I have been at Cisco many years and seen a few transformational events affect network engineers.
After I first joined Cisco in 1998, IP telephony came on the scene and disrupted not only classical circuit-switched communications but those of us in networking as well.
More recently, automation, programmability, and software grabbed everyone's attention, promising to upend the way we think about, design, and operate networks.
Whereas IP telephony and automation may have been reserved to specific places in IT, people from all walks of life are discussing and using AI. The networking industry specifically is shifting rapidly around technology and talent acquisition as well as product integration and focus.
Before going too much further, it's important to mention that AI is not just one thing.
AI is a class of machine learning that uses math to analyze large sets of data to make predictions, provide automatic classification, and summarize large data sets.
A few years ago, when this notion of machine learning started to first emerge in networking, I took an online course that focused heavily on the math behind machine learning to do things like cluster various test results to identify anomalies and analyze a large set of number images, providing new images so AI could correctly identify the number it receives.
This same kind of predictive and classification AI is already baked into several Cisco products.
This generative AI receives a prompt that specifies what type of content to create and in what fashion, and it uses its underlying model to satisfy the request.
Different generative AI tools exist for different media and different use cases.
Network engineering is an interesting use case for generative AI. You can ask a tool, such as ChatGPT, to build a simple OSPF configuration for a Cisco router, and it will not only generate a sample config, but it will also explain part of it.
This makes for a nice way to bootstrap a network testbed or help crystalize new networking technologies by way of example.
Cisco U. All-Access users can explore courses and learning paths on the foundations of generative AI, ethical and privacy concerns with generative AI, and others.
I'm sure it shares characteristics similar to all WiFi networks, but I'm also sure it has unique aspects of how and where to deploy it.
Cisco U. has content you can use to learn more about Catalyst Center Assurance as well as ThousandEyes Internet Insights and Meraki Insight.
On January 22, 2024, we announced a new CCNP concentration, Enterprise Network Assurance that covers skills you need to make use of these AI-enabled capabilities.
A past fear associated with automation was it would make network engineering obsolete.
Instead, it's made network engineering more scalable and exciting.
AI is a tool that helps push those excitement and capability boundaries farther.
When you're ready, post in the comments what you want most from AI and networking.
This Cyber News was published on feedpress.me. Publication date: Thu, 01 Feb 2024 18:43:05 +0000