Got in bed at 10:30pm last night and read Prey from start to finish… it was one of those books you just can’t put down until you’re done. Michael Crichton had to do research on genetics, nanotechnology, distributed intelligence and a host of other subjects to get this book out the door… I can’t wait for the movie, according to the official site:

“The film version of Prey is now in development at Twentieth Century Fox. No details yet.”

And how many fictional novels have a bibliography? Some of the more interesting books:

Cambrian Intelligence: The Early History of the New AI by Rodney Brooks, head AI guy at MIT

Swarm Intelligence: From Natural to Artificial Systems

Natural Enemies: The Population Biology of Predators, Parasites and Diseases

Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence

Hidden Order: How Adaptation Builds Complexity

Swarm Intelligence

Artificial Life: A Report from the Frontier Where Computers Meet Biology

Reasoning about Rational Agents

Reading this book made me want to start working with distributed intelligence and AI… Where would one start if you wanted to work in this industry? Go back to school? Write some software that emulates distributed intelligence? Cry for mommy?

Currently in Mammoth hanging at my parents house where we’re in the midst of a[nother] snowstorm. This one could dump as much as 2 feet!

So far I’ve finished 3 books on this trip: Bots: The Origin of New Species by Andrew Leonard, The Future of Ideas by Lawrence Lessig, and Fast Food Nation by Eric Schlosser. All great books, I’ve got a ton of dog eared pages for each book that I’d like to blog… but using the computer is off limits on vacation, right?

Books I’d like to read:

The Goal by Eliyahu M. Goldratt

Patterns of Enterprise Application Architecture by Martin Fowler

more from “Gödel, Escher, Bach: An Eternal Golden Braid“:

information-revealers — devices like a record or CD player which can pull information out of an information-bearer

information-bearer — a device that holds information…

Those words aren’t very exciting until you start thinking about stuff like this:

“Take the case of the genetic information commonly said to reside in the double helix of deoxyribonucleic acid (DNA). A molecule of DNS — a genotype — is converted into a physical organism — a phenotype — by a very complex process, involving the manufacture of proteins, the replication of the DNA, the replication of cells, the gradual differentiation of cell types, and so on. Incidentally, this unrolling of phenotype from genotype — epigenesis — is the most tangled of tangled recursions… Epigenesis is guided by a set of enormously complex cycles of chemical reactions and feedback loops. By the time the full organism has been constructed, there is not even the remotest simliarity between its physical characteristecs and its genotype. … And yet, it is standard practice to attribute the physical structure of the organism to the structure of its DNA, and to that alone. The first evidence for this point of view came from experiments conducted by Oswald Avery in 1946, and overwhelming corroborative evidence has since been amassed. Avery’s experiments showed that, of all the biological molecules, only DNA transmits hereditary properties. One can modify other molecules in an organism, such as proteins, but such modifications will not be transmitted to later generations. However, when DNA is modified, all successive generations inherit the modified DNA. Such experiments show that the only way of changing the instructions for building a new organism is to change the DNA — and this, in turn, implies that those instructions must be coded somehow in the structure of DNA.” [pg 158]

Still with Douglas? Continuing on with the next paragraph: “Therefor one seems forced into accepting the idea that the DNA’s structure contains the information of the phenotype’s structure, which is to say, the two are isomorphic. However, the isomorphism is an exotic one, by which I mean that it is highly nontrivial to divide the phenotype and the genotype into “parts” which can be mapped onto each other. Prosaic isomorphisms by contrast, would be ones into which the parts of one structure are easily mappable onto the parts of the other. An example is the isomorphism between a record and a pice of music, where one knows that to any sound in the piece there exists an exact “image” in the patterns etched into the grooves, and one could pinpoint it arbitrarily accurately, if the need arose… The isomorphism between DNA structure and phenotype structure is anything but prosaic, and the mechanism which carries it out physically is awesomely complicated. For instance, if you wanted to find some piece of your DNA which accounts for the shape of your nose or the shape of your fingerprint, you would have a very hard time. It would be a little like trying to pin down the note in a piece of music which is the carrier of the emotional meaning of the piece. Of course there is no such note, because the emotional meaning is carried on a very high level, by large “chunks” of the piece, not by single notes. Incidentally, such “chunks” are not necessarily sets of contiguous notes; there may be disconnected sections which, taken together, carry some emotional meaning.” [pg 160]

