INTUIT

Analogue scripting is the basis for architecture’s use of emergent theory. Emergent theory is the basis for all life organisms. Every living entity uses localization to complete its form as its coded DNA does not allow for a complete model to be built. The model is the structure of the organism. For instance human DNA codes for how the body will work, however, it does not code for placement of every cell. The cell’s placement is determined locally. The body becomes a cross between top down organization, DNA, and bottom up organization, localized input.

These crosses of organization allow for adaptability within with a given concept. This allows for variation and randomness within a homogeneous system, turning it into a heterogeneous system of organization. Whether body or architecture, both become more complex and unique when each moves from homogeneous to heterogeneous. The heterogeneous system can then take on localized optimizations. The architectural heterogeneous system can be optimized beyond a single comparative value. This is the beginning of the argument for the curve of construction.

Moving beyond that, the heterogeneous system allows for topological change of a typological system. Frei Otto’s soap bubble experiments are an example of this change. He was analyzing the ability of the soap bubble to continuously optimize for the smallest space it could enclose. He used the parametrics of the soap bubble as the typology. As he adjusted the forms for which the soap bubble was confined, the bubble (the parametric) was altered for the new topology. It’s typology did not change. Frei Otto determined that the soap bubble could pose multiple variations to appease the same parametrics. Each variation was optimized, but had differences from the other variations. The group of these variations is known as the epistatis. Different variations would be determined from the epistasis based on the input path to which the parametric responded.

This way of scripting and analysis allows for architectural variation. Like the localization idea, the epistasis takes on a variety of optimizations. As the optimizations are balanced differently, different variations are outputted from the epistasis. Each time the building is designed, it is changed, but still satisfies its previous requirements. The idea of doing this process in analogue is to capture a larger breadth of optimizable systems, especially those that cannot be determined digitally.

This scripted and emergent way of working allows for design optimization among a variety of agents. There then can be localized input to solve individual problems without compromising the greater concept. The top down, bottom up joint approach allows for an epistasis to be compiled and depending on the order of applied optimizations, final output becomes variant yet remains with the solution set, the epistasis.

The brain’s biological structure is a multilayered sequencing system. Each of its layers receive sequences to understand the environment in which the body exists. As inputs/sequences become more complex, higher levels of the sequencing system are used. This biological construction of the brain is responsible for our nested understanding of our environment. We classify everything around us. Everything has parts and is a part of something else because of our understanding of our environment. This may not actually be true, but for our brains to understand the world around us, we must understand everything as nested object. This abstract structuring of the world allows us to quickly understand the world by using all levels of consciousness to perceive the world. Because we can abstractly classify objects, we are able to quickly understand their importance. For instance, when we see a face, we do not just see a face. The face is the highest abstraction we can classify it as. We also see eyes, nose, mouth, and hair. Within each of those are subsets to determine what they are. The eye has a white part (sclera), a colored part (iris), and a black part (pupil). Each of these nested levels of detail fall within different layers of the brain’s sequencing system. We do this for each of the parts of the face when we see a face. But when asked what we see, we do not state each small part, but say their collective abstraction, ‘face’.

With the prediction model explaining how we perceive the world, reality becomes a series of checks to predictions we make about the environment around us. Every moment in life we are predicting what our somatosensory system will come across. As our body experiences the environment, it relays the information to the brain. The brain then verifies if its prediction was correct or not. This, however, leads to the phenomenon of false reality. Our brain predicts something that does not occur in the environment around us, but our somatosensory system does relay the correct information. The prediction is not corrected, so our perception is that the prediction is true. We have thus created a moment of false reality. This phenomenon happens more when the input from the environment is processed in lower cognitive levels.

If vertigo is the moment in which we live, the moment between our prediction of the future and the moment we base our prediction off of in the past, then we cannot separate time from intelligence. Time was not invented once humans began measuring it. It is an integral part of the intelligence model. Intelligence is bound by time because it uses the recognition of sequences to delineated different sensory inputs.

Humans are bound by time because our brain is bound by time. Our brain is a sequential organ. It must rely on sequences of firing neurons to comprehend the world around it. The brain does not see or hear; it only receives sequences of inputs from the body’s sensory organs. The sequences are interpreted within the brain to allow us to classify what we see or hear. The brain learns these sequences and is able to abstractly classify these sequences as individual objects in reality.

As the brain is able to classify repetitive sequences, it moves the sequences down the cognitive hierarchy. A lower zone of cognition can handle the sequence. As objects become more banal, they require less conscious focus to understand them. This is the result of the sequential input moving to a lower zone of cognition. The brain can now focus on understanding a higher degree of complexity because a lower level of cognition can comprehend the initial complex input. When an unexpected sequence occurs, the lower cognition level relays the sequence to a higher level of cognition for reclassification and more focused comprehension. This action can be generally classified as when one has things in the ‘back of his or her brain’.

