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MEDIA FUTURES 2006: 2/5 ALGORITHM: History of Algorithm

3 Sep

An algorithm is a machine that can be used to reproduce a unique pattern of behavior.   The history of the word traces back to the Greeks and the instruments they used for mathematics; for example, the sieve.  In the context of Media Futures, imagine that algorithms are tightly woven filters that capture the full range of human Automata and slowly sift through them to produce the most meaningful, intentional gestures.

Animation_sieb_des_eratosthenes







Ancient Algorithms

Finding its root in algorism, a reading of the name of Abu Ja’far Muhammad ibn Musa Al-Khwarizmi, the 9th century Persian mathematician who described a set of rules for solving both Linear and Quadratic equations, algorithm came to its present state by way of an 18th century European Latin translation and soon expanded its meaning to encompass all definite procedures for solving problems or performing tasks.  The very first algorithms are a part of the Babylonian mathematical legacy – a legacy which not only left us with algorithms for factorization, finding square roots and performing long division, but which also left us with the base 60 system that gives 60 minutes to an hour, 60 seconds to a minute, 360 degrees to a circle and 24 hours to a clock.  Babylonians were in fact able to calculate things with the same accuracy as Renaissance mathematicians due to their use of number tables, like the Plimpton Tablet, a table of Pythagorean Triples from about 1700 B.C.

Plimptontablet

While the Babylonians based their mathematical system in large part on algebra, the Greek system of mathematics was heavily based upon geometry.  It is speculated, though, that the founder of Greek science and mathematics, the philosopher Thales of Milet, visited Egypt and Babylon during his lifetime (634 – 546 B.C.) and brought back knowledge of their astronomy and geometry.  The Egyptians made great contributions in the fields of medicine, astronomy and applied mathematics, and while the former triumphs are well documented, there exist no records of the process by which they reached their mathematical conclusions.  Thales built on the knowledge brought back from his trips, inventing deductive mathematics and proving a number of theorems – a circle is bisected by a diameter; the base angles of an isosceles triangle are equal; and pairs of vertical angles formed by two intersecting lines are equal.

The foremost text on geometry came from fellow Greek Euclid, whose Elements put together former geometric knowledge with definitions, postulates and opinions – and, of course, Euclid’s elegant and rigorous proofs of the above.  In that text, he discussed the algorithm for finding the greatest common divisor of two numbers, which is today referred to as the Euclidean algorithm.  One hundred years later around 200 B.C., the world saw the next great algorithm – the Sieve of Eratosthenes, which was used to find prime numbers.

Sieve

From Wikipedia: 

Sieve of Eratosthenes is a simple, ancient algorithm for finding all prime numbers up to a specified integer. It is the predecessor to the modern Sieve of Atkin, which is faster but more complex. It was created by Eratosthenes, an ancient Greek mathematician.

 

Another important site in the history of the algorithm was Alexandria, home to Hero, Ptolemy, and Diophantos.  Hero, whom we will remember as the inventor of the steam eolipile and other Automata, published widely on geometrics, optics and mechanics – as well as mathematics.  Though sources suggest his work is derivative of Archimedes and the work of the Babylonians, his Formula to calculate the area of a triangle in terms of its sides and his Method to extract a root are important contributions to the world of mathematics.  Ptolemy published widely on astronomy and geography and calculated the best approximation of ‘pi’ for his time.  And Diophantos, known as the ‘father of algebra’, wrote his thirteen-volume Arithmetica on the solution of algebraic equations and the theory of numbers and introduced the use of algebraic symbolism with an abbreviation for the unknown for which he was solving.

But Diophantos shares the title of the ‘father of algebra’ with the aforementioned Al-Khwarizmi, whose work was responsible for significant advances in the world of mathematics. 

Alkhwarizmi_kitab_large

It was Al-Khwarizmi’s work that promoted the use of Hindu-Arabic numerals that not only pushed forward the numeral system we use today, but that gives us the very term algorithm. From the very first algorithms of the Babylonians to those of Al-Khwarizmi – to John Napier’s 1614 method for performing calculations using logarithms to the 19th century work of Boole, Frege and Peano, which set out to reduce arithmetic to a series of symbols which could be manipulated by rules – to the work of Babbage, Lovelace and Turing, which took these rules and transformed them into agents of action in computing, these feats of problem-solving are instrumental in understanding man’s quest for a grasp of the workings of the world at large.      

