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GOOD with numbers? Fascinated by data? The sound you hear is opportunity knocking.
Mo Zhou was snapped up by I.B.M. last summer, as a freshly minted Yale M.B.A., to join the technology company’s fast-growing ranks of data consultants. They help businesses make sense of an explosion of data — Web traffic and social network comments, as well as software and sensors that monitor shipments, suppliers and customers — to guide decisions, trim costs and lift sales. “I’ve always had a love of numbers,” says Ms. Zhou, whose job as a data analyst suits her skills.
To exploit the data flood, America will need many more like her. A report last year by the McKinsey Global Institute, the research arm of the consulting firm, projected that the United States needs 140,000 to 190,000 more workers with “deep analytical” expertise and 1.5 million more data-literate managers, whether retrained or hired.
The impact of data abundance extends well beyond business. Justin Grimmer, for example, is one of the new breed of political scientists. A 28-year-old assistant professor at Stanford, he combined math with political science in his undergraduate and graduate studies, seeing “an opportunity because the discipline is becoming increasingly data-intensive.” His research involves the computer-automated analysis of blog postings, Congressional speeches and press releases, and news articles, looking for insights into how political ideas spread.
The story is similar in fields as varied as science and sports, advertising and public health — a drift toward data-driven discovery and decision-making. “It’s a revolution,” says Gary King, director of Harvard’s Institute for Quantitative Social Science. “We’re really just getting under way. But the march of quantification, made possible by enormous new sources of data, will sweep through academia, business and government. There is no area that is going to be untouched.”
Welcome to the Age of Big Data. The new megarich of Silicon Valley, first at Google and now Facebook, are masters at harnessing the data of the Web — online searches, posts and messages — with Internet advertising. At the World Economic Forum last month in Davos, Switzerland, Big Data was a marquee topic. A report by the forum, “Big Data, Big Impact,” declared data a new class of economic asset, like currency or gold.
Rick Smolan, creator of the “Day in the Life” photography series, is planning a project later this year, “The Human Face of Big Data,” documenting the collection and uses of data. Mr. Smolan is an enthusiast, saying that Big Data has the potential to be “humanity’s dashboard,” an intelligent tool that can help combat poverty, crime and pollution. Privacy advocates take a dim view, warning that Big Data is Big Brother, in corporate clothing.
What is Big Data? A meme and a marketing term, for sure, but also shorthand for advancing trends in technology that open the door to a new approach to understanding the world and making decisions. There is a lot more data, all the time, growing at 50 percent a year, or more than doubling every two years, estimates IDC, a technology research firm. It’s not just more streams of data, but entirely new ones. For example, there are now countless digital sensors worldwide in industrial equipment, automobiles, electrical meters and shipping crates. They can measure and communicate location, movement, vibration, temperature, humidity, even chemical changes in the air.
Link these communicating sensors to computing intelligence and you see the rise of what is called the Internet of Things or the Industrial Internet. Improved access to information is also fueling the Big Data trend. For example, government data — employment figures and other information — has been steadily migrating onto the Web. In 2009, Washington opened the data doors further by starting Data.gov, a Web site that makes all kinds of government data accessible to the public.
Data is not only becoming more available but also more understandable to computers. Most of the Big Data surge is data in the wild — unruly stuff like words, images and video on the Web and those streams of sensor data. It is called unstructured data and is not typically grist for traditional databases.
When the World Stops, Traveling in John Keats’s ‘Realms of Gold’
But the computer tools for gleaning knowledge and insights from the Internet era’s vast trove of unstructured data are fast gaining ground. At the forefront are the rapidly advancing techniques of artificial intelligence like natural-language processing, pattern recognition and machine learning.
Those artificial-intelligence technologies can be applied in many fields. For example, Google’s search and ad business and its experimental robot cars, which have navigated thousands of miles of California roads, both use a bundle of artificial-intelligence tricks. Both are daunting Big Data challenges, parsing vast quantities of data and making decisions instantaneously.
