In the ever-evolving world of technology, the quest for more intuitive and user-friendly interfaces has been a constant. From the early days of punch cards and command-line interfaces to the graphical user interfaces that dominate today’s digital landscape, the evolution has been remarkable. Yet, the next big leap in this evolution is already upon us, and it’s Natural Language Understanding (NLU).
NLU, a subset of artificial intelligence, is the technology that enables machines to understand, interpret, and generate human language. It’s the technology that powers your digital assistants, chatbots, and increasingly, a wide array of other software applications. But beyond these applications, NLU is poised to redefine the way we interact with technology, making it more efficient, accessible, and dynamic.
This stage of digital evolution is being driven by the rise of OpenAI’s GPT and other Large Language Models (LLMs) that allow machines to understand natural languages. ChatGPT’s ability to understand questions and respond demonstrated that this was a game changing evolution in AI.
Bricklayer AI was started to take this type of translation between human and machine and bring it to the cybersecurity world. Cybersecurity organizations have a significant number of tools that they are leveraging and providing a way to “Ask, Automate, and Answer” is now possible.
Efficiency: Making Complex Tasks Simple
One of the most significant advantages of using natural language as an interface is the efficiency it brings. Traditional interfaces often require users to navigate through multiple screens or menus, or to remember specific commands. With NLP, these tasks can be simplified down to a single sentence or even a phrase. This is true for a range of tasks of varied complexity.
Speed is another area where natural language interfaces shine. By eliminating the need to navigate through menus or type in specific commands, NLP allows users to perform tasks much more quickly. This can be a significant advantage in today’s fast-paced world, where every second counts.
For instance, instead of searching for the news on a subject, glossing over each of them and trying to grasp what’s new, you could just ask, “What’s new in cybersecurity today?”. In both of these cases, the NLP-powered system would understand your intent, parse the details, and perform the task for you. This ability to simplify complex tasks into simple, natural language commands is a game-changer for the industry.
Example of a complex question requiring Bricklayer to look at recent news, compile an answer and then report the answer in a specified format – all in a single step of natural language querying
Accessibility: Bridging the Digital Divide
Another significant benefit of NLP is the accessibility it offers. Traditional interfaces often require a certain level of technical proficiency, which can be a barrier for many users. With natural language interfaces, this barrier is significantly lowered.
If a user can articulate what they want in their own words, they can interact with the technology. This opens up the world of technology to a much broader audience, including those who may not have formal training or who may be intimidated by traditional interfaces.
An example is a user that wants to know whether an Indicator of Compromise (IOC) is malicious. In this, the user would simply ask the question – “Is this malicious – insert IOC here?”. As in the case of the normal analyst process, the goal here is to leverage any sources at the disposal of the user to answer the question and to summarize the response.
Dynamic: Adjusting to your Audience
The dynamic capabilities of natural language interfaces are another factor that sets them apart. Unlike traditional interfaces, which are often static and rigid, natural language interfaces can adapt and learn over time. Further, another pain point with traditional machine interaction approaches has always been dealing with the unknown. The dynamicity of NL interfaces allows for sensible answers and decision making capacity even in such situations. They can understand context, handle ambiguity, and even learn from past interactions. This makes them not just more powerful, but also more personal.
Bricklayer has multiple roles that it can take depending on the question. These roles can be customized to communicate more clearly with various human users. For example, you might ask Bricklayer about a particular malware family that was on the news last night. The question could be asked with the following direction. “My CEO would like to understand [malware_name] better. Please provide a response that he can utilize at the c-level and board”. However, this same question could be asked from a technical perspective to understand whether the organization needs to worry about this malware and what recommendations exist for protection. “Please tell me what is known about [malware_name], what CVE’s it targets, and what recommendations you have for mitigation”.
Example of a high-level answer giving an overview
Example of a more technical answer providing details
The Future of Natural Language Interfaces
The potential of natural language as an interface between people and technology is vast. As NLP technology continues to advance, we can expect to see it integrated into more and more applications, making our interactions with technology more natural, efficient, and accessible.
The advent of natural language as an interface is not just an incremental improvement in technology—it’s a paradigm shift. It’s a shift from interfaces that require us to learn and adapt to the technology, to interfaces that adapt to us and our natural way of communicating. It’s a shift that promises to make technology more accessible and user-friendly than ever before, and it’s a shift that’s already well underway.
Bricklayer embraces the use of Large Language Models to empower technology and human integration to support increased efficiency, accessibility, and dynamicity.
