In fact this was one of my trade secrets–which, being retired, I can now reveal: in a legal contest, it is easier to defeat an adversary for whom you feel affection. The tension that inevitably develops between that tender human feeling and your legal obligations can be put to excellent use. As an attorney it is one’s legal obligation to “zealously” represent the interests of one’s client, and the sharp regret at working against the interests of someone for whom one bears affection is the clearest indication I know that one is actually representing one’s client with a single-mindedness and vigor that could be legitimately termed “zeal.”
From Slices of Pi for Total Morons
A Small Twist
Let’s try to compress some different data with Slices of Pi. This time we’ll try to compress:
27609
That’s a shorter number, so it should be pretty easy, right?
As usual, Slices of Pi starts by searching through the digits of pi for our data. This time we have to go a little further into pi–you might not want to try this at home!
… 9940012601642 27609 2608234930 …
There it is! Our data starts right at digit 34211 and runs for 5 digits, so Slices of Pi will compress it to:
34211 5
No problem, we’ve got this! But wait … do you notice something strange here? Let’s look at the two versions of our data–original and compressed–right next to each other, this time with the spaces squeezed out:
27609
342115
You see that? The compressed version is actually bigger than our original data! Not exactly what we were looking for in a compression algorithm!
So, umm … what’s up with that, Slices of Pi?
Getting Real
In the real world, this example wouldn’t cause us too much trouble–after all, “27609” is so small already–who cares if we can’t compress it?
But the same kind of problem crops up when we apply Slices of Pi to all sorts of real world data: sometimes Slices of Pi has to look so deep into pi to find a copy of our data that the number telling us which digit our data starts at is actually bigger than our original data was! What can we do in that case? Well, as you might have guessed, Slices of Pi has a few more tricks up its sleeve.
Divide and Conquer
One trick that Slices of Pi can use is just to split your data up into chunks and compress each of those.
Sometimes this works, and sometimes it doesn’t. But even when it doesn’t, Slices of Pi still isn’t ready to throw in the towel …
Recurses, Foiled Again! (And Again, and Again, and Again …)
The most important trick that Slices of Pi uses to solve this problem is called recursion. Don’t be scared: recursion is just a fancy word for an algorithm that can use itself as one of its steps.
With that in mind, let’s look at that pesky original data again …
27609
… and remember that Slices of Pi “compressed” it to
34211 5
… which was bigger than 27609.
But what if we try recursing? That is, what if we take part of the compressed version of our data–34211–and try to compress that with Slices of Pi?
You know the drill by now–first Slices of Pi tries to find 34211 in the digits of pi … and this time, it doesn’t have to look so far!
… 28034825 34211 7067 …
Slices of Pi finds our new data–34211–only 90 digits into pi. It’s 5 digits long, so the compressed version would be:
90 5
Hmmm … that’s looking pretty small–definitely smaller than 34211. So what if we took the compressed version of our original data, 27609, which looked like this:
34211 5
… and substituted in our compressed version of 34211? It would look something like:
90 5 5
Let’s squeeze the spaces out and compare it to our original again:
27609
9055
Hey! We’ve managed to make the compressed version smaller than the original version again!
Things looked dark for a moment there, but we’ve snatched victory from the jaws of defeat. Nice save, Slices of Pi!
From My 12 Memorable Cases (A Memoir), by Ulysses J. Fleetwell (unpublished)
When an intellectual property litigator walks into a court room, he is Ishmael of the Bible, entering a state of war with all present–not just the opposing counsel and the jury, when there is one, but even his own client, with his white lies and omissions and emotions muddying every matter.
But there is one opponent against whom the attorney always enjoys an advantage, if he is clever enough to exploit it: the judge.
Yes, his honor, the sternest of the stern, the fairest of the fair, ostensibly the least interested of all those present, harbors a hidden desire–and a hidden desire, if you discover it, is a handle by which you may turn a man any way you wish.
Once upon a time his honor was like you. He earned his daily bread and the respect of his fellows through the exercise of his intellect in the legal arena, and now, as a reward for his brilliance, he has won a post where that very intellect must remain subjugated and silent. Hence why judges so love to write opinions, and will jump on any opportunity to do so–and why, when they cannot write opinions, they write books. Every minute that his honor sits on the bench, impassive and silent, his intellect grows increasingly anxious and longs for exercise. It will not be denied forever.
[…]
So while it is nearly impossible to manipulate a judge by means of what you say–his raw intellect is at least a match for yours, and paces his skull like a caged panther, desperate for any chance to escape and tear your feeble reasoning to shreds–you may often manipulate even an excellent and impartial judge by the judicious exercise of what you leave out.
[…]
In my closing argument to Mariposa Media Conglomerate v. Partensky, I flirted with an idea, approaching it from several angles but never quite arriving at it. It was an idea without any legal weight whatsoever–an idea whose only merit was a certain wit, a certain turning of the themes of the case back upon the case itself. Had I employed this idea in my closing argument, Judge Bulger would have discounted it, immediately and appropriately. But dangling there–unstated, unconsummated–the idea was a lure, an irresistible promise of exercise for his honor’s restless intellect.