Further, these sequences move in loops of top down and bottom up. The general abstraction of what the brain is experiencing, classifying a series of notes as a song, is the brain functioning top down. The brain also predicts each note that is being played and checks the prediction with reality. This is the bottom up loop. Both of these loops work together and simultaneously to create a complex network of prediction and understanding of the reality we experience.

As a consequence, we have intelligence, which can further be summed as consciousness. Our unconscious lies in our ability to predict. We are able to predict events before they happen. Once an event happens we are conscious of what is happening (compared to our predictions). We compare our predictions and actuality, we then adjust our perception, either by predicting the next event or trying to understand the new event happening to us that we did not predict correctly.

The brain relies on the sequences to build its perception of the world. Everything that it experiences is understood through sequences. The brain understands touch as receptors in the skin firing specific sequences that the brain can then classify. The ‘feeling’ (sequence) is different between glass, sand, and gravel. Each has its own patterns of input into the brain. Abstractly we classify these on a scale of smoothness. If we could not received the sequence from the receptors, then we would not be able to classify what we were touching. For example, if you were asleep and I stuck your hand in a bucket of gravel, then I woke you up and asked you what you were touching. You would be able to feel pressure on your hand but would not be able to distinguish what you were touching, be it glass, sand, or gravel. But once you moved your hand, even just slightly, your brain would be able to classify a sequence of pressure on your hand and compare it to previous experience, thus allowing you to say “My hand is in gravel.” This is the same for the eye in how it recognizes regions of light shade and shadow. Light and shadow gradually build up to distinct objects that we can recognize in our higher cortical zones. You cannot tell what you see until your brain can create a sequence of inputs for it to interpret.

If we try to pull the human out of time, we would lose our ability to perceive. We are not bound by time because we cannot time travel or exist in multiple dimensions, but because we perceive and think in terms of sequences. These sequences are bound by time and thus we are also bound by time.

This is the reason why we remember thing sequentially, such as telling a story or describing a setting. Moving through events triggers the associated following event. The sequences we experience are stored as sequences in the brain. So to recall them, the sequences must be recalled. Everything we experience is stored in sequences within the brain. Sequences are put into other sequences, thus we are able to recall memories one step at a time, or with what came next. It takes people long periods of time to build up to their point because they have to process their sequence of events. People may not recall immediately what they want to say, but by starting their memory at an earlier point, they are able to work through the memory sequence to their point. The speaker continually progresses through their neural network associations until they can remember their point. This goes back to the idea of the catalyst being the key to memory recall.

The brain is the central place our intelligence can be located. It is where our body stores memories about the reality in which it exists, whether true or false. These memories aid in our ability to be intelligent. Intelligence is based in memory recall, but it is the power to use memories as a way to predict the future. The process of prediction using memories is intelligence. As we learn more about the world around us, our predictions become more accurate and grander. Our brain is a powerful prediction system that can be dynamically modified to learn. It is this skill, learning new predictions, that allows humans to be the most advanced cognitive species.

The cortical function can be seen analogously to this. Every moment we make thousands of predictions about the environment around us. As input is delivered to the brain, the predictions are updated. It is this cyclical process that allows our brain to move our body in real time. Without this prediction cycle, we would be analogous to robots (this is not to get into the Cartesian separation). For instance, when trying to catch a ball. We are constantly adjusting our hand to position it to where the ball is going to go. Every moment is crucial in updating the projected location of the ball. This sequence until the ball falls into our hand. Without this prediction cycle, we would need a determined point where the ball would land. We would move there and wait for the ball. However, no matter how accurately we calculated the path of the ball. It is very likely that the ball will not land in our hand due to the exuberant amount of forces acting on the ball. Physics is, in a sense, just a model of the world, not reality.

We experience this vertigo every moment in our life. We are in a constant balance between input from the environment and prediction of what the environment will be. Our perception of the world is this mix, part reality and part projection. As we move through space we are constantly predicting where things are and how they feel. In a sense we are constantly between the past and the future, but not in the present. We are comparing our experience with that of the past to make sense of it and understand it. We then make predictions about our environment, changing our behavior. This constant ‘prediction-check’ phenomenon is the vertigo we experience. We constantly live in a prediction of which way is up until the moment has past.

It is this ability to predict, and re-predict, that defines us as intelligent beings. We are able to understand a situation and compare it to memory, past events, and apply what we know. Then as the event changes, we can update our model with current information.

