Michelle Baba, Week 4 - Stephen Wolfram

Though I thoroughly enjoy the things that we cover in this class, I am a little troubled by the small amount of things that we take the time to actually learn about and discuss. I think that so much material has been crammed into each week, we don’t really get a chance to think about all of the different works and artists that we are shown.

Anyways, this past week, self-organization caught my eye. I wanted to know more about it and how it was connected to the artist that was mentioned in class, Stephen Wolfram:
Self-organization is when something increases in complexity without being guided or told to do so. Some examples would be morphogenesis (when a living organism develops and grows), the creation of structures among social animals/insects, and flocking behavior among birds. According to http://pespmc1.vub.ac.be/SELFORG.html , it is basically a process of evolution where the effect of the environment is minimal and the development of new, complex structures takes place primarily in and through the system itself. Below is a mathematical construct that displays self-organization created using “Rule 30,” a program created by Stephen Wolfram.

Wolfram, a computer programmer (among many, many other things), studies simple computational systems and believes that they, rather than traditional mathematics, are needed to model and understand complexity in nature. He creates programs such as “Rule 30” to create his art of shapes and geometrical forms.

And to change the topic to computer programs such as Weisenbaum's ELIZA, I'm not even certain that I would consider that as having weak A.I. since it is programmed to give certain responses and ask certain questions in a particular order. I suppose it does fit the definition of weak A.I. since it does perform simple tasks, however, I feel that it do not, in fact, live up to the "intelligence" part of its name... just something to consider. Oh! And there's also the similar program that is contacted via AIM called "Smarterchild" that can be used as a seemingly personalized/intimate search engine.

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Week 4 - Christopher Flannery

I liked the interview with Philip Galanter because he made connections between art and music. Generative art seems to have a lot in common with music performance because it is a live process within guidelines, but the outcome is always different. Improvisation and randomization have always existed in music, however it has become more common with the development of jazz and use of technology. Music and art are unfolding and temporal entertainment for the audience. He describes generative art as “verbs” and not “nouns” and I think that this is a great description of music as well.
My music theory teacher used a metaphor to explain why many listeners don’t have the patience for modern music. Listening to an abstract composition is like looking at a giant mural only five inches at a time. Generative and process art can lose an audience in the same way if they don’t come with the correct mindset.
We briefly discussed John Cage’s use of I Ching as a system to randomly designate which notes are played when. Cage is responsible for the resurgence of what has been named “aleatory music” – music where some or all details are left to chance. The system for randomization is pre-determined by the composer however is virtually out of their control. There is evidence of musical “games” involving rolling dice to determine some aspects of the composition as far back as the 18th century. Aleatory music is as close to generative art as music comes. Wikipedia gives a better explanation and links to a number of examples. (the hotlink function is not working for me ...) http://en.wikipedia.org/wiki/Chance_music
The most important point that I learned from the Philip Galanter interview is that generative art has always been around and that it is not restricted to only technology. Generative art has existed just as long as art. It is the use of systems and guidelines is what defines generative art, not the tools.
I liked the part of the lecture concerning swarm intelligence, but I was confused how it is any different than normal systems of information sharing. All operations of live need many parts to react and work locally for a larger goal. The human race does exactly that by recording history, collaboration, diplomacy, and professionalism or specialization. It seems to me that almost anything can be analyzed at this level if one steps back far enough. Along with self-assembly, it seems like it only one aspect of the larger concept of synergy which is the drive and original of life, or emergent properties.
Watching the movie Brazil in class, I was reminded of Steve Kurtz’s lecture focusing on the over-reaching power of the American government. Both present their message in a satirical manner of social commentary. On the other hand, I thought it was funny that we viewed the movie because I saw almost no examples of art in the film. The government apparently does not allow any forms of public expression, but the futuristic and bleak setting is shown through amazing imagery. The complicated and dark city-scape, dirty and futuristic electronics, and utilitarianism designs are iconic for government’s oppression of the people. The setting reminded me a lot of the new movie Children of Men, which is also set in the bleak future. In this film, the government has become even more oppressive because the social structure and responsibility has collapsed after every woman on the planet became infertile twenty years prior. It is obvious that film is now the most powerful method of social commentary.