The wealth of new data, in turn, accelerates advances in computing — a virtuous circle of Big Data. Machine-learning algorithms, for example, learn on data, and the more data, the more the machines learn. Take Siri, the talking, question-answering application in iPhones, which Apple introduced last fall. Its origins go back to a Pentagon research project that was then spun off as a Silicon Valley start-up. Apple bought Siri in 2010, and kept feeding it more data. Now, with people supplying millions of questions, Siri is becoming an increasingly adept personal assistant, offering reminders, weather reports, restaurant suggestions and answers to an expanding universe of questions.
To grasp the potential impact of Big Data, look to the microscope, says Erik Brynjolfsson, an economist at Massachusetts Institute of Technology’s Sloan School of Management. The microscope, invented four centuries ago, allowed people to see and measure things as never before — at the cellular level. It was a revolution in measurement.
Data measurement, Professor Brynjolfsson explains, is the modern equivalent of the microscope. Google searches, Facebook posts and Twitter messages, for example, make it possible to measure behavior and sentiment in fine detail and as it happens.
In business, economics and other fields, Professor Brynjolfsson says, decisions will increasingly be based on data and analysis rather than on experience and intuition. “We can start being a lot more scientific,” he observes.
There is plenty of anecdotal evidence of the payoff from data-first thinking. The best-known is still “Moneyball,” the 2003 book by Michael Lewis, chronicling how the low-budget Oakland A’s massaged data and arcane baseball statistics to spot undervalued players. Heavy data analysis had become standard not only in baseball but also in other sports, including English soccer, well before last year’s movie version of “Moneyball,” starring Brad Pitt.
Retailers, like Walmart and Kohl’s, analyze sales, pricing and economic, demographic and weather data to tailor product selections at particular stores and determine the timing of price markdowns. Shipping companies, like U.P.S., mine data on truck delivery times and traffic patterns to fine-tune routing.
Online dating services, like Match.com, constantly sift through their Web listings of personal characteristics, reactions and communications to improve the algorithms for matching men and women on dates. Police departments across the country, led by New York’s, use computerized mapping and analysis of variables like historical arrest patterns, paydays, sporting events, rainfall and holidays to try to predict likely crime “hot spots” and deploy officers there in advance.
Research by Professor Brynjolfsson and two other colleagues, published last year, suggests that data-guided management is spreading across corporate America and starting to pay off. They studied 179 large companies and found that those adopting “data-driven decision making” achieved productivity gains that were 5 percent to 6 percent higher than other factors could explain.
The predictive power of Big Data is being explored — and shows promise — in fields like public health, economic development and economic forecasting. Researchers have found a spike in Google search requests for terms like “flu symptoms” and “flu treatments” a couple of weeks before there is an increase in flu patients coming to hospital emergency rooms in a region (and emergency room reports usually lag behind visits by two weeks or so).
Global Pulse, a new initiative by the United Nations, wants to leverage Big Data for global development. The group will conduct so-called sentiment analysis of messages in social networks and text messages — using natural-language deciphering software — to help predict job losses, spending reductions or disease outbreaks in a given region. The goal is to use digital early-warning signals to guide assistance programs in advance to, for example, prevent a region from slipping back into poverty.
In economic forecasting, research has shown that trends in increasing or decreasing volumes of housing-related search queries in Google are a more accurate predictor of house sales in the next quarter than the forecasts of real estate economists. The Federal Reserve, among others, has taken notice. In July, the National Bureau of Economic Research is holding a workshop on “Opportunities in Big Data” and its implications for the economics profession.
Big Data is already transforming the study of how social networks function. In the 1960s, Stanley Milgram of Harvard used packages as his research medium in a famous experiment in social connections. He sent packages to volunteers in the Midwest, instructing them to get the packages to strangers in Boston, but not directly; participants could mail a package only to someone they knew. The average number of times a package changed hands was remarkably few, about six. It was a classic demonstration of the “small-world phenomenon,” captured in the popular phrase “six degrees of separation.”