Page 168 has a fascinating collage of various scripts including Mongolian and Buginese. It boggles my mind that the words I’m writing right now using the English alphabet mean absolutely nothing to people in other parts of the world.

All for tonight…

Still reading “Gödel, Escher, Bach: An Eternal Golden Braid”, couple nuggets. In Chapter V, Recursive Structures and Processes, Hofstader talks about modularization, loops, and procedures. Naturally, you’d think he was writing about computer programming, and to some extent he does. There’s a discussion about the difference between bounded loops (loops which have a known maximum number of steps) and free loops (loops whose boundary is not known) and nested loops (loops within loops). He diverts to the non-programming trail for a short time to talk about how loops (in the theoretical sense) exist in knitting and crocheting (“… very small loops are repeated several times in larger loops, which in turn are carried out repeatedly…”) and how loops reside in music (“… when a scale is played several times in a row, perhaps displaced in pitch each new time.”).

This book is fascinating in that I’m finding so computer science fundamentals explained in rich detail and yet I’m not reading a book on computer science. And maybe that’s one of the points of the book; at its’ core computer science is no different than music. Both are sets of symbols that we’ve assigned meaning too.

From Steven Johnson’s post, I knew I needed to read this book by Ray Kurzweil, now I need to get “Prey: A Novel” by Michael Crichton as well… I go through reading phases where I read all of a certain authors books in a short time… couple years ago now I read all of Michael’s books: Jurassic Park, Sphere, Andromeda Strain, The Terminal Man, and Airframe, among others… I think I had to leave all those books in California when we moved.. bummer. I’d love to pick one up right now and plow through it, especially since it’s 16 degrees and feels like 5 degrees according to weather.com.

I got a good chunk of reading yesterday because I went on the shortest ride of my life. It was about 60 degrees yesterday in Boston, perfect riding weather. I drove to Blue Hills, my favorite place to ride, had Blink on the CD player, and was all strapped in… bunny-hopped onto the trail-head and got a pinch flat when my back tire hit the curb. I didn’t have any extra tubes because I gave my last one to a guy who had a flat on my last ride at Blue Hills. Then I stepped in poo walking my bike back to the car. Sheesh…

So anyways.. I’m currently reading “Gödel, Escher, Bach: An Eternal Golden Braid” by Douglas Hofstadter. This book is over 700 pages and is described by one guy on the back of the book as “…an entire humanistic education..” so a) I’m not even going to try and give a description of what it’s about and b) I’m going to blog it as I go, rather than blog it after completing the book.

On Kurt Gödel’s discovery of the Epimenides paradox: “Epimenides was a Cretan who made one immortal statement: ‘All Cretans are liars.’ A sharper version of the statement is simply ‘I am lying’; or, ‘This statement is false’. It is that last version which I usually mean when I speak of the Epimenides paradox. It is a statement which rudely violates the usually assumed dichotomy of statements into true and false, because if you tentatively think it is true, then it immediately backfires on you and makes you think it is false. But once you’ve decided it is false, a similar backfiring returns you to the idea that it must be true…. The Epimenides paradox is a one-step Strange Loop, like Escher’s Print Gallery. But how does it have to do with mathematics? That is what Gödel discovered. His idea was to use mathematical reasoning in exploring mathematical reasoning itself. This notion of making mathematics ‘introspective‘ proved to be enormously powerful, and perhaps its richest implication was the one Gödel found: Gödel’s Incompleteness Theorem.” (pg 17)
— It’s interesting to see that introspection (in software development) probably has its roots in this mathematical introspection that Gödel introduced above…. what was the first language that used introspection?

