We Help Machines Understand People
We reverse-engineer the human mind using a top-down, inside-out approach in an attempt to uncover the specific primary agents that constitute the society of mind. Bringing together semantics, linguistics, psychology, and philosophy into a coherent high-resolution model of the human psyche.
In the future, nobody cares about CPU speed and disk space.
In the future, technology is everywhere and people choose their machines and apps strictly by their compatibility with the user – their humaneness.
We’re here to help this future get here sooner by teaching machines how to be more human-like. For a future in which people don’t use computers, but instead, they interact with them – just like we do with one another.
Here, at Bayon, we believe in semantics. True, semantics is scary and overwhelmingly complex, but without semantic capabilities, computers and people will never truly understand each other.
So, since it’s better to fail at doing the right thing than to succeed doing the wrong thing, that’s what we do here at Bayon.
We are here to close the gap between human and machine by explaining to computers the meaning of being human.
We build on the work of Marvin Minsky, who described the human mind as a society of agents.
By bringing together semantics, linguistics, psychology, and philosophy into a single coherent high-resolution model of the distributed system that is the human psyche we intend to create an environment for these mental agents. A type of an organized social environment that facilitates their organization and communication.
Within this environment, we will bring these mental agents to collaborate – creating the society of mind.
Thankfully, all of us humans come equipped with state of the art semantic supercomputer mounted inside our skulls. For this reason, we chose to focus on the top-down, or inside-out, approach rather than the mainstream bottom-up approach.
Indeed, this approach is by no means new as philosophers have been trying to figure out the constants of perception for millennia. However, with the help of some new technological advancements and a set of adjusted reverse engineering methodologies, we set off to explore the inner mechanisms of the humanOS with computerized scientific accuracy.
The Model, In a nutshell
I didn’t want to wait until everything’s done and ready to start publishing. So, I decided to use this website to publish the story as it’s being written.
This model is still a work in progress and new materials will be added periodically. But if you’re interested, you can start reading this book before it’s done and ready.
Nothing lives in a vacuum. Everything has an environment. Think of it as the space where atomic meaningful entities are used to construct elements of perception. Something like a mental circuit board.
The key for a good theory lies in repetitive and mothodological scrutiny, and large coherent theories are hard to find. These are the guidelines I use to maintain stractural stability.
There are many ways to perceive the same thing, but some are more accurate than others. Explore with us the capabilities and best practices of the human semantic network.