Today, social-network research involves mining huge digital data sets of collective behavior online. Among the findings: people whom you know but don’t communicate with often — “weak ties,” in sociology — are the best sources of tips about job openings. They travel in slightly different social worlds than close friends, so they see opportunities you and your best friends do not.
Researchers can see patterns of influence and peaks in communication on a subject — by following trending hashtags on Twitter, for example. The online fishbowl is a window into the real-time behavior of huge numbers of people. “I look for hot spots in the data, an outbreak of activity that I need to understand,” says Jon Kleinberg, a professor at Cornell. “It’s something you can only do with Big Data.”
Big Data has its perils, to be sure. With huge data sets and fine-grained measurement, statisticians and computer scientists note, there is increased risk of “false discoveries.” The trouble with seeking a meaningful needle in massive haystacks of data, says Trevor Hastie, a statistics professor at Stanford, is that “many bits of straw look like needles.”
Big Data also supplies more raw material for statistical shenanigans and biased fact-finding excursions. It offers a high-tech twist on an old trick: I know the facts, now let’s find ’em. That is, says Rebecca Goldin, a mathematician at George Mason University, “one of the most pernicious uses of data.”
Data is tamed and understood using computer and mathematical models. These models, like metaphors in literature, are explanatory simplifications. They are useful for understanding, but they have their limits. A model might spot a correlation and draw a statistical inference that is unfair or discriminatory, based on online searches, affecting the products, bank loans and health insurance a person is offered, privacy advocates warn.
Despite the caveats, there seems to be no turning back. Data is in the driver’s seat. It’s there, it’s useful and it’s valuable, even hip.
Veteran data analysts tell of friends who were long bored by discussions of their work but now are suddenly curious. “Moneyball” helped, they say, but things have gone way beyond that. “The culture has changed,” says Andrew Gelman, a statistician and political scientist at Columbia University. “There is this idea that numbers and statistics are interesting and fun. It’s cool now.”[Source]-https://www.nytimes.com/2012/02/12/sunday-review/big-datas-impact-in-the-world.html
Asterix Solution’s big data course
is designed to help applications scale up from single servers to thousands of machines. With the rate at which memory cost decreased the processing speed of data never increased and hence loading the large set of data is still a big headache and here comes Hadoop as the solution for it.
[The Results are in! The Winner is....]()
|Category ||Winner ||Reasoning |
|Popularity ||Sunset Company ||5 -1, in Sunset Company's favor! |
|Jojolity ||Sunset Company ||25 - 19 in Sunset Company's favor! Jojolity denial was the name of the game here. |
|Quality ||Diamond Dogs ||25 - 19 in the Diamond Dogs' favor! |
Turk: Hello Pepe. How are things looking where you are?
Pepe: Perfectly fine, why do you ask?
Turk: Well I wanted a little recap on our situation. One of our operatives, Lone, decided to go after The Overload.
Pepe: So? It isn't necessary to reach us.
Turk: It could be a problem if it fell into wrong hands. I count Lone as one of those wrong hands. He's proven himself a liability. I need to know if we can safely get rid of him.
Pepe: Well strictly speaking we don't need anybody. Your assistant is not even aware of our existence, Blin and his cronies can always make more pillars and defenses, but that is just insurance by now. We don't need his money. I think we are only keeping tabs on Line in case he remembers something and becomes a problem then, Lite is useful but ultimately unnecessary.
Pepe: And Lone is the least useful of everyone. The area is already destabilized. We do not need him any more.
Turk: Thank you, Pepe.
Pepe: Strictly speaking, even I'm too much. Your influence is all the organization really needs.
Turk: That's an exaggeration. So then hopefully Lone does not come back. We hardly need another Murray. I've cut him off so far but….
Turk: You understand.
Pepe: Yes, I understand. And do not worry, I will keep a close eye on the situation here. Best wishes! Felix Dawn
sighed as he reached the small village in the valley. It had been quite an unusual journey to get there. Dr. Feelgood had sent him to China on some intel that an artifact called the Overload could be found in the valley. About as soon as he’d landed in Beijing, Felix was accosted by another Stand user named James Burton
, who demanded to know if Felix had seen a California Redwood anywhere, claiming that the tree had crippled Burton’s friend. Somehow.
