Learn about NVIDIA cuOpt: Accelerated Data Analytics
Financial institutions struggle to detect fraud due to the large amount of transactional data that needs speedy processing
American Express trains its LSTM models faster using GPU parallel computing. GPUs allow live models to process massive transactional data for real-time fraud detection
Telecommunications companies create massive amounts of data from network devices, client contacts, invoicing systems, and network performance and maintenance
RAPIDS, a set of software libraries that accelerates data science and analytics pipelines, boosts NVIDIA cuOpt, enabling local search
AT&T is using NVIDIA RAPIDS Accelerator for Apache Spark to improve Spark-based AI and data pipelines
Medical researchers use these publications to restrict their hunt for new medicines
Pharma giant AstraZeneca created a BIKG to help scientists with literature reviews, screen hit rate, target identification, and more
The cost of harvesting renewable resources, such as solar energy, has decreased over the last ten years, making the transition to clean energy more straightforward than before
NVIDIA developed Karman, a distributed AI platform for the grid edge, employing a bespoke Jetson Orin edge AI module
Automakers want self-driving vehicles with real-time navigation and object recognition
Multiple AI models, preprocessing, and postprocessing make the autonomous driving inference pipeline difficult
Electric vehicle manufacturer NIO added NVIDIA Triton Inference Server to its inference pipeline to improve autonomous driving workflows
Data processing and analysis are essential for real-time inventory adjustments, customer personalisation, and price strategy optimisation in retail
Walmart, the world’s largest retailer, used accelerated computing to increase forecasting accuracy for 500 million item-by-store combinations across 4,500 shops
Walmart used NVIDIA GPUs and RAPIDs to improve forecasting
Walmart improved prediction accuracy from 94% to 97%, eliminated $100 million in fresh produce waste, and reduced stockout and markdown scenarios with advanced algorithms
Public and corporate organisations use immense aerial image data from drones and satellites to predict weather, follow animal movements, and monitor environmental changes