Intelligence breaks down into consciousness and unconsciousness. We do not control the predictions our brain makes beyond just experience. We can make predictions based off of events, but we cannot individualize what predictions lead to what. For instance, when reading our brain predicts patterns of words and phrases. We do not actually read and articulate every character and its order that we come across. We predict what comes next based on context of the sentence or thought we are reading. Only one of the predictions is correct. Input lets our brain know which prediction is encountered, allowing new predictions to be made. So, back to the sentence, we encounter the word ‘cat.’ Our brain predicts makes a series of predictions based on the subject cat. We then read ‘jumps.’ Our prediction that ‘the cat jumps’ is correct. We were not aware that our brain directly associated the word jumps with cat, but we are consciously thinking that who’s ever cat this is jumps.

This begins to dialogue the difference between the conscious and unconscious. Consciousness is a singular pathway that thought takes within a network of activation vectors (memory associations). Unconsciousness is the network of activation vectors. We are, therefore, creatures of unconsciousness, that live consciously in our lives. Our unconscious influences all actions we express consciously, passive and active. When speaking, we are conscious of the conversation and unconscious of what is influencing the conversation. There are influences that we can be conscious of in conversation, but we cannot be conscious of everything influencing the conversation we are having. This is the power of the unconscious. We are able to input more than we can consciously think about into everything we do.

Intelligence is our brain’s ability to predict. This prediction model rests on the idea that the brain does the same process throughout its biological entity. Whether in the motor cortex or visual corridor, the brain is predicting sensory input. This prediction process is able to happen because the brain has the ability to store memories, auto-associate, and classify invariant representations.

First, our brain has the ability store information. The brain activates certain neural pathways when we observe things. As this becomes a sequence our brain can recognize, our brain is able to reactivate the pathway, causing a memory to occur. When the neural pathways fire in specific sequence, we remember the event. It is no different than if we were experiencing the event first hand. Both perceptions activate the same neural pathway within the brain. Within our brain, we cannot discern between reality and memory. But we are able to discern between memory and reality as beings because we can check our neural firings with the environment around us. Our representation of the world exists between our predictions and input. Part of recalling memory is trying to recall the catalyst, which will initiate the pathways to fire.

Our brain would not be able to make memories without understanding that everything that happens is not random and can be classified. Every event the body experiences is able to be stored as a series of sequences that intern relate to sequences that we have encountered before. This in a sense is our brain being able to track things. If we close and open our eyes while staring at a red door, we are able to safely assume that it is the same door before we closed our eyes and that nothing has changed. This recognition is called auto-association.

To be able to recognize the objects we see through auto-association, the brain uses it’s third function, invariant representation. Our brain is capable of understanding that an object is still the same object if we are viewing it from a different orientation. We are able to understand that a face is still the same face if we are facing it or its side. We are able to recognize the same face if it is translated, rotated, and transformed, for the most part. This last ability allows us to project mean/classification on the world as we encounter it. Through these three processes, we are intelligent beings.

Because of these abilities we are creatures that live in the past. They allow our brain to compose and store memories to be recalled. The model of the world we compose is a representation of experiences in our lives. We are able to remember the past, recall objects, and project their meaning when we reencounter them in the future. Our perception of the world is based in the environments we have experienced. We predict our environment and then experience it to see if our prediction is correct.

These are a series of photos I took of a lava field in Hawaii. The field is exposed for a few miles above ground and then retreats under dried lava. It is re-exposed once it reaches the ocean, where large plumes of occur. I tried to capture both subject and experience. Enjoy.

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Art is limited by what media it is bound. In a systematic view, all art is subject to the rules of its media. For example, paint can be applied to surfaces but cannot be sculpted (unless its properties change). As architecture is modeled, it to is limited by its material properties. String models cannot be held in compression unless the string’s material properties have changes. Even with a top down approach to the model, the model is still informed by the material (bottom up determination). The model therefore contains information from both its concept and materiality. So when making a model, deciding material is as important as conceiving its concept.

Both the material and concept are inputting information into the model. As the concept becomes more informed, the model reflects that increase in information. A similar event happens with the material. As a model moves between materials, it responds to different parametric of each material. With the addition of new information, either from material or concept, complexity is added to the model. Events become more informed giving reason for events and design solutions to exist.

These events happen as a result of process. These procedures can be changes in media or additional conceptual information. As a model changes media, its properties change, giving it new potentiality or defining it in reality. In the recognition of the strengths of each variation, a model can become more informed, thus more complex. As a model becomes more complex, it becomes a stronger representation with more relevance for its existence.

