Cloud Computing
What is Cloud Computing?
Cloud computing is the delivery of computing resources—such as storage, processing, and networking—over the internet, enabling devices and applications to operate without local infrastructure. In Edge AI, cloud computing powers advanced analytics and machine learning by connecting edge devices to centralized or hybrid cloud environments.
Cloud computing also allows businesses to access scalable computing power and AI capabilities remotely, without maintaining physical servers. It works alongside edge computing to process data locally while leveraging cloud resources for heavy computation, model training, and large-scale analytics.
Why Is It Used?
It is used to reduce IT costs, accelerate AI model deployment, and enable real-time decision-making across distributed edge devices. Organizations rely on cloud computing to unify data, train models, and support intelligent applications without overloading local devices.
How Is It Used?
Data Storage: Store large datasets collected by IoT and edge devices.
Model Training: Train AI models centrally and deploy them to edge devices.
Analytics & Monitoring: Aggregate and analyze data from multiple edge nodes.
Hybrid Operations: Combine local edge processing with cloud-scale intelligence for optimal performance.
Types of Cloud Computing
Public Cloud: Hosted by providers like AWS, Azure, or GCP.
Private Cloud: Dedicated infrastructure for a single organization.
Hybrid Cloud: Combines public and private cloud resources.
Edge-Integrated Cloud: Specifically optimized to work with edge AI devices for real-time processing.
Benefits of Cloud Computing
Reduces latency when combined with edge computing.
Scales AI workloads efficiently.
Lowers infrastructure and maintenance costs.
Enables real-time insights and predictive analytics.
Supports seamless updates and AI model deployment across distributed devices.