NVIDIA enables end to end solutions from cloud to edge for various industries. Deploy large-scale AI initiatives, from training to inference with GPU-accelerated computing, and take advantage of unprecedented amounts of sensor and operational data to optimize industrial operations, improve time-to-insight, and reduce costs."> 大发11选5

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The most progressive industrial companies in the world are implementing NVIDIA technologies to deploy large-scale AI initiatives. GPU-accelerated computing enables AI at industrial scale, letting you take advantage of unprecedented amounts of sensor and operational data to optimize operations, improve time-to-insight, and reduce costs.

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Develop & Deploy
AI Faster

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The combined AI solutions from NVIDIA and partners give you an easier, faster path to GPU-accelerated deep learning and machine learning models.

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Gain Higher
Accuracy

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Use deep learning to make your algorithms for industrial  inspection and predictive maintenance more accurate.

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Leverage AI at
Industrial Scale

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Take advantage of the massive amount of data from your equipment to train your AI algorithms faster and optimize your operations at scale.

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One Platform for AI and HPC

One Platform for AI HPC

Design

  • HPC
  • Modeling & Simulation
  • Design for Manufacturability & Serviceability

Supply Chain

  • Forecasting
  • Supply Chain Optimization

Manufacturing

  • Robotics
  • CV Inspection
  • Predictive Maintenance
  • Process Control
     

Service

  • Predictive Maintenance
  • Field Inspection
  • Logistics Optimization
  • Parts Inventory Optimization
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Accelerate Your
Compute-Intensive AI Workflows

Use your data to train your algorithms and fuel insights.

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  • INDUSTRIAL INSPECTION

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  • PREDICTIVE MAINTENANCE

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  • ROBOTICS

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NVIDIA GPUs are used to develop the most accurate automated inspection solutions for manufacturing semiconductors, electronics, automotive components, and assemblies.

Along with accompanying software tools, GPUs enable efficient training of models for greater accuracy and optimized inference deployment at the edge. These models dramatically improve the accuracy of industrial inspection, resulting  in reduced test escapes and increased yield at greater throughput.

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1% increase in yield, which adds $60M in annual profits

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64% reduction in test escape rates

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200% automotive inspection throughput

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GPU-accelerated predictive maintenance solutions are helping industrial companies drive down operational costs by delivering greater accuracy than traditional machine learning-based methods in predicting equipment failure.

By reducing equipment failure and unplanned downtime, NVIDIA’s GPUs and software stack enable industrial companies to work smarter and more safely, while also reducing operations cost.

Oil & Gas

The deep learning-based Predictive Maintenance solution from Baker Hughes GE is powered by NVIDIAR DGX ?. It delivers a probabilistic orchestration engine, complete with a catalog of models powered by NVIDIA GPUs, to predict equipment failure two months in advance. The solution is ready to deploy in weeks and delivers 4-5 times greater accuracy in predicting equipment failure.

Aerospace and Manufacturing

The NVIDIA ecosystem of software partners and system integrators provides next-generation GPU-accelerated machine learning and deep learning predictive maintenance solutions, so you can train a model faster for greater accuracy.

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 Accelerate outcomes with pre-built and pre-trained deep learning algorithms, purpose-built for industrial equipment.

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Achieve 50% reduction in false positives and 300% reduction in false negatives.

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Experience 50X training speedup.

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AI-enabled smart factories are changing the landscape of manufacturing. This includes everything from compact robots trained in specific tasks and autonomous rovers delivering parts in manufacturing plants to cooperative robots (cobots) working together with people on the assembly lines. 

Autonomous optical inspection (AOI) robots now offer efficient ways to identify the smallest of defects, yet maintain the highest quality standards. Autonomous machines help transport finished products within factories point-to-point and alert self-driving UGVs to transport these products from the manufacturing floor to their final destinations.


With solutions like NVIDIA Jetson? at the edge or near-edge and NVIDIA Tesla? n the cloud, industrial robotics increase efficiencies while reducing costs.  

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Increase accuracy from 60% to 95% in robotic assembly.

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Automate repetitive, error-prone tasks with AI-enabled robots equipped with computer vision.

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Improve logistics and operations with robots that pick, transport, and deliver parts in the assembly line.

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NVIDIA Solutions for Industrial

Accelerated Computing at the Edge

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Today's industrial edge computing requires GPU-powered compute capabilities for industrial inspection and robotics in factories and predictive maintenance for equipment and assets in the field. NVIDIA Tesla-class edge GPUs and Jetson solutions accelerate the most powerful edge computing systems for these applications, and beyond.

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Powerful Computing for Data Centers

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

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

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Democratize the Data Center with Cloud

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Cloud computing has revolutionized industries by democratizing the data center and completely changing the way businesses operate.

NVIDIA GPUs are available on demand in all major cloud platforms worldwide and NVIDIA GPU Cloud (NGC) provides GPU-accelerated containers for easy deployment, including deep learning frameworks such as TensorFlow, PyTorch, MXNet, and more.

NVIDIA’s Metropolis Application framework is fully integrated with Azure Edge IoT and will soon be integrated with Amazon Green Grass.

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Accelerating Deployment with Software

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NVIDIA 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. This software investment is designed to accelerate customer time-to-deployment of and reduce the overall development costs.

These NVIDIA SDK investments include JetPack? for embedded, DeepStream for IVA, Isaac? TensorRT? for inference, Transfer Learning Toolkit for tuning DNNs, NVIDIA GPU Cloud for containers and AI software, and much more.

NVIDIA is also working closely with a broad ecosystem of partners to deploy out-of-the-box solutions that customers can leverage for their applications.

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