Major Studio/Rouvelle/SPRING '05

Monday 3pm-8:40pm. (Dinner break from 5-6)

2 W13th St., room 1006

Contact: james_rouvelle@hotmail.com

Course Description:

This studio course explores the concepts of Computation as well as related concepts of Information, Simulation, Ubiquitous Computing, and Interaction Design.

Warning

We will build simple circuits in this class. Students will be expected to work with (and purchase) a micro-controller such as the Basic Stamp as well as other components. The cost will be about $150 per student, but depends on what you build. Programming in Basic will be necessary. In addition to the Basic Stamp2, I will demo a bluetooth device called embeddedblue, in addition, I will demo a serial to Ethernet converter called the xport. I will also provide examples for interfacing micro-controllers to terminal programs such as: Processing, Max/MSP/Jitter, Java, and, if need be, Flash. A good reference text for this sort of thing is Physical Computing – but I bet you already know that… Two other excellent texts are: Code, by Charles Petzold, and The Pattern on the Stone, by Daniel Hillis.

Introduction

We will study computation from the ground up, and implement physical and virtual computation artifacts and interfaces from aesthetic, technical, social, theoretical and political perspectives.

In addition to the weekly exercises, readings and discussions, we will complete three projects. One will concentrate on interaction and computation outside of the electric computer, this project will be presented in proposal format only. The second project will concentrate on interface design for memory, and the other on meaningful interactions based on computation, information, and simulation using the hardware and software of your choice. We will think of concepts, simple circuit design, and any other materials covered in class as a medium akin to wood or paper and experiment with materials that can enable simple expressive computational forms.

Students will be expected to work with Basic Stamp and various sensors/outputs as well as simple circuits. The third class will include an introduction to the Basic Stamp. Students will be expected to purchase ($150) their own materials kit and build their Stamp during weeks three through six. No prior hardware experience is necessary but students must be prepared to get their hands dirty.

The weekly assignments will include readings, summaries of readings, conceptual prototypes and electronics exercises. All weekly assignments will be archived in student web journals and presented weekly in class.

Objectives

In this course, students will read, think, sketch, design, code, solder and build. We will focus on conceptual development, prototyping and implementation of Virtual and Physical Computing artifacts from the perspective of technical proficiency, functionality, aesthetics and personal/social meaning. Readings will emphasize critical thinking, technology, social and design issues.

Readings, lectures, videos tapes and slides will augment the studio practice. Each student will keep a web journal throughout the term to chronicle and share thoughts, ideas and resources. The web journal will be updated weekly. It will serve as a repository for weekly assignments and to document the development process for projects. Include a photo and a short bio. The website will include link(s) to all weekly assignments, link(s) to your previous web work and a RESOURCE section where you will list influential web sites and tools as well as information sources.

Students will be expected to present their weekly assignments in class, speak about their work during evaluations and participate in collective critique process of the work of other class members.

Evaluation:

Grades in this course will be based on regular class attendance, the quality of your work, class participation, and progress. Tardiness and excessive absences will adversely affect your grade. Participation in discussions and critiques is mandatory.

Projects & Grading:

Students will be graded by letter, A-F, on all evaluated work. Work must be completed on time and in full satisfaction of each project goal. Late work (assignments handed in or posted after the start of in-class critique sessions) will be automatically downgraded by one letter grade.

A	Well above the expectations of the course. Outstanding participation, attendance, and exceptional progress.
B	Above average assignments and participation. No more than one absence.
C	Average execution of assignments, participation, and no more than two absences.
D	Well below average: work, attendance (two absences), projects, and participation.
F	Unsatisfactory: work, attendance (more than two absences), projects, and participation

Attendance:

Two or more unexcused absences from class may result in failure. Two unexcused late arrivals, or early departures (eg, not returning from dinner, or other unexplained disappearance) will be marked as the equivalent of one absence. Absence from a class is not an excuse for skipping a tutorial, reading assignment, or posting an assignment. You are fully responsible for completing work.

Readings:

Readings and tutorials will often be delivered through the web - via links (URLs). Critiques will frequently be initiated from various topics covered in the readings - in other words, please use the concepts you read about in discussion of fellow students' work.

Food and Drink in the Computer Labs:

No.

Weekly Schedule

________________________________________________________________________

Week 1

Introductions

in class:

Introductions; course overview, resources, setting up personal/class blogg at www.blogger.com , and registration matters.

Timeline of Computing from Wikipedia

The Greatest Moments of Computer History are Speeding Up

Some preliminary terms:

Process: is a series of tasks that result in a goal

Computation: is the act of determining the specific tasks and the instructions to accomplish those tasks that need to be performed to reach the goal. If one can specify a sequence of tasks and related instructions which when followed will result in the completion of the goal then the problem is thought to be computable. Computation is about breaking a process into a series of tasks. Often these tasks must be performed in a specific sequence, where, for example, the performance of task 2 is predicated on the performance of task1, etc… A series of tasks leading to a specific result is called an Algorithm.

Algorithm: A series of tasks leading to a specific result. Do you hear that echo?

Functional Abstraction: lets us manipulate information without worrying about the details of its underlying representation.

Data: Representation of facts, concepts, or instructions in a formalized, symbolic manner suitable for communication, interpretation, or processing by humans or by automatic means. Any representations such as characters or analog quantities to which meaning is or might be assigned.

Information: a difference that makes a difference: a perceptible, experiential, and meaningful change of state. Information is stimuli that have meaning in some context for its receiver. Some (if not all) kinds of information can be converted into data and then passed on to another receiver. Relative to the computer, we can say that information is made into data, put into the computer where it is stored and processed as data, and then put out as data in some form that can be perceived as information. Information must have a means of its representation. If we had the right kind of magic microscope, we should always be able to see the digits that represent whatever information is present. Information is never "just there”.

Simulation: the act of transposing the internal, symbolic processes and resulting data of a computation into the sensual domain of a human.

Here are two simulations:

Hubble Spacetelescope – scroll down and to the left to “how Hubble images are made”

UCSD Supercomputer visualizations

Game of Life Applet

Assignment:

Read:

The Computer: a tool for thought experiments – Frank Dietricht, Sections I and II

Prepare:

Prepare a brief (10 min) presentation on your work to present to class next time. The point of this is for me to get to know you.

________________________________________________________________________

Week 2

On Computation and the physical world

First let’s see your works….

Then we’ll review, then:

Discussion on Dietrcht Text, with examples of works mentioned in the text

Some Definitions. Reference to Code, by Charles Petzold, and The Pattern on the Stone, by Daniel Hills.

Assignment: readings:

The Last Question, by Isaac Asimov
God is the machine, Kevin Kelley, from Wired Magazine.

****DON’T Worry about ----àWrite a brief code for the virtual Turing Machine, TM - Java Applet

If you would like a comprehensive review of the BS2 – I’ll go over this in class next time

PLEASE BRING YOUR PHYSICAL COMPUTING SUPPLIES TO OUR NEXT CLASS

________________________________________________________________________

Week 3

Discuss readings,

Summarize with concepts of descriptive/causative language. General purpose computer vs. specific purpose computer. Recursion, Finite-State Machine Concept of digital ground…

God is the Machine

1. Cellular automata n.) A system made up of many discrete cells, each of which may be in one of a finite number of states. A cell or automaton may change state only at fixed, regular intervals, and only in accordance with fixed rules that depend on cells own values and the values of neighbors within a certain proximity.

Cellular automata are - by definition - dynamical systems which are discrete in space and time, operate on a uniform, regular lattice - and are characterized by "local" interactions - from: (http://cell-auto.com/definition/)

On Finite-State Machines, from Daniel Hillis’ “The Pattern on the Stone”.

We can use the methods above to implement any function that stays constant in time, but a more interesting class of functions are those that involve sequences in time. To handle such functions, we use a device called a finite-state machine. Finite-State Machines can be used to implement time-varying functions – functions that depend not just on the current input but also on the previous history of inputs. Once you learn to recognize a finite-state machine, you’ll notice them everywhere – in combination locks, ballpoint pens, even legal contracts. The basic idea of a finite-state machine is to combine a look-up table, constructed using Boolean logic, with a memory device. The memory is used to store a summary of the past, which is the state of the finite-state machine.
A combination lock is a simple example of a finite-state machine. The state of a combination lock is a summary of the sequence of numbers dialed into the lock. The lock doesn’t remember all the numbers that have ever been dialed into it, but it does remember enough about the most recent numbers to know when they forms the sequence that will open the lock. An even simpler example of a finite-state machine is the retractable, ballpoint pen. This finite-state machine has two possible states – extended and retracted – and the pen remembers whether its button has been pressed an odd or an even number of times. All finite-state machines have a fixed set of possible states, a set of allowable inputs that change the state (clicking on a pen’s button, or dialing a number into a combination lock), and a set of possible out-puts (retracting or extending the ballpoint, opening the lock). The outputs depend only on the state, which in turn depends only on the history of the sequence of inputs.

Rechnender Raum, Konrad Zuse

Some things to think about:

Realize the relationship between what an algorithm is - eg, a series of discreet tasks designed to produce a specific result, and the definition of cellular automata above.
The Boolean logic gates function as discrete cells. In other words, the computer, as currently understood as a Boolean algebra machine is an example of cellular automata.
The point of periodicity is interesting. The flow of electricity through the computer creates a fundamental pulse, or pulses. Our heartbeats, what other rhythms unite us?
From the description of the Turing Machine above: software (logic) dependant, independent of the hardware. As Dietch points out: “Whereas nature simply is, the art object is and also exists for ourselves; thus art serves as a means for human consciousness to reduplicate itself. Art is then a method of mirroring the thinking consciousness by externalizing its content. And by becoming an external object that presents itself to the mind, art becomes the manifestation and origin of other mental activities. Therefore, the creation of art and its perception can be understood as a dialectical act of becoming conscious of ourselves. “

A. Remember that I will ask you to create a proposal for a “software (logic) dependant/independent of the hardware” work in a few weeks…

The Last Question:

1 What is “entropy”? Here’s a useful definition, but I would like to point out there there are several definitions of entropy, each depending on the system that it is applied to, anyway, for our talk, let’s go with this definition : In classical thermodynamics, the entropy of a system is the ratio of heat content to temperature, and the change in entropy represents the amount of energy input to the system which does not participate in mechanical work done by the system. This definition comes from here: What is entropy? We might also need to know what Chaos is – as it is mentioned at the end of the story: so, let’s imagine a roulette wheel, and define a chaotic system as – a system in which a small change in the initial conditions (the throw of a ball, the mass of the ball, the diameter of the wheel, and so forth) can produce a large change in the state to which the system evolves.

a. Let’s think about this quote, from media theorist Friedrich Kittler (excerpted from “on the implementation of knowledge, toward a theory of hardware”, available Kittler Text Hub) .“to the degree that it appears in binary code, writing gains the enormous power to do what it says. It is no accident that what we call in ordinary speech a statement is called, in programming language, a command. Whatever technical drawing simply puts before the eyes, effectively takes place.”

b. Let’s look at this old film from 1965, Logic by Machine (part 1) (Yes, this is a VERY dry film, and these mathematicians don't exactly light up the screen with star power, but I still found it very worthwhile. Part 2 is especially interesting, as they get into the philosophical and social implications of these new machines, symbolic reality, artificial intelligence, etc.
The animation is cheap but effective, and the music by Morton Subotnick (who was to become an electronic music pioneer) is creepy and sparse.
(Recommended for those with the patience for it.)