On intelligent behavior: “No one knows where the borderline between non-intelligent behavior and intelligent behavior lies; in fact, to suggest that a sharp borderline exists is probably silly. But essential abilities for intelligence are certainly:
— to respond to situations very flexibly;
— to take advantage of fortuitous circumstances;
— to make sense out of ambiguous or contradictory messages;
— to recognize the relative importance of different elements of a situation;
— to find similarities between situations despite differences which may separate them;
— to draw distinctions between situations despite similarities which may link them;
— to synthesize new concepts by taking old concepts and putting them together in new ways;
— to come up with ideas which are novel.” (pg 26)
— Makes these ‘intelligent agents‘ not seem so smart doesn’t it? Next time you see a claim that this or that software is intelligent, apply the above tests to see if it passes. I’d love to know about software that does…

On being inside and outside a ‘System’: “… Now let me be very explicit about what I meant by saying this shows a difference between people and machines. I meant that it is possible to program a machine to do a routine task in such a way that the machine will never notice even the most obvious facts about what it is doing; but it is inherent in human consciousness to notice some facts about the things one is doing. But you knew this all along. If you punch ‘1’ into an adding machine, and then add 1 to it, and then add 1 again, and again, and again, and continue doing so for hours and hours, the machine will never learn to anticipate you, and do it itself, although any person would pick up the repetitive behavior very quickly. Or, to take a silly example, a car will never pick up the idea, no matter how much or how well it is driven, that is supposed to avoid other cars and obstacles on the road; and it will never learn even the most frequently traveled routes of its owner…. The difference, then, is that it is possible for a machine to act un-observably; it is impossible for a human to act unobservant.” (pg 36-37)
— The newest versions of Windows *are* in fact observant… the “Programs” menu ‘learns’ what programs you use most frequently and shows only those programs. How else could software applications become ‘observant’? Might your Palm handheld ‘notice’ that it gets synced every night before you go to bed and ‘suggest’ to you that it schedule itself to sync at 9pm? Wouldn’t it be nice if your cell phone saw that you called take-out twice in the last week and suggest that you add that phone number to your list of contacts?

On jumping out of systems: “It is an inherent property of intelligence that it can jump out of the task which it is performing, and survey what it has done; it is always looking for, and often finding, patterns.” (pg 37)
— Substitute the word ‘intelligence’ for ‘software developer’ or ‘business manager’. Revealing isn’t it?

Took me a couple days but I finished “War in the Age of Intelligent Machines” by Manuel De Landa today. I’m fascinated by AI research and I love reading about all the new autonomous machines our military machine comes up with so I thought this book would be right up my alley. It was, but not for those reasons. The book spent quite a few pages explaining the history of warfare, tactics, strategies and weapons and how those entities changed society and then scattered like a cluster bomb to cover such topics as RAND Corporation, organized chaos, collective rationality and singularities. Because I’m not a great book reviewer and because I write this blog for myself as much as for anyone else, here’s a great summary of the book by Wired and then some quotes from the book that sparked my interest.

From Wired 1.04: “De Landa’s argument turns on the notion that singularities – the “transition points…where order spontaneously emerges out of chaos” – catalyze curiously lifelike behavior in nonorganic matter. By extension, he argues, the military apparatus might be seen as a self-organizing process in which human agents function as “industrious insects pollinating an independent species of machine-flower that simply [does] not possess its own reproductive organs.” More auspiciously, he speculates on the use of the “machinic phylum” – a superset containing all singularities – to facilitate “a symbiosis in which the evolutionary paths of humans and machines interact for their mutual benefit.” [source]

