Welcome to the oldest document online. My name is Craig Brown. As an unemployed Marine Biologist, I became interested in technology when microcomputers were invented.

They say that history is written by the winners, but if you want to know the truth, ask one of the losers. There is nothing but truth on this site—truth recorded at the exact moment it occurred. There is no rewriting of history here.

This is my real-life story. My life’s work resulted in a technology that is difficult to separate from the hype surrounding modern artificial intelligence. The American people voted for a country controlled by billionaires. The billionaires claim artificial intelligence will replace everyone, that they have invested successfully, and that we should all accept our fate. I don’t know what it takes to make people believe in truth over money, but everything on this site is a truth I lived through.

There is something time-critical you need to understand while reading through this site: it isn’t only about me.

When I heard Jensen Huang’s opening speech at the October 2025 NVIDIA conference essentially claim that NVIDIA invented everything, it was upsetting. It was upsetting because I knew many of the hundreds of pioneers who contributed to the foundational libraries NVIDIA is sitting upon ten layers up. I am the last one I know of who has stayed in the industry; others have retired, and many have passed away. What I am trying to introduce with my company, GRAYBELT Innovations, is not just my own work—it is what I learned working alongside those original pioneers. And when I say original, I mean original: writing in assembly language with zero documentation.

Decisions made back then shaped every software development from 1980 until today. What might be the foundational innovation in software history is now just used as a simple introductory exercise: the “Hello, World!” program.

In early personal computers, there was no single instruction for putting text on a screen. Displaying even a single letter required a complex sequence of machine instructions. A programmer had to calculate the exact video memory location, load the character code into a processor register (like the accumulator), and execute the instructions to push that value into memory. That entire process had to be repeated for every single letter in the output. It made no sense for every developer to constantly rewrite the exact same low-level code, so we created reusable routines. As methods for sharing code evolved, these routines were compiled into libraries, allowing others to display “Hello, World!” without reinventing the machine-code wheel.

Libraries were built on top of libraries. When a coder spent days or weeks solving a brutal problem, they didn’t keep it to themselves—they contributed it to repositories for other programmers to use. Over time, many platforms emerged, with Stack Overflow becoming the most famous. These were contributions we made freely. In those days, working seven days a week was standard, and we weren’t paid for those extra hours. For anyone wondering where all those uncounted hours went: you are using them every time you think AI is helping you write code.

I considered taking down this website because I believe we’ve reached a point where very few people actually understand the full stack underlying modern AI. People believe tech billionaires who maybe wrote a “Hello, World!” program early on, but that’s about it. I would challenge any current tech executive to explain how their underlying stack actually functions.

Which brings us to why this site is still live. Look at GRAYBELT and consider this: this technology is grounded in reality.

This is what should have been the first AI boom 30 years ago when it was initially conceived. But the original tech billionaire—Bill Gates—decided to shut it down. I demonstrated this technology to people at the NVIDIA conference and was told it would be of great interest in two years, once people get tired of what they currently call AI. But I am working two jobs while managing serious health issues. If I don’t pass this on, all of this technology goes with me.

Even more upsetting than being told to come back in two years was the fact that these employees were genuinely surprised anyone my age could still be functioning at this level. I am not exaggerating—I was directly asked how I was capable of doing this work. And, of course, I couldn’t get anywhere near NVIDIA’s top executives.

A few weeks prior, I attended an IBM AI conference. I had hoped to speak with an executive and propose how my technology fits into IBM’s existing business. It wasn’t about having an inflated sense of self-importance, but I encountered the exact same reaction as I did at NVIDIA: “How does somebody your age still function?”

Why does this matter? Because this technology clearly demonstrates how it actually benefits humanity. It is not “artificial intelligence.” The term itself is an oxymoron; there is no such thing as artificial intelligence—not yet, anyway. The technology I pioneered began in 1982 with a simple question: How do you teach a computer about human behavior? That question stayed with me throughout my entire career.

The ancestor to GRAYBELT AI was created 30 years ago in a program called Floater. It never claimed to think; it simply learned how a user preferred specific situations to be handled. Instead of calling it “Floater Mimic,” the label “AI” had a cooler vibe back then. My intent wasn’t to deceive anyone—I was just paying homage to science fiction.

The technologies developed by GRAYBELT require human input at critical stages. It does not make critical decisions without human direction, and it does not suffer from hallucinations. It directly contradicts everything today’s AI promoters claim: it doesn’t require massive, energy-draining data centers, nor does it demand endless token purchases. While certain components of the system—which I call cogs—utilize frontier AI to process information, those tokens are spent only once. Think of it like charging a battery once and storing that energy indefinitely.