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Section 4 Week 4

Okay, so this week we covered a lot of topics a handfull of which I thought were REALLY interesting. The first thing that caught my eye was the idea of generative art because it has an intrinsic relative nature to it. Upon first hearing the word generative art (with some understanding) we consider computer-based and organic systems like insects or computer algorithms that create intricate paths from which we can derive patterns or what we think are recurring paths. Using these things and robotic graphing systems we can create art and then the question "is that really art?" is realized. Randomized computer graphing, interactive art that grows as you touch it or walk near it or yell at it, what makes this art? For organic systems, it almost seems like a comedy that nature plays on us; we try to map it out and predict its next moves but then it pulls a quick one, making us realize we can't replicate what it has made. Math can't define nature, nature just defines math. People see it as a concrete idea but ultimately it is just as fluid and changing as the seasons. This is the beauty and artistic nature of our computations is that they're sometimes infinitely close but at the same time, close is not right. Also one of the things I think particularly plays into this relativity is that sometimes humans like to separate themselves from these systems when we are just as natural and just as mathematical as any. I believe that when 1,000 people are in the same place, they will interact almost the same as another thousand because there is an equal probability of random variety among them and as the saying says "places change but people don't." We are as easily mapped as ants or plant growth patterns or anything else. It is for this reason that I love the generative art that Philip Galanter does as it grows as people interact and is considered random and happens while the observer interacts with it while it is somewhat predictable and deviates only a bit.
The next topic of interest is artificial intelligence. I read an article in Popular Science about artificial intelligence from a nobel laureate in the field. Somebody asked the question 'is the development of artificial intelligence the equating of human consciousness into a computer?' to which he replied, very smartly and simply, "no." He explained that a human can walk into a room ten times and feel differently and interpret the room in ten different ways while a computer entering a room simply interprets it in one. Humans have the ability to discern an actual item from its symbolic counterpart. We can ascribe meaning and emotion into a song or thing or voice or view while a machine can only interpret what has been fed into it. Even if it learns from its environment, it will never understand the feelings something can hold even if it understands further the entire knowledge base that the internet contains. And so, it is to this extent that AI can reach. Interestingly enough, Wilson reflects in his article that the artistic nature of AI is in its goal to reach into human nature and fool a human into believing that it is itself a human. Being able to hold converstaions, reflect feeling and understanding are all part of being a human and it requires researchers to look both into the limitations of machinery and the far stretches of humanity to make AI a reality.
I actually found an interesting video on youtube.com about a robot from Cornell University that is able to map out itself. First it moves and then utilizes several sensors that allows it to interpret how much pressure is applied to different areas of its body and where it is spacially to determine what it looks like and how it works. Additionally, when it is injured, it repeats the learning process to find out what is wrong with it, and how it can move without that part. When you think about it, we kind of learn in this way. We move and say and do things to test how far we can go not only in physical measures but socially. I think this a huge step in moving toward AI. This is the link to one of their vids but I can't find the original video that I watched.
http://www.youtube.com/watch?v=MNdDsK_t1Vs

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Week 4 - Justin Nordheim - The Art and Science of the Future

As a child, I thought "real" art existed only in museums or in the homes of the rich and famous. Growing up, I realize that art could actually be created by me or anyone who wanted to. It is obviously hard to create world reknowned work, but art is just a translation of feeling onto a medium that can be understood by human perception. The most recent lectures have been very interesting because they have helped show me some work of the present and works that look into the future. In the public school system, we are exposed to classic literature (not modern) and almost no art (and the art we are exposed to is of a classical nature). This is the first time I have received an education in current events with the focus on artists and new developments. However, as stated by another poster, I am uncertain as to what recurring themes surface in this art movement, how it possibly started, and other specifics besides what artists participated and what kind of artwork they generated.
Artificial intelligence is one of the largest current art forms in my opinion. In fact, it opened my eyes to idea that art is doing much more for society than most people think. Design may not be a necessity of human existence, but how boring would the world be without it? Also, I'm pretty sure it's proven somewhere that visual and auditory beauty help with our emotions, mindstate, and well being. Furthermore, artificial intelligence is an incredible way to connect humans to all forms of media, including other human beings. I found this website to be very interesting and a very simple presentation of where artificial intelligence is currently, where it has been in the past, and where it is looking to progress: http://people.csail.mit.edu/phw/briefing.html. Upon reading this page, I was surprised as to how many things use artificial intelligence or some other aspect of design and technology to help with human compatibility in regard to electronics.
I found artificial intelligence to be the most interesting topic of the week because of a number of reasons. First, science directs the actions involved, but a human with artistic talent must inevitably design a program that recognizes certain triggers and acts upon them. Thus, artificial intelligence is inherently artistic because it is the idea of designing something to act like something else, which cannot be expressed solely using equations. Second, it is so prevalent to the future. Many movies have debated the idea, artists have formulated ideas of what the future might hold for this technology, and currently it is already sweeping the nation with ideas such as interactive art, computers, and robots.
I'm a guy. I have played tons of video games. The AI in video games is almost ubelievable; lifelike figures have life like movements and lifelike reaction speeds. In fact, AI has changed the video game revolution because it's as if you could sit down at your compute and live a very realistic alternative life of something you probably couldn't do normally (such as become a member of a SWAT team, fire futuristic, non-existent weapons, or pretend you're a fish or other animal). I believe this type of research and more specifically, art form, holds the key to the future of technology.