From the Decision of Mariposa Media Conglomerate v. Partensky (by the Honorable Marcus Whitney Bulger)
In closing, I must note the irony of Mr. Partensky’s counter-claims in light of the fact that the very method he invented and purports to own–the “Slices of Pi” compression algorithm–depends upon the pre-existence of all conceivable data–whether those data describe a movie, a song, or even an invention–in the digits of pi. We presume, for example, that the “Slices of Pi” compression algorithm must itself be found encoded somewhere in that endless march of numbers–and that furthermore it has always been there, waiting for us to discover, not invent it. In this light the very concept of “invention” is meaningless outside the legal sphere–and inside the legal sphere, the concept of “invention” is neither more nor less than an exercise in the application of certain contractual laws and the rights and responsibilities they confer. In this case those laws, while subtle, are clear.
From Slices of Pi for Total Morons
Dealing with Loss
In the real world, loss is always a sad thing–but when it comes to compression algorithms, loss can actually be a great tool to help us make our data even smaller!
How does that work?
Compression algorithms come in two flavors: lossless and lossy. Slices of Pi is a lossy compression algorithm, which means that when you compress data with Slices of Pi, the data you get back after decompression might be just a little different than the data you started with. In other words, a little bit of your original data might have been lost.
But wait, why would you ever choose to lose data? Simple! Because loss
y compression algorithms can often make your data even smaller than lossless compression algorithms–and after all, making your data small is the whole point of compression!
Sure, for some kinds of data you never want to lose anything, and then you would use a lossless algorithm. But for other kinds of data–like photos, videos, and music–you won’t even notice a little loss. You’ll sure notice the extra space on your hard drive and the quicker downloads, though!
Getting Lossy–the Normal Compression Way
You remember that normal compression algorithms work by finding patterns in data, and that broken patterns–or surprises–are harder for them to compress.
So some normal compression algorithms are lossy because they smooth out little wrinkles and surprises in the data to make more patterns. For example, a normal compression algorithm might be lossy by smoothing “1112111” into “1111111,” which is more patterned and much easier to compress.
But remember–unlike normal compression algorithms, Slices of Pi doesn’t work by finding patterns!
Choosing to Lose–the Slices of Pi Way
So if Slices of Pi doesn’t care about patterns, why is it even lossy at all? Well, because sometimes Slices of Pi can find slight variations on your data much earlier in the digits of pi–and remember that the earlier Slices of Pi finds your data, the smaller it can make it!
(By the way, don’t worry: Slices of Pi is careful to make sure that those slight variations don’t affect the quality of your video or audio too much.)
So I guess you could say, when it comes to Slices of Pi: loss is a win!
From “Irrational Beauties: the Verse and Person of Ulysses Fleetwell”
Off camera: Did you ever actually meet him?
Nick Caverly: Yeah, I met him once. I’d been out of school for, like, three years, and Unreasoning Songs was like my Bible at the time, so I screwed up my courage and found his work address and emailed to ask if he would meet me for a beer. I emailed him like four times over a month without an answer, but finally his secretary emailed back with a time and place–some high-end “establishment” in the financial district. No beers on the menu, either, by the way–just cocktails. I think the cheapest was like $20, which is what I ordered–it was pink and really sweet. Pretty nasty.
He got there like 20 minutes late, and when they led him to the table he looked me up and down–I was dressed pretty much the same as I am right now–and he kind of sniffed, and I was like “How about you take a look at your own self, man? You look like you just came from a funeral.” And he–I’ll never forget this–just looked me right in the eyes for like 30 seconds, and then said: “I just came from a funeral.”
Off camera: Was he serious?
Nick Caverly: Yeah, man, he was serious as a heart attack. So I’m tripping all over myself to apologize, and I’m like “Was it someone you knew well?” And he says “I knew him quite well: I killed him.” Then he orders his drink.
Off camera: Wow.
Nick Caverly: Yeah, you’re (bleep) right wow.
Off camera: But he was just messing with you, right?
Nick Caverly: I guess, but I don’t know–that’s all he would say about it. He just moved right on and asked me what my “motive” was for wanting to meet him–I remember, that was the word he used.
First I tried telling him I was just a big fan, etc. etc. etc., but he was having none of that–he was smart about people, you could tell that right away. He could really read them. Finally I broke down and admitted that I’d wanted to ask him to take a look at some of my poetry, and maybe write me a recommendation for Iowa–you know, only if he liked what he read, no pressure, etc.
So I gave him some poems, which he folded and stuffed in his inside pocket–presumably to toss in the first trash can he passed–and then he asked me a couple questions about who I was reading and so on, and that was that. Oh, and he paid for our drinks, so that was nice I guess.
Off Camera: Did he (inaudible)?
Nick Caverly: Did he what?
