Solve These Tough Data Problems and Watch Job Offers Roll In

Late in 2015, Gilberto Titericz, an electrical engineer at Brazil’s state oil company Petrobras, told his boss he planned to resign, after seven years maintaining sensors and other hardware in oil plants. By devoting hundreds of hours of leisure time to the obscure world of competitive data analysis, Titericz had recently become the world’s top-ranked data scientist, by one reckoning. Silicon Valley was calling. “Only when I wanted to quit did they realize they had the number-one data scientist,” he says.

Petrobras held on to its champ for a time by moving Titericz into a position that used his data skills. But since topping the rankings that October he’d received a stream of emails from recruiters around the globe, including representatives of Tesla and Google. This past February, another well-known tech company hired him, and moved his family to the Bay Area this summer. Titericz described his unlikely journey recently over colorful plates of Nigerian food at the headquarters of his new employer, Airbnb.

Titericz earned, and holds, his number-one rank on a website called Kaggle that has turned data analysis into a kind of sport, and transformed the lives of some competitors. Companies, government agencies, and researchers post datasets on the platform and invite Kaggle’s more than one million members to discern patterns and solve problems. Winners get glory, points toward Kaggle’s rankings of its top 66,000 data scientists, and sometimes cash prizes.

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Alone and in small teams with fellow Kagglers, Titericz estimates he has won around $ 100,000 in contests that included predicting seizures from brainwaves for the National Institutes of Health, the price of metal tubes for Caterpillar, and rental property values for Deloitte. The TSA and real-estate site Zillow are each running competitions offering prize money in excess of $ 1 million.

Veteran Kagglers say the opportunities that flow from a good ranking are generally more bankable than the prizes. Participants say they learn new data-analysis and machine-learning skills. Plus, the best performers like the 95 “grandmasters” that top Kaggle’s rankings are highly sought talents in an occupation crucial to today’s data-centric economy. Glassdoor has declared data scientist the best job in America for the past two years, based on the thousands of vacancies, good salaries, and high job satisfaction. Companies large and small recruit from Kaggle’s fertile field of problem solvers.

In March, Google came calling and acquired Kaggle itself. It has been integrated into the company’s cloud-computing division, and begun to emphasize features that let people and companies share and test data and code outside of competitions, too. Google hopes other companies will come to Kaggle for the people, code, and data they need for new projects involving machine learning—and run them in Google’s cloud.

Kaggle grandmasters say they’re driven as much by a compulsion to learn as to win. The best take extreme lengths to do both. Marios Michailidis, a previous number one now ranked third, got the data-science bug after hearing a talk on entrepreneurship from a man who got rich analyzing trends in horseraces. To Michailidis, the money was not the most interesting part. “This ability to explore and predict the future seemed like a superpower to me,” he says. Michailidis taught himself to code, joined Kaggle, and before long was spending what he estimates was 60 hours a week on contests—in addition to a day job. “It was very enjoyable because I was learning a lot,” he says.

Michailidis has since cut back to roughly 30 hours a week, in part due to the toll on his body. Titericz says his own push to top the Kaggle rankings, made not long after the birth of his second daughter, caused some friction with his wife. “She’d get mad with me every time I touched the computer,” he says.

Entrepreneur SriSatish Ambati has made Kagglers a core strategy of his startup, H2O, which makes data-science tools for customers including eBay and Capital One. Ambati hired Michailidis and three other grandmasters after he noticed a surge in downloads when H2O’s software was used to win a Kaggle contest. Victors typically share their methods in the site’s busy forums to help others improve their technique.

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H2O’s data celebrities work on the company’s products, providing both expertise and a marketing boost akin to a sports star endorsing a sneaker. “When we send a grandmaster to a customer call their entire data-science team wants to be there,” Ambati says. “Steve Jobs had a gut feel for products; grandmasters have that for data.” Jeremy Achin, cofounder of startup DataRobot, which competes with H2O and also has hired grandmasters, says high Kaggle rankings also help weed out poseurs trying to exploit the data-skills shortage. “There are many people calling themselves data scientists who are not capable of delivering actual work,” he says.

Competition between people like Ambati and Achin helps make it lucrative to earn the rank of grandmaster. Michailidis, who works for Mountain View, California-based H2O from his home in London, says his salary has tripled in three years. Before joining H2O, he worked for customer analytics company Dunnhumby, a subsidiary of supermarket Tesco.

Large companies like Kaggle champs, too. An Intel job ad posted this month seeking a machine-learning researcher lists experience winning Kaggle contests as a requirement. Yelp and Facebook have run Kaggle contests that dangle a chance to interview for a job as a prize for a good finish. The winner of Facebook’s most recent contest last summer was Tom Van de Wiele, an engineer for Eastman Chemical in Ghent, Belgium, who was seeking a career change. Six months later, he started a job at Alphabet’s artificial-intelligence research group DeepMind.

