I’ve been at Cisco a few years and seen just a few transformational occasions have an effect on community engineers. After I first joined Cisco in 1998, IP telephony got here on the scene and disrupted not solely classical circuit-switched communications however these of us in networking as nicely.
More lately, automation, programmability, and software program grabbed everybody’s consideration, promising to upend the best way we take into consideration, design, and function networks.
Today, you may’t go 10 toes (3 meters for these of you outdoors the US) with out somebody speaking about AI. CES 2024 has simply wrapped up, and Artificial Intelligence (AI) was in all places.
Whereas IP telephony and automation might have been reserved to particular locations in IT, folks from all walks of life are discussing and utilizing AI. The networking business particularly is shifting quickly round expertise and expertise acquisition in addition to product integration and focus. All this transformation and hype can depart folks confused and questioning how they’ll wrap their head round what AI is and tips on how to finest make use of it.
Before going an excessive amount of additional, it’s vital to say that AI is not only one factor. It additionally isn’t new. AI is a category of machine studying that makes use of math to investigate giant units of information to make predictions, present automated classification, and summarize giant knowledge units.
In truth, just a few years in the past, when this notion of machine studying (and AI) began to first emerge in networking, I took a web based course that centered closely on the maths behind machine studying to do issues like cluster varied take a look at outcomes to establish anomalies and analyze a big set of quantity photos, offering new photos so AI might appropriately establish the quantity it receives. This similar form of predictive and classification AI is already baked into a number of Cisco merchandise. Have you ever been on a Webex with somebody mowing outdoors, but nobody on the decision can hear something? That adaptive noise canceling is a type of AI.
Capturing all the eye as we speak, nevertheless, is generative AI, a brand new use case that, as its title suggests, is about producing new content material by analyzing an array of current content material. This generative AI receives a immediate that specifies what sort of content material to create and in what vogue, and it makes use of its underlying mannequin to fulfill the request. Different generative AI instruments exist for various media and totally different use circumstances. Here are some methods of utilizing it:
- Ask varied generative AI techniques to put in writing a brief story within the type of Ernest Hemingway.
- Create an image of you shaking Albert Einstein’s hand.
- Convert a video you shot in your telephone right into a silent film.
Because of the viability and availability of generative AI, the excitement surrounding it has grown to an all-out symphony. People have been attempting out totally different use circumstances for it in addition to performing immediate engineering to fine-tune the outcomes. As with all highly effective instruments although, we should take care. ChatGPT, for instance, warns you that it will probably make errors.
Network engineering is an fascinating use case for generative AI. You can ask a software, similar to ChatGPT, to construct a easy OSPF configuration for a Cisco router, and it’ll not solely generate a pattern config, however it can additionally clarify a part of it. The preliminary config it generates could have placeholders in it, however you may immediate ChatGPT to then regenerate the config with pattern values within the placeholders. This makes for a pleasant approach to bootstrap a community testbed or assist crystalize new networking applied sciences by means of instance.
How are you able to be taught extra about AI, its use circumstances, and its caveats? Cisco U. has you lined. Cisco U. All-Access customers can discover programs and studying paths on the foundations of generative AI, moral and privateness considerations with generative AI, and others.
For these trying to be taught extra about how generative AI can form community engineering and operations, we simply launched two tutorials included in Cisco U. Free, “Create a ChatGPT Client with Python” and “Chatting with Cisco IOS XE”. These are nice if you wish to learn to construct your personal integrations with generative AI.
Remember I mentioned that Cisco has been folding AI into our merchandise for some time now? You can begin to get worth from AI as we speak in your networks utilizing a wide range of Cisco options.
Consider your WiFi community. I’m positive it shares traits much like all WiFi networks, however I’m additionally positive it has distinctive features of how and the place to deploy it. Instead of utilizing static, manually tuned thresholds, you need to use predictive AI in Catalyst Center Assurance to supply extra correct alerts when issues happen. In the picture beneath, the inexperienced band is the predicted baseline, calculated over an prolonged time interval, whereas the blue line is the precise worth. The pink bands sign anomalies, which can generate alerts.
Cisco U. has content material you need to use to be taught extra about Catalyst Center Assurance in addition to ThousandEyes Internet Insights and Meraki Insight. On January 22, 2024, we introduced a brand new CCNP focus, Enterprise Network Assurance (ENNA) that covers abilities you have to make use of those AI-enabled capabilities. The studying coming this spring for ENNA will delve deeper into these analytics and assurance options.
I began out speaking about how, if you happen to’re on this business lengthy sufficient, you’ll see your share of disruptive applied sciences. A previous worry related to automation was it could make community engineering out of date. Instead, it’s made community engineering extra scalable and thrilling. Likewise, AI is a software that helps push these pleasure and functionality boundaries farther. Now is your time to be taught, experiment, and talk about.
When you’re prepared, publish within the feedback what you need most from AI and networking.
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