The meaning of models
In recent years we have assimilated a lot of new ideas. Imagine yourself as a drafter in the 1950s, and how mind-blowing printing technology is today. How about a lot of the tedious calculation-based work that has been replaced with software tools: quantity take-offs, spatially organizing office space in a building, or even in creating models themselves. We work in an industry that is constantly evolving and changing. BIM, our chart and compass guiding us in the right direction.
We plan, construct and reconstruct entire buildings through BIM models. Hundreds of times a day, we mention the word model due to the high demand for our BIM services. But, have you ever taken a minute to ponder the meaning of the work itself? While there are many definitions for this term, we can say that a model is a simplified representation of the more complex reality. Through this representation, we will better understand how this reality works and understand less tangible concepts.
A BIM model allows us to represent in a simplified way what a building is. We can understand how it works to anticipate or predict possible problems through this reconstruction. But there are many other types of models as well.
A map is also a model. A plan is a two-dimensional representation of a three-dimensional reality. This representation only takes the relevant information, leaving out unnecessary details. A model allows us to understand how an object, an event, or a phenomenon of any kind is.
There is a great example of this, in a ted talk called "When Machines have ideas" by Ben Vigoda. He explains the solar system’s evolution, utilizing models which allow us to conceptualize these celestial concepts in an easier way. The first model places the earth at the center of the system. Today we know that this was an incorrect model, but at the time, it was a crucial paradigm shift in understanding how the solar system worked. By placing the sun at the solar system center, we get more accurate predictions, although we still have errors that scientists are working out. The path of Mars is not exactly as described in the model. Finally, by changing circular orbits for oval orbits, we arrive at a model that perfectly explains the reality we want to study.
Machine learning and visualization tools take these concepts to a higher level. If I said I was wearing a shirt that is “Not Red” you might think of me wearing a polka-dotted shirt, maybe it’s blue and pink. Then again, what is the model? The logic diagram? Me modeling the shirt? This blog forcing you to consider the mundane?