Some questions:

Where is the energy input to the system that does not participate in mechanical work done by the system coming from?
How is entropy “reversed” in the story?

How Binary Math works

On Logic and Switches:

To the ancient Greeks, logic was a means of analyzing language in the search for truth and thus was considered a form of Philosophy. The basis of Aristotle’s logic was the syllogism.

In a Syllogism, two premises are stated, with each one being assumed correct. From these two premises a conclusion is deduced.

Here is a famous syllogism from antiquity:

· All men are mortal;

· Socrates is a man;

o Hence, Socrates is mortal.

Here is a modern syllogism, from Lewis Carroll (author of Alice in Wonderland, as well as a Mathematician)

· All philosophers are logical;

· An illogical man is always obstinate.

Any thoughts on a solution to Mr. Carroll’s syllogism?

How about:

· Some obstinate persons are not philosophers – not obvious at all….

For almost two thousand years, mathematicians wrestled with Aristotle’s logic, attempting to corral it using mathematical symbols and operators. Prior to the nineteenth century, the only person to come close was Gottfried Wilhelm von Leibniz (1648-1716), who dabbled with logic early in life but then went on to other interests.

Then came Charles Boole. I will go into Boole’s life in more detail a bit later, but, for now let’s consider the title of one of his most influential works from 1854 entitled: An Investigation of the laws of thought on which are founded the mathematical theories of logic and probabilities, often referred to as: The Laws of Thought. The title of the book suggests an ambitious motivation: Because the rational human brain uses logic to think, if we were to find a way in which logic can be represented by mathematics, we would also have a mathematical description of how the brain works. Remember the timing of this work, and it’s country or origin: The industrial revolution in England.

Boole invented a kind of algebra that looks and acts very much like conventional algebra. Let’s review a few fundamentals of algebra so that we may appreciate the genius of Boole. When we do conventional algebra, we follow certain rules. These rules have probably become so ingrained in our practice that we no longer think of them as rules and might even forget their names.

The first rule is that addition and multiplication are commutative. That means we can switch around the symbols on each side of the operation;

· A + B = B + A

· A x B = B x A

By contrast, subtraction and division are NOT commutative.

Addition and multiplication are also associative, that is:

· A + (B + C) = (A + B) + C

· A x (B x C) = (A x B) x C

And, finally, multiplication is said to be distributive over addition:

· A x (B + C) = (A x B) + (A x C)

Another Characteristic of conventional algebra is that it always deals with numbers, such as pounds of tofu, or numbers of ducks or distances that a train travels or the ages of family members. Here is the genius of Boole: he made algebra more abstract by divorcing it from concepts of number.

In Boolean algebra, the operands refer not to numbers but instead to classes. A class is simply a group of things, what in later times came to be known as a set

The + symbol in Boolean algebra means a union of two classes, and has come to be called a logic OR

The x symbol in Boolean algebra means an intersection of two classes, and has come to be called a logic AND

The 1 in Boolean logic represents “the universe”, or EVERYTHING.

The 1 – in Boolean logic represents the universe excluding something.

Boolean Searching – perhaps this will make things more clear…

To exemplify this, let’s reconsider the syllogism from the top of the page.

Boolean algebra provides a mathematical method for solving syllogisms. Let’s look at the first two-thirds of that famous syllogism again, but now using gender-neutral language:

· All persons are mortal;

· Socrates is a person;

Let’s represent this in a Boolean algebraic expression:

Let’s use P to represent the class of all persons, M to represent the class of mortal things, and S to represent the class of Socrates. What does it mean to say “all persons are mortal”? It means that the intersection of the class of all persons and the class of all mortal things is the class of all persons:

Hence, All Persons are mortal = P x M = P, where “x” is the sign for intersection/AND. In case you are wondering, it would be wrong to say that P x M = M, Why? Because the class of all mortal things includes EVERYTHING that is mortal, animals, plants, etc…

To say, “Socrates is a person”, means that the intersection of the class containing Socrates (a very discrete class) and the class of all persons (a much larger class) is the class containing Socrates:

· S x P = S

Because we know from the first equation that P equals (P x M) we can substitute that into the second equation:

· S x (P x M) = S

By the associative law, this is the same as:

· (S x P) x M = S

But we already know that (S x P) equals S, so we can simplify by using this substitution:

· S x M = S

And now we’re finished. This formula tells us that the intersection of Socrates and the class of all mortal things is S, which means that Socrates is mortal. If we found that (S x M) equaled 0, we’d conclude that Socrates wasn’t mortal. If we found that (S x M) equaled M, the conclusion would have to be that Socrates was the only mortal thing and everything else was immortal…

Using Boolean algebra might seem like overkill for proving the obvious fact, but Boolean algebra can also be used to determine whether something satisfies a certain set of criteria. We’ll look more into that in a moment.

So:

Boolean Logic. bool´ē-&n loj´ik) (n.) Named after the nineteenth-century mathematician George Boole, Boolean logic is a form of algebra in which all values are reduced to either TRUE or FALSE. Boolean logic is especially important for computer science because it fits nicely with the binary numbering system, in which each bit has a value of either 1 or 0. Another way of looking at it is that each bit has a value of either TRUE or FALSE.

Boolean Logic and Digital Circuits

Now lets make a vacation destination computer using the Boolean gates: And, Or, Xor, and Not. The steps we need to take are to list the qualities we are looking for in a vacation destination and figure out if they are necessary – meaning everybody MUST have them, or generally acceptable, meaning everyone is OK with them.

If a feature is a unanimous, lets call it an AND
If a feature gets a few votes, lets use OR
If two features are both acceptable but mutually incompatible, lets use an XOR

Now lets make a list of the features that we are willing to consider. Lets limit ourselves to five or six…

After we have selected the features, and decided how important they are, lets create an expression for our criteria.

In Boolean Algebra: an >>

“x” is used to denote an AND, while
“+” is used to denote an OR.
“1” will denote Yes.
“1 – some symbol” is used to denote NOT

We will use brackets to clarify our logic. Usually we will need to make a few drafts of the expression to make it clear. When we have arrived at a clear expression, we will convert it into a virtual computer using Boolean Logic Java Applet

As a preliminary exercise, let’s use the Boolean Logic Java Applet and use AND blocks and INVERTERS to construct and OR block.

In class Boolean Logic exercise/lab. Here’s the problem: Randy Sarafin told me that he wants a male cat, neutered, either white or tan; OR a white cat, neutered, any color but white; or he’ll take any cat I can find if it’s black. Please help Randy by:

Summarize his needs in a Boolean Expression, then
Go to our new favorite toy (Boolean Logic Java Applet) and build Randy a cat computer…

Boolean Logic Tutorial – with test at the end!!! – but you don’t have to take it….

On Finite-State Machines, from Daniel Hillis’ “The Pattern on the Stone”.

We can use the methods above to implement any function that stays constant in time, but a more interesting class of functions are those that involve sequences in time. To handle such functions, we use a device called a finite-state machine. Finite-State Machines can be used to implement time-varying functions – functions that depend not just on the current input but also on the previous history of inputs. Once you learn to recognize a finite-state machine, you’ll notice them everywhere – in combination locks, ballpoint pens, even legal contracts. The basic idea of a finite-state machine is to combine a look-up table, constructed using Boolean logic, with a memory device. The memory is used to store a summary of the past, which is the state of the finite-state machine.
A combination lock is a simple example of a finite-state machine. The state of a combination lock is a summary of the sequence of numbers dialed into the lock. The lock doesn’t remember all the numbers that have ever been dialed into it, but it does remember enough about the most recent numbers to know when they forms the sequence that will open the lock. An even simpler example of a finite-state machine is the retractable, ballpoint pen. This finite-state machine has two possible states – extended and retracted – and the pen remembers whether its button has been pressed an odd or an even number of times. All finite-state machines have a fixed set of possible states, a set of allowable inputs that change the state (clicking on a pen’s button, or dialing a number into a combination lock), and a set of possible out-puts (retracting or extending the ballpoint, opening the lock). The outputs depend only on the state, which in turn depends only on the history of the sequence of inputs.

An example of a finite-state machine is an arrangement of logic blocks called a flip-flop.

Here’s more from Mr. Hillis:

“Except for the miracle of reduction, there is no special reason to build computers with silicon technology. Building a computer out of any technology requires a large supply of only two kinds of elements: switches and connectors. The switch is a steering element (a hydraulic valve, or the transistor), which can combine multiple signals into a single signal. Ideally, the switch should be asymmetrical, so that the input signal affects the output signal but not vice versa, and it should have a restoring quality, so that a weak or degraded input signal will not result in a degraded output. The second element, the connector, is the wire or pipe that carries a signal between switches. This connecting element must have the ability to branch, so that a single output can feed many inputs. These are the only two elements necessary to build a computer. Later we will introduce one more element - a register, for storing information – but this can be constructed of the same steering and connecting components. “

Remember that I will ask you to create a proposal for a computer that does not rely on a desktop. It will be a work of physical computing in a pure sense, where your logic will affect changes in an environment other than the motherboard of a PC. Think about switches, connectors and registers, and let’s think too about how the “things” we experience in our world as being external – specifically existing is a space separate from our mind – may actually be elements of an ongoing, recursive computation (recursion involves inserting a word inside of its own definition –we are continually externalizing aspects of our own mind into an “external” environment in order to define ourselves… McLuhan often brought up the myth of narcissus – narcissus – whose name is from the word narcosis – narcotic, didn’t realize he was looking at himself – how does this relate to this recursive, reflective, dialectic relationship I’m describing?) – a part of our computed/built environment. Toward this aim, lets begin to think about objects in our world as switches, connectors and registers (memory devices) – as coprocessors to our own computative actions, that change roles depending on who is experiencing with them. Realize that static objects are neither. Our physiological processes designed to take in stimuli are constantly active – simply because we see a chair does not mean that our eyes are then no longer sending the information into our brains that is experienced as chair.