My goal is to launch projects in developing nations where current automation is displacing workforce jobs, as well as initiatives in the U.S. that genuinely serve people. Frankly, I’ve reached a point where I don’t care what the establishment thinks. The venture capitalists I spent my career doubting would be a welcome sight compared to the baseless claims of today’s tech figureheads.

Is the American Dream dead? It is for anyone without connections in the top 1%. But the inventions featured on this site are real, backed by media coverage from the eras they were built. GRAYBELT wasn’t built by just slapping old technologies together; it was built by combining the fundamental techniques used to create them.

Why does that matter? Consider one invention from my patent application: a communications system designed to route data between servers without any server knowing the IP address of the others. How? By adapting techniques from early Bulletin Board Systems (BBS)—real dial-up era methodology. Why take that approach? Because it renders the system inherently unhackable.

If that sounds like a bold claim, ask how I verified it: I spent three years in Russia working alongside top security researchers and hackers. They admitted they couldn’t find a way around it. People love to talk about “eating your own dog food” in tech. Did any of today’s tech giants risk their lives testing theirs? I did.

I have been dealing with a rare situation, and I would very much like to hear from anyone else who needs to do the same thing.

GRAYBELT Innovations can be viewed as multiple companies. It is not an exaggeration to say that more than 46 years of coding and engineering experience were put into this organization. This was not the intended result of what I started more than 13 years ago. The intended result was an information security product called Reflex.

Untethered by a project manager, solving one problem led to the discovery of another. And by problem, I mean a fundamental hole in technology that was required to create a comprehensive solution. I went from Digital Equipment Corporation to Cullinet Software to Lotus Development Corporation—companies that led the world in innovation. I am programmed not to focus on what currently exists, but to imagine a solution and work backward. I would dare say any experienced software engineer reviewing the Reflex platform would be surprised by all the new technology that has been created.

The situation mentioned above occurred when I had to organize every advancement into a patent application. Reflex breaks down into 15 distinct, unique inventions. I don’t mean changing a few lines of code and claiming it as an invention—I mean totally new concepts.

And these inventions are packaged into what I call COGS. A COG is not like a software library; it is more like an entire system contained within an object. COGS are combined to make new applications—not “apps” in the casual software sense, but entire businesses existing across different market segments. And this is where things get complicated when describing the system to a potential acquirer.

The Portfolio Breakdown

• Reflex (CISOware): As stated above, many of these COGS originated in Reflex. Reflex is managed under a company called CISOware and is marketed as an information security and incident response platform. However, it is really a framework at its heart. It has its own version of AI—the evolution of the principles behind the Floater AI engine. My vision of explaining a person to a computer was successfully implemented. The vocabulary used is industry-specific, but by swapping in a different vocabulary, an application for an entirely different industry (where Reflex-like functionality applies) is created.
• GRAYBELT Situations: Built using these same COGS, this application applies to any planned procedure. It does not involve understanding human behavior and is much simpler than Reflex, but it is applicable to almost any organization.
• GRAYBELT HR: Uses a COG called the Universal Translator to understand words used in a domain-specific way. For example, an information security manager might post a job requiring “malware expertise,” while an applicant lists “experience with antivirus.” Current recruitment technology cannot match those two variants of the same meaning. GRAYBELT HR solves this. It is a disruptive technology for human resources, using a complex formula that accounts for skill terminology, years of experience, and the actual percentage of time spent on that skill to calculate a precise numeric rating.
• GRAYBELT GOV: An offshoot of GRAYBELT HR focused on the U.S. government NICE (National Initiative for Cybersecurity Education) framework. It goes far beyond standard compliance mapping. Not only can it translate common terms into NICE terms, but it can also evaluate a specific certification and determine exactly what it represents in terms of hands-on NICE experience.
• GRAYBELT Domains: The platform with likely the biggest potential impact. This is a system for creating domain-specific AI that runs on consumer-grade hardware. This is not a RAG system. It is based on GRAYBELT AI and does not require a Large Language Model to operate. Because GRAYBELT AI does not natively speak in human prose, a small open-source LLM is strictly used when the desired output is a constructed response in English. If raw data is preferred, the system returns it directly for user editing. The system comes complete with hardware specifications.

Global & Sovereign AI Potential

GRAYBELT Domains can be used by a nation to create sovereign, domain-specific AI and become a major player in the AI category without relying on support from American tech billionaires. I am actively seeking interest from foreign governments.

(Note: GRAYBELT AI is fundamentally different from current frontier AI models. There are no national security-related risks or functions associated with it.)

The rest of this website is all about credibility. I’ve made some big statements above, and you will find the applicable skills and history detailed throughout these pages.

Thank you for your time!