“Mission-oriented tactics, in which only the outlines and overall goal of an operation are laid down, leaving the execution details up to field officers and soldiers, decrease the overall flow of information and therefore decreases the global effects of noise and friction. When armies adopt such decentralized tactical schemes during battle, they begin to resemble the self-organizing dissipative structures mentioned above, islands of stability amid the turmoil of war. Indeed, like the system of eddies and vortices in a self-organizing turbulent flow, decentralized modern armies (like the Israeli army in 1956) have sometimes been viewed as a form of ‘organized chaos.'” (pg 79)

In regard to an invitation that political scientist Robert Axelrod sent out to professional game theorists for strategies in a round-robin Prisoner’s Dilemma tournament: “Many different programs were submitted and then pitted against one another. A majority of programs simulated ‘traders’ who were out to explit other traders (reflecting the traditional pro-conflict bias), while other programs simulated traders who were willing to cooperate. Surprisingly the ‘winners’ of this competition were programs that emphasized cooperation. ‘Winning’ was not defined as defeating rivals in single encounters (in which case betrayers would have won), but in maximizing the benefits of trade. In this situation, programs that tended to betray quickly ran out of partners with which to trade, since one betrayal would start a vicious circle of counter betrayals and mistrust. In the long run, the winning programs were the ones that had the following characteristecs: they were not out to exploit other programs (in Axelrod’s terminology they were ‘nice’, because they did not betray first); they retaliated in kind after being betrayed; and they were willing to reestablish a relationship after retaliating (they were ‘forgiving’). Even in a second tournament, when the human programmers knew that ‘nice, retaliatory and forgiving’ programs had won(and were therefore able to writing betraying programs that took advantage of this knowledge), the same kind of programs won again.” (pg 86)

“A new form of computation is emerging. Propelled by advances in software design and increasing connectivity, distributed computational systems are acquiring characteristecs reminiscient of social and biological organizations. These open systems, self-regulating entities which in their overall behaviour are quite different from conventional computers, engage in asynchronous [that is, parallel] computation of very complex tasks, which their agents spawn processes in other machines whose total specification is unknown to them. These agents also make local decisions based on both imperfect knowledge and on information which at times is inconsisten and delayed. They thus become a community of concurrent processes which, in their interations, strategies, and competition for resources, behave like whole ecologies.” (pg 107)

On predatory machines: “Autonomous weapons are a revolution in warfare in that they will be the first machines given the responsiblity for killing human beings without direction or supervision. To make this more accurate, these weapons will be the first killing machines that are actually predatory, that are designed to hunt human beings and destroy them.” (pg 128).

On the transition from the clockwork to the motor as the dominant assembly paradigm: “An example of a clockwork logical system is the Aristotelian syllogism. Such a syllogism is a formalization of a small portion of deductive reasoning, yet it dominated logical thought for two millenia. Aristotle gave us a recipe for the mechanical transmission of truth from premises to conclusions, a recipe to go from “All x’s are y’s” and “All z’s are x’s” to All z’s are y’s”. If this doesn’t seem very exciting, that’s because it isn’t: the syllogism is a rather trivial mechanism that can correctly transmit data along a given path, but cannot produce new knowledge….. We may view logical notations as little machines, as conveyor belts for transporting truth from one sentence to another sentence. While dedeductive systems transport truth from a general principle (“All men are mortal”) to a particular statement (“I am mortal”), inductive systems operate in the opposite direction. They transport truth from a particular piece of evidence (“This emerald is green” to a statement applying a general category of things “All emeralds are green”). While deductive conveyor belts are prevalent in mathematics, inductive ones are the basis of the natural sciences. Only deductive logic has been mechanized, either as clockwork (the syllogism) or as a motor (Boolean logic). Inductive logic, on the other hand, cannot be mechanized so easily. Indeed, a mechanical version of inductive conveyor belts is equivalent to building a machine that can learn from experience.” (pg 144)

On intercept-antenna farms: “… One such area is Pine Gap, in the heart of the Australian wasteland, an endless expanse of wind-swept earth, reddened like a Martian desert by whirling dust storms of iron-oxide sand … But the conditions that were so disastrous to the local population were precisely those considered ideal by the NSA. Less rain meant less chance of a signal being washed out and less possibility of interference from an electrical storm. The isolation of the area brought with it the advantage of freedom from interference from spurious signals and lowered the chance of being detected…. Today Pine Gap looks like an advance moon colony in the Sea of Tranquility. Hidden in the valley is a secret community of 454 people, eighteen single story buildings…and most startling, a futuristic array of six silver-white igloo-like radomes containing dish antennas ranging in size from less than 20 feet to about 105 feet.”

