瓜瓜第一次发帖略微有些羞涩 。瓜瓜还有四天一战GMAT，求小分队庇佑。 
主要是三篇文章 creative intelligence的话题，robot recruiter（瓜瓜是HR专业，估计以后会有更多的管理类型的文章噢嘿嘿嘿嘿） ，以及最后一个大数据与商业结合的越障 。 enjoy~~~！！
Article 1 Who Has The Right To Know Where Your Phone Has Been?
[Rephrase 1]
[Dialog, 4:00]
Transcript
http://www.npr.org/templates/transcript/transcript.php?storyId=241415668
Source: NPR
http://www.npr.org/blogs/alltechconsidered/2013/10/29/241415668/who-has-the-right-to-know-where-your-phone-has-been
Part II: speed
Article 2
First There Was IQ. Then EQ. But Does CQ — Creative Intelligence — Matter Most?
In his new book Creative Intelligence, Bruce Nussbaum argues that creativity is an undervalued skill that anyone can cultivate. Not just for artists and musicians, creative intelligence (or CQ) is the secret sauce that separates winners and losers in business too.
[Time 2]
In his new book Creative Intelligence, Bruce Nussbaum argues that creativity is an undervalued skill that anyone can cultivate. Not just for artists and musicians, he argues, creative intelligence — or CQ for short — is what separates the winners and losers of the business world as well. The author, a professor at Parsons The New School for Design in New York, recently spent a few minutes explaining how each of us can go about cultivating our own CQ.
What is creative intelligence?
Taking original ideas and scaling them into the creation of new products and services. I really believe that we are all born with a capacity to be creative, and we get it beat out of us in a lot of the schools that we go to. We have to relearn it, and it’s not that hard.
How can we be more creative?
Creativity is all about making connections and seeing patterns. It’s not a light bulb that goes off in your head. Before that light bulb goes off, lots of things are happening. Lots of ideas. We need time to step back and make connections between those things. We need to stop being hyper connected and deliberately take a moment to be mindful about what we’re doing.
People often associate creativity with solo artists, but you argue that collaboration fosters creativity more often than working alone. How so?
Creativity is social. When you read books about creativity today, the narrative of creativity is that it is a brain function or it’s a genius thing. It is rare and comes out of the individual. But when you look at almost all the innovations that are meaningful in our lives today, like Facebook and Google, they’re all done by two or three people. All the innovators have a buddy.
[311words]
[Time 3]
Yahoo recently announced a controversial ban on working from home on the grounds that being physically together improves speed and quality. Does this argument hold water?
Creativity comes out of small teams of twos and threes and fours and fives and sixes. That’s quite different from having thousands and thousands of people in the same place at the same time. You can also put technology in people’s homes that allows them to communicate with small teams to be social and creative. It’s probably not really required to have everyone in the office, but you do need certain people interacting.
Why don’t old-fashioned brainstorming sessions work for generating new ideas in companies?
When you go to a lot of brainstorming sessions, you have people throwing ideas out that have absolutely no relation to the specific topic at hand. In these kinds of environments, people hold back their best ideas. They’re not going to share it with strangers. It doesn’t work. Instead you need “magic circles,” small teams of people who trust each other, are familiar with each other, and play together. That’s where you get some really great originality that has value.
You cite Groupon as an example of a creative company, thanks to its popular daily deal strategy, but it just fired its CEO amid big losses. What gives?
People were saying, “Give me 50% off, sure.” But whether they go back again and again is something very different. It turned out people didn’t want to do that. Groupon seems to have plateaued at a certain level, and it’s possible that they can’t go beyond that level. It’s still a successfully creative company. It just means that it’s a company that’s not going to grow all that much larger, and its stock price isn’t going to go much higher.
[331 words]
[Time 4]
What is the “economy of creativity” and why do we need to pay more attention to that instead of mere efficiency?
The true source of economic activity is creativity. It’s coming up with new things that give us fat profits. That is more beneficial to shareholders in the long run, generates more jobs, and is better for all of us than an economy based on efficiency. We should go back to the origins of capitalism and accept the fact that creativity is the source of economic value and creativity drives capitalism.
Dell became a top PC maker because of its efficiency. Now it’s struggling. Did putting efficiency first compromise its creativity?
No. The great creative model of Dell was its efficiency. It was brilliant. Just go online and you could create your own computer, made to order. It was wildly successful until it wasn’t. I think it’s failing because it doesn’t allow you to create the products you want to create today. No one wants to create a computer any more.