An exercise could be choosing an object and defining what it is computing and how it functions as a mirror, and conveyor and register of memory. Think about the components of computation: switches, connectors and registers. Things that we can identify can alternate between all three states, depending on what pattern they are a part of. Can you pick some thing and describe it as a switch, as a connector, and as a register?

A potentially simple example:

Found Photo Project

Perhaps these quotes by Francois LaChance might be useful. But first some definitions….

Axiom's of Francois LaChance

Transcoding: Conversion of character data between different character sets. The process of converting a media file or object from one format to another
Semiotics refers to theories regarding symbolism and how people glean meaning from words, sounds, and pictures. The study of doctrine of signs, sometimes supposed to be a science of signs; the systematic investigation of the nature, properties, and kinds of sign, especially when undertaken in a self-conscious way. While semiology is sometimes used to refer to the Saussurean tradition, and semiotics sometimes refers to the Peircean tradition, nowadays the term semiotics is more likely to be used as an umbrella term to embrace the whole field,
Semiosis is a term introduced by Charles Peirce. In the field of semiotics, semiosis is any action or influence involving the establishment or perception of relationships between signs. Semiosis can be understood as logical sign processing or manipulation. It is the process by which meaning is established.

· Recursion

Inserting a word inside of its own definition.
An expression, such as a polynomial, each term of which is determined by application of a formula to preceding terms.
A formula that generates the successive terms of a recursion

Triangulation The location of an unknown point, as in navigation, by the formation of a triangle having the unknown point and two known points as the vertices. Remember syllogism???

Abstraction is good. Clear communication about abstraction better. One is of the life of the mind. The other, of the life of the mind in a body.

These boldly stated values are contagious. The propagation of stances that affirm both feeling and thinking is salutary for bodies and minds contending against anti-erotic and anti-intellectual forces, positions, and effects. Passionate theorizing fosters a culture of the question and such a culture cannot be disinterested, cannot be insensitive to the manner of posing questions, cannot neutralize inquiry. To remind oneself of this at the outset is also to remind oneself that passionate theorizing and adequate abstraction, like appropriate technology, contribute to clarity and action. Theory has consequences.

Abstraction transports one from the given to the possible. As abstraction moves away from an underlying reality, a putative last instance, it moves towards a form, a portable pattern, a template. Abstraction is akin to transcoding. In the succession of analytic and synthetic moments, in the movements of separation and recombination, a materialism is feasible, thought and bodily patterns readable.

Technology, perception and reproduction are ideologically inflected. This itself is an ideological position. It is a position that claims that an apparatus orients meanings. It is also a position that redeploys points of departure in that meanings orient the apparatus. Of course, meanings and apparatus inflect the orientation. Such a shell game in a field of axioms, such a bending of metalevel relations, has material consequences for one's understanding and interaction with machines and systems.

Depending on how one constructs one's machines, one may be locked into two-player games and double-bind situations. (n1) A dialectical understanding of the senses offers alternative games and a machine fuelled by its own activity.

A sensorium is a receiver and a dispatcher. A sensorium is a semiotic machine. Such a device is capable not only of sensation. It remembers; it perceives. Acts of perception as discrete somatic signals form a sequence. Sequences and their manipulation are the basis of sorting activities and of stories. The possibility of treating somatic signals sequentially also ensures that a sensorium can be its own translation device. One sensory modality can "inform" another. Indeed, cross-modal encoding acts as a material support for narrativity in cognition. An interactive sensorium permits a functional but non-reductive approach to narration. Narratives can serve a mnemonic function or act as an algorithm for problem solving.

For such a machine, perception is communication and furthermore the fundamental unit of human interaction is non-dyadic. Such design criteria pose a challenge to the reproductive and perceptual models of Marshall McLuhan, Walter Benjamin, Louis Althusser and Mary O'Brien. Adequate models of reproduction and perception require triangulation.

3.0	Asking a question is akin to telling a story. Drawing a picture is like telling a story. Both, drawing pictures and asking questions, are ways of orienting. Both focus attention. Of course telling stories is a way of orienting. The circularity of these assertions depends not upon the equivalency of the products, question, picture, story, but the activities, asking, describing, telling.	3.0
3.1	As ways of orienting, all are moments of a relentless semiosis, all rework representations, all participate in some measure of transcoding. These ways of doing are readily framed as the potential of an object. What can be described becomes narratable and open to interrogation; what is askable has a story. Actions and objects correlate; praxis bears on semantics.	3.1

Some artworks:

– We Edit Life - "Experimenters in visual perception are using computers to create weird and random patterns that never occur in real life to find out what and how people see when these patterns are shown to them. The art of computer graphics is only in its infancy yet it is already stimulating creative thought in far out areas where research is likely to get complex and unwieldy. If offers not only the means to quicken the pace of discovery but an ideal of communicating what we may discover" - We Edit Life., by vicki bennett – check her site, you’ll like it.

We Edit Life was commissioned in Spring 2002 by Lovebytes in partnership with the Studio of the North, funded by the European Regional Development Fund and the Regional Arts Lottery Programme. We Edit Life is now available for purchase on a compilation DVD called "Volatile Media".

This is some next-level stuff, people

- Marcel van der Drift – doors of perception 7 videos.

Tech:

Introduction to Physical Interaction Theory

Physical Computing

BS2_Tutorial

Physical Computing: references and materials page – check it out.

Jitter: video tracking

There are some objects for video tracking for Jitter. With the standard

installation there is an object called jit.findbounds which will attempt to find

color variations in a video frame. You then can have it watch one color and

it will track it. This object works pretty well but it can take some time to

configure.

Also there are a number of objects that a grad student at IAMAS(Japan) created

called, cv.jit. These are a collection of computer vision objects that are much

smarter. I have done a few things with these but I haven't had a project yet

that needed them. Here is the link for the objects.

http://www.iamas.ac.jp/~jovan02/cv/

Processing is a programming language and environment based in Java and built for the electronic arts and visual design communities. It is created to teach fundamentals of computer programming within a visual context and to serve as a software sketchbook. Used by students, artists, design professionals, and researchers for learning, prototyping, and production, it is a powerful and approachable, and dynamic language. Give it a whirl.

Sound in Processing:

Sonia by Amit Pitaru is a “plug-in” for using either .wav or .aiff sound files in Processing.

Programming reference material:

Notes and code samples for Variables
Notes and code samples for Arrays
Notes and code samples for Functions
Notes and code samples for Objects

A. (solution and comparison to the object oriented assignment from Nice intro tutorial)

From the Processing Website:

NullPointerException – an explanation
Libraries extend processing’s functionality.
technotes offer a tour through specific topics of interest in the forum.

Processing Video code: will work with any video source and does not require jmyron

half a wake (ing) life (ish)...

Assignment:

________________________________________________________________________

Week 4

Recursion, artifice, and gestalt in the built environment

· Recursion

Inserting a word inside of its own definition.
An expression, such as a polynomial, each term of which is determined by application of a formula to preceding terms.
A formula that generates the successive terms of a recursion

Review of Graspable User Interfaces, Tangible Bits, Ubiquitous Computing, Calm Technology and Physical Computing.

1. Graspable User Interface , (graspable can be understood as “available”, too)

2. Tangible Media

Herb Simon Concepts: The Will to recognize pattern, The Environment as mold, Natural/Artificial (artifice). Relationship between internal and external – homeostasis. The wandering ant analogy, complexity.

If the things we construct within our built environments are embodiments of mind, then can we think of objects as elements in a parallel processing scheme?

Dave Furcy on Herb Simon’s Sciences of the Artificial:

Artificial systems (or artifacts) are contingent on their designer's goals or purposes.
Complexity naturally takes the form of hierarchy.
The near decomposability property of hierarchies.
The empty world hypothesis.
State- vs. process-description of a system.

Summary

The thesis of the book is that certain phenomena or entities are "artificial" in the sense that they are contingent to the goals or purposes of their designer. In other words, they could have been different had the goals been different (as opposed to natural phenomena which are necessarily evolved given natural laws). Chapter 1 tackles the following issue: Since artifacts are contingent, how is a science of the artificial possible? How to study artifacts empirically? Chapter 4, on the other hand, deals with the notion of complexity. This is necessary because "artificiality and complexity are inextricably interwoven."

Detailed outline

Chapter 1: Understanding the Natural and Artifical Worlds

Natural science is very familiar to us (especially physics and biology) but the world around us is mostly man-made, artificial. It evolves with mankind's goals. So science must encompass both natural and goal-dependent (artificial) phenomena. Chapter 1 discusses how to relate these two. There are two perspectives on artifacts, synthetic vs. analytic. The science of the artificial is really the science (analytic or descriptive) of engineering (synthetic or prescriptive).

Artifacts are

synthesized,
may imitate appearances of natural things,
can be characterized in terms of functions, goals, adaptation, and
are often discussed in terms of both imperatives and descriptives.

Fulfillment of purpose involves a relation between the artifact, its environment and a purpose or goal. Alternatively, one can view it as the interaction of an inner environment (internal mechanism), an outer environment (conditions for goal attainment) and the interface between the two. In this view, the real nature of the artifact is the interface. Both the inner and outer environments are abstracted away. The science of the artificial should focus on the interface, the same way design focuses on the "functioning".

Simulation is the imitation of the interface and is implied by the notion of artificiality. Simulation can also be viewed as adaptation to the same goal. It can be used to better understand the original (simulated) entity because simulation can help predict behavior by making explicit "new" knowledge, i.e. knowledge that is indeed derivable but only with great effort. Simulation is even possible for poorly understood systems by abstraction of organizational properties.

Computers are organizations of elementary components whose function only matters. They are a special class of artifacts that can be used to perform simulations (in particular of human cognition). They can be studied in the abstract, namely using mathematics. Yet, they can and must also be studied empirically. Their study as an empirical phenomenon requires simulation (example of time-sharing systems). In conclusion, the behavior of computers will turn out to be governed by simple laws, the apparent complexity resulting from that of the environment they are trying to adapt to.

