by another hand. Sighing, Bloch said, “Come in!” The door opened, and standing there was Lincoln Shepard, breathless, with Karen O’Neal standing behind him.
“Boss,” he said, still at the door. “I think I got something.”
“You mean we got something,” said Karen O’Neal, elbowing her way into the office. O’Neal was their resident data analyst. Petite, lean, and half-Vietnamese, she’d been one of the wunderkinder of Wall Street quants—that is, quantitative analysts, people who did in-depth financial data analysis and came up with complex schemes to make a killing in the markets. O’Neal had been a little too creative and outside the box, though she would still insist that it was all perfectly legal. However, the SEC had disagreed. Bloch had offered her a deal similar to the one that she had offered Shepard. O’Neal had been a little more reluctant than Shepard, but it hadn’t taken long for her to come around.
“Anyway, it’s this program I’m perfecting,” said Shepard. “Based on Karen’s financial analysis.”
“He’s more like a scribe, really,” said O’Neal. “For my brilliant ideas.”
“I don’t care who’s the genius behind this,” Bloch said impatiently. “Just tell me what you found!”
“Well, you see,” O’Neal began excitedly, looking at Shepard then back at Bloch, “everything’s being tracked these days. Well, not everything , we’re actually quite far from the theoretical limit to how much data we can gather—” She picked up either on Bloch’s impatient stare or on Shepard’s elbowing. “Anyway, we have all this information available to us. Just terabytes of raw data. I’m talking tons . Everything from economic indicators to website page views to changes in weather. But data, by itself, doesn’t get you anywhere. It’s just a bunch of numbers on a page.”
“And that’s where—” began Shepard.
“Shut up and let me finish,” said O’Neal. “So we have all this data, but what do we do with it? Well, that’s where quantitative analysis comes in. Me. So, analyzing information—it’s all about finding connections, right? Specifically, those connections that no one has seen before. Those that no one has ever imagined even existed. Like how once someone thought to look at all the satellite pictures of cows, they found out that they all face either north or south when they eat. Or when they looked the length of a man’s index finger and found out that it has a connection to how aggressive he is. That kind of stuff. But the problem with that is that you have to imagine the connection before you test for it.” She was speaking so fast she was nearly panting by this point.
“Unless . . .” said Shepard, prompting O’Neal.
Bloch raised an eyebrow impatiently. “Unless?” “Unless you can have some massively parallel computer program doing it for you,” said O’Neal. “One with no preconceptions about what should correlate with what, and who can literally just look at everything item by item. And that ,” she said, moving just slightly aside and motioning to Shepard, “is where Linc comes in.”
“Excuse me,” he said, as he took over her computer and brought up a simple interface that showed a blank graph. “I came up with this baby over the past couple of weeks. It’s been running on our servers, engaging every little bit of processing power that wasn’t being used. And it’s been sorting through data, looking for things that correlated with the attacks.”
“What kinds of things?” asked Bloch.
“Literally everything we had,” said O’Neal.
“Isn’t that senseless?” said Bloch. “What use is a correlation between the attacks and, say, the weather?”
“That’s the beauty of it,” said O’Neal. “Even if you have no idea what the causal connection is— it doesn’t matter . Not as long as it makes good predictions.”
Bloch looked skeptical.
“It’s a new age, Bloch,” she continued. “Data is
“Boss,” he said, still at the door. “I think I got something.”
“You mean we got something,” said Karen O’Neal, elbowing her way into the office. O’Neal was their resident data analyst. Petite, lean, and half-Vietnamese, she’d been one of the wunderkinder of Wall Street quants—that is, quantitative analysts, people who did in-depth financial data analysis and came up with complex schemes to make a killing in the markets. O’Neal had been a little too creative and outside the box, though she would still insist that it was all perfectly legal. However, the SEC had disagreed. Bloch had offered her a deal similar to the one that she had offered Shepard. O’Neal had been a little more reluctant than Shepard, but it hadn’t taken long for her to come around.
“Anyway, it’s this program I’m perfecting,” said Shepard. “Based on Karen’s financial analysis.”
“He’s more like a scribe, really,” said O’Neal. “For my brilliant ideas.”
“I don’t care who’s the genius behind this,” Bloch said impatiently. “Just tell me what you found!”
“Well, you see,” O’Neal began excitedly, looking at Shepard then back at Bloch, “everything’s being tracked these days. Well, not everything , we’re actually quite far from the theoretical limit to how much data we can gather—” She picked up either on Bloch’s impatient stare or on Shepard’s elbowing. “Anyway, we have all this information available to us. Just terabytes of raw data. I’m talking tons . Everything from economic indicators to website page views to changes in weather. But data, by itself, doesn’t get you anywhere. It’s just a bunch of numbers on a page.”
“And that’s where—” began Shepard.
“Shut up and let me finish,” said O’Neal. “So we have all this data, but what do we do with it? Well, that’s where quantitative analysis comes in. Me. So, analyzing information—it’s all about finding connections, right? Specifically, those connections that no one has seen before. Those that no one has ever imagined even existed. Like how once someone thought to look at all the satellite pictures of cows, they found out that they all face either north or south when they eat. Or when they looked the length of a man’s index finger and found out that it has a connection to how aggressive he is. That kind of stuff. But the problem with that is that you have to imagine the connection before you test for it.” She was speaking so fast she was nearly panting by this point.
“Unless . . .” said Shepard, prompting O’Neal.
Bloch raised an eyebrow impatiently. “Unless?” “Unless you can have some massively parallel computer program doing it for you,” said O’Neal. “One with no preconceptions about what should correlate with what, and who can literally just look at everything item by item. And that ,” she said, moving just slightly aside and motioning to Shepard, “is where Linc comes in.”
“Excuse me,” he said, as he took over her computer and brought up a simple interface that showed a blank graph. “I came up with this baby over the past couple of weeks. It’s been running on our servers, engaging every little bit of processing power that wasn’t being used. And it’s been sorting through data, looking for things that correlated with the attacks.”
“What kinds of things?” asked Bloch.
“Literally everything we had,” said O’Neal.
“Isn’t that senseless?” said Bloch. “What use is a correlation between the attacks and, say, the weather?”
“That’s the beauty of it,” said O’Neal. “Even if you have no idea what the causal connection is— it doesn’t matter . Not as long as it makes good predictions.”
Bloch looked skeptical.
“It’s a new age, Bloch,” she continued. “Data is
Similar Books