Off Camera: Did he write a recommendation for you?
Nick Caverly (laughing): Naw, man, he never wrote anything for me. I mean, except the poems. Those he wrote for all of us, right?
From Posthumous and Uncollected Poems of Ulysses Fleetwell
Forgiveness, like light,
Has a speed:
If we flee our sins too quickly it cannot
Overtake us
[…]
Hurtling away from all things
At the speed of forgiveness
Plus one
I can see him still–
Gigantic and ursine
Even slouched in defeat,
Wild eyes searching for an ally
As a dancing bear
Might search the audience
For one look of compassion
Before the whip
Cracked
[…]
But the numbers go forever
Counting all things done
And all things undone
In their endless flow of
Everywhere and everywhen:
All things as they are and were,
All things as they should have been
Note, in its Entirety, Found on Igor Partensky’s Kitchen Counter
My dearest Ida,
From Wikipedia’s “Igor Partensky” Page
This article has multiple issues. Please help improve it or discuss these issues on the talk page.
[…]
Death
[…]
After his legal defeat and divorce, Partensky withdrew from public view. His behavior became increasingly erraticaccording to whom?.
[…]
Police estimated that the car was traveling at over 70 MPH when it struck the tree. Vodka was found in the car, and Partensky’s blood alcohol level was measured at 0.4, over 4 times the legal limit in Massachusetts.
Legacy
Partensky’s daughter, Ida, studied intellectual property law at Georgetown University. Inspired by her father’s misfortunesource?, she established the “Igor Partensky Project for Intellectual Honesty,” a non-profit entity that represents individual inventors pro bono and lobbies for intellectual property reform.
The Projectsplit to new page? has achieved several notable and much-needed reformsbiased or partisan attitude? and is currentlyclarify time frame engaged in an ongoing class-action suit against Mariposa Media Conglomerate.
In order to maintain impartiality, the Project does not accept outside funding, and operates solely off their large original donationsource?.
The original donor has chosen to remain anonymous.
Future Perfect
The cookies had been baked in the shape of butterflies, but then frosted with asymmetric black and white designs and piled carelessly on a pewter tray as if to conceal the resemblance. Butterflies had been stitched in stout black thread on the headpieces of the black leather chairs distributed around the oval conference table, from whose wavy wooden grain distorted butterflies seemed desperate to escape. The trash can opened by means of a rotating panel attached with screws at what would have been the head and tip of the abdomen. A beam of sun at just the right angle released an engraved horde from the frosted glass above the door, and even the carpet, Janine Smalls noticed, sported a suspiciously papilionaceous weave. She was squinting at the ceiling, searching for butterflies in the plaster, when someone opened the door so violently that the breeze compelled her to close her eyes.
“Miss Smalls, Mr. Bradley,” said the small round man who rode in on the breeze, “please don’t get up! Jerome Pope, CEO, so sorry to have kept you waiting, but how excellent to put faces to names! And such faces! When we spoke on the phone”–this to Janine Smalls–“I had no idea I was talking to a displaced movie star. And Mr. Bradley, before today we have exchanged only emails, but I imagined you just as you are–the corn-fed Midwestern boy made good, all warmth and casual charm. So,” he said as he took a seat across the table,
“how many did you count?”
Almost without moving her head Janine Smalls glanced at Ryan Bradley, in case he wanted to field the question, but at the slight suggestion of furrow in his brow she jumped in.
“How many emails?” she asked.
“Butterflies, Miss Smalls!” said Mr. Pope, sounding somehow like a movie Nazi. “How many butterflies. Some of our clients have counted hundreds.”
“We’re not clients,” Mr. Bradley said.
“Not yet. But you can still count the butterflies if you’d like. That’s free.”
Mr. Bradley shifted in his seat, as if seeking a fortified position from which to attack, and Miss Smalls spoke before he could settle.
“Mr. Pope, why don’t we get right to it and take a look at the campaign?”
“Before you do,” said Mr. Bradley, “it might be good to do a little level-setting. If I were in your position, I’d want to know right off the bat where I stood, so I’m going to be honest with you: I’m only here because of the tremendous respect I have for Janine. She–cover your ears, Janine–is the one who brought the Upkeeper back from the brink–no, Janine, I don’t mind saying it–with her ‘Man the Towers’ campaign. So if she tells me you’ve got a way for us to finally win the hearts and minds of that elusive 18 to 25 year old crowd, then fine, I’ll take a look at it. If she asks me to fly half way across the country to see this mysterious campaign, instead of you coming to present it to us–perverting the natural order of things–all right, I do it. That’s how much respect I have for her. But at heart I’m still an old-school, facts-and-figures type CEO–I believe in sales and smart spends with measurable ROI. I get a little nervous around all this pie-in-the-sky touchy-feely branding talk, and even my tremendous respect for Janine only buys you so much: one pitch, to be exact. And it better be quick, and it had better be killer, because as far as I’m concerned you’re starting out with two strikes against you.”
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