Reinventing Retail with AI

Reduce Shrinkage.
Improve Forecasting. Drive Revenue.

Leading retailers are leveraging AI to reduce shrinkage, improve forecasting, automate warehouse logistics, determine in-store promotions and real-time pricing, deliver personalization and recommendations to customers, and deliver better shopping experiences both in stores and online.

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    Intelligent
    Stores

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    Demand
    Forecasting

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    Warehouse
    Logistics

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    E-Commerce and
    Recommenders

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    Conversational
    AI

Intelligent Stores

Intelligent Stores

Using data from cameras and sensors, retailers are leveraging AI to reduce shrinkage, eliminate stockout, and gain visibility into customer behaviors. The same infrastructure can also power faster checkouts. Explore the four ways retailers are using AI to create intelligent stores: asset protection, store analytics, autonomous shopping, and store operations.

Forecasting and Inventory Management

Forecasting and Inventory Management

AI is also improving demand forecasting and inventory management. Demand forecasting uses data from various sources to ensure the right products are available in the right store at the right time. ?

Using machine learning to improve forecast accuracy has a significant impact on optimizing the supply chain.?

Effective forecasting takes more than demographics and location into consideration. Many external events such as weather or local sporting events can impact supply and demand too. Leveraging NVIDIA RAPIDS? software libraries on NVIDIA GPUs, retailers can accelerate training of their machine learning algorithms by up to 20X. This means that they can use more data and process it faster with more accuracy. ?

Walmart Improves Forecasting

Walmart Improves Forecasting

Walmart, for example, has trained their machine learning algorithms 20X faster with RAPIDS open-source data processing and machine learning libraries. Built on CUDA-X AI? and leveraging NVIDIA GPUs, RAPIDS has enabled Walmart to get the right products to the right stores more efficiently, react in real time to shopper trends, and realize inventory cost savings at scale.

See how Walmart is improving forecasting
AI in Warehouse Logistics

AI in Warehouse Logistics

Combining AI and warehouse management in supply chains is possible with deep and reinforcement learning. This combination adds a level of consciousness to the operation, allowing warehouse robots to take a holistic view of products—leveraging both physical and theoretical properties—to make informed decisions. ?

The NVIDIA EGX? platform improves warehouse productivity, efficiency, and accuracy of orders by deploying GPU-accelerated AI at the edge—in the warehouse itself. GPU-powered warehouse robots processing orders can operate in real time, measuring all variables before making decisions and adapting on site as situations change. They are capable of automated reporting that can incorporate demand forecasting and last-mile delivery, which delivers end-to-end visibility and results in increased accuracy of the orders picked, packed, and shipped.?

Robotics in Retail

Robotics in Retail

Store associates are the face of retail organizations. As a result, retailers are increasingly working to reduce the amount of time they spend on non-customer-facing tasks, such as performing inventory counts or replacing misplaced items.

Large retailers are using new robotics technology to check stock levels, correct shelf locations, and ensure price accuracy. They’re also using new tech to sort items unloaded from trucks based on priority and department, allowing associates to move inventory to the sales floor more efficiently.

Smart assistants are also helping large department stores minimize the amount of time employees spend checking inventory or cleaning floors, reinvesting in more face-to-face customer service.

See how robots are tracking inventory at Lowe’s
Recommendation and Visual Search

Recommendation and Visual Search

Understanding customer behavior has never been more critical for retailers looking to drive growth. ?AI applications powered by video analytics can give retailers the same visibility into customer behavior ?in stores as they currently have online. ?
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With insights into popular aisles, dwell times, and demographics, retailers can improve merchandising and offer real-time promotions in store to increase revenue and provide a better experience. ?
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For e-commerce, retailers are using GPU-powered machine learning and deep learning algorithms for faster, more accurate recommendation engines, which can improve revenue by 60 percent.?
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And with the growing trend of shopping online and picking up orders in store, AI is instrumental in delivering the best omni-channel experience.

By using algorithms to understand customer preferences, Stitch Fix created a fashion service that combines the art of personal styling with data analytics powered by GPU-accelerated deep learning.

Conversational AI

Conversational AI

Natural language processing (NLP) is helping retailers personalize experiences for customers and improve customer service. It’s also used to compile and analyze consumer data to derive actionable insights. NVIDIA is enabling real-time conversational AI by optimizing the training and inference of BERT, a popular NLP model.

NVIDIA Jarvis is a platform for building and deploying AI applications that fuse deep learning models for speech recognition and speech synthesis, language understanding, and vision. Jarvis runs on the NVIDIA EGX stack, which is compatible with all commercially available Kubernetes infrastructure.

Trailblazing Retail Startups

These innovators are the powerful engineers of several new creations benefitting the retail industry. As part of the NVIDIA Inception program, NVIDIA’s startup incubator, they’ve developed game-changing, GPU-based AI tools for retail.  Inception nurtures the entrepreneurship ecosystem by connecting pioneers to a massive network of deep learning experts and thought leaders. Explore some of the most fashionable applications at the forefront of the fourth Industrial Revolution. 

AnyVision—Streamlining Access with Intelligent Video Analytics

AnyVision—Streamlining Access with Intelligent Video Analytics

AnyVision is using AI-generated heatmaps for intelligent in-store analytics to improve user experiences and optimize layouts in retail stores.

Malong Technologies—Classifying Unlabeled Images

Malong Technologies—Classifying Unlabeled Images

Malong is improving efficiencies and using intelligent video analytics to accurately reduce shrinkage and improve self-service in stores.

NVIDIA AI Consulting Partner Network

Service Delivery Partners have special expertise in the transformational business benefits afforded by deep learning (DL), machine learning (ML), and artificial intelligence (AI). Learn about the consulting services they provide, as well as impactful solutions specifically for critical use cases in retail like asset protection and predictive analytics.

AI Retail from Edge to Data Center to Cloud

Real-Time AI at the Edge

Real-Time AI at the Edge

NVIDIA’s edge solutions are designed to gather and compute continuous streams of data at the network’s edge. AI computations are performed entirely in the store, delivering real-time insights and notifications to store associates on shrinkage and providing insights into customer demographics, shopping preferences, and more.

Smart retail is possible with today’s powerful AI and the NVIDIA EGX platform, which brings the power of accelerated AI computing to retail stores.

Powerful Computing for Data Centers

Powerful Computing for Data Centers

The NVIDIA Tesla? GPU-accelerated computing platform dramatically speeds up deep learning and ML model training to deliver never-before-possible insights. From edge to data center, Tesla GPUs are available from every major computer system and server manufacturer to accelerate training of AI models.

They’re also available in NVIDIA DGX? systems, which are equipped with the DGX software stack for rapid AI deployment to meet the demands of deep learning and machine learning developers.

Democratization, from Data Center to the Cloud

Democratization, from Data Center to the Cloud

NVIDIA GPUs are available in all major cloud platforms worldwide, and NGC provides GPU-accelerated software containers for easy deployment, including deep learning frameworks like TensorFlow, PyTorch, MXNet, and more. NVIDIA Metropolis is also available in the cloud, fully-integrated with Azure IoT Edge and is soon-to-be integrated with AWS IoT Greengrass.

NVIDIA’s software libraries and SDKs create a scalable solution that enables customers to deploy inference and AI in the cloud, on their servers, or at the edge. These SDKs include NVIDIA JetPack? for embedded, DeepStream for IVA, NVIDIA Isaac? for robotics, NVIDIA TensorRT? for inference, Transfer Learning Toolkit for tuning deep neural networks (DNNs), and NGC for containers and AI software.

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