“Canada.”
“Oooh! Is it snowing?”
“Not yet,” said Kuroda. “It’s still September, after all.”
“Hi, Caitlin,” Anna said.
“Hello, Professor Bloom.”
“You can call me Anna. So, what can I do for you?”
Kuroda recounted what they’d dreamed up so far: legions of ghost packets floating in the background of the Web, somehow self-organizing into cellular automata. Then: “So, what do you think?”
“It’s a novel idea,” Anna said slowly.
“Could it work?” asked Caitlin.
“I … suppose. It’s a classic Darwinian scenario, isn’t it? Mutant packets that are better able to survive bouncing around endlessly. But the Web is expanding fast, with new servers added each day, so a slowly growing population of these ghost packets might never overwhelm its capacity — or, at least, it clearly hasn’t yet.”
“And the Web has no white blood cells tracking down useless stuff,” said Caitlin. “Right? They would just persist, bouncing around.”
“I guess,” said Anna. “And — just blue-skying here — but the checksum on the packet could determine if you’re seeing it as black or white; even-number checksums could be black and odd-number ones white, or whatever. If the hop counter changes with each hop, but never goes to zero, the checksum would change, too, and so you’d get a flipping effect.”
“I thought of something similar,” Kuroda said, “although the checksum didn’t occur to me.”
“And,” Caitlin said to Dr. Kuroda, “you said cellular automata rules can arise naturally, right? Like with that snail that uses them to paint its shell? So maybe all of this just spontaneously emerged.”
“Maybe indeed,” said Kuroda, sounding intrigued.
“I think I smell a paper,” said Anna.
“You want to be a mathematician when you grow up, right, Miss Caitlin?” asked Kuroda.
I am a mathematician, she thought. But what she said was, “Yes.”
“How’d you like to get the jump on the competition and coauthor your first paper with Professor Bloom and me? ‘Spontaneous Generation of Cellular Automata in the Infrastructure of the World Wide Web.’”
Caitlin was grinning from ear to ear. “Sweet!”
* * *
Chapter 28
“Well, there’s no doubt now, is there?” said Shoshana, shifting her gaze from the painting to Dr. Marcuse and then back again. “That’s me again, all right.”
They were in the main room of the bungalow, watching the live video feed as Hobo painted away in the gazebo. Four LCD monitors were lined up on a workbench, one for each of the cameras; it reminded Shoshana of the security guard’s station in her apartment building’s lobby.
Marcuse nodded his great lump of a head. “Now, if he’d just paint something other than you.” A pause. “Note that he’s doing your same profile again: you looking off to the right. If he’d done it the other way, that might have torpedoed my thought about it reflecting brain lateralization.”
“Well,” said Shoshana, “it is my good side.”
He actually smiled, then: “Okay. Let’s put your video-editing skills to work.”
Shoshana had a not-so-secret hobby: vidding. She took clips of TV shows she’d snagged from BitTorrent sites and cut them to fit popular songs, making humorous or poignant little music videos that she shared with like-minded vidders on the Web. Her fandoms included the TV medical drama House, which had a lot of slashy subtext that was great for mixing to love songs, and the latest incarnation of Doctor Who. Marcuse had caught her working on these once or twice over lunch, using the fancy Mac the Institute had had donated to it.
“When Hobo’s done,” continued Marcuse, “take the footage from all four cameras and splice together a version that shows the whole thing as it happened. Real Hollywood-style, okay? Shot of Hobo, shot of canvas over Hobo’s shoulder, close-up on canvas, back to Hobo, like that. I’ll write up a voice-over commentary to go with it.”
“Sure,” Shoshana said, looking forward to the assignment. Timbaland has nothing on me.
“Good, good.” Marcuse rubbed his big hands together. “After this hits YouTube, the only cutting room our Hobo is going to be involved with is your edit suite.”
* * *
“What we really could use,” Kuroda said, down in the basement, “is an expert on self-organizing systems.”