They don’t realize that their creative model wasn’t about computers. It was about everything. If they allowed us to put together the things we wanted to put together, like an iPhone or another smart phone, it would be wildly successful. They think they are a computer company, and they’re not. They’re a creative assembly company.
What’s the best way to get out of a creative rut?
Find a creative friend to play with either at work or outside work. Read my book. Travel. See something that’s dramatically different and think about it. Disconnect every day for 20 minutes and think about what you’re doing and how you can do it better. Think about your creativity and then go back in.
[317 words]
Source: Time
http://business.time.com/2013/03/05/first-there-was-iq-then-eq-but-does-cq-creative-intelligence-matter-most/#ixzz2j7kxOUFq
Article 3 Robot recruiters How software helps firms hire workers more efficiently
[Time 5]
The problem with human-resource managers is that they are human. They have biases; they make mistakes. But with better tools, they can make better hiring decisions, say advocates of “big data”. Software that crunches piles of information can spot things that may not be apparent to the naked eye. In the case of hiring American workers who toil by the hour, number-crunching has uncovered some surprising correlations.
For instance, people who fill out online job applications using browsers that did not come with the computer (such as Microsoft’s Internet Explorer on a Windows PC) but had to be deliberately installed (like Firefox or Google’s Chrome) perform better and change jobs less often.
It could just be coincidence, but some analysts think that people who bother to install a new browser may be the sort who take the time to reach informed decisions. Such people should be better employees. Evolv, a company that monitors recruitment and workplace data, pored over nearly 3m data points from more than 30,000 employees to find this nugget.
Some 60% of American workers earn hourly wages. Of these, about half change jobs each year. So firms that employ lots of unskilled workers, such as supermarkets and fast-food chains, have to vet heaps—sometimes millions—of applications every year. Making the process more efficient could yield big payoffs.
[230 words]
[Time 6]
Evolve mines mountains of data. If a client operates call centers, for example, Evolv keeps daily tabs on such things as how long each employee takes to answer a customer’s query. It then relates actual performance to traits that were visible during recruitment.
Some insights are counter-intuitive. For instance, firms routinely cull job candidates with a criminal record. Yet the data suggest that for certain jobs there is no correlation with work performance. Indeed, for customer-support calls, people with a criminal background actually perform a bit better. Likewise, many HR departments automatically eliminate candidates who have hopped from job to job. But a recent analysis of 100,000 call-center workers showed that those who had job-hopped in the past were no more likely to quit quickly than those who had not.
Working with Xerox, a maker of printers, Evolv found that one of the best predictors that a customer-service employee will stick with a job is that he lives nearby and can get to work easily. These and other findings helped Xerox cut attrition by a fifth in a pilot programme that has since been extended. It also found that workers who had joined one or two social networks tended to stay in a job for longer. Those who belonged to four or more social networks did not.
There is no point asking job-seekers if they are honest. But surveys can measure honesty indirectly, by asking questions like “How good at computers are you?” and later: “What does control-V do on a word-processing programme?” A study of 20,000 workers showed that more honest people tend to perform better and stay at the job longer. For some reason, however, they make less effective salespeople.
Algorithms and big data are powerful tools. Wisely used, they can help match the right people with the right jobs. But they must be designed and used by humans, so they can go horribly wrong. Peter Cappelli of the University of Pennsylvania’s Wharton School of Business recalls a case where the software rejected every one of many good applicants for a job because the firm in question had specified that they must have held a particular job title—one that existed at no other company.
[376 words]
Source ：Economist
http://www.economist.com/news/business/21575820-how-software-helps-firms-hire-workers-more-efficiently-robot-recruiters
Article 4 Nutonian CEO: Business and Science Face Same Desperate Big-Data Problem
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Is “big data” starting to fade away as a tech-business theme? Hardly.
A couple of Boston-area startups in the field just announced Series A funding rounds this week.Sqrrl, a Cambridge, MA-based company founded by former NSA scientists, raised $5.2 million from Atlas Venture and Matrix Partners. The startup has developed a new kind of secure database and is led by CEO Mark Terenzoni, who joined from F5 Networks early this year.
And today, fellow Cambridge startup Nutoniansays it has raised $4 million led by Atlas Venture to build out its big-data analytics software platform—with the promise of discovering key patterns and relationships in mountains of data and translating them into insights for businesses. (Of course, that’s a Holy Grail—more on that below.