We are constantly involved in a creative, computative, process. We are “goal oriented” beings continually (recursively) establishing, and checking relationships with what is ostensibly an external world but what is really a constant routine to build ourselves and, by extension, the (an) environment. It’s as if we need to constantly make sure we are still “there” – “there” being defined by an ability to express a thought and then experience it’s reflection, and then reflect on it. We don’t really know about an objective, external world; we work to index ourselves in an “it” – to find our own reflection – we ping the external and come to know solely via interaction. Objects in our built environment function as elements (think of them as subroutines), in this recursive algorithm that is the common, human process. Objects, when considered as embodiments of mind, are processing elements intrinsically linked to the process by which we build ourselves at each moment. We cannot have one without the other – we are they and they us, we are coupled. We are recursive beings literally – our being is defined by our being – a continual process that needs artifice to function. Narcissus had trouble because he didn’t understand that he was looking at himself.

early childhood research project – George Forman

The Universal Computer

A famous proof by the mathematician and theorist Alan Turing in the 1930s holds that all common computers are universal in the sense that their functioning is dependent on the software and independent of the hardware. This means that an Intel-based machine (the common desktop PC) can do whatever a Motorola or PowerPC machine (a Macintosh) can do and vice versa. In fact, either of these can do what a Cray supercomputer can do, only they take more memory and more time in which to do it. After the simple logic gates are constructed (there are only three basic logic gates), the abilities of the computer are entirely a function of the programming. Fredkin's student Roger Banks put forth in 1971 a proof that the same is true of the less conventional computer architecture of a cellular automaton. Because all computers (including cellular automata) are universal, and because the engine at the bottom of the physics of the natural world is a computer of some sort, Fredkin concludes that the ultimate computer is universal (because it is a computer, Q.E.D.).

If the ultimate computer is universal, as it must be, then we should be able to simulate or, more properly, emulate its operations by the correct programming of our own feeble computers (in the way that a good programmer should be able to emulate a Cray supercomputer using a desktop PC). All of physics as we know it should be expressible as a computer program. As Fredkin puts it,

"What cannot be programmed cannot be physics. This is a very important idea. If a process cannot be programmed on a particular universal computer, despite having enough memory and time, then it cannot be programmed on any computer. If we can't program it on an ordinary computer, Finite Nature implies it can't be a part of physics because physics runs on a kind of computer."

The difficulty here is that there are features of our world which have long been thought to be impossible to duplicate by computer. If these feats are truly impossible for a computer, then Finite Nature must fail. However, Fredkin shows that the most problematical of these tasks -- true quantum randomness and the reversibility of computation -- are not the insurmountable barriers they were once thought to be.

Turing machine/Universal Computer/Finite State Machine stuff: java applet: TM - Java Applet

Article on Turing Machines – includes a bit of a definition of computing, “Intuitively a task is computable if one can specify a sequence of instructions which when followed will result in the completion of the task. Such a set of instructions is called an effective procedure, or algorithm, for the task.”

Cellular automata n.) A system made up of many discrete cells, each of which may be in one of a finite number of states. A cell or automaton may change state only at fixed, regular intervals, and only in accordance with fixed rules that depend on cells own values and the values of neighbors within a specific proximity.

Here is an excerpt from Daniel Hillis’ book: “The Pattern on the Stone”

“We are now in a position to summarize how a computer works, from top to bottom. The work performed by the computer is specified by a program, which is written in a programming language; this language is converted to sequences of machine-language instruction by interpreters or compilers, via a predefined set of subroutines called the operating system. The instructions, which are stored in the memory of the computer, define the operations to be performed on data, which are also stored in the computer’s memory. A finite-state machine fetches and executes these instructions. The instructions as well as the data are represented by patterns of bits. Both the finite-state machine and the memory are built of storage registers and Boolean logic blocks, and the latter are based on simple logical functions, such as And, Or, and Invert. These logical functions are implemented by switches, which are set up either in series or in parallel, and these switches control a physical substance, such as water or electricity, which is used to send one of two possible signals from one switch to another: 1 or 0. This is the hierarchy of abstraction that makes computers work. “

Some definitions:

Narrative is the communication of meaning by means of a temporal process, it is the transformation of a sequence into a story, or specific result or meaning. It is a FORM in which things are arranged in such a way as to produce a specific result. It is identical to an algorithm.

Narrativity is a potential for some thing to express meaning(s) within a sequence, within a narrative. Depending on the dimension of the thing (could be a word, a sound, a color, a shape, a sentence) it could also be understood as the potential of transforming any sequence into a story.

Gestalt is a German word that does not translate easily. It is often put to use during grad seminars at art schools across the planet and is sometimes understand as a situation where the sum is different from the parts. It can be used to imply a transformation – even a sort of alchemy that occurs when certain things – words, images, sounds, objects of any kind, are placed in a sequence of some kind. It means a complete pattern or configuration. The catch is the word complete. There are three parts to a definition of gestalt: a thing, its context or environment, and the relationship between them. Imagine this: I have a bunch of lava rocks around a potted cactus in my apartment. There are about ten of them. As the plant grows, I occasionally rearrange the rocks. This is not a highly charged activity. I can be pretty casual, almost absent minded, about it. But I picked each one of those rocks out of tall grass very near a smoldering volcano that was about to erupt. Out there, when I reached for the rocks and carefully freed them from the thorny grass I am not absent minded. The volcano is smoking and while I think I’ll be OK I’m not sure – there are very nervous people rushing past me as I stop.

Get it? The context is really different, although the objects, the dried, lava rocks, are the same. But in considering Gestalt we say that the rocks are not the same, because the context is a part of the definition of the object. The experienced whole (the gestalt) includes the thing itself (the figural rocks) and its meaning. Meaning is derived from its relationship to the context (the ground /apartment vs near the volcano). Therefore, the gestalt of the rocks in the flowerpot is different from the gestalt of the rocks on the ground by the volcano. The same thing applies when we are talking about ourselves or another person. We can only define ourselves in terms of relationships - that is, in terms of our interaction with the immediate environment or present context. Who defines that? Only the “experiencer.” This is also the definition of phenomenology.

Personal experience is understood in terms of figure and ground relationships. The immediate situation is constructed from the individual's awareness of self, awareness of the environment, and awareness of the relationship between the two. The awareness of relationship involved in a particular situation constitutes a gestalt, a meaningful pattern or configuration.

Constellations

But note this: Gestalts seem to have the psychological property, (or “affect”) of “wanting” completion. In other words they are experienced as leading toward a result. Sound familiar? Experiences that have been successfully resolved fade into the background. Those that have not, continue to absorb energy and attention, even when they are out of awareness. We sometimes call that “unfinished business”, and it can distort our present experience as well as our anticipation of the future.

It therefore follows that the relationship between environment and our self is crucial. We affect the environmental context through our interaction with it. The narrative is the form from which we arrive at an understanding. Narrativity is the potential of each object in our environment to express meaning(s) within different sequences. Those sequences are determined by interactions from all elements of the environment and are dynamic, and are defined solely by the “experiencer” – think again of the concept of the constellation. Experience therefore, must be defined in terms of the integrity of both sides, plus the fluidity of the interaction between the two. It seems imperative, that individuals direct their attention to the interrelationship among all things in the world. This implies a compelling curiosity that can lead to the excitement of discovery that is one of the most important goals of Gestalt.

A foil:

Saint Louis Design

Modernism

Mondrian

Robert Smithson and Richard Serra both believed that sculpture should have a dialog with its environment. Two sculptures of Richard Serra are shown in an urban environment - Fulcrum in the Broadgate development at Liverpool Street in London and Tilted Arc in New York - the latter has since been destroyed.

Earthworks, Cristo, Heizer, Smithson De la Marre

9 Evenings

Pepsi Pavilion

Pyroboy

Here’s way to think about the internet: It is an open-ended, non-linear structure that can be added to and recontextualized endlessly. Do you remember the Dietricht from the beginning of my talk? Perhaps it would be good to think of a project as a way to explore the internet as a de-centered production space, in the vein of internet bulletin boards and online interactive projects, but with a focus on developing innovative ways to expand and structure these models…. But we’ll worry about that later.

Cyberman

Stelarc – URL Body, PingBody, animatronic head – is only as smart as the person interrogating it….

Stuart Moulthrop - victory garden and pax

The Sims / Secondlife

Game of Life Applet

cellular automata dynamics slide show - geared for the computer science major

ATTA (leaf cutter) ants, by Lisa Arenson

emergent ATTA ant behavior

Analysis of Learning: Experiences of Art and Ideas for Connections - Walker Digital – various projects in informatics and emergent behavior. All CA based.

Some things to think about:

Realize the relationship between what an algorithm is - eg, a series of discreet tasks designed to produce a specific result, and the definition of cellular automata above.
The Boolean logic gates function as discrete cells. In other words, the computer, as currently understood as a boolean algebra machine is an example of cellular automata.
The point of periodicity is interesting. The flow of electricity through the computer creates a fundamental pulse, or pulses. Our heartbeats, what other rhythms unite us?
From the description of the Turing Machine above: software (logic) dependant, independent of the hardware. As Dietch points out: “Whereas nature simply is, the art object is and also exists for ourselves; thus art serves as a means for human consciousness to reduplicate itself. Art is then a method of mirroring the thinking consciousness by externalizing its content. And by becoming an external object that presents itself to the mind, art becomes the manifestation and origin of other mental activities. Therefore, the creation of art and its perception can be understood as a dialectical act of becoming conscious of ourselves. “

A. Remember that I will ask you to create a proposal for a “software (logic) dependant/independent of the hardware” work in a few weeks…

Assignments:

Reading:

Graspable User Interface - George Fitzmaurice's Ph.D Thesis. Explores the idea of multiple physical objects as handles for elements in a computing environment, as opposed to a single physical object (the mouse).

Virtual Perspective And The Artistic Vision: by Edward A. Shanken

Propose:

Create a proposal for a work that involves computation and interaction but does not make use of the familiar paradigm of desktop computer running software…

Think about how you use perspective, computation, and dimensionality in your work, and as a means to a specific end. Each of you will present your proposal to the class for critique. Think of expanding the functions (input/output,logic) of the desktop computer into the physical world – by using common objects as switches, connectors and registers (memory). This is a thought experiment, don’t worry about practicality, and its fine to develop a “simple” project.

More info/ideas (posted too late, perhaps…. Sorry – but maybe it will help?)

“The word interaction has lately been applied to just about any relationship between people or things, as though shapes interact in a Picasso painting. More properly, the work implies deliberation over the exchange of messages. Much experience can be understood as interaction, of course. As a usual point of departure, on can approach interaction as a conversation. One party acts or speaks, and the other interprets and then responds. This distinguishes the exchange from mere transmittal. The more that the response follows one assertion and invites another, the more engaging the interaction is thought to be. Supporting contexts and protocols help keep this on track.”

Malcolm McCullough, Digital Ground, MIT PRESS 2004

Overture:

Dr. Paul Bach-y-Rita. He mentions the plasticity of the human mind. Patterns of stimuli on the hand or tongue can cause the brain to visualize or balance itself, its called sensory substitution. Notice how Dr. Bach-y-Rita says that the user can visualize “with conditioning” – we all needed to learn to make sense of the data coming into our brains via the optic nerve. Check out the first video, and the last one on the page – the one with the guy wearing a camera on his forehead. This person is blind and has learned to see via lingual stimulation from the brainport…

Lifelong Kindergarten Group, MIT: “Toys to think with”. We looked at this in class.