“And there’s never one around when you need one!” Caitlin declared in mock seriousness. “But my dad’s a physicist. He must know something about them.” In fact, he knew something about just about everything, in her experience — at least in theoretical areas. “I’ll go get him.”
Caitlin headed upstairs. She took a detour, going all the way up to her bedroom first. It really was chilly in the basement, so she grabbed her PI sweatshirt, which her mom had thoughtfully run through the dryer after last night’s storm.
She found her dad in his den, which was a little room near the back of the house. It was easy enough tracking him down: he had a three-disc CD player in there, which seemed perpetually loaded with the same discs: Supertramp, Queen, and The Eagles. “Hotel California” was playing as she stepped through the open doorway. He was typing on his keyboard; he had an ancient, heavy IBM one that clicked loudly. She rapped her knuckles gently on the door jamb, in case he was too absorbed in his work to notice her arrival, and said, “Can you help Dr. Kuroda and me?”
She heard his chair pushing back against the carpet, which she took as a “yes.”
Once they got downstairs, Caitlin let her dad have the chair she’d been sitting in, and she leaned against the worktable; through the small window, she could hear a few of the neighborhood kids playing street hockey. Anna Bloom was still hooked up via webcam from the Technion in Israel.
“Even if there are lost packets persisting on the infrastructure of the Web,” her dad said, after Kuroda had briefed him, “why would Caitlin see them? Why would they be represented at all in the feed she’s getting from Jagster?”
Kuroda shifted noisily in his chair. “That’s a good question. I hadn’t—”
“It’s because of the special method Jagster uses to get its data,” Anna said.
“Sorry?” said Kuroda, and “What?” said Caitlin.
Anna’s voice sounded tinny over the computer’s speakers. “Well, remember, Jagster was created as an alternative to the Google approach. PageRank, the standard Google method, looks for how many other pages link to a page, right?
But that isn’t necessarily the best measure of how frequently a page is accessed. If you’re looking for info on a hot rock star, like, say, Lee Amodeo…”
“She’s awesome!” said Caitlin.
“So my granddaughter tells me,” said Anna. “Anyway, if you’re interested in Lee Amodeo, how do you find her website? You could go to Google and put ‘Lee Amodeo’ in as the search term, right? And Google will serve up as number one whichever page about her has the most links to it from other pages. But the best Lee Amodeo page isn’t necessarily the one people link to the most, it’s the page they go to the most. If people always go directly to her page by correctly guessing that the URL is leeamodeo.com—”
“Which it is,” Caitlin said.
“ — then that might be the most popular Lee Amodeo site even if no one links to it, and Google wouldn’t know it. And, in fact, if you upload a document to the Internet but don’t link it to any Web page, but you send a link to it to people via email, again, Google — and other search engines — won’t know it’s there, even if ten thousand people access the document through the email links.”
“Okay,” her dad said. Caitlin doubted Anna knew how privileged she was to get an acknowledgment at all.
Anna went on. “So, besides just traditional spidering, Jagster monitors raw Web traffic going through major trunks, looking at the actual stream of data moving through the routers, and that would include lost packets.”
“Isn’t t
hat sort of like wiretapping?” Caitlin asked.
“Well, yes, exactly,” said Anna. “But Jagster is the good guy here. See, in 2005, a whistle blower named Mark Klein outed the fact that AT T has special equipment at its central office in San Francisco — and, indeed, at several of its other facilities — that allows the NSA to tap into raw Internet traffic.”
Caitlin knew the NSA was the National Security Agency in the US. She nodded.
“It’s a tricky technical problem,” continued Anna. “You can monitor what’s going on in copper wire without interfering with the signal, because the magnetic fields leak out. But more and more of the Web is carried by fiber optics, and those don’t leak. If you want to monitor the traffic, you actually have to put in a splitter, diverting part of the signal, which reduces the signal’s strength. And that, among other things, was what they were — and are — doing at AT T, apparently. It’s called vacuum-cleaner surveillance: they just suck up everything that’s going down the pipe.”