As it turned out, Burton had also been sent after the Overload based on intel gathered by Huey Lewis and was conducting his own personal investigation on the side. The two shared an interest in archery and decided to work together to find the Overload. Burton seemed like a pretty decent guy to Felix, though it felt odd to always be referred to as “Best Felix” by his partner. Still, it was better than “Other Felix”, which was what Burton had called him at first. As the two trekked toward the Kyrgyzstan border, they heard enough rumors and clues to point them in an increasingly specific direction. They also became a pretty ironclad team, fully prepared to take on whatever enemy Stand users they encountered.
When they finally reached the village, they even knew that the Overload was a knife and which specific house it was supposed to be in. And of course, the ancient shack was empty. Burton was turning the whole place upside down trying to find the knife when a gravelly Texan drawl stopped them.
“Sorry, losers, but y’all’re a little late.”
Felix and Burton spun around to see a large man wearing a UT Varsity Jacket and, for some reason, a cat mask. He was also holding an ancient Chinese dagger: The Overload.
“The name’s Lone, but you can call me… Lone. Anything else and I kill ya. Though I’m probably gonna kill ya anyway.”
“Hey, Tex,” came a second voice, this one more dignified, and with Australian accent. “Earth to Austin Texas. You got the knife or what, mate?”
“This isn’t Texas, dumbass,” Burton said in response to Lone’s unseen partner.
“I know, mate. Austin Texas is just his name,” said the Australian, stepping into view. He was quite a bit shorter than Lone and dressed in a tuxedo modified with numerous pouches, a Civil War rifle slung over his back. “Speaking of, might as well add, I’m Cliff. Cliff Currenti.”
“See, when that asshole Line sent me after this thing, I bet he planned on it being a suicide mission, but I brought company,” Lone continued, clearly agitated that Cliff had given away his real name.
“Can’t say I blame this Line guy,” Cliff muttered. “I’m gonna have to hold so many balls when I get out of this.”
Felix was pretty confused about what these two were talking about, but the situation reminded him of Null’s story about what had happened to him at the Colosseum. He had a feeling this would be a little harder.
“You must be one of those ‘Golds’ that Chance has been raving about ever since the baseball game,” Burton said. “I’mma deck you in the schnoz.”
Lone looked taken aback by that for a moment, then regained his composure. “Do you dumbasses even know what the Overload does?” Lone asked. “When it pierces you, it boosts your Stand threefold in every way. Fuckin’ morons.”
Overhead, rain clouds began to form.
“C’mon, Best Felix. We can still take ‘em. Two on two!” Burton said.
,” came a third voice, this one with a Spanish accent, coming from somewhere outside. “More like, dos en tres. Is a bad fate for you.”
“Figured I wouldn’t take any chances in case someone else got to the Overload first,” Lone said. “Turns out, I didn’t need it. I’m going to have fun
killing you two.”
Felix shared a look with Burton, glad to have the other archer’s help. The two summoned their Stands and readied for battle. As Lone drove the Overload into his own forearm, Felix wondered why he kept needing to deal with knife theft.
“Ow! Shit! Ugh, hurts like a bitch. [Lone Digger], you idiots, kill them!”
A little blood trickled out of Lone’s forearm. A pink tube, his Stand, slithered out from the wound and dove underground. Lone shot the duo a menacing glare. Suddenly a massive wall of earth shot out of the ground, reaching towards the heavens. Felix turned around, only to see another wall rumbling up. Everyone, even the others Lone brought, looked shocked at this display of power.
Lone stood up. “My Stand is normally pretty weak. It can only move things like a foot. But you fuckos done screwed yourself. [The Overload gets rid of my weakness.”
He turned to his allies. “Well what am I paying you for? Kill them already!”
Remain in Light #3: [The Overload]
Appearance: An ancient dagger of Chinese make.
