Accelerating Retail with AI.
Image courtesy of AiFi
Leading retailers are tapping into AI to automate warehouse logistics, determine in-store promotions and real-time pricing, enable customer personalization and recommendations, deliver better shopping experiences, and more—both in stores and online.
Learn about the most important AI use cases in retail today across supply chain optimization, omnichannel management, and intelligent stores.
NVIDIA AI and simulation solutions are delivering better-than-ever efficiency to the supply chain.
Don't miss these three upcoming retail sessions at GTC
Learn how to implement the Triton Inference Server to develop recommendations and personalized search systems. We'll demonstrate how you can serve multiple models at scale with Triton, A/B test models, serve ensemble models, and monitor progress in production. We'll also deep-dive in to the MLOps processes and the importance of a cross-functional approach from concept to deployment, and share performance results to illustrate the impact of this deployment.
A Fulfillment Center is considered a critical node in providing optimal customer service levels in a supply chain network and for e-commerce. Therefore, improving order fulfillment time becomes critical to achieve world-class operations. One of the key processes involved in order fulfillment is that of decanting and picking, the activities that consume the most time when operating a fulfillment center in general and fulfilling an order in particular. This presentation highlights the analysis of an actual system that stores products within an automated system and releases orders to a picking station. We will demonstrate the use of two key platforms from NVIDIA. (1) Omniverse: to create digital twin 3D assets and an architecture enabling variations in simulation models to address different scenarios and strategies aimed at improving system performance. (2) Metropolis: to enable highly scalable IVA applications to provide high quality perception data and operational situation awareness. We will discuss specific KPIs to compare the different strategies and scenarios, such as: order fulfillment lead-time, picks per man-hour, average picking time per order, average time to pack an order. These purposed solutions will provide insights that lead to improvements in order processing time, order fulfillment rate, and increased operator efficiencies.
In this session, we will showcase how developers can use new Retail Pre-trained Models and Metropolis SDKs and microservices to develop Retail applications for Loss Prevention. Developers will learn how to leverage the the pre-trained models as is as well as how to think about how to customize and fine-tune them for a variety of use cases. Additionally, developers will learn how to build and customize applications using Metropolis microservices.
NVIDIA is a tremendous partner to help us get the math, to help us get the discoveries, to help us get the research and development done, whether it's runtime libraries, whether it's the equipment itself, or whether it's just having another ecosystem partner that can come in and lend some expertise to help us through some very difficult times.
– Wesley Rhodes, Vice President of Technology Transformation and R&D, Kroger
January 14–January 17, 2023
Join NVIDIA at NRF to learn how we’re helping retailers use AI to improve forecast accuracy, personalize consumer recommendations, optimize store layouts, accelerate throughput in distribution centers, and track routing optimizations for last-mile delivery.
Developers can quickly build loss-prevention applications using NVIDIA Retail AI Workflows, built on cloud-native microservices, that include models pretrained on hundreds of products prone to theft.
Learn about the AI and high-performance computing (HPC) hardware, software, and networking solutions for retail.
The ability to glean faster insights can mean saving time, reducing cost, and improving customer experiences. That’s why retailers are looking to tap into the data generated from billions of IoT sensors found in stores, warehouses, and supply chains. NVIDIA’s edge computing solutions are designed to gather and compute continuous streams of data at the network’s edge, delivering real-time notifications to store associates on shrinkage and insights into customer demographics, shopping preferences, and more.
NVIDIA DGX™ systems—which interconnect NVIDIA A100 Tensor Core GPUs with NVIDIA NVLink® and NVIDIA NVSwitch™—are architected to deliver the fastest time to solution on the world’s most complex AI challenges facing retailers. From improving forecast accuracy to preventing inventory loss to delivering enhanced customer experiences, DGX systems, including NVIDIA DGX A100 and NVIDIA DGX SuperPOD™, deliver the performance and scale needed to deliver faster ROI on AI use cases for retail.
NVIDIA software libraries and software development kits (SDKs) enable customers to deploy AI in the cloud, on their servers, or at the edge. These SDKs include NVIDIA Jetson™ for AI at the edge, DeepStream for intelligent video analytics (IVA), NVIDIA Isaac™ for robotics, NVIDIA® TensorRT™ for inference, and the TAO Toolkit for tuning deep neural networks (DNNs).
NVIDIA GPUs are available in all major cloud platforms, and NVIDIA NGC™ provides GPU-accelerated software containers for easy deployment. NVIDIA Metropolis is also available in the cloud, fully integrated with Azure IoT Edge and soon integrated with AWS IoT Greengrass.
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Learn more about how NVIDIA AI is bringing leading-edge technology to our everyday retail experiences.
Sessions
Learn how to build and execute end-to-end, GPU-accelerated data science workflows that let you quickly explore, iterate, and move your work into production. In this self-paced lab, you’ll learn how to use RAPIDS™ accelerated data science libraries to perform data analysis at scale with a wide variety of GPU-accelerated algorithms.
In this lab, you’ll learn how to interact with the NVIDIA Riva speech server to process various conversational AI requests. You’ll learn how to send audio to an automatic speech recognition (ASR) model and receive back text, use natural language processing (NLP) models to transform and classify text, and send text to a text-to-speech (TTS) model and receive back audio.
Develop the skills you need to do your life’s work in AI, data science, and more. The NVIDIA Deep Learning Institute (DLI) offers hands-on training in AI, accelerated computing, and accelerated data science.
Influencer Chris Walton interviewed Azita Martin, NVIDIA’s general manager of AI for retail, CPG, and QSR for the inaugural episode of Omni Talk’s Ask An Expert interview series. Find out what she thinks are the most immediate use cases for AI in retail.
Grant Gelven, a machine learning engineer at Walmart Global Tech, joined NVIDIA AI podcast host Noah Kravitz for the latest episode of the AI Podcast. Gelven spoke about the big data and machine learning methods making it possible to improve everything from the customer experience to stocking to item pricing.
Connect with millions of like-minded developers and access hundreds of GPU-accelerated containers, models, and SDKs—all the tools necessary to successfully build apps with NVIDIA technology—through the NVIDIA Developer Program.
Evolve your startup with go-to-market support, technical expertise, training, and funding opportunities.
Our solutions for the retail industry go beyond products. Our partners are here to assist your organization at every level to build and execute transformative AI strategies, products, and services.
Our experts can help your business unlock potential and unleash innovation.
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