Babbage and Turing

One great advantage which we may derive from machinery
is from the check which it affords against the inattention, the
idleness, or the dishonesty of human agents.
From Babbage’s 1832 work “On the Economy of Machinery and Manufactures”

In our discussion of rules that govern the Internet, we must turn to the work of Babbage and Turing, for it serves as the important foundation for computing at all.  Babbage’s work grew out in part out of a need for more accurate mathematical tables, which were essential calculating aids used in navigation and astronomy, insurance and civil engineering.  These tables were produced by human computers and by hand – and as such, they were prone to error in terms of computation and reporting.  Even the slightest errors in navigational or astronomical tables can be costly – so it is no surprise that in the years leading up to Babbage’s project, government sources were willing to fund projects that would minimize the costs of troubleshooting. 

For example, the British Nautical Almanac, the world’s first permanent table-making project – had a reputation for ever-improving accuracy since its inception in 1766.  But moving into the 19th century, that seaman’s bible swung into a dangerous territory of inaccuracy and error, and the British government recognized the promise of producing mathematical tables mechanically and typesetting them by the same machine. 

So Babbage set out, with financial support (and the admirals’ prayers) to improve the accuracy of those ever-important mathematical tables by constructing algorithm-driven machines.  It was a move that mechanized the production of thought, a move that would eliminate human folly in computation, transcription and typesetting.  The result would be better answers, answers which would in turn be used for giving new instructions, as inputs in other algorithms.   

Babbage never finished his Difference Engine – though, in 1832 his manufacturing engineer did construct a working portion of it, which measured two and a half feet high by two feet wide by two feet deep.  Babbage moved forward to conceptualizing what would be the world’s first programmable digital computer – the Analytical Engine.  Babbage’s designed the engine such that it would separate the sites of arithmetic computation from the storage of numbers.  The computation would be carried out through a series of steps recorded on punch cards, such as the ones used in the technology of the Jacquard loom. 

A_engine

But however intriguing and important the technology seemed, Babbage’s Analytical Engine – due to factors financial and logistical – was never built.  It comes to us only through Ada Lovelace’s annotated translation of a French introduction to the machine – a piece of writing that established the algorithm for the computation of Bernouilli numbers, and a piece of writing that established the idea of computer programming.  Turing would later build on the work of Lovelace and Babbage, formalizing their concepts in the Universal Machine.

When Turing introduced the mathematical description of the Universal Machine in the 1936 paper “On Computable Numbers”, he set out to answer the Entscheidungsproblem, the third question left by mathematician David Hilbert.  Gödel had already answered Hilbert’s first two questions – No, mathematics was not complete, and it was not consistent.  Turing showed that mathematics was not decidable.  And that recipe to solve a particular problem, gave us an answer that begs the asking of a new set of questions.

Media Futures 2006: 1/5 Automata: A Brief History of Automata: Cranking Away Since Alexandra

30 Jul


 

If every instrument could accomplish its own work, obeying or anticipating the will of others.  If the shuttle could weave, and the pick touch the lyre, without a hand to guide them, chief workmen would not need servants, nor masters slaves.

So wrote Aristotle of the possibilities of the automaton: an object acting of itself, something bearing the power of spontaneous motion.  The advent of such a mechanism not only promised to change labor – eliminating the need for servants and slaves – but also had the potential to change media production and publication. 

In tracing the development of the automaton from its roots in ritual articulated objects to its contemporary versions, (particularly in the context of robots and models of cellular automata in computability theory and theoretical biology), it is useful to keep Aristotle’s commentary from the fourth century B.C. in mind. 