Etude:

Imagine if you could embed any common object with a sensor and then gather the data, process it, and produce a related output. That output can be a monitor, a speaker, an LED or some other embedded feedback device (vibration in the back of a chair, for example). With this “pervasive” computing, devise a system of interactivity that uses input (a sensor) – output and feedback. The goal is to engage a user (cause them to create input to the system), encourage them to explore and participate with the objects (have the output of the system be clear and somehow inviting), and reward them for doing so (keep their attention, perhaps by letting them understand that their actions produce specific results that lead to an outcome). The goal can be simply having a user realize that there is a cause and effect relationship happening and that there is a logic that evolves over time. What we are exploring here is the plasticity of the human mind, our innate curiosity to understand pattern, and our ability and willingness to transpose. With this in mind, try to allow the normal usage of the object(s) you select to trigger the beginning of the piece. Your concept can focus on an individual, a group, or a combination of the two. Pay attention to (and be able to describe) the environment you are imagining as a setting for the work.

Week 5

Crit #1

A kind of review:

“Because, as those far-sighted folks at Sun Microsystems are fond of saying, the network IS the computer. A digital computer is nothing more than banks and banks of on/off switches. As the number of transistors that can be put on one chip increases, so does Computer Processing Power. The Net is a collection of possible connections, and a connection is a switch being thrown. When you connect your desktop computer to the Internet, it becomes part of a vast computer. “

from: Friends of Tuva

Some more words on Context:

“Ubiquitous computing, in its universalist version has overlooked the value of context. Humanity has had thousands of years to build languages, conventions, and architectures of physical places. Wave upon wave of technology has transformed those cultural elements, but seldom done away with them. Context appears to have unintended consequence for information technology.”

Malcolm Mcullogh, Digital Ground, MIT Press, P. 11

on interaction

The word interaction has lately been applied to just about any relationship between people or things, as though shapes interact in a Picasso painting. More properly, the word implies deliberation over the exchange of messages. Much experience can be understood as interaction, of course. As a usual point of departure, one can approach interaction as a conversation. One party acts or speaks, and the other interprets and then responds. This distinguishes the exchange from mere transmittal. The more that the response follows one assertion and invites another, the more engaging the interaction is thought to be. Supporting contexts and protocols help keep this on track.”

Malcolm Mcullogh, Digital Ground, MIT Press

Interactivity is, like the narrative, like Art, and like the immersive environment, a matter of form, which is to say a matter of sequence/algorithm/narration/environment/gestalt.

Strategies for interaction:

Input – sensor.

a sound sensor, for example

Output – effecter.

a light bulb, for example.

Form: feedback, cause and effect, sequence, algorithm.

Let’s discuss how to make this sensor/effecter pair meaningful. As a way into this discussion let’s think about a simple sound synthesizer. Remember Fitzmaurice’s et als ideas about Graspable User Interface? The notion is to multiplex a medium – to attach handles to a multitude of elements. In the sound synthesizer example, we can control pitch via a potentiometer, or a keyboard, or a bend sensor, we can control amplitude via another potentiometer, or input device, we can control timbre, and we can control envelope similarly. Each of these elements is a handle that we can make available to a user to grasp. With each new handle we potentially deepen the level of interaction. What else can we manipulate?

Related Artworks:

Ken Goldberg

MemexEngine Marc Lafia The Vanndemar Memex or Laura Croft Stripped Bare by her Assassins, Even The Vandemar Memex is a rumination on the many fascinating tropes of extended self, distributed narrative, artificial life, collective intelligence and emergent systems. The Memex, set up in the context of a game, re-assembles Duchamp, Vannevar Bush, video games and many contemporary art works putting forward the notion of a engine from which works happen. The work is structured as a series of events, organized by episodes, a tool set, narrative tracks and collective networked actions. The user first selects a code name, then an image that tells the machine something of their psychological type and soon is set along a path. Authors (www.vanndemar.com) Marc Lafia : direction, concept, story, images, interface Mark Meadows : story, design Gabriella Marks: words, images, design, play mechanics, code

Ghost City Jody Zellen Ghost City is a website that focuses on the representation of the city by the mass media. It is a labyrinthine environment through which viewers can navigate, either following the linear narrative that unfolds by moving from page to page, or they can delve into the non-linear chaos of random links. Each space is made up of appropriated images and texts. The images are culled from various print media sources. The texts are either found passages from urban theory or specifically written poetic musings on the city. Rather than present static images, Ghost City is a collage of moving parts. It is a pulsating grid of flashing images that loop indefinitely. The viewer is an urban wanderer moving through the site, step-by-step, page by page. One moves forward and back retracing one's steps within the urban grid, discovering new spaces and new meanings. One clicks on a word: "walk," "time," "space" or an image of a silhouette, a shadow or a fa�de. The movement freezes, a color flashes and you are someplace else. One by one a new grid of images appears. Some seem familiar. Have you been here before? Ghost City is about memory, and about travelling through time and space. The time is infinite. The space is finite. Yet the time and space of Ghost City metaphorically relate to the experience of the city where people walk and talk and interact. Within the confines of Ghost City visitors can pause and think and move backwards and forwards. Ghost City is a city of fragments. A memory. A ghost of reality. A ghost city.

Wax Web is an interactive narrative 3D environment that is based upon and distributed via the internet. It goes back to Blair's 1991 electronic movie »Wax or the Discovery of Television Among the Bees«. Scenes from this film are interwoven with image, sound and text elements to build an associative net of references where the linear story is no longer valid. Depending on the interaction with the viewer, the elements gather to build new narrative threads and generate new interaction possibilities. By shifting into virtual space, the movie turns into interactive cinema.

IsAnyOneThere? Stephen Wilson. A Voice Activated Tour of San Francisco Via its Pay Telephone. Overview For one week a computer telemarketing device makes hourly calls to selected pay telephones, engages whoever answers in conversations about life in the city, and digitally stores the conversations. The installation later allows viewers to interactively explore the city via a database of these recorded calls and digital video of life near the phones. It appropriates the often intrusive computer-based telemarketing technology and uses it in a new way, involving people who don't traditionally participate in the art world in an event that probes the diversity of life in the city and the relation of truth to fiction.

Virtual >> Physical:

“Systematized Illusion”, Charles Halary on Virtual Reality

Our understanding of the world comes from physiological processes that are variable – it seems that we intuitively understand this and that may be why we understand things in sequence – a series of checks and balances if you will that acts as a unifying and defining form. on the physiology of seeing

Has anyone seen wakinglife? We adapt to whatever environment we are in – and can’t tell the difference between a dream and waking life. Comments?

o Dr. Paul Bach-y-Rita. He mentions the plasticity of the human mind. Patterns of stimuli on the hand or tongue can cause the brain to visualize or balance itself, its called sensory substitution. Notice how Dr. Bach-y-Rita says that the user can visualize “with conditioning” – we all needed to learn to make sense of the data coming into our brains via the optic nerve. Check out the first video, and the last one on the page – the one with the guy wearing a camera on his forehead. This person is blind and has learned to see via lingual stimulation from the brainport…

javoice – Java “Visual Prosthesis” Applet – graphic sonification, try it, you’ll like it.

Usman Haque

electronetwork

Immersive environments – we know that we are inextricable from the environment

Pervasive computing:

Project Oxygen: Overview

Oxygen Today

Oxygen in Application

Tech:

Embeddedblue from Parallax, Bs2, Jitter, TcpServer_Processing

Assignments: Reading, Immersion and Interaction – Oliver Grau

Week 6

“Is a dog a place? Yes, to a flea.” Jamy Sheridan

Boolean Logic, slight return. Based on the interesting projects you presented last week, and some questions I received this week regarding how to implement those projects I thought it would be a good idea to spend a little time on Boole’s logic and the Integrated Circuits that can help us implement it. To assist in this demonstration I’ve provided a hand out from Code, by Charles Petzold, Chapter 11, starting on page 102. I’ve also brought into class some IC’s a breadboard, and some LED’s to build a flip-flop – an example of a finite-state machine (see below). Silicon Logic Gates, The 3914 Dot Bar Display Chip – you can do ADC with it and it works beautifully with the Logic Gates.

Analog input: Ridiculously Sensitive Charge Detector . Add some relays and you’ve enough to build many projects.

Here is some stuff from a few weeks ago:

Boolean Logic and Digital Circuits

If a feature is a unanimous, lets call it an AND
If a feature gets a few votes, lets use OR
If two features are both acceptable but mutually incompatible, lets use an XOR

Now lets make a list of the features that we are willing to consider. Lets limit ourselves to five or six…

After we have selected the features, and decided how important they are, lets create an expression for our criteria.

In Boolean Algebra: an >>

“x” is used to denote an AND, while
“+” is used to denote an OR.
“1” will denote Yes.
“1 – some symbol” is used to denote NOT

As a preliminary exercise, let’s use the Boolean Logic Java Applet and use AND blocks and INVERTERS to construct and OR block.

Summarize his needs in a Boolean Expression, then
Go to our new favorite toy (Boolean Logic Java Applet) and build Randy a cat computer…

Boolean Logic Tutorial – with test at the end!!! – but you don’t have to take it….

On Finite-State Machines, from Daniel Hillis’: “The Pattern on the Stone”.

We can use the methods above to implement any function that stays constant in time, but a more interesting class of functions are those that involve sequences in time. To handle such functions, we use a device called a finite-state machine. Finite-State Machines can be used to implement time-varying functions – functions that depend not just on the current input but also on the previous history of inputs. Once you learn to recognize a finite-state machine, you’ll notice them everywhere – in combination locks, ballpoint pens, even legal contracts. The basic idea of a finite-state machine is to combine a look-up table, constructed using Boolean logic, with a memory device. The memory is used to store a summary of the past, which is the state of the finite-state machine.
A combination lock is a simple example of a finite-state machine. The state of a combination lock is a summary of the sequence of numbers dialed into the lock. The lock doesn’t remember all the numbers that have ever been dialed into it, but it does remember enough about the most recent numbers to know when they form the sequence that will open the lock. An even simpler example of a finite-state machine is the retractable, ballpoint pen. This finite-state machine has two possible states – extended and retracted – and the pen remembers whether its button has been pressed an odd or an even number of times.

All finite-state machines have a fixed set of possible states
a set of allowable inputs that change the state (clicking on a pen’s button, or dialing a number into a combination lock), and
a set of possible outputs (retracting or extending the ballpoint, opening the lock).
The outputs depend only on the state, which in turn depends only on the history of the sequence of inputs.