Power: None (Though it is sharp enough to pierce human skin)
Ability: [The Overload], when stabbed into a Stand user, will triple all of the Stand’s stats, and will boost their ability a ridiculous amount. However, this only works for a minute, and after which, [The Overload] will never work for that person again.
Name: Austin Texas (Lone)
Appearance: Lone wears a generic Varsity Jacket open over a white T Shirt and blue jeans. He is relatively small. He wears a cat mask on at all times, so his actual facial features are unknown.
Bio: From the moment he was born, Austin Texas was given every reason to hate the world. His parents were cocaine addicts who thought it would be funny to name their child after the city in which he lived. While they were at it, they alternatively neglected or abused him. So, when he first learned what murder was, he figured he’d try it out on them, but wasn’t really sure how.
Luckily for him, around this time, his Stand [Lone Digger] was awoken. In exploring his newfound powers, Austin killed two birds with one stone, using his Stand to kill his parents. Its ability ripped their hearts right out of their chests. Arguably, this killed three
birds with one stone, as it gave the child an inspiration for his new codename to replace the atrocious “Austin Texas”: Lone.
Personality: Lone is a thug. He's a murderer who doesn't care about human life, and is willing to sell anyone else out for his own gain. He's been covering the role of general murderer in the team, and has been pretty happy with being low level in the group.
He doesn't especially mind if his allies die and will probably try and kill them afterwards to save money.
Intimidation: 1 (Lone does not command any fear or respect from anyone.)
Stand Name: [Lone Digger]
Stand Appearance: [Lone Digger] takes the appearance of a glowing neon pink tube, capped at both ends with silver metal. It is about 1m long and 5cm in diameter.
Power: E (It can't attack nor escape if it is caught)
Speed: D (Lone Digger is not fast, especially while tunneling.It's about 5 mph when tunneling and 10 mph when not.
Durability: A (It can be caught but is essentially unbreakable.)
Precision: D (Lone can control his Stand, but it is much easier to use the ability on large objects
Ability: First of all, [Lone Digger] has the ability to tunnel through anything the metal caps touch, leaving it unharmed. It cannot do any damage whatsoever, and pulling it out by force with not do harm either.
Second of all, it can move anything that both of the metal caps touch by up to 1 foot. This ability is better on large objects, as they are easier to touch with its low Precision. Objects up to tectonic plates can be manipulated, albeit slowly and only 1 foot at a time. However, smaller objects require planning and careful use of the Stand’s tunneling abilities to touch with both caps.
Name: Miguel Marcado
Appearance: A small man wearing slightly rumpled clothing, with black hair and a somewhat equine face.
Personality: Miguel is a very simple man. He likes money, likes his life much more, and wants both of them. He prefers staying back, as his Stand is not a combat based one at all.
Running Away: 5
Stand Name: [Wheel in the Sky]
Stand Appearance: Clouds, which can be anything from stormy black to fluffy white in color and shape.
Power: E (The clouds have no offense whatsoever. All they can do is rain.)
Speed: E (This Stand is very slow.)
Range: A ([Wheel in the Sky] can go up to 50 miles away from its user.)
Durability: A (It’s far in the air, and cannot really be attacked at all.)
Precision: E (This Stand can only really do one thing, and the user cannot control the predictions from it.)
Ability: [Wheel in the Sky] can rain. This can either be an isolated sprinkle or raging monsoon. This rain is real, but will go back to the Stand as it evaporates. There’s a large amount of rain stored, so the user doesn’t need to worry about that. It could feasibly rain constantly on a city for a matter of weeks.
Whenever it rains, the user of [Wheel in the Sky] hears a piece of advice to avoid some misfortune that will happen to them in the future. They can choose to avoid this misfortune, but at the cost of it being "passed" onto someone else. They can only hear one prediction every minute, and only if there is something in the next hour that affects the user negatively.