“And that’s where Jagster gets its data?” Caitlin asked. “From AT T?”
“No, no,” said Anna. “There’s a class-action suit about all this, initiated by the Electronic Frontier Foundation: Hepting versus AT T.” She paused, perhaps trying to remember — or maybe she was googling at her end. “AT T is a for-profit corporation, but an awful lot of Internet traffic goes through universities — always has, right back to the early days. And a bunch of universities decided to tap their trunks, just to show what sort of data could be mined, so they could file amicus briefs in Hepting; they wanted to show that the government could access all sorts of private stuff this way — things they should need a warrant to get. The university consortium put scrambling routines in up front, so that certain data strings — email addresses, credit-card numbers, and the like — are always munged before the feed is made public, but otherwise, they’ve basically done what AT T did under government instructions, in order to demonstrate, despite the government’s claims to the contrary, just how invasive this sort of monitoring can be.”
“Cool,” said Caitlin.
“Jagster decided to use that same data-stream,” continued Anna, “because it lets it rank pages based on how many times they’re actually accessed, rather than just how many times they’re linked to. And since your eyePod is being fed a raw Jagster dump of everything, you’re seeing the orphaned packets.”
“And she visualizes those packets as cellular automata?” her dad said.
“Well,” Kuroda said, “the idea that they’re orphaned packets is just our provisional guess, Malcolm. And, credit where credit is due: it was your daughter’s idea. They could be something else, of course — maybe a virus. But, yes, she’s seeing cellular automata, complete with spaceships moving across the grid.”
“Maybe we should send an email to Wolfram,” said Anna. “Get his take on it.”
Caitlin straightened up. “Wolfram?” she said. “Stephen Wolfram?”
“Yes,” said Anna.
“The guy who wrote Mathematica?”
“That’s him.”
“He’s, like, a god,” Caitlin said. “I mean, most of the stuff Mathematica can do is beyond me — so far — but I love playing with it, and the command-line interface is great for those of us who can’t see. People talk about it all the time on the Blindmath list.” She paused for a moment. “And Wolfram knows about cellular automata?”
“Oh, my goodness, yes,” said Anna. “He wrote a book you could kill a man with — twelve hundred pages — called A New Kind of Science. It’s all about them.”
“We should totally ask him what he thinks!” Caitlin said.
Outside, one of the street-hockey players shouted, “Car!,” warning his friends to get off the road.
“Gently,” said Kuroda, “if I may suggest, let’s keep this between the four of us for now.”
“Why?”
“We don’t want anyone stealing our thunder,” he said. “And…”
“Yes?” said Caitlin.
But Kuroda said nothing more. Finally, Caitlin prodded him again with another, “Yes?”
After a moment, Anna answered for him: “The University of Tokyo will want to license any technology or applications that are based on what Masayuki’s equipment has made possible, I’m sure. If there are spontaneously emerging cellular automata in the background of the Web, there may be commercial applications for them — in cryptography, in distributed computing, in random-number generation, and so on. The cellular automata might be patentable, and certainly the method for accessing them is.”
“Dr. Kuroda?” said Caitlin. “Is that what you’re thinking?”
“Such thoughts have crossed my mind, yes. My university owns the research, and I’ve got an obligation to help them monetize it where possible.”
“But it’s my websight!”
“Which website?” Anna asked.
“No, no. My websight, s-i-g-h-t — my ability to see the Web. They can’t patent that! If anything, we should open-source it, or put it out under a Creative Commons license.”
There was an awkward silence. At last, Kuroda said, “Well.”
Caitlin crossed her arms in front of her chest. Well, indeed!
* * *
Chapter 29
The atmosphere in the basement was still chilly, and not just because of the temperature. Caitlin’s dad must have swiveled his chair slightly; she heard it squeak. “Look,” he said, his tone conciliatory, “the cellular automata are probably just an epiphenomenon.”