The history of automata begins with “creation” itself.  Genealogies of these self-replicating objects extend back to the creation myths of every religion and culture – from the story of God’s creation of Adam to the story of Prometheus, who made the first man and woman on earth from clay, which he animated with the fire he stole from heaven.  Moreover, the earliest articulated objects from prehistory of early historic times probably served both artistic and religious purposes: used by shamans, priests, and entertainers, these simple clay or wooden dolls with turning heads, arms, legs and hands could provide the illusion of movement as it occurs in nature, thus adding emotional impact to plays and fables.   


This baker kneading dough is an articulated Egyptian toy, one which was
probably found in the tomb from the time of the XII dynasty onwards.
By being deposited in the tomb, the baker became forever bound to his
master, accompanying him into the Beyond to continue to perform his
duties through the rest of time.

The purposes of automata were not strictly in the realm of morality and spirituality.  Hero of Alexandria (who is credited with the invention of the crank, the cam-shaft and a system of rotations and counterweights, as well as with having demonstrated the principles of the vacuum and the incompressibility of water) used automata to illustrate scientific principles.  In his Treatise on Pneumatics from A.D. 62, he laid out applications of science in the forms of singing birds, sounding trumpets, animals that could drink and coin-operated machines.  Hero’s most famous automaton, though, is the steam eolipile, which, in showing the expansion of gas when heated and the force of reaction in its escape, is regarded as an ancestor of the steam engine:

Above all, automata were sources of delight and entertainment: mechanical orchestras, living snuff boxes and cuckoo-clocks.   From King-shu Tse’s 500 B.C. flying magpie of wood and bamboo to Jacques de Vaucanson’s A.D. 1738 duck, which could eat, drink, splash around the water and digest its food like a real duck, inventors imitated nature for the delight of man:

 

Over time, the makers of automata moved from simply trying to recreate the motion of creatures in the natural world to trying to use these motions to accomplish the work of those very creatures.  This is not to say that entertainment automata disappeared – after all, fake talking human heads like Roger Bacon’s from the 13th century still capture the wonder (and horror) of onlookers at circus fairs and carnivals, as do automaton scribes, dancers and singers in the tradition of those seen below (and in the tradition of “It’s a Small World”). 

 

Picture: The Jaquet-Droz Writer, 1774.  Artifact courtesy of the Neuchâtel Museum.

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Media Futures 2006: 1/5 Automata: A Brief History of Automata: Cranking Away Since Alexandra

30 Jul


 

If every instrument could accomplish its own work, obeying or anticipating the will of others.  If the shuttle could weave, and the pick touch the lyre, without a hand to guide them, chief workmen would not need servants, nor masters slaves.

So wrote Aristotle of the possibilities of the automaton: an object acting of itself, something bearing the power of spontaneous motion.  The advent of such a mechanism not only promised to change labor – eliminating the need for servants and slaves – but also had the potential to change media production and publication. 

In tracing the development of the automaton from its roots in ritual articulated objects to its contemporary versions, (particularly in the context of robots and models of cellular automata in computability theory and theoretical biology), it is useful to keep Aristotle’s commentary from the fourth century B.C. in mind. 

The history of automata begins with “creation” itself.  Genealogies of these self-replicating objects extend back to the creation myths of every religion and culture – from the story of God’s creation of Adam to the story of Prometheus, who made the first man and woman on earth from clay, which he animated with the fire he stole from heaven.  Moreover, the earliest articulated objects from prehistory of early historic times probably served both artistic and religious purposes: used by shamans, priests, and entertainers, these simple clay or wooden dolls with turning heads, arms, legs and hands could provide the illusion of movement as it occurs in nature, thus adding emotional impact to plays and fables.   


This baker kneading dough is an articulated Egyptian toy, one which was
probably found in the tomb from the time of the XII dynasty onwards.
By being deposited in the tomb, the baker became forever bound to his
master, accompanying him into the Beyond to continue to perform his
duties through the rest of time.