An example of a finite-state machine is an arrangement of logic blocks called a flip-flop

We Train to the Medium…

Where is this guy? >>Head Mounted Display: HMD

IMMERSION

The feeling of presence, of 'being there', surrounded by space and interacting with available objects. The point of view in the immersive world is omni-directional. Immersion is enveloping, a 360 degree surround, that is physical rather than cognitive. For Joseph Nechvatal, immersion in a Virtual Reality work implies a unified total space, a homogeneous world without external distraction, striving to be a harmonious whole. He identifies 'two grades of immersion: (1) cocooning and (2) expanding within which, when these two directions of psychic space cooperate ... we feel ... our bodies becoming subliminal, immersed in an extensive topophilia ... an inner immensity where we realize our limitations along with our desires for expansion.'

Illusion – immersion – a quest for the perfect illusion. Polysensuality. Immersion means a few different things to different contingencies. For our purpose it will relate to artworks that envelope an viewer and turn them into an immersant – in the commercial world of electronic gadgetry immersive simply means polysensual – experiences that you can hear, see, touch, etc… The major difference between the two is that in the art world the immersant is completely within the artwork so that any references to the “outside” world are solely in the mind. In the commercial application, you are sitting at your desk and are working with your materials – but your materials have more “handles”. This difference is very important, as immersive art is sometimes considered to be a radical shift from traditional art disciplines in that it (immersive art) makes critical/dialectical inquiry difficult. Why?

“We don’t know who discovered water, but it certainly wasn’t a fish” Marshall McLuhan

Humans are dialecticians. Immersive environments challenge that form of logic because they make it difficult to understand oneself apart from that which we are considering.

Think about visiting the gallery or museum – think about things within a frame, think about a frame of reference – its all about perspective and dialecticism that results from that. I’ve mentioned the idea before that the things we make are embodiments of mind – we have a will to build into our environment in order to perceive our thoughts externally and consider them dialectically. In order for this to function, there is an implication that we will be able to triangulate. The issue of triangulation within an immersive environment is significant because all of your stimuli is coming from the immersive environment – where is the frame?

SPACE

spatium = [Latin] space Space or Outer Space are the seemingly empty places (vacuum) between planets and stars. Space is not really empty, but the material in space is so dilute that it is hard to detect it. Space looks black. A particular camera or detector cannot observe all kinds of radiation (such as all colors of light, infrared and ultraviolet radiation, radio waves, and X rays), so if a bright object happens not to emit radiation of the kinds that the camera can detect, then the picture looks like a picture of outer space.
www.sunspot.noao.edu/sunspot/pr/glossary.html

A space is a particular frame of reference for an object. Specifically, it defines the transformations that are applied to an object to put it into the frame of reference.
www.davidgould.com/Books/Glossary.htm

Most minimally, any film displays a two-dimensional graphic space, the flat composition of the image. In films that depict recognizable objects, figures, and locales, a three-dimensional space is represented as well. At any moment, three-dimensional space may be directly depicted, as onscreen space, or suggested, as offscreen space. In narrative film, we can also distinguish between story space, the locale of the totality of the action (whether shown or not), and plot space, the locales visibly and audibly represented in the scenes.
www.mhhe.com/socscience/art-film/bordwell_6_filmart/student/olc/glossary.mhtml

So, Space is a means, and not a mere setting. “To speak of ‘producing space’ sounds bizarre, “ wrote the critical theorist Henri Lefebvre in 1974, “so great is the sway still held by the idea that empty space is prior to whatever ends up filling it”.

Memory, like Space, is a frame of reference – see the excerpt above from Dan Hillis on finite-state machines.

LOCATION

a point or extent in space
www.cogsci.princeton.edu/cgi-bin/webwn

“Places (locations) emerge at crossovers between infrastructures. Where one flow prompts, regulates, or feeds another, development occurs. Where the boats met the trains great cities grew. Electronic communication has intensified, not undermined, the hubs of activity.” Malcolm McCullogh, Digital Ground, MIT press, 2004

Char Davies Osmose video explanation

And This Guy ? If his eyes are twitching, he’s definitely >>

Dreaming – the mechanics of immersion

What is the deal with dreams, anyway? Why do we dream at all for that matter? According to Joel Achenbach in his book Why Things Are:

The brain creates dreams through random electrical activity. This electrical activity is concurrent with Rapid Eye Movement (R.E.M.). (Rapid eye movement sleep occurs at several points during the night. Most people experience three to five intervals of REM sleep per night, and brainwaves during this period speed up to awake levels. If you ever watch a person or a dog experiencing REM sleep, you will see their eyes flickering back and forth rapidly. In many dogs and some people, arms, legs and facial muscles will twitch during REM sleep. Periods of sleep other than REM sleep are know as NREM (non-REM) sleep.

REM sleep is when you dream. If you wake up a person during REM sleep, the person can vividly recall dreams. If you wake up a person during NREM sleep, generally the person will not be dreaming.)

Random is the key word here. About every 90 minutes the brain stem sends electrical impulses throughout the brain, in no particular order or fashion. The analytic portion of the brain -- the forebrain -- then desperately tries to make sense of these signals. It is like looking at a Rorschach test, a random splash of ink on paper. The main points here are that the brain pays attention and becomes cognizant of changes in state over time – it is not cognizant of stasis. The only way of comprehending it is by viewing the dream (or the inkblot) metaphorically, symbolically, since there's no literal message.

This doesn't mean that dreams are meaningless or should be ignored. How our forebrains choose to "analyze" the random and discontinuous images may tell us something about ourselves, just as what we see in an inkblot can be revelatory. And perhaps there is a purpose to the craziness: Our minds may be working on deep-seated problems through these circuitous and less threatening metaphorical dreams.

Here are some other things you may have noticed about your dreams:

You experience them as real.
Dreams tell a story. They are like a TV show, with scenes, characters and props.
Dreams are egocentric. They almost always involve you.
Dreams incorporate things that have happened to you recently. They can also incorporate deep wishes and fears.
A noise in the environment is often worked in to a dream in some way, giving some credibility to the idea that dreams are simply the brain's response to random impulses.
You usually cannot control a dream -- in fact, many dreams emphasize your lack of control by making it impossible to run or yell. (However, proponents of lucid dreaming try to help you gain control.)

Grasping

“One important characteristic of the sensors in your skin is referred to as the Rate of Adaptation. Most human mechanoreceptor cells respond to a change in the external stimulus (pressure, temperature,...) by producing voltage pulses across neurons. Immediately after the change in external stimulus, these pulses begin to appear. Over some time, the pulse rate declines and eventually returns to the original passive level. The rate of adaptation is the rate at which the mechanoreceptor pulse rate returns to normal after a change in stimulus. Simply put, sensors with adaptation do not provide information about static signals - only about changing signals. To use such a sensor to sense a static quantity, like roughness, it is necessary to make the roughness produce a time-varying contact force on the tactile sensors in the fingers.”

We are twittering machines. This cognizance of activity is used by subsystems of our bodies, think about the physiology of grasping something:

Mechanical Grasping

On Seeing:

Banana

All objects absorb and reflect light in predictable ways. By measuring how much light an object absorbs in some colors (or wavelengths) and reflects in others, we can tell a lot about that object. For instance, suppose there are three bananas on a table—one is dark brown with a wrinkled and leathery appearance, one is dull yellow in color with a smooth skin, and the third is pale green with a slick and shiny texture—which would you pick to eat and why? Noting its color and texture, most people would choose the yellow banana because these characteristics indicate it is ripe.

The banana example illustrates a concept basic to the art and science of remote sensing. The various colors (or wavelengths) of light that bounce off the banana and travel to your eye allow you to determine whether the banana is ripe, and you never have to touch the banana to make that judgment. This is similar to how “remote sensing” works. (The term “remote sensing” refers to the use of an artificial device to make measurements or observations of an object from a distance.) By observing and measuring things like color, shape, and texture, scientists can learn a lot about Earth’s environment.

Image

In Ways of Seeing, John Berger stipulated that 'image' means a 'sight which has been created or reproduced ... detached from the place and time in which it first made its appearance and preserved.' In other words, an image is an aspect of culture, not nature. Since images are made by humans, they embody 'ways of seeing' -- i.e., the assumptions, desires and values of the makers.

In Art/Science and DNA Structure , Dr. Root-Bernstein writing on the possibility that the visual representation of Watson and Crick’s double-helix may be wrong, states: “What too many scientists, writers, and illustrators have overlooked-or do not understand-is that images are “understanding”. The visual form in which a theory is represented becomes a working model of that theory, whether it is accurate or not.46 What becomes familiar through visual repetition becomes the basis for our aesthetic appreciation and sets our standards for judging the rest of a field, be that field science or art.

Again, We train to the Medium

Predictable is a key word in that description. The vast majority of 3-D graphics are created by applying the notions above – the illusion of 3-D is created by representing light on surfaces. What happens when predictability is diminished? on the physiology of seeing When what we see defies our assumptions we….. adapt, and work to understand what is going on. Illusions are defined as erroneous mental representations. When we can compare illusory images with non-illusory images it is relatively easy to differentiate between the two.

These are Optical Illusions – they can be understood as “erroneous mental representations” due to context – we can immediately compare them to the things around us that we know.

This one is a bit more difficult to “explain”, as it is sculptural and Panoramic, immersive.

Ames Room

When we cannot clearly differentiate between real/unreal our tendency is to develop a frame of reference, an organizing principle that makes sense out of what we are perceiving – as in a dream. Again, we train to the medium. Sometimes this can be useful

Dr. Paul Bach-y-Rita

In other words:

Optical illusions can be experienced as such if we can have a critical perspective to understand them – meaning, if we can use our stored knowledge of the world to compare with what we are experiencing in one location, we can, often deduce that it is, in fact, illusory – when we are in an immersive environment this criticality is significantly less available so the illusion becomes, in essence, real – and we respond as we would to a real event.

Our sense of touch, our sense of sight, dreams, sensory substitution – what does all of this say:

We train to the: dreams / Illusion – immersion – VirtualReality MEDIUM.

Our conscious mind is a simulation and we have learned to play with this simulation, to develop a dialectic relationship with our autogenic (self-regulating) systems of our body for the sake of pleasure. We can “play” with our mechanism for creating reality. That’s pretty amazing, isn’t it? Immersive art can be understood as a recent apotheosis of this act.

We make it up with every heatbeat – ridges on fingertips – physiology of grasping, holding phenomena, nystagmus, twittering constantly.

