In the tech world, every year is the year of something. Recent examples include the year of the metaverse, the year of blockchain and the year of the cloud (a perennial favorite dating back to the last century). But in 2023, artificial intelligence (AI) took its turn.

AI, of course, is hardly new – flashback to "2001: A Space Odyssey" and the classic line from HAL 9000: "I'm sorry, Dave, I'm afraid I can't do that." While AI and machine learning (ML) aren’t new and have been progressing for years, generative AI (genAI) and ChatGPT, in particular, made AI cool, pervasive and mainstream.

AI, naturally, was a mainstay of our coverage in 2023, touching nearly every area of our coverage. While our readers flocked to AI stories, like AI itself, our top 10 list spans a broad spectrum – from AI being used by the bad guys to AI’s impact on networking to synthetic data to large acquisitions. And we also reported on the hype and misinformation prevalent in the industry and the confusion it's causing for enterprises.

And with that human-generated intro, here are our top AI stories of 2023.

In our top AI story of the year,  SDxCentral’s Emma Chervek reported on a session at the Nvidia GPU Technology Conference (GTC) in March. Experts from Nvidia, Deloitte and the Defense Advanced Research Projects Agency (DARPA) outlined the landscape and challenges that AI poses for creating a cyberdefense strategy in an AI-driven world. The article provided a series of examples and suggestions for ways that both public and private organizations can mitigate potential AI cybersecurity risks.

Looking at the risks and how AI is changing the threat landscape, the role of generative AI technologies, such as ChatGPT cannot be understated. Kathleen Fisher, director of the Information Innovation Office at DARPA, commented that with generative AI, adversaries are now able to generate fake websites rapidly and are able to create customized phishing messages that can be highly effective.

AI and ML were unsurprising topics of popularity at Cisco‘s annual sales kickoff in terms of how those technologies will impact the industry at large and Cisco’s networking business. Chervek wrote that while AI has existed in some form since the 1960s, its current iterations are finally able to change the definition of what is possible in terms of unlocking the value of data, Cisco VP Thomas Scheibe, who leads data center networking product management, told SDxCentral.

Today’s IT estates are massive, comprehensive and increasingly difficult to manage. IT leaders want to be more efficient, intuitive and sustainable – but they often don’t know where to start, wrote contributor Taryn Plumb in our third most popular AI story of the year.

“Enterprises today are sitting on mountains of data that, in many cases, they do not know how to mine, analyze or use to benefit their business,” said Antoine Shagoury, global CTO of Kyndryl.

To address this problem, the multinational IT infrastructure services provider introduced its intelligent open-integration technology services platform Kyndryl Bridge in September. Over the last 10 months, the platform has experienced significant gains, including an estimated $1 billion in annualized customer savings, the IBM-spinoff company announced.

Generative ATI platforms, such as ChatGPT, are undoubtedly one of the most groundbreaking and discussed technologies of 2023.

But when looked at from a broader view, writes Plumb, it is still a very young technology. And because it has been pushed out so rapidly, it has its limitations – notably when it comes to accuracy, scalability, and its recollection capabilities. Plumb wrote that this has led to a growing call for what has been deemed “long-term memory” for AI applications.

As the name would suggest, this allows models to remember things for a long time – rather than just short intervals, as is the current standard.

“While AI models such as GPT from OpenAI are trained on billions of pieces of data, they don’t remember anything you show them or even anything they give back to you,” said Edo Liberty, founder and CEO of Pinecone. “AI models are stateless. They have no memory.”

Given the rise in mainstream coverage of AI, it’s no surprise that our AI definition article landed in the fifth spot. In case you need a refresher, AI is defined as a digital machine’s capability to perform cognitive-like functions typically associated with intelligent beings. This includes interacting with their environments, solving problems, deducing facts, forecasting, offering suggestions and performing complex calculations.

Most of today’s advanced AI models are self-learning, meaning that they have the ability to iteratively improve on themselves through feedback loops. Others that are only just evolving have the ability to generate text, audio, video and code – even music and art thought previously to be solely the domain of humans. This is known as genAI.

AI needs data – lots and lots of data. While enterprises are collecting data in the order of petabytes, exabytes and even zettabytes, data is messy, often disparate and siloed. Many enterprises are hesitant to use it (and thus gain insights from it) in certain environments because it is highly proprietary; in regulated industries like telecommunications, most data can’t even be touched due to its highly sensitive nature.

For these reasons and others – including lack of available data that is needed for large scale AI, biases in data or data drift – a growing number of enterprises are turning to synthetic data. This, as its name suggests, isn’t real data, but closely resembles it.

“We have to make sure that customer data is completely kept private, that nothing is leaking out,” said Guenter Klas, senior manager for R&D, research clusters, AI and quantum at telecom giant Vodafone, which is beginning to leverage synthetic data.

Coming in at No. 6 is contributor Sean Michael Kerner’s report on how Versa Networks is boosting the capabilities of its secure access service edge (SASE) and SD-WAN portfolio with a series of new security and networking enhancements that benefit from the power of AI.

The new AI features leverage Versa’s telemetry data collected across customer deployments. This allows the company to train its algorithms to bolster security in real time, optimize network operations and simplify management.

Contributor Chris Preimesberger looked at why Databricks bet $1.3 billion that generative AI will continue to be the most strategic development in IT since the dawn of the cloud. That pile of cash goes into the bank accounts of investors in MosaicML, a 2-year-old, under-the-radar San Francisco startup that Databricks bought this summer. MosaicML makes a generative AI platform using machine learning that enables users to train and deploy custom AI models with their own data.

This acquisition could reveal the start of an important trend: That companies able to help other companies fine-tune their AI strategies for business advantage can expect to see their corporate values shoot way up over the coming months and years to become takeover targets.

“The Databricks-MosaicML merger is a sign of the growing importance of generative AI,” said Mike Gualtieri, principal analyst at Forrester Research.

In the movie "Jurassic Park," Dr. Ian Malcolm (played by Jeff Goldblum) says, “I’m simply saying that life finds a way” in reference to dinosaurs finding a way to reproduce despite all being the same gender. Like life in "Jurassic Park," technology also finds a way – a way into the enterprise, a fact not lost on IT and security teams that have had to deal with everything from Google Search to mobile phones creeping their way into the organization. Once inside the enterprise, they reproduce like the dinosaurs in "Jurassic Park."

In June, we reported that the latest technology that users are accessing at work is ChatGPT, which carries unique implications and challenges, leaving some CISOs and other technology leaders wondering if they should block ChatGPT. And many have. According to a report by HR Brew, many companies – including Apple, JP Morgan Chase, Amazon, Accenture and other — have banned or limited its use.

What approach should you take? Like any critical question, this one isn’t easy to answer. But it is one that James Robinson, deputy CISO at SASE provider Netskope, had to address.

Coming in at No. 10, SDxCentral CEO Matt Palmer dug into AI, analyzing our own reader-driven data to provide insight into this broad and complex technology and its adoption at the enterprise level.

What were SDxCentral members reading? Everyone is trying to figure out what AI is, or,more precisely, what it means to them in the context of enterprise or service provider infrastructure and operations.