Name: Cliff Currenti
Occupation: Mercenary, Ballroom Dancer
Bio: The youngest of three brothers, all Stand users, Cliff always felt left out. He was a late bloomer and developed his Stand later in life than his brothers, and his Stand was also unlike the others in his family, though probably the strongest of the three. Cliff developed a passion for ballroom dancing, and, through that, discovered a secondary ability of his Stand. When he went off to college, he cut ties with his family in order to start work as a mercenary, using his Stand to make money for various illegal deeds. While he never charged a high price, it was enough to make a living. These days, he spends about as much time organizing fancy dance parties as carrying out jobs, using his hard-earned money and his Stand’s ability to throw the biggest balls around.
Personality: Cliff is someone who believes that someone should do as much good in the world as they do evil, which has led him to throw his charity balls alongside performing his dirty deeds. On a job, he is analytical and quick to understand a situation. He doesn’t especially like hurting people, though he never shies away from a job. He’s also a fan of puns and wordplay, leading him to quickly be able to come up with anything that can be considered a ball.
Physical Description: A small man, Cliff is stronger than he looks. Even on a job, he’s dressed for a ballroom dance, with his various pouches, belts, and packs of gear over it.
Equipment: Springfield Rifle Model 1861 and 20 Minié Balls
, a baseball
, a rubber bouncy ball
, 30 ball
bearings, a ball
of twine, two steel balls
, and a miniaturized bowling ball
Throwing Balls (This applies to both actual balls and fancy dancing balls): 4
Stand Name: 「Big Balls」
Appearance: 「Big Balls」takes the appearance of a smooth faceless punchghost clad in fancy attire.
Ability: It has the ability to completely control the size of anything called a ball. With two exceptions, the power functions to increase or decrease the mass and/or volume of a ball within its range, so long as the Stand has touched the ball since the ball entered its range. The Stand does not need to be touching the ball at the time the ball’s size is being affected. 「Big Balls」 can control the rate at which the balls change their size and the user often chooses to do so at a rate where the mass and volume increase or decrease at rates such that density remains constant. The two ways the Stand affects balls that are exceptions to its typical functionality are this: 「Big Balls」 can metaphorically grow the user's "balls", increasing the user's confidence, charisma, and combat skill at the cost of making the user less careful and intelligent. 「Big Balls」 can also increase the "size" of a fancy dance party, essentially affecting the energy and enthusiasm of the participants so long as they are within the ballroom.
Range: B (About 50m of range total.)
Potential: B Objective:
Defeat the enemy. For the purposes of this match, you really only need to defeat Austin and one other person. Once you do that, the other will bolt. Location:
A valley on the border of Kyrgyzstan and China, with the remains of a village in it. There are large walls on both sides, blocking everyone in. Lone is about 3m away from the contestants, and he has about 20 seconds left that The Overload will work. The user of Wheel in the Sky is near some walls about 10m behind the contestants. An extra note about how his abilities work is that the nearest person to him will have the fate he was about to have passed over. Cliff is ahead of the group about 10m in the other direction. The slopes of the surrounding mountains are arid, and excessive rain will cause mudslides. None of the bosses will go especially out of their way for eachother.
Jojolity points will be awarded for style and feasibility of its execution, independently of the plausibility of winning the fight.
