Artificial Intelligence (AI) has become a massive buzzword in the tech world over the last year or two, but it’s still generally misunderstood. When you hear AI at a keynote or in a board meeting, you’re most likely hearing people discussing generative AI and how it can be useful for content. At Gomboc AI, we’ve built a different kind of AI — deterministic AI — that uses specific datasets and definitive semantics to vastly improve the DevSecOps experience.
Deterministic AI vs. Generative AI
Generative AI is essentially built to reference a massive library of information and use that information to generate something new in accordance with a user’s inputs to mimic the experience of talking with a human. It gives you a new answer every time and sometimes twists itself in pretzels to deliver a polished-looking product. Generative AI typically uses models with billions of parameters over which customers have limited visibility and control. This can be problematic in the world of cybersecurity where precision and context are key. It can also have hallucinations — ChatGPT has been known to completely make up information for the sake of meeting the user's requested prompt. Such a tool would not go over very well in the world of cybersecurity where precision and consistency are key.
Deterministic AI is built to reference a completely finite data set. It operates on a predefined set of rules and algorithms, meaning it produces the same output for the same input, 100 percent of the time. There is no randomness, no hallucinations and no lack of consistency. Even on the off-chance that the Generative AI was trained on a security dataset, it’s not your security dataset. Gomboc.AI circumvents this problem by virtue of taking inputs from the customer's actual configuration and security policy. Using this technology, the Gomboc platform offers a precise and tailored approach to safeguarding cloud infrastructure which offers all the convenience of AI without the headaches.
Deterministic AI vs. Machine Learning
Machine Learning was, in many ways, the AI of yesteryear. It has been around for decades and has helped numerous IT products improve the customer experience. At its core, machine learning is a statistical model which takes historical data and uses it to predict the most probable outcome. However, even these are wrong a significant portion of the time. Let’s illustrate this point with an example.
Imagine a person goes into a restaurant and asks for a wine recommendation. A sommelier using a machine learning approach might suggest a selection with 83 percent likelihood it's what the customer wants. What the sommelier is really doing is creating a profile of the customer, putting them in a category, and determining that 83 percent of the past customers in that category enjoyed that wine. While that’s a pretty decent hit rate, it still means that 17% percent of the customers will not get the wine they want, and therefore, the model has failed them.
Machine learning is an excellent model for plenty of use cases, and can be very effective in fields like sales and marketing. But once again, effective cloud security requires precision. A 17 percent rate of failure in security would result in a lot of breached information and lost customer trust.
A sommelier using a deterministic AI approach to this encounter wouldn’t rely on historical data to make the decision. They would instead engage with the customer and ask them questions from a predefined list to narrow down an exact wine selection. They would ask questions like red or white, sweet or dry, old world or new world. Each answer would narrow down the options until only one remained. This wine would be exactly what the customer wants with absolute certainty.
Cure What Ails You
Gomboc's unique approach to AI in cloud infrastructure security is built to determine exactly what our customers need, and deliver that product with absolute precision. It's not about historical transactions but about comprehending the current state of the cloud infrastructure. It's not a pattern matching technology that scans online sources and regurgitates information whether it makes sense or not. This is a system that actually understands cause and effect just like a human would. The model acts as a cloud expert, determining what a system’s unique needs are and delivering a product which is tailored to the specific circumstances of the user.
Security product vendors like to tell stories about shiny new problems and convince you to buy new products because you’re constantly facing new threats. But the dirty little secret of the industry is that most breaches have always happened for the same reasons: lack of hygiene. People don’t change their passwords enough, don’t bother to encrypt or forego logging and monitoring. It's kind of like a collective lack of security handwashing—everyone understands the importance, but the execution falls short.
Instead of painting a narrative of an increasingly sophisticated threat landscape, our focus is on the enduring common vulnerabilities. Deterministic AI figures out which of those risks threaten your infrastructure and simply takes those problems off your plate, while eliminating a great deal of risk in the process. While we take care of those menial, hygiene-related tasks, your DevSecOps experts can devote their time to what matters most: building the business.
To get started using deterministic AI to work smarter, not harder — and save your security team hours out of their week, click here.
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