H2O is trying to bottle some of the lightning that sparks from Kaggle grandmasters. Select customers are testing a service called Driverless AI that automates some of a data scientist’s work, probing a dataset and developing models to predict trends. More than 6,000 companies and people are on the waitlist to try Driverless. Ambati says that reflects the demand for data-science skills, as information piles up faster than companies can analyze it. But no one at H2O expects Driverless to challenge Titericz or other Kaggle leaders anytime soon. For all the data-crunching power of computers, they lack the creative spark that makes a true grandmaster.

“If you work on a data problem in a company you need to talk with managers, and clients,” says Stanislav Semenov, a grandmaster and former number one in Moscow, who is now ranked second. He likes to celebrate Kaggle wins with a good steak. “Competitions are only about building the best models, it’s pure and I love it.” On Kaggle, data analysis is not just a sport, but an art.

Tech

Qualcomm offers EU concessions over $38 billion NXP takeover bid

BRUSSELS (Reuters) – U.S. smartphone chipmaker Qualcomm has offered concessions in an attempt to allay EU antitrust concerns over its $ 38-billion bid for NXP Semiconductors, the largest ever in the semiconductor industry.

Qualcomm, which supplies chips to Android smartphone makers and Apple, submitted its proposal on Oct. 5, a filing on the European Commission site showed on Monday, without providing details.

The EU competition enforcer, which suspended the deadline for its decision on Aug. 17 for a second time while waiting for information data from Qualcomm, said it would set a new deadline once the company has complied with its request.

The Commission is expected to seek feedback from rivals and customers in the coming days. It is concerned the combined company may use incentives to squeeze out rivals and raise prices, as well change NXP’s intellectual property licensing model.

Reporting by Foo Yun Chee; editing by Jason Neely

Our Standards:The Thomson Reuters Trust Principles.

Tech

App Annie's new product offers insight into consumer trends in China

FRANKFURT (Reuters) – The pioneer of mobile app analytics, App Annie, on Tuesday said it has begun tracking Android app usage in China, a landmark for understanding consumer behavior in the world’s top smartphone market, which increasingly sets the pace for global trends.

App Annie said it was now able to offer real-time statistics on mobile application usage in China by tracking hundreds of thousands of Android users there, both through its own apps and with additional data supplied by external partners. Statistical methods are used to identify general trends, it said.

“It’s crucial to provide an accurate picture to app publishers and brand (marketers) of what’s happening in China but also what’s happening globally in terms of app usage,” said Bertrand Schmitt, chief executive and co-founder of App Annie.

App Annie, which tracks mobile software downloads, counts 94 of the world’s top 100 app publishers as customers. They use the service to monitor the performance of their own apps against rivals. Major advertising brands such as McDonald‘s, Nike, Citibank and AstraZeneca also use App Annie to target customers with their own apps.

The company said its new China Android monitoring service can track usage metrics on 5,000 top apps such as active users, which apps are used together and data usage, both for app makers looking to track their performance versus rivals there or brand marketers looking to target advertising spending within apps.

China accounted for 60 percent of the world’s $ 1.3 billion total app spending including ecommerce, paid app store downloads and in-app advertising in 2016, according to App Annie.

Four of the world’s most played mobile games come from China, while Tencent’s WeChat ranks No. 3 globally among messaging apps behind Facebook’s WhatsApp and Facebook Messenger.

App Annie was founded in Beijing in 2010 to measure the growth of the nascent smartphone apps market. It has tracked app usage on Apple iOS since its early days in China and expanded to cover Apple and Android users globally since then.

But the explosion of smartphones in China since 2012 thanks to Android phones, which now outnumber Apple users by 6 to 1 in a market with more than 700 million phone users, has been guesswork because of a lack of independent data on the market.

“When you look at mobile usage behavior and attitudes, China is really leading. The Chinese market is definitely ahead of the curve,” said Forrester mobile analyst Thomas Husson. “It was more or less a black box, so you need some clarity as to what’s going on, in aggregate, in the world’s biggest market.”

Dozens of mobile app analytics firms compete worldwide, including big software names such as Adobe, Facebook, Google and IBM and more focused players such as Apmetrix, Localytics, SimilarWeb and Taplytics. But only App Annie so far offers an integrated global view, including China.

App Annie is now headquartered in San Francisco and has $ 150 million in funding from venture investors including Sequoia Capital and IDG Capital Partners. Two-fifths of its 500 employees and most of its engineering staff are based in China.

Reporting by Eric Auchard; Editing by Adrian Croft

Our Standards:The Thomson Reuters Trust Principles.

Tech

Zones Offers Microsoft Surface Products to Global Customer Base

IT Solutions Provider Selected for Surface Multi-National Purchasing Program

(PRWeb July 21, 2016)

Read the full story at http://www.prweb.com/releases/2016/07/prweb13567637.htm

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Google Offers Cheaper Version of Cloud Services to Run Low Priority Jobs

Some departments in your company do not need cloud computing resources to carry high-performance tasks, right? Because Google has just formatted a service plan for such demands. Google launched Preemptible Virtual Machine, a new cloud service that allows to use computing resources at low costs. The offer is suitable for workloads with low priority and can, therefore, be interrupted.