|Team ||Combatant ||JoJolity |
|Players ||Both ||"You're really good at sobbing J.Geil. Well, you're about to fall down to hell, sobbing the whole way down. But there's one thing I can't really on the guardians of hell to do for me. And that's... To turn you into a pincushion!": RETIRE another combatant using [The Overload], and do not purposefully stab yourself with it. |
|Boss ||Lone ||"I am a god in all but name! With the powers at my command, I will rule this world!": Let nobody else get their hands on The Overload! |
|Boss ||Cliff and Miguel ||"American style. French style. Japanese style. Italian. Specifically Naples style. The world's fingers for fuck off.": Get Lone RETIRED during the fight! Seriously, screw that guy! |
|Reddit Name ||User Name ||Stand Name ||Team ||Status |
|u/Zanegaru ||Junky Luck ||Robot Parade ||Sunset Company ||Active |
|u/pm_ur_veggie_garden ||Diamond Boy ||Dirty Dancer ||Sunset Company ||Active |
|u/Mightymindsoup ||Elliot J ||Love Bites ||Sunset Company ||Active |
|u/johntindlemen ||Adriano Donati ||Clearest Blue ||Sunset Company ||Active |
|u/boredCommentator ||Duvelleroy ||Great King Rat ||Sunset Company ||Active…? |
|u/jem_rye ||Albrecht Durer ||Just Push Play ||Sunset Company ||RETIRED |
|u/Shark_Steel ||Duke Rhayader ||What is Love ||Sunset Company ||RETIRED |
|u/Strange_Bean ||Dana Davis ||Stay ||Sunset Company ||RETIRED |
|u/Gallerian ||Jitterbug ||Amun-Ra ||Sunset Company ||Active |
|u/phinsa123 ||Jack Mercury || Mötley Crüe ||Temperance Machine ||Active (2 KOs) |
|u/Unknowni123 ||Stefania Sandu ||Rich Girl ||Temperance Machine ||RETIRED |
|u/YoloSwagginsV12 ||Nicola Henderson ||Exmilitary ||Temperance Machine ||Active |
|u/Otha_Joestar ||Savage Garden ||Jungle Love! ||Temperance Machine ||Active (2 KOs) |
|u/Bentonic64 ||James Creech ||Northern Hues ||Temperance Machine ||RETIRED |
|u/Nivrap ||Dionne ||Stained Glass Heart ||Temperance Machine ||RETIRED |
|u/Quickdrawnmoron ||Dr. Alice Slash ||Mississippi Queen ||Temperance Machine ||Active (1 KO) |
|u/bauccgia0 ||Rip Van Winkle ||Self Called Nowhere ||Temperance Machine ||RETIRED |
|u/KiwiArms ||David "2D" Delasoul ||Feel Good Ink ||Right Now, Forever ||RETIRED |
|u/SweaterSnake ||Spandau Ballet ||Paint Box ||Right Now, Forever ||Active |
|u/Toedpens ||Seth Turmur ||Heart of the Sunrise ||Right Now, Forever ||RETIRED |
|u/Dead_Star_World ||Cassandra Johnson ||Getaway ||Right Now, Forever ||RETIRED |
|u/farispie ||Nermin Reeds ||Spooky Skeleton ||Right Now, Forever ||RETIRED |
|u/PerPapple ||Christina “Chris” Carlisle ||Shadow on the Wall ||Right Now, Forever ||Active |
|u/Skelly-Tan ||Marco Forneira ||Man Eater ||Right Now, Forever ||RETIRED |
|u/WoobidyWoo ||Stefan C. Megiddo ||Switch - 625 ||Right Now, Forever ||Active |
|u/Leafsw0rd ||Rooftop Singer ||Wintergatan ||(Cannot Decide on a Name) ||RETIRED |
|u/TheMysteriousDoc ||Sigmund “Ziggy” Tremaine ||Demon Days ||(Cannot Decide on a Name) ||Active (3 KOs) |
|u/HeavenAscensionTaric ||Erick "Rick Max" Maximilian ||Withered Delilah ||(Cannot Decide on a Name) ||Active |
|u/NowWithPulp ||James Chance ||Electric Avenue ||(Cannot Decide on a Name) ||Active (2 KOs) |
