Edge AI: Going Cloudless

Cloudless computing, alternatively referred to as edge computing or fog computing, represents a computing model that prioritizes data processing and application execution at the network's periphery, in closer proximity to the data origin or end-user device, instead of relying solely on centralized cloud infrastructure. In cloudless computing, the objective is to bring computational capabilities and services nearer to their required location to minimize latency, enhance performance, and augment data privacy and security.

In this article, we’re going to share how to decide whether you should be going cloudless with your computing, or rely on a good old cloud.

Factor #1. Energy consumption
What is really great about cloud computing is that you don’t have to worry about how much energy your infrastructure may be consuming.
In fact, AI models frequently require a lot of processing power that may be limited on Edge.

Factor #2. Storage capacity
Similarly to the previous factor, storage capacity plays a huge role when it comes to choosing where and how it is possible to perform the computing part. Cloud computing enables users to conveniently store, access, and retrieve data using highly scalable remote storage systems. By eliminating the need for local storage devices, networks can rapidly adjust their storage capacity, expanding or shrinking as required. Instead of being bound by fixed pricing structures, most plans offer the flexibility to pay only for the specific storage capacity that is required.

Factor #3. Local computing for real-time data
In some cases, sending data to be computed to the server and then getting it back may be somewhat excessive. A great solution in the matter would be to perform processing and analysis at the edge of applications which allows for nearly instantaneous or real-time analysis. This is particularly crucial in scenarios such as autonomous vehicles, where immediate analytics and processing play a vital role in ensuring safety and optimizing efficiency.

Factor #4. Security and privacy
Cloud computing enhances the overall security of your network by reducing the necessity of sending sensitive data to the cloud for processing. Storing data in the cloud can make business and operational procedures more susceptible to vulnerabilities. However, by minimizing the amount of data that is transmitted, the risk of man-in-the-middle security breaches is significantly reduced.

Factor #5. Connectivity issues
Having a reliable connection is very important for many AI applications. Let's take autonomous vehicles as an example. They rely on continuous connectivity to operate safely. Edge AI is a technology that ensures this connectivity without needing a strong internet connection. It allows the AI system to work perfectly even when the internet connection is not stable.

Want to learn more about Edge AI challenges? Check out our survey results post containing some fascinating stats: https://www.linkedin.com/posts/rtsoft-swdc_edgeai-edgecomputing-edgedevices-activity-7064524972701970433-3tTH?utm_source=share&utm_medium=member_ios