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Leading retailers are using AI to reduce shrinkage, improve forecasting, automate logistics, determine in-store promotions and real-time pricing, enable personalisation and recommendations for customers, and deliver better shopping experiences both in-store and online.
With data from cameras and sensors, retailers use AI to reduce shrink, eliminate stock shortages and visualise customer behaviour. The same infrastructure can also enable faster completion of the purchase process. Learn more about the five ways retailers are using AI to create smart shops: Asset Protection, Store Analytics, Autonomous Shopping and Store Operations.
AI also improves demand forecasting and inventory management. Demand forecasting uses data from multiple sources to ensure the right products are available in the right shop at the right time.
Improving forecast accuracy with machine learning has a critical impact on supply chain optimisation.
Effective forecasting requires more than looking at demographics and location. Many external influences such as weather or local sporting events can also affect supply and demand. By using NVIDIA RAPIDS™ software libraries on NVIDIA GPUs, retailers can speed up the training of their machine learning algorithms by up to 20 times. This means they can use more data and process it faster with higher accuracy.
WALMART IMPROVES FORECAST
Walmart, for example, has trained machine learning algorithms 20 times faster using RAPIDS open source data processing and machine learning libraries. Based on CUDA-X AI™ and leveraging NVIDIA GPUs, RAPIDS enables Walmart to get the right products to the right shops more efficiently, respond to shopper trends in real time and realise cost savings on inventory.
KI IN WAREHOUSE LOGISTICS
Warehouse logistics is the art of optimising, integrating, automating and managing product flow in fulfilment or distribution centres. The combination of NVIDIA AI solutions for intelligent video analytics (IVA), robotics, automation and management in supply chains leads to operational efficiency and increased process throughput. GPU-powered AI adds a level of awareness to processes by leveraging physical and virtual properties to increase real-time performance and accuracy. Warehouse robots processing orders can evaluate all variables before making decisions and adapt to changing situations. Thanks to automated reporting, they can optimise routes and provide end-to-end visibility and higher accuracy regarding orders picked, packed and shipped.
Natural Language Processing (NLP) helps retailers personalise experiences for customers and improve customer service. It is also used to compile and analyse consumer data to provide actionable insights. NVIDIA makes real-time conversational AI possible by optimising training and inference from BERT, a popular NLP model.
NVIDIA Jarvis is a platform for building and deploying AI applications that combine deep learning models for speech recognition and synthesis, speech understanding and vision. Jarvis runs on the NVIDIA EGX stack, which is compatible with all commercially available Kubernetes infrastructures.
Understanding customer behaviour has never been more important for retailers looking to drive growth. With the help of AI applications equipped with video analytics, retailers can gain the same visibility in-store as they currently have online.
With insights into popular aisles, dwell times and demographics, retailers can improve merchandising and offer real-time promotions to increase sales and provide a better experience.
In e-commerce, retailers are using GPU-powered machine learning and deep learning algorithms for faster, more accurate recommendation engines that can increase sales by 60 per cent.
As the world turns to remote working, consumer buying trends are changing too - and retail professionals, from IT managers to data scientists, need to keep up. Learn how GPU-powered hardware and virtualisation software can help your business make the digital transformation and keep pace with an ever-changing world.
These are the powerful engineers behind several new innovations benefiting the retail industry. Some are mature companies, others are part of the NVIDIA Inception programme, NVIDIA's start-up incubator, where they have developed breakthrough GPU-based AI tools for retail. Find out who is at the forefront of the fourth industrial revolution, delivering new capabilities for smart shops, warehouse logistics and omnichannel management.
DEEP NORTH - BETTER EXPERIENCE WITH KI FINDINGS IN THE STORE
Deep North enables local retail shops and transport centres to attract consumers back into shops through better experiences from the online world.
CLARIFAI - ACCELERATE KI-SUPPORTED DATA ANNOTATION
Clarifai's new Labeler tool helps data scientists cut the time it takes to annotate images.
KI SCALABILITY FROM THE PERIPHERY TO THE DATA CENTRE TO THE CLOUD
REALTIME SKI FOR EDGE APPLICATIONS
NVIDIA's Edge solutions are designed to capture and compute continuous streams of data at the edge of the network. The AI calculations are performed entirely in the store. They provide store associates with real-time shrink information and notifications, as well as information about customer demographics, shopping preferences and more.
Smart Retail is possible with today's powerful AI and the NVIDIA EGX platform, which gives retail shops access to the power of accelerated AI computing.
The NVIDIA Tesla® GPU-accelerated computing platform dramatically accelerates the training of deep learning and machine learning models to deliver insights never before possible. From the peripherals to the data centre, Tesla GPUs are available from every major computer system and server vendor to accelerate the training of AI models in your data centre.
They are also available in NVIDIA DGX™ systems equipped with DGX add-on software for rapid AI deployment to meet the needs of Deep Learning and Machine Learning developers.
DEMOCRATISATION - FROM THE DATA CENTRE TO THE CLOUD
NVIDIA GPUs are available globally on all major cloud platforms, and NGC provides GPU-accelerated software containers for easy deployment, including Deep Learning frameworks such as TensorFlow, PyTorch, MXNet and more. NVIDIA Metropolis is also available in the cloud, fully integrated with Azure IoT Edge and soon to be integrated with AWS IoT Greengrass.
NVIDIA software libraries and SDKs form a scalable solution that enables customers to deploy inference and AI in the cloud, on their servers or in the periphery. These SDKs include NVIDIA JetPack™ for embedding, DeepStream for IVA, NVIDIA Isaac™ for robotics, NVIDIA TensorRT™ for inference, Transfer Learning Toolkit for optimising Deep Neural Networks (DNNs) and NGC for containers and AI software.