The search giant introduced a new cloud platform that cost 70% less than the same default setting in Compute Engine. The Preemptible Virtual Machine can do well cheap, about $ 0.01 per instance/hour. The most affordable VM charges per hour can range anywhere between $ 0.03 per hour, up to $ 0.11 per hour or more. The problem is that the VMs may stop working when you need it or face peak periods.

The company argues, however, that the offer (in beta) serves very well the various computational tasks. The company cites, for example, some critical workflows that can be distributed among multiple virtual machines. However, it would be a bad idea to adopt the approach to process analysis, modeling, and simulations that require high computing power and instant answers.

To provide the service, Google will use the free capacity in its data center. At times when there is a peak in demand and Google needs more resources, virtual machines involved in Preemptible Compute Engine VMs are recalled and interrupts the current processing. Users receive a notice period of 30 seconds, which should be enough to save your work. Google said No Preemptible VM can run for more than 24 hours straight.

According to the Google post, “all machine types are charged a minimum of 10 minutes. For example, if you run your instance for 2 minutes, you will be billed for 10 minutes of usage. After 10 minutes, instances are charged in 1 minute increments, rounded up to the nearest minute. For example, an instance that lives for 11.25 minutes will be charged for 12 minutes of usage.”

According to Google, there are many that utilize cloud scalability and pricing model to calculate relatively intensive, but short-term assignments. It includes the coding of video, reproduction of visual effects and calculations based on large amounts of information, such as in data analysis, simulation, and genomics.

The solution is quite similar to that of Spot Instances offered by Amazon Web Services (AWS). The model of AWS differs in price. Google has a fixed cost while the competitor price varies according to demand.

The market leader AWS routinely cuts their cloud pricing. The company is facing tough competition with Google and Microsoft to maintain its lead in cloud computing and tries to woo more developers to come to its solutions with lower prices, more hardware offerings and more advanced technologies. Microsoft, on the other hand, progressed enough to be a serious threat to Amazon’s dominance in the market.

Related Articles:

  • Amazon is Still the Leader When it Comes to Cloud Pricing
  • Google Invests Massively in IaaS and Decreases Prices
  • Google Unlocks Competition to Amazon with Compute Engine
  • Gartner Magic Quadrant Report Shows Only a Race Between AWS…
  • Google Gambles on Management Tool Docker for Building Open…


CloudTimes

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Google Offers Cheaper Version of Cloud Services to Run Low Priority Jobs

Some departments in your company do not need cloud computing resources to carry high-performance tasks, right? Because Google has just formatted a service plan for such demands. Google launched Preemptible Virtual Machine, a new cloud service that allows to use computing resources at low costs. The offer is suitable for workloads with low priority and can, therefore, be interrupted.

The search giant introduced a new cloud platform that cost 70% less than the same default setting in Compute Engine. The Preemptible Virtual Machine can do well cheap, about $ 0.01 per instance/hour. The most affordable VM charges per hour can range anywhere between $ 0.03 per hour, up to $ 0.11 per hour or more. The problem is that the VMs may stop working when you need it or face peak periods.

The company argues, however, that the offer (in beta) serves very well the various computational tasks. The company cites, for example, some critical workflows that can be distributed among multiple virtual machines. However, it would be a bad idea to adopt the approach to process analysis, modeling, and simulations that require high computing power and instant answers.

To provide the service, Google will use the free capacity in its data center. At times when there is a peak in demand and Google needs more resources, virtual machines involved in Preemptible Compute Engine VMs are recalled and interrupts the current processing. Users receive a notice period of 30 seconds, which should be enough to save your work. Google said No Preemptible VM can run for more than 24 hours straight.

According to the Google post, “all machine types are charged a minimum of 10 minutes. For example, if you run your instance for 2 minutes, you will be billed for 10 minutes of usage. After 10 minutes, instances are charged in 1 minute increments, rounded up to the nearest minute. For example, an instance that lives for 11.25 minutes will be charged for 12 minutes of usage.”

According to Google, there are many that utilize cloud scalability and pricing model to calculate relatively intensive, but short-term assignments. It includes the coding of video, reproduction of visual effects and calculations based on large amounts of information, such as in data analysis, simulation, and genomics.

The solution is quite similar to that of Spot Instances offered by Amazon Web Services (AWS). The model of AWS differs in price. Google has a fixed cost while the competitor price varies according to demand.

The market leader AWS routinely cuts their cloud pricing. The company is facing tough competition with Google and Microsoft to maintain its lead in cloud computing and tries to woo more developers to come to its solutions with lower prices, more hardware offerings and more advanced technologies. Microsoft, on the other hand, progressed enough to be a serious threat to Amazon’s dominance in the market.

Related Articles:

  • Amazon is Still the Leader When it Comes to Cloud Pricing
  • Google Invests Massively in IaaS and Decreases Prices
  • Google Unlocks Competition to Amazon with Compute Engine
  • Gartner Magic Quadrant Report Shows Only a Race Between AWS…
  • Google Gambles on Management Tool Docker for Building Open…


CloudTimes

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