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Artificial Proof and Art

I really liked the guest lecturer this week, Edward Shankin. Several things that he said really hit home for me. The first was what he said about art and interpretation. I know from the experience of attending an arts boarding high-school that, when it comes to the visual art medium, things can be pretty abstract and, at times, they can seem “pointless” and just plain “weird”. When professor Shankin said that most people aren’t able to as specifically interpret art as they are other things, it struck me that this was why visual artists are seen as “weird” and their art as wildly passionate but lacking purpose. I can recall countless exhibits, both at my old boarding school and in the art galleries of UCLA and Cal Arts (where I visit almost every week) in which a first glance appeared to be randomness or abstractness for the sake of it. I believe that the reasons for my interpretations are that I am not accustomed or used to analyzing things that have no real concrete basis for which to start an investigation.
1. In writing, you start with words and what they mean and what they don’t mean. Then you move on to the sentences and, after all meaning is examined (with a dictionary) you explore what ideas they could reflect.
2. With music you can analyze the harmonic movement and compare it to the common practices of different eras in musical development. Then, you can examine the modality and the nature of the melodic lines and rhythmic elements. 3. With movies and animations you can examine actions and dialogs and examine the first with the expectations and stereotypes that are present in society and the second with the same technique that is used to examine literature. All of these forms of art have concrete ways that all people already have a solid grasp on (language, sound, and chronological, real-life actions). When we come to visual art, however, there is suddenly almost nothing present that is familiar enough for most people to examine it with. Often the single thing that people will use to interpret a piece of visual art is the title, because it is in a language that they understand.
The second point that professor Shankin made ties in now. He said that art and science often have parallel ideas and arrive at the same resolution, but that art rarely gets credit or recognition. I believe that this is because the fundamental language of art is more foreign to people than the hypothesize>test>report method of science. In fact, I cant even tell you the equivalent statement for art. Maybe its realize>develop>display, or hypothesize>rephrase>reveal. What I do know now is that I need to look a little closer at the next art exhibit that I habitually approach as an abstract stab in the dark.
The other topic that I have been thinking about lately has been that of artificial intelligence and the relationship between biological and computerized systems. I personally believe that computers cannot become intelligent by virtue of their complexity. I think that the source of human awareness needs to be discovered before we can know how it may be artificially achieved and reproduced. In the current approach to making an intelligent machine, code must be written that a chip them compiles into binary and is executed. I think that this is the fundamental barrier that must be overcome before we get computers that are really self aware an intelligent. By design, programming languages are based on the need for reactions, limits, parameters, and computation orders. Because of this, no computer will be able to connect two abstract ideas or think for itself. They will only be able to choose a correct response out of stored responses that were already thought of. New approaches to programming languages are needed. I think that some type of language that can be continuously revised by the computer based on its experiences and encounters is needed, but such a language would need to be able to reference things and know how to use references. In a sense, an aware program would need to have included in its script all knowledge and experience that can be absorbed and developed in any person between infancy and adulthood (or have the ability to acquire them). The code would have to be able to judge actions and reactions not solely on winning and losing or gaining and giving (standard languages only know addition and subtraction). These are the barriers that must be crossed before we have truly intelligent machines.
The majority of artificial intelligence websites define AI as “the area of computer science focusing on creating machines that can engage in behaviors that humans consider intelligent.” The problem I see here is that we are judging intelligence on things that we consider to be behavior that an intelligent being would exhibit. Not only could our perception of intelligent behavior change, but intelligent behavior alone is not proof of intelligence.

One such website is here:
http://library.thinkquest.org/2705/
it has lots of info regarding AI, its history, and numerous approaches at creating it.

I believe that AI can and will be created, but all the research i have seen and the attempts i have read about have jumped to the conclusion that our programming languages are sufficient and our knowledge of where our intelligence comes from and what intelligence is are correct.

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Blogging Instructions

Each week by Sunday at midnight each student must post a 500-800 word blog entry. Reflect on the questions raised in Prof. Vesna's lecture, guest lectures, and readings. Connect these concepts to self-directed research. Provide one link for each post to something you've discovered. Examples are news articles about scientific, artistic, political events etc. that relates to class topics. Images are optional but enjoyable for everyone.

Use the "Create New Post" button in your "dashboard" once you've logged in. Use the buttons above the text box to add photos, links, and text formatting.

When Posting Always...

Label your post with your section in this format (without quotes): "Section 1"
This allows your TA to find your blog posts.

Email myself or your TA if you have technical issues.
oleary@ucla.edu
xarene@ucla.edu
zblas@ucla.edu
datadreamer@ucla.edu

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