The purposes of automata were not strictly in the realm of morality and spirituality.  Hero of Alexandria (who is credited with the invention of the crank, the cam-shaft and a system of rotations and counterweights, as well as with having demonstrated the principles of the vacuum and the incompressibility of water) used automata to illustrate scientific principles.  In his Treatise on Pneumatics from A.D. 62, he laid out applications of science in the forms of singing birds, sounding trumpets, animals that could drink and coin-operated machines.  Hero’s most famous automaton, though, is the steam eolipile, which, in showing the expansion of gas when heated and the force of reaction in its escape, is regarded as an ancestor of the steam engine:

Above all, automata were sources of delight and entertainment: mechanical orchestras, living snuff boxes and cuckoo-clocks.   From King-shu Tse’s 500 B.C. flying magpie of wood and bamboo to Jacques de Vaucanson’s A.D. 1738 duck, which could eat, drink, splash around the water and digest its food like a real duck, inventors imitated nature for the delight of man:

 

Over time, the makers of automata moved from simply trying to recreate the motion of creatures in the natural world to trying to use these motions to accomplish the work of those very creatures.  This is not to say that entertainment automata disappeared – after all, fake talking human heads like Roger Bacon’s from the 13th century still capture the wonder (and horror) of onlookers at circus fairs and carnivals, as do automaton scribes, dancers and singers in the tradition of those seen below (and in the tradition of “It’s a Small World”). 

 

Picture: The Jaquet-Droz Writer, 1774.  Artifact courtesy of the Neuchâtel Museum.

technorati tags:, , , , ,

Media Futures 2006: 1/5 Automata

28 Jul

 Rengerpatzchautomata 

Automatic Motion and the Gestures of Social Media

The Attention Economy is based on human behavior, behavior which includes the full range of physical gestures that we use to express our inner intentions.  These gestures could be saying something,  stretching our arms, walking past a group of people, or reading a book.

Many gestures end in themselves, as discrete actions.  Other gestures trigger subsequent gestures: for the person who performs the gesture (such as throwing a ball into the air and then catching it on the way down) or for the one that receives the gesture (such as calling somebody on the phone who then picks up their phone).  Since its introduction as mass consumer platform over ten years ago, the Internet has attracted an increasing amount of the latter: electronic gestures that use keyboards and mice (and increasing voice and video) to trigger subsequent gestures from others across the Internet.  It is not simply that more human behavior is being expressed through the Internet; entirely new kinds of human behavior are being created by virtue of the medium.  Many of these gestures are able to authenticate intentions with great subtlety so as to increase the ratio of signal to noise.

These are the gestures of social media, where influence is measured by the amount of Attention one gets relative to the amount of information one gives  The most influential online individuals combine a high pagerank that lands them above the Google fold (ie their unique algorithm) and a rich personal stream of syndicatable "what makes me me"-ness:  ie their natural API. 

The Turing test measures whether a computational response is mistakable for an actual human being.  George Dyson’s recent essay Turing’s Cathedral imagined this test to be central to Brin and Page’s agenda for Google.  They are trying to build an artificial intelligence whose automatic responses to queries seem natural and humanistic.  In order to experience the rich social media of a post-Web 2.0 landscape, however, we need to venture beyond the shadow of the Google page-rank Golem.  How can we trust an electronic reality based solely on the single perspective of pagerank (ie the link model), when our actual behavior seems more like, in the words of William James, a “blooming, buzzing confusion” of human electronic gestures.

"Egosystems, not Ecosystems"

Stallman, Torvalds, Doc Searls, R0ml and many others have established the underlying value of an Open Source ecosystem.  At the first public meeting of AttentionTrust.org in October 2005, Tim O’Reilly suggested that the next generation of the Web (3.0?) was going to be about "Data Inside".  And so if you apply the discipline of a truly Open system to all of the behavioral data that is expressed by these electronic gestures, you end up with a new organizing framework- a framework of egosystems which, for the first time, bind human behavior to the transport policies of Open Source ecosystems.  My wife Tina Sharkey came up with this brilliant expression, "egosystems, not ecosystems." in which the notion of an egosystem can be used to express the rich variety of our interactions across the Internet:  email, search, browsing, buying, tagging, chatting, and other electronic activities.  One egosystem may interact with other egosystems in infinitely different ways.  And so even at maximum resolution, this social media fabric appears richly woven and densely textured:  tiny threads of gestribution bundled transparently around eachother.

