In this article I will rant about a subject that I know nothing about. I think I’ve got some pretty good ideas, though.

What does it mean to know something? To know what a Lenovo Laptop is? To know how to play the guitar? Knowing something is very base in our minds as human beings, so basic that we barely question what it means to know something. How does our mind piece together data and conclude “I know X”? At the most basic level, via experience. The brain perceives events via its sensors – eyes, ears, tongue, skin, etc. – and stores data regarding those events in memory. Let’s say you ate some cake. It was one of those generic platter cakes you find at Safeway, so it was a bit dry and the frosting was sickly-sweet. The frosting was mostly white, but red letters spelled out a crude but funny in-joke for your co-worker, whose birthday you were celebrating. That last bit wasn’t so much a descriptor of the cake, but its importance will become apparent later. Now, when you think of cakes, specifically cheap platter cakes, what are the important characteristics you remember? Sweetness (sometimes too much!), rectangular shape, spongey inside that’s not as sweet, etc. Thinking of abstracted things (like a non-specific platter cake) doesn’t link to a bunch of pictures of cakes you’ve saved in your mind, it links to ideas that you’ve linked to platter cakes in the past. You can imagine each of these abstract objects as a node, whose defining characteristics are manifest as connections of certain strength or proximity to other nodes that characterize it.

Think of the platter cake as the node of interest: we know platter cakes. Platter cakes are connected to various nodes: it has a strong connection to sweet, a strong connection to celebration, and somewhat weaker connection to gross, etc. You can imagine that the abstract idea of platter cakes is portrayable as a long list of connected nodes and their affinities. For example, through a very convoluted memory of my own, platter cakes are also tied to 9/11. That 9/11 node connects to many other nodes, some of which may be ideas, some of which may be memories, but looking into the node that is 9/11 my brain automatically explores the other paths to a certain extent, filling out the idea of 9/11 that takes it past a series of characters to a collection of memories, ideas, and feelings. This description elicits images of the brain being a computer in a vast net of nodes (ideas, memories, etc) chasing nets around and receiving external stimulus via its sensors that may push it towards certain nodes, or even create new nodes.

This idea of knowledge as a connection of nodes also explains the “Eureka!” momemts that people experience. Their brain is sitting there, racing around its node-track, when some external stimulus pushes the brain in a certain direction. Perhaps it is puzzling about why objects are intrinsicly drawn towards the earth, and suddenly an apple strikes them in the head. In reaction, the brain examines the situation, checking out nodes connected to apples, etc, creating connections between nodes where it sees them, when suddenly, the track is completed! The disconnect between one set of nodes (theory) and another set of nodes (reality) had been connected via a short route! The brain races to compare other nodes in the close proximity, and discovers other connections that can be made. Sometimes, this leads the person to experiment more, gathering more data, and creating more connections until the idea is more complete and explainable to others in a way that will allow them to create the necessary nodes and connections. This even sheds some light on why two people that both “know about the same things” have trouble having in-depth communications about them. This is particularly true in the more abstract engineering practices.

Engineering itself is very much centered on individual contributors coming together to figure out problems. The problems discussed on the broad spectrum are usually not very abstract and are easy to imagine. Those problems share connections with very common nodes and connections, like those involving system architecture and communication. But, when the problem becomes deeper, and the separate parties have come to understand the same idea in different ways (described the same phenomena with different nodes and interconnects), it becomes difficult for them to have efficient conversation, as they spend time and effort fitting the other person’s ideas into their own web of nodes. When companies impose standards or hold large training sessions, engineers can much more easily discuss the topics due to the commonality of their node placement and interconnection.