Network Support for AI

This post was originally published on Network Computing

AI (artificial intelligence) processing and data payloads differ substantially from what they are in traditional network workflows. What changes do you need to consider to get your network ready for support of AI applications?

This is the “front-and-center” question facing enterprise network professionals because AI is coming.

At the end of 2023, 35% of companies were using some kind of artificial intelligence, but the majority of organizations using it were resource-rich tech companies. As other companies begin to deploy AI, new investments and revisions to network architecture will have to be made.

See also: AI-Powered Networks: Transforming or Disrupting Data Centers?

How much does a network pro have to know about AI?

Historically, network staffs didn’t have to know much about applications except for how much data they were sending from point to point and what the speeds and volumes of transactions were. This changed somewhat with the introduction of more unstructured “big” data into network traffic, but the adjustment to big data for video, analytics, etc., still wasn’t a major disruption to network plans.

AI will change all that—and it will require network staff to learn more about the AI application and system side.

This is because there is no “one size fits all” model for

Read the rest of this post, which was originally published on Network Computing.

Previous Post

Need GPUs? Take a look at microclouds

Next Post

PCI DSS 4.0 Requirements