Enter the worms (which happen to be the subject of the last section of the last chapter on Arbitrage).  These little creatures that both consume and produce in equal measures provide the best model for understanding the physics of the Attention Economy.

Hamlet explains that:

We fat all creatures else to fat us, 
and we fat ourselves for maggots. Your fat king and your lean beggar is

but variable service- two dishes, but to one table.

So Hamlet 2.0 might say:

We encourage others to participate so that we may consume them
and we make ourselves interesting for the blogosphere.  Your Internet CEO and your Joe Blogger are just different algorithms- two APIs, but to one network.

What distinguishes social media from other forms of media is this worm-like behavior, where production and consumption occur simultaneously.  You can look at it as a form of therapy, where individual data is constantly being reorganized (quantitatively) to generate richer (qualititative) meaning.  This is the  Gillmor moment, when the naval-gazing gesture of an individual’s Attention feeds back, anonymously, into crystal-clear affinity pools of metadata.  Inference and influence reverberate off of eachother, turning a mess of discrete gestures into a continuous Gesture stream.

Attention Science

Attention has forever been described as an absence in terms of distractions, deficits and obligations.  Media Futures is a model for talking about Attention as something more; as an active substance that we create, express, share and remember.  This Attention substance- let’s call them attentrons- operates at a size and frequency that makes it invisible to our naked eye.  Fortunately, none of us need travel very far to reach the Attention super collider, where we can test for traces of these attentrons.  The mashups that emerge on Digg are powerful reactions of data and people.  From the new dance clubs in Second Life ripple new patterns of social networks.  How can we analyze these seemingly spontaneous phenomena so as to make visible the elements and interactions that drive their behavior?

This is the project of Media Futures: to come up with a conceptual
schema that synthesizes the  constructivist aspects of social media
and the analytical rigor of the Attention Economy.  It is a
language game:  as complex as Chess, and as fleeting as Chutes and
Ladders.  Computer scientists in the 1950’s gave us the building blocks of Input, Store, View and Output;  MS-DOS gave us operations like copy, file, print and run; Unix gave us root access.  In the Attention OS, it’s the 5 A’s: Automata, Algorithm, API, Alchemy and Arbitrage.

Maggie Dillon has done a great job aggregating brief histories of each topic, both to establish its historical credibility and to expose the subtleties of its use over time.  This syntax of Media Futures is valuable, however, only in so far as it is applied to real social media use cases.  These new services require active minds, creative imaginations and lots of quality code.  What’s missing is the sense of continuity between early computing history and the widget design for next week’s release.  And that is what we are working on here.  Enjoy.

Mediafuturesartautomata71606

Next: History of Automata

Media Futures 2006: 1/5 Automata

28 Jul

 Rengerpatzchautomata 

Automatic Motion and the Gestures of Social Media

The Attention Economy is based on human behavior, behavior which includes the full range of physical gestures that we use to express our inner intentions.  These gestures could be saying something,  stretching our arms, walking past a group of people, or reading a book.

Many gestures end in themselves, as discrete actions.  Other gestures trigger subsequent gestures: for the person who performs the gesture (such as throwing a ball into the air and then catching it on the way down) or for the one that receives the gesture (such as calling somebody on the phone who then picks up their phone).  Since its introduction as mass consumer platform over ten years ago, the Internet has attracted an increasing amount of the latter: electronic gestures that use keyboards and mice (and increasing voice and video) to trigger subsequent gestures from others across the Internet.  It is not simply that more human behavior is being expressed through the Internet; entirely new kinds of human behavior are being created by virtue of the medium.  Many of these gestures are able to authenticate intentions with great subtlety so as to increase the ratio of signal to noise.

These are the gestures of social media, where influence is measured by the amount of Attention one gets relative to the amount of information one gives  The most influential online individuals combine a high pagerank that lands them above the Google fold (ie their unique algorithm) and a rich personal stream of syndicatable "what makes me me"-ness:  ie their natural API. 