On IMMERSION:

Images/Works:

Sacri Monti

Sacri Monti II

Panoramarotunda

Anton von Werner - Sedan Panorama

Fresco Pompeii - 360 deg. fresco

Panorama X - Panorama

Expo 2000

CAVE - Cave

Sensorama 1962

Stereoscope 1850

Stereoscopic Television 1960

Head Mounted Display: HMD Headmounted from Disc

Fred Waller's „Cinerama“ made its appearance in the USA. Similar to today's IMAX cinemas, in the 1950s it provided around one hundred cinemas across the world with three-dimensional image worlds, many of them ultra-fast moving ones cinerama

Char Davies Osmose video explanation

Telematic Dreaming video

Home of the Brain

Murmuring Fields

A-Volve video explanation

Marcos Novak - Liquid Architecture

Marcos Novak

Some of these artists are from last week’s foreshortened class (snow event closed school early)

Ken Goldberg

IsAnyOneThere? Stephen Wilson. A Voice Activated Tour of San Francisco Via its Pay Telephone. Overview For one week a computer telemarketing device makes hourly calls to selected pay telephones, engages whoever answers in conversations about life in the city, and digitally stores the conversations. The installation later allows viewers to interactively explore the city via a database of these recorded calls and digital video of life near the phones. It appropriates the, often intrusive, computer-based telemarketing technology and uses it in a new way, involving people who don't traditionally participate in the art world in an event that probes the diversity of life in the city and the relation of truth to fiction.

Virtual >> Physical:

“Systematized Illusion”, Charles Halary on Virtual Reality

Our understanding of the world comes from physiological processes that are variable – it seems that we intuitively understand this and that may be why we understand things in sequence – a series of checks and balances if you will that acts as a unifying and defining form. on the physiology of seeing

Has anyone seen wakinglife? We adapt to whatever environment we are in – and can’t tell the difference between a dream and waking life. Comments?

javoice – Java “Visual Prosthesis” Applet – graphic sonification, try it, you’ll like it.

Usman Haque

electronetwork

Immersive environments – we know that we are inextricable from the environment, yet our logic is dialectical…

Pervasive computing:

Project Oxygen: Overview

Oxygen Today

Oxygen in Application

Tech:

Embeddedblue from Parallax, Bs2, Jitter, TcpServer_Processing,

Silicon Logic Gates, The 3914 Dot Bar Display Chip – you can do ADC with it and it works beautifully with the Logic Gates. Ridiculously Sensitive Charge Detector . Add some relays and you’ve enough to build many projects.

Micro Lab #2

Assignment:

Reading:

Tangible Bits

The Last Farewell

complexity and art –Peter Gallanter

destruction vs. deConstruction – Kevin Taylor

View:

Space-telescope data visualizations, Hubble Spacetelescope – scroll down the right side to “how the hubble images are made” and UCSD Supercomputer visualizations

Artworks by,

Andrea Polli

Golan Levin

In class Presentation

Micro Lab #1

Great Bs2 Tutorial

Tangible Media Lab of MIT

Assignment: work on Micro project.

Charles Halary, “Art and Electromagnetism: a relationship in the form of a wave” – scroll down to Art and Design Art and Electromagnetism

Read: The Coming Age of Calm Technology Marc Weiser and John Seely Brown on ambient technology

________________________________________________________________________

Week 7

Combinations and Sequences, adding memory.

Brief Review

Digital Logic from Play-Hookey.com – good job of describing and illustrating Digital Logic, both Combinational and Sequential

Combinatorial logic circuits

Logic gates that only depend upon the current logic states of all inputs
State of output depends solely on input.

>>>

How to do potentially cool things with Boolean Logic (Combinational and/or Sequential)

Create a truth table (Truth Table and karnaugh map), for fun check out these one-dimensional cellular automata from Stephan Wolfram: Wolfram's 1D Cellular Automata
Figure out how to convert that truth table into an array of Logic Gates (And, Or, Not, etc…)This great applet will do it for you
Figure out how to minimize the circuit so that it uses NAND gates exclusively Logic Gates and their NAND equivalents
Build the circuit via simcir, simmcir , or Boolean Logic Java Applet . You can also try Simulaworks to construct elaborate systems. Link is to free trial download – for PC only…
Build it on a bread board with switches as inputs and LED’s as outputs
Substitute the sensors of your choice for the switches (inputs), and the outputs of your choice for the LED’s. Using Relays to control both inputs and outputs is a good idea. To make your life easier, choose logic gates (Silicon Logic Gates, The 3914 Dot Bar Display Chip – you can do ADC with it and it works beautifully with the Logic Gates. Ridiculously Sensitive Charge Detector ) from Digikey , or Mouser, or Newark, that start with 74LSxxx – these chips have a high enough current output to trigger relays.

switches control the flow of current through a junction in a circuit:

transistors and relays are switching devices:

Building a Transistor

***If you use the silicon chip versions of the logic gates mentioned above you will notice something: a logic 1 will be represented by 0 voltage on the output pin – that’s right. The reason? An aspect of chip manufacturing is that the output voltage of individual pins varies – sometimes it reaches +5VDC, sometimes it’s lower. What users of these chips realized is that each and every pin will always “source”, or reach exactly 0 volts. So, to avoid instances where the output voltage fluctuation is enough to cause an LED (for example) to remain dark when it should be lit, engineers and chip designers decided to have 0 = True (1). Got it? BTW, as Micro-controllers have the same issue (they are made from the same materials as our Logic IC’s, it’s a good idea to write your code with this fact in mind.

>>>

Sequential logic circuits

Circuits that "remember" the past states of their inputs and use this information along with current inputs to produce outputs are called Sequential
They are Sequential because they act in accordance with a sequence of input signals
Such circuits can be used to construct registers and other memory elements
Output depends on state of inputs and memory
Previous inputs have effect on current output
The same input signals at different times can produce different outputs
Sequential systems are built by adding memory to combinational systems

***In class Lab assignment:***

Please pick, or create a truth table and build a virtual circuit for it. Please come up with a version of it that uses “real world” inputs and outputs. Then visit Digital Logic from Play-Hookey.com and click on any of the Sequential Circuits and build one in the simulator (simmcir , or Boolean Logic Java Applet) of your choice. When you have done this, call me over and we’ll talk about it. Then, combine a Sequential circuit with a Combinational circuit

Let’s discuss memory…

Some stuff:

Mathpuzzle – check out the Spieker Circle Table near the bottom

C02 AND gate from IBM

Leeds Electric – cool surplus in Brooklyn

Science Ebooks – many cool links, some dead…

Java Applets - physics, electricity, electromagnetism, etc...

PhysicsWeb

An idea:

We train to the medium, any medium >>

Look at this: Double Helix Illustration

Art/Science and DNA Structure – Dr. Robert S. Root-Bernstein

Excerpt from above linked article:

“The problem is that there is a very small but real possibility that Watson and Crick got part of the structure wrong. Oh, the base-pairing idea, the basis for how information is encoded in genes, is certainly right. Genetic engineering, if nothing else, proves that by the fact that we can synthesize almost any gene sequence we want and have it make the corresponding protein. The rungs in the ladder of the double helix are certainly right. It's the double-helix part that is a bit doubtful. And that's where aesthetics and visual conventions come in.

To understand how it is even conceivable that DNA might not be a helix, it is necessary first to recognize that scientific research, like all arts, is a process of questioning nature. In all processes there are an infinite number of possible turnings and detours one could take at any given junction that could lead to alternative end points. Imagination or oversight determines the path. Scientists, like artists, therefore try to miss as little as possible by elaborating classes of possibilities that they narrow down by a series of informed choices.6 As Henri Poincare said, "To invent is to choose," an aesthetic statement equally valid in any creative field. What therefore underpins all creative endeavors is the interplay between the elaboration of possibilities and the criteria of choice that are employed for selecting among them. If an idea is never imagined, it cannot be chosen. And to be chosen, it must fit the dominant aesthetic criteria of the field, or give rise, laboriously, to a new one.

***Here I must emphasize that scientists, just as much as artists, are dependent upon aesthetic criteria in making their investigative choices. A considerable literature exists arguing that the choice of a problem; the criteria used to analyze its possible solutions; concepts of beauty, harmony, simplicity, symmetry, consistency; and even the skill and style with which the solution is reached and is propounded are all replete with aesthetic choices that differ in no significant manner from those made by the artist.8 As the turn-of-the-century neuroanatomist and Nobel laureate Santiago Ramon y Cajal wrote, great scientists have a: "congenital inclination to economy of mental effort and the almost irresistible propensity to regard as true what satisfies our aesthetic sensibility by appearing in agreeable and harmonious architectural forms. As always, reason is silent before beauty."9 These words, as we shall see, certainly apply to Watson and Crick and their work on DNA. Both Watson and Crick were strongly predisposed to favor helical models for DNA from the very beginning. Upon meeting the two men in 1952 while they were developing models of DNA structure, nucleic acid specialist Chargaff wrote in his diary "two pitchmen in search of a helix."l0 Pitchmen is a pun: pitch refers to the degree of inclination or slope formed by a helix as it twists around and equally to the fact that Watson and Crick were giving Chargaff a "pitch," or sell job, to the effect that DNA must be a helix. This decision was made even before there was any evidence for it, as Watson's Double Helix makes evident. For example, Watson records that during 1952, he believed:

"The idea [of helices] was so simple that it had to be right. Every helical staircase I saw that weekend in Oxford made me more confident that other biological structures would also have helical symmetry. For over a week I pored over electron micrographs of muscle and collagen fibers, looking for hints of helices."ll

What too many scientists, writers, and illustrators have overlooked-or do not understand-is that images are “understanding”. The visual form in which a theory is represented becomes a working model of that theory, whether it is accurate or not.46 What becomes familiar through visual repetition becomes the basis for our aesthetic appreciation and sets our standards for judging the rest of a field, be that field science or art. If the visual conventions and models adopted by a field are therefore misleading-untruthful-then a lack of rigor becomes generally acceptable. Clearly, just such a lack of rigor has become acceptable in our portrayals of DNA. Just as clearly, there is an outstanding problem here, whether that problem is with the structure of DNA itself or with our understanding of DNA replication.

In sum, I have no idea whether the double-helical model of DNA is correct. That is not the point of this paper. The point is to underscore just how important aesthetic considerations-beauty, ugliness, simplicity, the connection between structure and function, and overlooking or ignoring complications-are to science. There is no objectivity here-nor, if you believe Crick about the necessity of bravely ignoring data to see the forest for the trees, can there be. But in portraying the forest of genetic structures, I have also found that there is a very real danger of oversimplification, as represented by the completely inaccurate representations of DNA replication that are found in every textbook I have examined. It is bad enough that our visual conventions are misleading, but it is doubly inexcusable when the text that accompanies the illustrations gives not even a hint as to the topological, structural, functional, and mechanistic problems that the visual conventions hide. Thus, whatever the historical fate of side-by-side models of DNA turns out to be, they have played an important role in clarifying and extending our ever-changing view of the stuff of life.

