A Practical Implementation and A/B Test — TL;DR To address inefficiencies in training data selection for autonomous driving DNNs, we implemented a scalable active learning approach on our internal production-grade AI platform called MagLev. Focusing on nighttime detection tasks, our methodology shows that data selected with active learning yields relative improvements in mean average precision of 3x on…

Training with larger batches is a straightforward way to scale training of deep neural networks to larger numbers of accelerators and reduce training time. However, as the batch size increases, numerical instability can appear in the training process. The purpose of this article to provide an overview of one class…

To experiment with BERT, or to learn more, consult this notebook, containing the full code. What is BERT? BERT, or Bidirectional Encoder Representations from Transformers, is a state-of-the-art NLP model. …

There is no shortage of ideas in which we might be able to use machine learning to change the way our businesses operate. This is certainly the case for many of the world’s leading retailers who are looking at how to use machine learning to improve the overall operations of…

Large scale language models (LSLMs) such as BERT, GPT-2, and XL-Net have brought about exciting leaps in state-of-the-art accuracy for many natural language understanding (NLU) tasks. …

For developing an application based on object detection or classification you’ll need deep learning models, however building these models from scratch is challenging and time-consuming. Training the models carefully with data over time and preserving accuracy is crucial as well. Neural networks learn from data that is stored as “weights”…

NVIDIA had the pleasure of hosting the Bay Area Bioinformatics group August meeting, also known as BayBifx. The group’s mission is to help scientists collaborate and grow by providing a network for sharing ideas and technical knowledge about bioinformatics. …

When DIY Robocars first launched, it took three months worth of development and meetup events for a scale robocar to complete the indoor track on its own. Now, with the help of breakthroughs in AI computing and open-source software, cars are breaking records and moving on to greater challenges. With…

The idea of a system that can learn from data, identify patterns and make decisions with minimal human intervention is exciting. Deep learning, a type of machine learning that uses neural networks is quickly becoming an effective tool to solve many different computing problems from object classification to recommendation systems…