Cloud Computing Role in Edge AI: Why It’s More Important Than You Think

Cloud computing and edge AI are two sides of the same coin.

As we stand on the brink of a new era, characterized by the exponential growth of data and the necessity for real-time processing, understanding how these two components interact is vital for any forward-thinking organization.

By 2025, a staggering 75% of enterprise-generated data will be created and processed at the edge. (Gartner).

At the same time, cloud computing is set to play an indispensable role in managing, analyzing, and optimizing this data.

In this blog, we’ll explore the cloud computing role in edge AI, grounding our discussion in concrete statistics, real-world applications, and industry insights that resonate with our experiences in product engineering.

The Growth of Edge AI: Why It Can’t Survive Without Cloud Computing 

The demand for edge AI is driven by an explosion of data that we can barely comprehend.

As per Edge Delta, in 2023, the world created around 120 zettabytes (ZB).

This creates a pressing need for processing capabilities that can manage and analyze data in real-time.

Cloud as the Brain

Edge devices are fast, but limited. They can handle small-scale tasks, but when the process gets complex, it requires a cloud.

In fact, 80% of the heavy lifting — model training, long-term analytics, data crunching — still happens in the cloud.

The reality is simple: edge devices act as the eyes and ears, while the cloud serves as the brain, orchestrating the analysis and decision-making processes.

Edge Devices as Sensors

Take autonomous vehicles for example.

Source

Every Tesla on the road generates about 1 terabyte of data per week.

While the car itself makes real-time decisions at the edge, all that data needs to be uploaded to the cloud for further analysis, refining the AI models that will make future vehicles smarter.

Without the cloud, this process would be impossible.

Cloud Computing Role in Edge AI: 4 Real-World Use Cases

Let’s dig into some tangible examples that illustrate the power of cloud computing and edge AI working together.

Technical Breakdown: The Cloud-Edge AI Workflow

To appreciate the cloud computing role in Edge AI, we must examine the workflow that defines their relationship.

Edge Devices Handle Immediate Inference (Low Latency)

Edge AI excels in situations where latency matters — when decisions need to be made in real time.

For example, facial recognition at airports. The edge AI at kiosks has just 100 milliseconds to verify your identity before letting you through security.

But the edge can’t do everything.

The kiosk sends your data to the cloud, where more in-depth security checks happen. This approach ensures both fast service and secure data handling.

Cloud Performs Model Training and Heavy Computation

On the other hand, tasks like AI model training require enormous computational power.

Utilizing hardware such as H200 GPUs is a game-changer, drastically accelerating model training in the cloud with unmatched computational power, essential for driving real-time AI advancements in fields like autonomous driving and healthcare, ensuring faster and more efficient outcomes.

Google’s cloud-based AI platforms can train models 10x faster than traditional on-premise systems.

This is crucial for industries that rely on constantly evolving AI, such as autonomous driving, healthcare, or finance.

The Challenges and Real Solutions

Our Thoughts? Cloud Computing is the Backbone of Edge AI 

We’re a software product development company. 

For the past 15 years, we’ve been helping businesses solve real problems with NextGen technologies. 

At the core of our expertise is a deep understanding of both cloud computing and edge AI and how they can work in harmony to deliver tangible results.  

From implementing large-scale cloud architectures to optimizing edge-based AI systems, our team brings the technical depth, industry knowledge, and hands-on experience needed to deliver solutions that work — not just in theory, but on the ground, where it matters most. 

If you’re ready to explore how cloud computing and edge AI can drive growth and innovation in your business, let’s connect.