Developer Resources For Retail
A hub of news, SDKs, technical resources, and more for developers working on retail, CPG and restaurant AI solutions.
App Frameworks and SDKs
NVIDIA Riva
Multimodal conversational AI
NVIDIA Riva is an SDK for building and deploying AI applications that fuse vision, speech and other sensors. It offers a complete workflow to build, train and deploy GPU-accelerated AI systems that can use visual cues such as gestures and gaze along with speech in context.
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NVIDIA Metropolis and DeepStream
AI-enabled video analytics
NVIDIA Metropolis is an application framework that simplifies the development, deployment and scale of AI-enabled video analytics applications from edge to cloud. It includes production ready pre-trained models and TAO Toolkit for training and optimization, DeepStream SDK for streaming analytics, other deployment SDKS, CUD-X libraries and the NVIDIA EGX platform.
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RAPIDS
Data science software
The RAPIDS suite of open source software libraries and APIs gives you the ability to execute end-to-end data science and analytics pipelines entirely on GPUs. Licensed under Apache 2.0, RAPIDS is incubated by NVIDIA® based on extensive hardware and data science experience. RAPIDS utilizes NVIDIA CUDA® primitives for low-level compute optimization, and exposes GPU parallelism and high-bandwidth memory speed through user-friendly Python interfaces.
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NVIDIA Omniverse
Simulation and digital twins
NVIDIA Omniverse™ is a powerful multi-GPU real-time simulation and collaboration platform for 3D production pipelines based on Pixar's Universal Scene Description and NVIDIA RTX™technology.
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NVIDIA NGC | The NGC container registry provides researchers, data scientists, and developers with simple access to a comprehensive catalog of GPU-accelerated software for AI, machine learning and HPC - and includes performance-engineered containers featuring AI software like TensorFlow, PyTorch, MXNet, NVIDIA TensorRT™, RAPIDS and more. These containers take full advantage of NVIDIA GPUs on-premises and in the cloud. Each is fully optimized and works across a wide variety of NVIDIA GPU platforms. |
NVIDIA TAO Toolkit | The term “transfer learning” implies that you can extract learned features from an existing neural network and transfer these learned features by transferring weight from an existing neural network. TAO Toolkit enables you to build high performance IVA based applications such as retail analytics, logistics, smart cities, access control and more. |
TensorRT | NVIDIA TensorRT™ is a platform for high-performance deep learning inference. It includes a deep learning inference optimizer and runtime that delivers low latency and high-throughput for deep learning inference applications. |
Triton Inference Server | The NVIDIA Triton inference server simplifies the deployment of AI models at scale in production. Triton Server is open-source inference server software that lets teams deploy trained AI models from many frameworks, including TensorFlow, TensorRT, PyTorch, and ONNX. |
Automatic Mixed Precision | Deep Neural Network training has traditionally relied on IEEE single-precision format, however with mixed precision, you can train with half precision while maintaining the network accuracy achieved with single precision. This technique of using both single- and half-precision representations is referred to as mixed precision technique. |
NVIDIA ISAAC SDK Robotics SDK | Learn More | Build and deploy commercial-grade, AI-powered robots. The NVIDIA Isaac SDK™ is a toolkit that includes building blocks and tools that accelerate robot developments that require the increased perception and navigation features enabled by AI. |
NVIDIA Merlin Recommendation system framework | Get Started | Merlin empowers data scientists, machine learning engineers, and researchers to build high-performing recommenders at scale. Merlin includes tools that democratize building deep learning recommenders by addressing common ETL, training, and inference challenges. Each stage of the Merlin pipeline is optimized to support hundreds of terabytes of data, all accessible through easy-to-use APIs. With Merlin, better predictions than traditional methods and increased click-through rates are within reach. |
NVIDIA Morpheus Cybersecurity app framework | Apply for early access | NVIDIA Morpheus is an open AI application framework that provides cybersecurity developers with a highly optimized AI pipeline and pre-trained AI capabilities that, for the first time, allow them to instantaneously inspect all IP traffic across their data center fabric. Bringing a new level of security to data centers, Morpheus provides dynamic protection, real-time telemetry, adaptive policies, and cyber defenses for detecting and remediating cybersecurity threats. |
Browse by Resource Type
GTC Content
AI in Supply Chain and Logistics
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E-Commerce and Recommendation Systems
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Retail Data Science
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Intelligent Stores
View SessionsCreate Intelligent Places Using NVIDIA Vision AI Models & DeepStream SDK
This webinar will briefly introduce new features of DS5.0 and TAO Toolkit 2.0, and show an end-to-end demo using Peoplenet/DS/TAO Toolkit, for people counting/occupancy analytics, which can be used widely in retail stores or public spaces.