Clarification is the point. Clarification of our view of life is, in the end, what joins the sciences and arts. Arts, just like sciences, should be revealing. They must have integrity and coherence. They must give us a perspective that permits a deeper understanding of its subject. They should tell the truth, even if they must make up a fiction in order to do so. In the long run it is aesthetic criteria that set the masters of any field off from the pedants and epigones of any generation. What concerns me more than anything about the case of DNA is the way in which models, illustrations, and art itself have been subverted to the use of a theory, revealing not the inner details, surprises, and fascination of the material, but covering up its complications and controversies. There is a rich field here for the modeler and the artist who can approach the questions of DNA structure and function as an explorer and explicator because DNA is nowhere as simple as the object that so many of us now take as an icon.

And perhaps, someday, side-by-side models-the warped zipper in particular-may also become icons. At the very least, considered purely as architectural models, they are surprising and new. At the very least, Rodley, Bates, Sasisekharan, and their colleagues have been intensely creative in a purely artistic way. They have discovered something unexpected about natural forms and, contrary to Crick's opinion, what they have discovered has its own beauty. Thus, I would apply the same conclusion to their work that I applied a few years ago to the attempts artist Ken Snelson is making to model the quantum atom:

"[Have they] succeeded in [their] hopes of modeling the atom[sJ? Or [have they], in [their] search for the basic structures of matter, provided a solution to a problem that has yet to be invented? The criterion of beauty tells us nothing on this point. And in the end, it doesn't matter. What does matter is the surprising insight [they] bring to [their] invention. At the very least, we can no longer think of[DNA]. . . as we did before. Rodley, Bates, Sasisekharan, and their colleagues have expanded the universe of the possible."58

What more can we ask of either science or art, or of their surprising and explosive intersections? “

ARTWORKS:

Found Photo Project

Mark Napier

Ken Goldberg

Ghost City Jody Zellen Ghost City is a website that focuses on the representation of the city by the mass media. It is a labyrinthine environment through which viewers can navigate, either following the linear narrative that unfolds by moving from page to page, or they can delve into the non-linear chaos of random links. Each space is made up of appropriated images and texts. The images are culled from various print media sources. The texts are either found passages from urban theory or specifically written poetic musings on the city. Rather than present static images, Ghost City is a collage of moving parts. It is a pulsating grid of flashing images that loop indefinitely. The viewer is an urban wanderer moving through the site, step-by-step, page-by-page. One moves forward and back retracing one's steps within the urban grid, discovering new spaces and new meanings. One clicks on a word: "walk," "time," "space" or an image of a silhouette, a shadow. The movement freezes, a color flashes and you are someplace else. One by one a new grid of images appears. Some seem familiar. Have you been here before? Ghost City is about memory, and about traveling through time and space. The time is infinite. The space is finite. Yet the time and space of Ghost City metaphorically relate to the experience of the city where people walk and talk and interact. Within the confines of Ghost City visitors can pause and think and move backwards and forwards. Ghost City is a city of fragments. A memory. A ghost of reality: a ghost city.

IsAnyOneThere? Stephen Wilson. A Voice Activated Tour of San Francisco Via its Pay Telephone. Overview For one week a computer telemarketing device makes hourly calls to selected pay telephones, engages whoever answers in conversations about life in the city, and digitally stores the conversations. The installation later allows viewers to interactively explore the city via a database of these recorded calls and digital video of life near the phones. It appropriates the, often intrusive, computer-based telemarketing technology and uses it in a new way, involving people who don't traditionally participate in the art world in an event that probes the diversity of life in the city and the relation of truth to fiction.

Poetry for Simultaneous Voices – Jim Rosenberg

The Cut-up Machine – an Hommage to William S. Burroughs

Diagrams - 5, Jim Rosenberg

Stuart Moulthrop - victory garden and pax

The Sims / Secondlife

Assignment:

Read: Absorbing and Squeezing Out - On Sponges and Ubiquitous Media - Bill Buxton

________________________________________________________________________

Week 8

Non-binary Combinational Digital logic. Memory: Feedback and Flip-flops, Rhythm.

“A chaotic system can be described as a system where a small change in the initial conditions can produce a large change in the state to which the system evolves. Digital computers are predictable and unpredictable in exactly the same senses as the rest of the physical world. They follow deterministic laws, but these laws have complicated consequences that are extremely difficult to predict. It is often impractical to guess what computers are going to do before they do it.

As is true of physical systems, it does not take much to make a computation complex. In computers, chaotic systems– systems whose outcomes depend sensitively on the initial conditions – are the norm.” D. Hillis – pattern on the stone, page 67.

We’ve discussed binary possibilities of working with Boolean Algebra. What can we do using binary counting and Boolean Gates? Whatever we want to…

As an example of a non-binary function, suppose we want to build a machine to act as a judge of the children’s game of Rock/Paper/Scissors. This is a game for two players in which each chooses, in secret, one of three “weapons” – rock, paper or scissors. The rules are simple” scissors cuts paper, paper covers rock, rock crushes scissors. If the two children choose the same weapon, they tie. Rather than building a machine that plays the game (which would involve guessing which weapon the opponent is going to choose), we will build a machine that judges who wins. Here’s the input/output table for the function that takes the choices as inputs and declares the winner as output. The table encodes the rules of the game:

Input A	Input B	Output
Scissors	Scissors	Tie
Scissors	Paper	A wins
Scissors	Rock	B wins
Paper	Scissors	B wins
Paper	Paper	Tie
Paper	Rock	A wins
Rock	Scissors	A wins
Rock	Paper	B wins
Rock	Rock	Tie

The Scissors-Paper-Rock judging function is a combinational function, but it is not a binary function, since its inputs and output have more than two possible values. To implement this function as a combinational logic block, we must convert it to a function of 1’s and 0’s. This requires us to establish some convention for representing the inputs and outputs. A simple way to do this would be to use a separate bit for each of the possibilities. There would be three input signals for each weapon: a 1 on the first input represents scissors, a 1 on the second input represents rock, and a 1 on the third input represents paper. Similarly, we could use separate output lines to represent a win for player A, a win for player B, or a tie. So the box would have six inputs and three outputs.

Using three input signals for each weapon is a perfectly good way to build the function, but if we were doing it inside a computer we would probably use some kind of encoding that required a smaller number of inputs and outputs. For example, we could use two bits for each input and use the combination 01 to represent scissors, 10 to represent paper, and 11 to represent rock. We could similarly encode each of the possible outputs using two bits. This encoding would result in the simpler three-input/two-output table shown below:

Scissors =	01
Paper =	10
Rock =	11
A wins =	10
B wins =	01
Tie =	00

The three-input/two-output truth table:

Input A	Input B	Input C	Output A	Output B
0	0	0	0	0
0	0	1	0	1
0	1	0	1	0
0	1	1	0	0
1	0	0	1	1
1	0	1	0	0
1	1	0	0	0
1	1	1	0	0

The trick with multiple output truth tables is to first break them into multiple (in this case two) one-output truth tables, like this:

Truth table for Output A

Input A	Input B	Input C	Output A
0	0	0	0
0	0	1	0
0	1	0	1
0	1	1	0
1	0	0	1
1	0	1	0
1	1	0	0
1	1	1	0

Truth table for Output B

Input A	Input B	Input C	Output B
0	0	0	0
0	0	1	1
0	1	0	0
0	1	1	0
1	0	0	1
1	0	1	0
1	1	0	0
1	1	1	0

This link shows you how to convert any truth table into logic gates Truth Tables to Logic Gates - scroll down

Here is what the circuit would look like (made with CircuitMaker ):

Then we need to create another truth table to determine the final result of the game.

Input A	Input B	Output
01	01	00
01	10	10
01	11	01
10	01	01
10	10	00
10	11	10
11	01	10
11	10	01
11	11	00

As above, here is the truth table

Input A		Input B		Output
0	1	0	1	0	0
0	1	1	0	1	0
0	1	1	1	0	1
1	0	0	1	0	1
1	0	1	0	0	0
1	0	1	1	1	0

Truth table for Output A

Input A		Input B		Output (A)
0	1	0	1	0
0	1	1	0	1
0	1	1	1	0
1	0	0	1	0
1	0	1	0	0
1	0	1	1	1

Truth table for Output B

Input A		Input B		Output (B)
0	1	0	1	0
0	1	1	0	0
0	1	1	1	1
1	0	0	1	1
1	0	1	0	0
1	0	1	1	0

Here’s the resulting circuit:

Logic Gates made from Legos

Building a Transistor

Electron Wrangling for beginners – Mark Allen’s course at the Machine Project in LA – check the lecture notes: concise, helpful.

Sequential Logic

An idea:

We train to the medium, any medium >>

Look at this: Double Helix Illustration

Art/Science and DNA Structure – Dr. Robert S. Root-Bernstein

Excerpt from above linked article:

What more can we ask of either science or art, or of their surprising and explosive intersections? “

Lab Assignment:

Go Through: Chapter 14, “Feedback and Flip-Flops”, from Code, by Charles Petzold. Using Boolean Logic Java Applet , or CircuitMaker Download (for PC only), build the sequential logic circuits in the chapter.

Some Artwork and other things I’ve been meaning to show you…

electronet – amazing site for art and electronics, please scroll down to the category Art and Design and read Charles Halary’s article: Electromagnetism and Art; a relationship in the form of a wave.

Leeds Electric – cool surplus in Brooklyn

Science Ebooks – many cool links, some dead…

Java Applets - physics, electricity, electromagnetism, etc...

PhysicsWeb

######################################################

Ghost City Jody Zellen Ghost City is a website that focuses on the representation of the city by the mass media. It is a labyrinthine environment through which viewers can navigate, either following the linear narrative that unfolds by moving from page to page, or they can delve into the non-linear chaos of random links. Each space is made up of appropriated images and texts. The images are culled from various print media sources. The texts are either found passages from urban theory or specifically written poetic musings on the city. Rather than present static images, Ghost City is a collage of moving parts. It is a pulsating grid of flashing images that loop indefinitely. The viewer is an urban wanderer moving through the site, step-by-step, page-by-page. One moves forward and back retracing one's steps within the urban grid, discovering new spaces and new meanings. One clicks on a word: "walk," "time," "space" or an image of a silhouette, a shadow. The movement freezes, a color flashes and you are someplace else. One by one a new grid of images appears. Some seem familiar. Have you been here before? Ghost City is about memory, and about traveling through time and space. The time is infinite. The space is finite. Yet the time and space of Ghost City metaphorically relate to the experience of the city where people walk and talk and interact. Within the confines of Ghost City visitors can pause and think and move backwards and forwards. Ghost City is a city of fragments. A memory. A ghost of reality: a ghost city.