Oh you silver-tongued devil! thought Caitlin. Only her dad could try smoothing over a tense moment with bafflegab. Still, that he was speaking up of his own volition meant that even he recognized that she was pissed off. But the fact that she didn’t know what an epiphenomenon was just made her even more angry. She didn’t say anything, but perhaps Kuroda read something in her expression — whatever the hell that meant!
“He means he thinks they’re just a random by-product of something else,”
Kuroda said gently. “Like foam, which is an epiphenomenon of waves: it doesn’t mean anything; it just occurs.”
She got it: her dad was saying, hey, see, nothing here worth fighting about; if the cellular automata are meaningless, there’s probably nothing of value to patent anyway. But that hardly excused Kuroda even thinking about making a buck — a yen! — off something that she was doing. Yes, yes, his hardware was feeding her the signals, but it was her brain that was interpreting them. Websight wasn’t just hers, it was her.
“You may be right, Malcolm,” said Anna Bloom, over the webcam link from Haifa. Caitlin was still fuming, and wondered if Anna really knew the mood here. She was seeing a very limited view through the camera, no doubt, and the crappy computer mike probably wasn’t picking up subtlety of tone.
Anna went on: “One bit does affect the next, at least in copper wire; the magnetic fields do overlap, after all. So maybe some sort of … I don’t know, constructive interference, perhaps … could accidentally give rise to cellular automata.”
“But they would still just be noise,” her dad said.
“You’re probably right,” Kuroda replied. “But um, what is it you like to say, Miss Caitlin? You’re ‘an empiricist at heart.’”
He was trying to cajole her, to include her, she knew, but she remained angry. Kuroda worked with computers all day long, for crying out loud — didn’t he know that information wants to be free?
Caitlin was still leaning against the worktable. The street-hockey game continued outside: someone just scored.
“Miss Caitlin?” said Kuroda. “Testing what your father just suggested will involve some cool maths…”
“Like what?” she said, her tone petulant.
“Perhaps a Zipf plot…”
Caitlin didn’t know what that was, either, but to her great surprise her father said a very enthusiastic, “Yes!” That was enough to make her curious, but she wasn’t ready to give in just yet. “Is there empty room on this
table?” she said, patting its surface. “And do you think it’ll hold me?”
“Sure,” said Kuroda after a pause, presumably to give her father a chance to answer first. “Everything to the left — your left — of the computer is clear.”
Caitlin boosted herself up onto the table, the folding legs groaning slightly as she did so, and she sat cross-legged on it. “Okay,” she said, her tone still not very cheery. “I’ll bite. What’s a Zipf plot?”
“It’s a way of finding out if there’s any information in a signal, even if you can’t decode the signal,” Kuroda said.
Caitlin frowned. “Information? In the cellular automata?”
“Could be,” said Kuroda in a tone that sounded like it should be accompanied by a shrug.
“But, um, can cellular automata contain information?” Caitlin asked.
“Oh, yes,” said Anna. “In fact, Wolfram wrote a paper about encoding information into them for cryptographic purposes as far back as, um, 1986, I think. And a bunch of people have tried to develop public-key cryptography systems using them.”
“Anyway,” Kuroda said, “George Zipf was a linguist at Harvard. In the 1930s, he noticed something fascinating: in any language, the frequency with which a word is used is inversely proportional to its rank in a table of the frequency of use of all words in the language. That means—”
You don’t have to spoon-feed Calculass! “That means,” she said, “the second most-common word is used one-half as often as the first most-common, the third most-common is used one-third as often as the first most-common, the fourth most-common is used one quarter as often, and so on.” She frowned. “But is that really true?”
“Yes,” said Kuroda. “In English, the most-common word is ‘the,’ then ‘of,’ then ‘to,’ then … um, I think it’s ‘in.’ And, yes, ‘in,’ or whatever it is, is used one-quarter as often as ‘the.’”
“But surely that’s just a quirk of English, isn’t it?” said Caitlin, shifting slightly on the table.
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