IoT Company NVIDIA

NVIDIA pioneered accelerated computing to tackle challenges no one else can solve. Our work in AI and digital twins is transforming the world's largest industries and profoundly impacting society. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling industrial digitalization across markets. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry.

The rapid evolution of artificial intelligence (AI) and the proliferation of billions of IoT devices are transforming almost every industry. As businesses across industries grapple with vast amounts of data, more complex operations, and more dynamic markets, edge AI is playing a growing role in helping them rapidly respond. Edge computing takes the power of AI directly to those devices and processes the captured data at its source—instead of in the cloud or data center. This accelerates the AI pipeline to power real-time decision-making and software-defined autonomous machines. Through a combination of computing power, AI technology, data analytics, and advanced connectivity, the edge extends compute capabilities from data centers out to the edge of networks, allowing organizations to act quickly on data where it’s captured. Reducing the distance between where data is captured and where it’s processed not only alleviates data transit costs, but also improves latency, bandwidth utilization, and infrastructure costs.

AI at the edge comes with a unique set of requirements. Edge systems, dispersed across vast physical distances, lack the centrality that a data center presents. Software or system updates either need to be performed manually or to be centrally managed to easily deploy, manage, and scale software across vast fleets of devices. Moreover, the security requirements for edge computing infrastructure differ from cloud or data center computing models. Edge locations lack the physical security that data centers have, so an end-to-end security model that protects both the application intellectual property and the sensor data is paramount for a successful deployment.

Billions of IoT sensors—in retail stores, on city streets, on warehouse floors, in hospitals—are generating massive amounts of data. Tapping into faster insights from that data can mean improved services, streamlined operations, and even saved lives. But to do this, enterprises need to drive decisions in real time, and that means taking their AI compute to where the data is, the network’s edge. AI and cloud-native applications, IoT and its billions of sensors, and 5G networking make large-scale AI at the edge possible. Explore the NVIDIA solutions in enterprise edge, embedded edge and industrial edge, all of which transform that possibility into real-world results, automating intelligence at the point of action and driving decisions in real time.

The NVIDIA EGX™ platform allows enterprise IT to deliver diverse applications on high-performance and cost-effective infrastructure. The platform is a combination of high-performance GPU computing and high-speed, secure networking in NVIDIACertified Systems™, built and sold by our partners. The EGX platform allows customers to prepare for the future while driving down costs by standardizing on a single unified architecture for easy management, deployment, operation, and monitoring. The EGX platform supports a vast suite of accelerated applications for edge AI, delivering faster insights where they matter the most.

In addition to accelerated computing and simplified deployments, NVIDIA solutions for edge computing offer industry-leading security protocols to ensure data is always protected. All processed data is encrypted in transit and at rest, and the secure and measured boot prevents AI runtime tampering. NVIDIA also provides ongoing managed security, with constant monitoring and automated bug fixes and patches, reducing the need for costly specialized staff to build and maintain these features.