Finished microserfs by Douglas Coupland last night (2 days total).

Various quotes:

On VC’s running due-diligence checks: “.. What is the significance or defensibility of the technology underlying the idea? What is the overall viability of the idea? What do you have that others don’t? Is the necessary technical acumen on the team?” (pg 152) — Good principles to apply to any business plan.

“I say ‘Ummm … ‘ a lot. I mentioned this to Karla and she says it’s a CPU word. ‘It means you’re assembling data in your head — spooling.'” (pg 176) — What a great way of explaining ‘Ummm…’!

Ethan, the CEO of the young startup, upon being barraged with dog fur and goo by the house dog Misty: “Quite often I feel like pawing and slobbering over people I like too, but I never, of course, actually do it.” (pg 177)

On Fry’s and men shopping: “The Fry’s chain completely taps into MSE: Male Shopping Energy. This is to say that most guys have about 73 calories of shopping energy, and once these calories are gone, they’re gone for the day — if not the week — and can’t be regenerated simply by having an Orange Julius at the Food Fair.” (pg 185)

On CES (which is now Comdex right? [ps: actually, no CES is a different show]): “Karla pointed out that there’s really not that many types of things a person can have in their house in the end. ‘You can have a stereo and a microwave and a cordless phone . . . and the list goes on a bit from there . . . but after a certain point you run out of things to need. You can get more powerful and expensive things, but not really new things. I guess the number of things we build defines the limits of ourselves as a species.” (pg 356)

On the company probably becoming something: “… but you know what? All I care about is that we’re all still together as friends, that we’re not enemies, and that we can continue to do cool stuff together. I thought the money would mean something, but it doesn’t. It’s there, but it’s not emotional. It’s simply there.” (pg 358)

Finished ‘Weaving The Web‘ by Tim Berners-Lee tonight. Tim writes like he talks, moving quickly one from thought to another. Reading the book is a reminder of how nascent the WWW is, it was just over 10 years ago that he formally proposed the WWW while at CERN. We’ve seen so much so fast the last couple years.

Not to be outdone by Tim, here are my scattered notes:

Quote from Michael Dertouzos, the director of the MIT Laboratory for Computer Science: “Many people in the world believe that technology is dehumanizing us. At LCS, we believe that technology is an inseparable child of humanity and that for true progress to occur, the two must walk hand in hand, with neither one acting as servant to the other.” (postscript: Michael died on 8/27/2001)

“The fundamental principle behind the Web was that once someone somewhere made available a document, database, graphic, sound, video or screen at some stage in an interactive dialogue, it should be accessible (subject to authorization of course) by anyone, with any type of computer, in any country.” (page 37) — And that folks, is the Web, in a nutshell.

“Atoms each have a valence — an ability to connect with just so many other atoms. As an individual, each of us picks a few channels to be involved in, and we can cope with only so much. The advantage of getting things done faster on the Web is an advantage only to the extent that we can accept the information faster, and there are definite limits. By just pushing the amount we have to read and write, the number of emails we have to cope with, the number of Web sites we have to surf, we may scrape together a few more bytes of knowledge, but exhaust ourselves in the process and miss the point.” (page 202, emphasis mine) — I know some people who should take this principle to heart. Yeah! You! 🙂

It’s interesting to note (as Tim does on page 195) that most radical innovations are at first scorned or thrown aside; “… A few people get it; most don’t.” Do venture capitalists look for ideas like this? How are innovations like this grown and matured into feasible entities?