One person these two startups have in common isAtlas partner Chris Lynch, who led both investments. Lynch, the former CEO of Vertica Systems and Acopia Networks, certainly seems to be doing his part to keep Boston in the broader big-data discussion. He’s involved in other local startups, including Hadapt, as well as the workspace hack/reduce near Kendall Square.
Nutonian (pronounced “Newtonian”) is based on some pretty deep science. The company’s founder and CEO, Michael Schmidt, did his PhD at Cornell University in computational methods for data mining in physics and biology. In a 2009 paper inScience, Schmidt and his Cornell adviser, Hod Lipson (also an adviser to Nutonian), showed they could develop an algorithm to derive fundamental laws of physics based only on experimental data; their key advance was automating that centuries-old scientific process.
Leave it to a VC like Lynch to see the business value here. “I offered Michael a term sheet the day I met him,” Lynch says. “He is a superstar.” Boston-area tech luminaries Jit Saxena and Cheng Wu invested with him in the startup, and Lynch bullishly predicts that the three of their business accomplishments, combined, “will be a pebble in the ocean against the value and impact Michael and Nutonian make.”
The idea behind Nutonian is to apply Schmidt’s algorithmic approach not only to science but to fundamental business problems—sales forecasts, manufacturing predictions, stock trading, and so on. The 14-person startup, which Schmidt (pictured) started in 2011, says its technology already has been used by thousands of scientific researchers and by people in the life sciences, oil and gas, retail, and finance industries.
This is one of those plays where the technology itself is key. Nutonian’s software, known as Eureqa, is based on a technique called symbolic regression, which is related to artificial-intelligence methods such as machine learning and genetic programming.I wanted to get a better sense of what makes this company (and founder) tick—and what its real chances of success might be. So here’s a transcript of a Q&A with Schmidt:
Xconomy: This feels like a Holy Grail startup to me—exciting but very challenging. Why is the market timing right?
Michael Schmidt: Nutonian is based on new technology that can detect laws of physics from data. But there are almost no “laws of physics” in most businesses. With the data being collected today we can change that, giving businesses the same advantages that scientists have leveraged for years. Most of today’s sophisticated [business intelligence] tools make “black box” predictions from your data: they can tell you what’s likely to happen, but not why it will happen or how you can avoid or reproduce it in the future. It’s all just correlation without any deeper causal understanding or meaning. Our software, Eureqa, was created to solve that problem, by uncovering and explaining the relationships within big data that drive predictions. The market is ready now because the data storage technology is mature. We can store and access enormous data sources quickly and efficiently. Great companies were started and solved that problem. But, the companies we talk with are spending millions storing that data annually; there’s a desperation to deliver on the promises of big data.
Xconomy : Your target customers seem very broad in terms of industry. How do you focus, and where’s your sweet spot?
MS: We’ve had incredible traction in science and medicine—everything from characterizing the formation of galaxies in the universe, to improving cancer detection. Many researchers have cited our software in their results.We see a broad interest in the industry as well. For example, we’ve seen a major chemical manufacturer scale their production of pharmaceuticals by using Eureqa to pinpoint the limiting factor in their production (e.g., how heating and mixing rates impact yield). We’ve also seen retailers using our technology to anticipate changes in store sales across all their products.Our goal is to be able to serve anyone that needs to predict, control, or understand phenomenon in the data they collect.
Xconomy: Do you see Eureqa mainly as transforming business intelligence, or changing the way we do science, or perhaps morphing into something else that has even greater societal impact?
MS: I want to help the world scale with the amount of data we collect and the things we want to understand. It used to be that a lone scientist could retreat to their chalkboard and come back with a unified theory on how something works. Today we need armies of researchers to make progress.
Fundamentally, I see the problem that scientists face as the same problem facing businesses. There are things that are staggeringly complex to understand. The difference today, and only within the past few years, is that we can now efficiently store and access massive amounts of data and information on them. We will increasingly need to rely on technologies that enable us to detect what’s important and explain the hidden patterns; and that’s where we’re going with Eureqa. [1008 words]
Source： Xconomy
http://www.xconomy.com/boston/2013/10/23/nutonian-ceo-business-science-face-big-data-problem/
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发表于 2013-10-30 22:46:28
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楼主
还不太熟练，什么以后还要多多请教噢
？