As modeling has moved from analogue to digital media, models have lost valuable information generated from the analogue modeling. Digital models lack information that can only be obtained through analogue modeling. Gravity is an example of one of the information systems digital models lack. Gravity is a system that adds complexity to a model, making it more informed. An analogue model contains load transfer, a major architectural system that determines hierarchy within the model. Gravity acts upon everything in the model, materials and its connections. However, in a digital model, gravity is absent. The computer can simulate gravity, but its simulation is only a representation of gravity, causing a loss of information. Although models are correctly in terms of size to materialistic properties, analogue models contain a complexity of materiality and gravity, which is more than can be done with a digital model.

Digital models further lack in their perceptual abilities because information of perception is lost as a viewer tries to understand a three dimensional space on a two dimensional media (usually a screen). When sitting in front of a screen, a viewer can change their placement around a model to enhance their perception. But their perception will always be limited by the model’s translation to the display. With an analogue model, viewers can perceive the space because space actually exists. The model exists within three dimensions. The additional information gained from a spatial model over a digital model adds to the model’s complexity, giving its representation a better relation to reality.

Each model is beneficial due to the information that can be added to it, but a purely digital model lacks materiality, gravity, and a real third-dimension. All of these are major systems to which architecture must respond. Models lacking these systems lack major information inputs.

Our understanding of architecture is limited by our perception of it. Our brain is our primary means of processing the world around us, thus it is the major contributor to how we perceive our environment. Our brain is limited to where it is taken by our body and conversely our body is limited to its destination by the will of the brain. This symbiotic relationship is what makes us as humans move and understand our environment. This duality has given the reason for modernism’s success. I would argue that both the perception of the brain and action of the body are each important unto themselves, they should not be disjoined.

With this view of the unison of body and brain, it would make sense to design space with the same relation. The plan (action plane) is in a sense the limitation of the body. The wall (perception plane) therefore is the limitation of the brain. The body cannot move beyond the action plane and the brain cannot perceive beyond the perception plane. However, when each the brain and body function together, a greater understanding of space is granted, allowing for new movement and perception. Instead of designing each separately, it is important to take each into account together, creating a summation of perception plane and action plane. Lars Spuybroek refers to this summation as the curve of construction. It is the limit of both the body and the brain, action and perception.

This does not immediately translate into disguising the edge between each plane. Simply by adding curved surfaces where walls and floors meet does not transcend the modernist view of plan over elevation. It is the non-separation between floor and wall, that which wall becomes floor becomes wall, that supersedes their individual relationship. This brings about an alteration of perception and action. What is moveable space and what is not movable space. It becomes a higher cortical function. The brain must focus more upon the architecture to understand. The body must move cautiously to make sure it can continue to move forward. With architecture moving into a higher conscious process, the person becomes more consciously aware of their environment.

This elevated state of consciousness of the environment allows for the mind to be excited, focusing on its surroundings while trying to develop perceptual patterns. This allows for higher cognitive action, giving the brain exercise. This exercise keeps the brain a viable organ enabling it to continue to learn and provoke new cortical pathways within its network. It is not the novelty of the structure that does this. But inability of the brain to process its environment without using a higher/ more focused conscious level.

Through the construction curve, designs may not be optimized spatially, are locally optimized between a variety of factors beyond spatial organization. The structure becomes optimized in relation to the construction curve. It is the construction curve that can lead to variance within an optimized system, allowing for uniqueness within architecture. It is similar to baking a cake. Although the same recipe is followed, the result is different every time. The construction curve, analogous to the recipe, allows for variation within the process of design. The construction curve allows for design beyond function, basing design in user experience again instead of action of space.

Architecture is everywhere and everyone interacts with it. But not everyone understands it because they have a naivety to a language that only a few use to communicate. It can be used to explore the way we (humans) perceive the world. Architecture is a language in which architects use as a tool to understand the world around them. I would argue that the reason why we study architecture of previous civilizations is because it reveals a culture’s perception of the world. The great Greek ruins are examples of how the Greeks believed the gods controlled life and interacting with them would bring prosperity or despair. Thus temples were built throughout the empire to all of the gods they could classify. Every culture has this sort of relationship to its architecture. It is this relationship that puts the architect in a place that they are responsible for their perception of the world and their architecture they share their perception through.

Architecture can also become a laboratory of experimenting with different relationships. Architects can design spaces and use architecture to further understand immediately unrelated subjects. Not to say that everything is independent – it is not – but phenomena we experience may have no immediate consequence to architecture. It is these phenomena that can be expressed in terms of architecture. In this way architecture becomes a looking glass to analyze these experiences. In these abstractions, the altered views, new relationships can be formed. It gives rise to new ways of other subjects. This cross breeding of ideas becomes mutual, each interjecting new ideas into stale thought processes. This is how I wish to use architecture.