|u/Slaycube ||James Burton ||Of Wolf and Man ||(Cannot Decide on a Name) ||Active (2 KOs) |
|u/Addem_Up ||Huey Lewis ||Change of Heart ||(Cannot Decide on a Name) ||Active (2 KOs) |
|u/Sh0tgunLlama ||Felix “Fat Rat” Arrowsmith ||Set in Stone ||(Cannot Decide on a Name) ||Active |
|u/ChocolateDiscloud ||Bill Dolby ||It’s Raining Men ||(Cannot Decide on a Name) ||RETIRED |
|u/CPU_Dragon ||DJ ||Rasputin ||(Cannot Decide on a Name) ||Active (1 KO) |
|u/rederister ||Michael Sembello ||Automatic Man ||Diamond Dogs ||Active |
|u/Repider ||Jason “Gray Jay” Jukes ||Hush ||Diamond Dogs ||Active |
|u/Calumba ||Dr. Francesca Marvel ||Ting Tings ||Diamond Dogs ||RETIRED |
|u/anxientdesu ||Airis Ani ||Musical Star ||Diamond Dogs ||Active…? |
|u/JinxTheFrosslass ||Farewell Angelina ||Chains of Love ||Diamond Dogs ||Active |
|u/yelualstar ||Kenneth “Ken” Masters ||Leather Rebel ||Diamond Dogs ||RETIRED |
|u/Ongsay ||Moseph Sabat ||Digital Lover ||Diamond Dogs ||Active |
|u/SilverJakler ||Leonard Davis ||Ace of Spades ||Diamond Dogs ||Active |
|u/KantuK ||Kewlin Cuidad ||Smooth Criminal ||Loca's Motions ||RETIRED |
|u/VforVanarchy ||Presto ||Fly By Night ||Loca's Motions ||Active (3 KOs) |
|u/spyguy318 ||Dr. Nick Mason ||Dark Side of the Moon ||Loca's Motions ||RETIRED |
|u/Ronandstone ||Cole Pineburg ||Slim Shady ||Loca's Motions ||Active (2 KOs) |
|u/Drebin996 ||Kate Smith ||Cibo Matto ||Loca's Motions ||Active |
|u/Tesla__Coil ||Cassandra Corazon ||Through the Fire and Flames ||Loca's Motions ||Active (2 KOs) |
|u/ArtisanBubblegum ||Steve Genoard ||Dance Comander ||Loca's Motions ||Active (2 KOs) |
|u/SP-Q-R ||Viviana “Vivi” Bianchi ||Noisy Pink Bubbles ||Loca's Motions ||Active |
|u/yelualstar ||Steppen ||Born to be Wild ||Loca’s Motions ||Active |
|u/Ismat_Urbur ||Pascal “Paz” Chaleur ||Canned Heat ||White Stripes ||Active |
|u/SmashPachi ||Evan Lain ||Count on Me ||White Stripes ||RETIRED |
|u/StonedVolus ||David L. Palmer ||Harder, Better, Faster, Stronger ||White Stripes ||Active |
|u/Screedledude ||Harvey Harold Hillhouse ||Flatlands ||White Stripes ||Active |
|u/kljg ||Kenny Nixon ||Grease Lightning ||White Stripes ||RETIRED |
|u/JMBChaos ||Niban Shosha ||Ocean Man ||White Stripes ||Active |
|u/tryburningundam ||Elio Valez ||Danger! High Voltage ||White Stripes ||Active |
|u/NatsuruSpringfield ||Natsuru Springfield ||Evil Woman ||White Stripes ||Active |
|u/CptDouglasJFalcon ||”Waveshaper” ||Wisdom of Rage ||White Stripes ||Active |
|u/webdiings ||Null(Neal) ||Fly Me To the Moon ||The F.L.E.A.s ||RETIRED |
|u/vyhox ||Gami ||Haru Haru ||The F.L.E.A.s ||RETIRED |
|u/Spade4103 ||Don Under ||Hot Space ||The F.L.E.A.s ||Active |
|u/WayofAlexGaming ||Nicholas Al-Bach ||Camera Shy ||The F.L.E.A.s ||Active |
|u/Sullivanity333 ||Dr. Floyd Feelgood ||Moving Pictures ||The F.L.E.A.s ||Active (2 KOs) |
|u/Mosses76 ||Felix Down ||Learn to Fly ||The F.L.E.A.s ||Active (2 KOs) |
|u/FastLikeLightning ||Famoso Pietraduro ||Wayward Son ||The F.L.E.A.s ||Active (2 KOs) |
|u/TornkeS ||Donatello Blackwell ||I Am ||The F.L.E.A.s ||Active (2 KOs) |
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