of Windows ML, ONNX, and NVIDIA Tensor Cores for efficient deployment of pretrained deep learning models in Windows applications.