Generative AI is a powerful technology that can create new content, insights, and solutions from data. But how can businesses leverage it to gain a competitive edge and accelerate their growth? In a recent interview with NeuralNation, Matt Wood, VP of product at AWS, shared his insights on how generative AI can create a flywheel effect for business growth.
Wood explained that generative AI can be applied to four major buckets of use cases. The first three, generative interfaces, search ranking and relevance, and knowledge discovery, are already well-known and implemented by many businesses. However, the fourth bucket, automated decision support systems, is the most challenging yet impactful. It enables businesses to solve complex problems with the help of autonomous intelligent systems.
And this is where companies can build a flywheel. When implemented correctly, the flywheel can create a significant advantage over competitors, according to Wood.
The AWS VP will be speaking at VB Transform 2023 next week in San Francisco, a networking event for technical executives seeking to understand and implement generative AI. I’ll be moderating a panel where Wood will be joined by Gerrit Kazmaier, VP and GM for data and analytics at Google. During the panel, they will delve deeper into the impact of large language models (LLMs) for enterprise leaders and explore the flywheel concept.
Cybersecurity serves as a prime example to illustrate the flywheel potential of LLMs for other enterprises, as explained by Wood. Imagine experiencing a set of emerging threats in your application, with subtle signals scattered across multiple services and architectures. LLMs, with their ability to find correlations between data points, excel at detecting these subtle differences and correlating them into a larger signal.
“So what would otherwise be split across a diluted surface area now stands out like a flashing siren,” said Wood.
Investigating root causes of cyberattacks
Delving deeper into this example, LLMs also enable automatic investigation of the root cause of an attack, providing an explanation in natural language. Furthermore, LLMs can identify the specifics of the threat and suggest defense strategies.
Once you review and approve the suggestion, you can simply click a button, and the LLM system will execute the necessary code to remediate the attack, vulnerability, or operational problem.
“Compare that to the level of human investment and high-judgment decisions that would need to be made today in order to get to that level of specificity,” said Wood. “And just, you know, going and finding all those log entries and then figuring out the attack vectors and then figuring out what to do, takes a remarkable amount of skill, a remarkable amount of time.”
He added: “Imagine all of that is happening all the time, automatically under the hood. And what you’re presented with is not a random set of ones and zeros that are operating slightly unusually, you’re presented with a full incident report, as if it was created by a set of humans, which you can interact with, and fine-tune and revise.”
Constantly improving feedback loop
Generative AI also creates a feedback loop that continuously improves the system’s performance over time.
“If you take the feedback from these sorts of interactions, the improvements you would make to a threat report and the remediation, for example, then if you bake those into the large language model, the language model will perform better, and you’ll get more users,” said Wood. “If you get more users, you’ll get more feedback. If you get more feedback, you’ll get an improved model. If you get a better model, you get more feedback.”
All of your interactions make the threat report better for the next time. This creates a flywheel effect that organizations can leverage. “Flywheels are a very rare technology as it turns out, but there is a real flywheel here with generative AI,” said Wood.
He added: “The earlier you can spin that as an organization and the faster you can spin it, you’ll be able to create much more intelligence, much more automation, much more accuracy, much less hallucination as you go, and at some point, if you can spin that flywheel early enough and quickly enough, then you’ll have this enormous gap against your competitors, and competitors won’t be able to catch up at any cost because that’s how valuable the flywheel is.”