The Turing test measures whether a computational response is mistakable for an actual human being.  George Dyson’s recent essay Turing’s Cathedral imagined this test to be central to Brin and Page’s agenda for Google.  They are trying to build an artificial intelligence whose automatic responses to queries seem natural and humanistic.  In order to experience the rich social media of a post-Web 2.0 landscape, however, we need to venture beyond the shadow of the Google page-rank Golem.  How can we trust an electronic reality based solely on the single perspective of pagerank (ie the link model), when our actual behavior seems more like, in the words of William James, a “blooming, buzzing confusion” of human electronic gestures.

"Egosystems, not Ecosystems"

Stallman, Torvalds, Doc Searls, R0ml and many others have established the underlying value of an Open Source ecosystem.  At the first public meeting of AttentionTrust.org in October 2005, Tim O’Reilly suggested that the next generation of the Web (3.0?) was going to be about "Data Inside".  And so if you apply the discipline of a truly Open system to all of the behavioral data that is expressed by these electronic gestures, you end up with a new organizing framework- a framework of egosystems which, for the first time, bind human behavior to the transport policies of Open Source ecosystems.  My wife Tina Sharkey came up with this brilliant expression, "egosystems, not ecosystems." in which the notion of an egosystem can be used to express the rich variety of our interactions across the Internet:  email, search, browsing, buying, tagging, chatting, and other electronic activities.  One egosystem may interact with other egosystems in infinitely different ways.  And so even at maximum resolution, this social media fabric appears richly woven and densely textured:  tiny threads of gestribution bundled transparently around eachother.

Enter the worms (which happen to be the subject of the last section of the last chapter on Arbitrage).  These little creatures that both consume and produce in equal measures provide the best model for understanding the physics of the Attention Economy.

Hamlet explains that:

We fat all creatures else to fat us, 
and we fat ourselves for maggots. Your fat king and your lean beggar is

but variable service- two dishes, but to one table.

So Hamlet 2.0 might say:

We encourage others to participate so that we may consume them
and we make ourselves interesting for the blogosphere.  Your Internet CEO and your Joe Blogger are just different algorithms- two APIs, but to one network.

What distinguishes social media from other forms of media is this worm-like behavior, where production and consumption occur simultaneously.  You can look at it as a form of therapy, where individual data is constantly being reorganized (quantitatively) to generate richer (qualititative) meaning.  This is the  Gillmor moment, when the naval-gazing gesture of an individual’s Attention feeds back, anonymously, into crystal-clear affinity pools of metadata.  Inference and influence reverberate off of eachother, turning a mess of discrete gestures into a continuous Gesture stream.

Attention Science

Attention has forever been described as an absence in terms of distractions, deficits and obligations.  Media Futures is a model for talking about Attention as something more; as an active substance that we create, express, share and remember.  This Attention substance- let’s call them attentrons- operates at a size and frequency that makes it invisible to our naked eye.  Fortunately, none of us need travel very far to reach the Attention super collider, where we can test for traces of these attentrons.  The mashups that emerge on Digg are powerful reactions of data and people.  From the new dance clubs in Second Life ripple new patterns of social networks.  How can we analyze these seemingly spontaneous phenomena so as to make visible the elements and interactions that drive their behavior?

This is the project of Media Futures: to come up with a conceptual
schema that synthesizes the  constructivist aspects of social media
and the analytical rigor of the Attention Economy.  It is a
language game:  as complex as Chess, and as fleeting as Chutes and
Ladders.  Computer scientists in the 1950’s gave us the building blocks of Input, Store, View and Output;  MS-DOS gave us operations like copy, file, print and run; Unix gave us root access.  In the Attention OS, it’s the 5 A’s: Automata, Algorithm, API, Alchemy and Arbitrage.

Maggie Dillon has done a great job aggregating brief histories of each topic, both to establish its historical credibility and to expose the subtleties of its use over time.  This syntax of Media Futures is valuable, however, only in so far as it is applied to real social media use cases.  These new services require active minds, creative imaginations and lots of quality code.  What’s missing is the sense of continuity between early computing history and the widget design for next week’s release.  And that is what we are working on here.  Enjoy.

Mediafuturesartautomata71606

Next: History of Automata

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