AI Networking: Training the Unruly Child

Personal Experience

Thirty years ago, I founded an AI-based software company. AI was described as “knowledge-based systems” back in those days. From a basis of sales knowledge and experiential data, I programmed the software to make recommendations to improve sales. It measured and forecast performance, adapting as the sales of individuals and the company progressed. 

Critically, how I made it intelligent was my applying sales experience, judgement and adaptation to results achieved that was programmed into the software. The complexity of today’s evolving networks and massive increase in compute power plus cybersecurity threats make it a whole different world. Artificial Intelligence has been around for a while—using data and adapting to change are not new.

The application of AI to networking and security is what had me write this article since today’s complexity and opportunities for network as a service, network management, data curation and cybersecurity make the exploration a necessity. It seems like an exploration at this point because although there are attractions—cost savings and responsiveness to changing conditions—there are significant unresolved issues that the article raises yet still it looks optimistically at the potential possibilities.

Challenges

The main challenge for GenAI is the distracting and misleading use of the word “Intelligence.” Yes, it already has outstanding characteristics, bringing plain language explanations of learned concepts, coding and surprising graphics capabilities. It’s much more than the knowledge-based systems I referred to above. However, it does not meet our definition of intelligence by any of the obvious criteria.

Also, it currently does not accurately adapt to new information. Here’s an actual example. My wife asked Copilot how to do something on her Galaxy phone. Copilot claimed it knew about the latest software loaded on her phone—but the instructions it gave were incorrect. When asked why, its many apologies included “I have certain limitations and potential weaknesses in how I adapt to new information.”

Imagine if applying GenAI to a critical part of your network infrastructure, data curation, service performance or transaction security and the results were incorrect. You would be putting your organization at great risk. You may have already experienced something similar. 

Can GenAI apply judgement or innovative thought in the context of our business goals? How can it deal with the unacknowledged emotional aspects of every decision we make? We shall see! Suddenly, it doesn’t sound so intelligent.

This article is not intended to be a Luddite rant, since I do think that this is an exciting journey for all of us. However, before we get to the positive aspects, there’s still the issue of cybersecurity threats penetrating the large language models (LLMs). I.e., how do you know if the data you are basing your decisions on is inaccurate or deliberately misleading? For instance, if a threat actor deliberately distorts data about an asset’s authentication or privilege, then your network and organization is now toast.