The Role of Edge Data Center in the Era of AI Technology

The Role of Edge Data Center in the Era of AI Technology

By Published On: January 29, 2024Categories: Article
The Role of Edge Data Center in the Era of AI Technology

Amid the massive development of Artificial Intelligence (AI) technology that has occurred recently, there is one problem that is often faced by developers, it has been quite difficult to find resources that can meet their needs. Behind the sophistication of AI technology that can do many things, this technology also requires large computing resources, not only a matter of storage size but also how fast data can be sent.

Edge Data Center provides a solution to meet this need, where Edge Data Center will enable developers to run AI technology with decent data transfer speeds while remaining cost-effective. So what is an Edge Data Center, and how does this type of Data Center play a role in the development of AI Technology? Let’s discuss this one topic.

 

What is an Edge Data Center?

Edge Data Center has a compact data center facility that provides cloud computing resources that are connected to a central Data Center or several other larger Data Centers.

Data processing and services are built to be located as close to the end user as possible, making Edge Data Centers support organizations to reduce latency, improve user experience, and reduce expenses due to bandwidth consumption.

Read Also: The Importance of Low Latency Data Center for the Financial Service Industry

The Role of Edge Data Centers in the Era of AI Technology

As mentioned earlier, AI development requires huge computing resources. If the system is developed in a centralized data center, the data processing will be slow, and costs will increase due to latency and bandwidth consumption.

To overcome this, some developers are taking an approach known as Edge AI, an AI technology system that is hosted in a data center located near the user. There will be many benefits that can be felt if AI is built using the Edge Data Center, including:

1. Lower Latency

Edge Data Centers that are built near end users make the latency level low, which in turn can make AI technology capable of sending data faster, even in real-time. This speed in transmitting data in real-time is important for AI, especially if the technology is applied to autonomous vehicles or IoT. This approach will work better when combined with regional Internet Exchange.

2. Bandwidth Savings

If AI is built using a centralized Data Center in a remote location, this will cause several problems, ranging from ineffective data delivery (congestion) to increased bandwidth costs. AI built on the Edge Data Center can answer this challenge perfectly, its close location makes the delivery route more efficient, so network costs can be reduced.

3. Data Security

Artificial Intelligence is often created by utilizing sensitive data, and of course, developers must ensure the security of that data. By utilizing Edge Data Center, it means that the data is processed within the local scope, which in turn can help the risk of data theft due to remote connections. In addition, Edge Data Centers can also be used to comply with laws and regulations that require sensitive data to be stored domestically.

4. Reliability

Some AI technologies may tolerate downtime, but if these technologies are applied to healthcare, autonomous vehicles, or automated industries, reliability and redundancy systems must be a priority because if the data center goes down, the consequences will be fatal. Edge Data Center can also be used as a redundancy system that allows it to continue operating, even if the network to the central Data Center is down.

5. Scalability

Scalability should also be a concern when utilizing AI, given that this technology often experiences spikes in demand or the amount of data stored. Edge Data Centers are also quite flexible when it comes to increasing capacity, which does not even have a significant impact on the existing infrastructure at the center.

Conclusion

Through the above discussion, we can conclude that AI technology requires specific resources, starting from low latency, security, reliability, and scalability. Edge Data Center can meet these demands well, which can even reduce network costs.

If you are currently in need of a low-latency, Jakarta-based, customizable Edge Data Center, you can get acquainted with EDGE DC’s services. Reach out to our team, by filling out the form below.

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