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Driving Agility in Retail with AI
AI is helping retailers not only keep employees and customers safe, but also improve business agility to increase e-commerce sales, improve contactless checkout in stores, reduce shrink, and accelerate distribution center automation. Learn how the most innovative retailers are using AI to deliver the greatest business value.
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Using Pre-Trained Models and TAO Toolkit 3.0 for Robotics
Learn how to train your own gesture recognition deep learning pipeline. We’ll start with a pre-trained detection model, repurpose it for hand detection, and use it together with the purpose-built gesture recognition model.
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Getting Started with DeepStream for Video Analytics on Jetson Nano
You’ll learn how to:
- Set up your Jetson Nano and (optional) camera
- Build end-to-end DeepStream pipelines to convert raw video input into insightful annotated video output
- Configure multiple video streams simultaneously
Fundamentals of Accelerated Data Science with RAPIDS
You’ll learn how to:
- Use cuDF, Dask, and BlazingSQL to manipulate massive datasets directly on the GPU
- Utilize a wide variety of GPU-accelerated machine learning algorithms including XGBoost, cuGRAPH, and several cuML algorithms to perform data analysis at massive scale
- Perform multiple analysis tasks on several massive datasets in an effort to stave off a simulated epidemic outbreak affecting the entire UK population
Building Intelligent Recommender Systems
You’ll learn how to:
- Build a content-based recommender system using the open-source cuDF library and Apache Arrow
- Optimize performance for both training and inference using large, sparse datasets
- Deploy a recommender model as a high-performance web service
AI Workflows for Intelligent Video Analytics with Deep Stream
You’ll learn how to:
- Deploy DeepStream pipeline for parallel, multi-stream video processing and deliver applications with maximum throughput at scale
- Configure the processing pipeline and create intuitive, graph-based applications.
- Leverage multiple deep network models to process video streams and achieve more intelligent insights
Interactively Visualizing a DriveTime Radius from Any Point in the US
Retailers who understand these factors have an advantage over their competitors and can thrive. In this blog post, we’ll explore how RAPIDS’ cuDF, cuGraph, cuSpatial, and Plotly Dash with NVIDIA GPUs can be used to solve these complex geospatial analytics problems interactively.
Best Practices of Using AI to Develop an Accurate Forecasting Solution
Learn about the best practices of using AI and data science to improve forecasting in retail. This blog explains the Instacart Market Basket Analysis Kaggle competition, how to explore the data visually, train the model and run a forecasting predictio.
Beginner’s Guide to GPU- Accelerated Event Stream Processing in Python
Learn about the various aspects of RAPIDS that allow its users solve ETL (Extract, Transform, Load) problems, build ML (Machine Learning) and DL (Deep Learning) models, explore expansive graphs, process geospatial, signal, and system log data, or use SQL language via BlazingSQL to process data.
PROGRAMS FOR YOU
Developer Resources
The NVIDIA Developer Program provides the advanced tools and training needed to successfully build applications on all NVIDIA technology platforms. This includes access to hundreds of SDKs, a network of like-minded developers through our community forums, and more.
Technical Training
NVIDIA Deep Learning Institute (DLI) offers hands-on training in AI, accelerated computing, and accelerated data science to solve real-world problems. Powered by GPUs in the cloud, training is available as self-paced, online courses or live, instructor-led workshops.
Accelerate Your Startup
NVIDIA Inception—an acceleration platform for AI, data science, and HPC startups—supports over 7,000 startups worldwide with go-to-market support, expertise, and technology. Startups get access to training through the DLI, preferred pricing on hardware, and invitations to exclusive networking events.
NVIDIA Retail News
Visual Components Connector for NVIDIA Omniverse: A Perfect Recipe for Manufacturing Digitalization
Learn about how the Visual Components NVIDIA Omniverse Connector creates a simulation solution for the manufacturing industry to resolve operational and planning challenges.
Upcoming Event: Join NVIDIA at Automate 2022
Join NVIDIA at Automate 2022, June 6-9, to learn about AI platforms for manufacturing, robotics, and logistics that improve efficiency, scalability, and production across industries.
The Computational Fluid Dynamics Revolution Driven by GPU Acceleration
The end of 2021 and beginning of 2022 saw the two largest commercial CFD tool vendors, Ansys and Siemens, both launch versions of their flagship CFD tools with support for GPU acceleration.
Implementing Industrial Inference Pipelines for Smart Manufacturing
Using an NVIDIA Triton Inference Server, industrial manufacturer Sansera improved quality control and documentation through a custom AI pipeline.
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