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jerryking : quentin_hardy   27

Gearing Up for the Cloud, AT&T Tells Its Workers: Adapt, or Else - The New York Times
FEB. 13, 2016| NYT | By QUENTIN HARDY.

For the company to survive in this environment, Mr. Stephenson needs to retrain its 280,000 employees so they can improve their coding skills, or learn them, and make quick business decisions based on a fire hose of data coming into the company.....Learn new skills or find your career choices are very limited.

“There is a need to retool yourself, and you should not expect to stop,”....People who do not spend five to 10 hours a week in online learning, he added, “will obsolete themselves with the technology.” .......By 2020, Mr. Stephenson hopes AT&T will be well into its transformation into a computing company that manages all sorts of digital things: phones, satellite television and huge volumes of data, all sorted through software managed in the cloud.

That can’t happen unless at least some of his work force is retrained to deal with the technology. It’s not a young group: The average tenure at AT&T is 12 years, or 22 years if you don’t count the people working in call centers. And many employees don’t have experience writing open-source software or casually analyzing terabytes of customer data. .......By 2020, Mr. Stephenson hopes AT&T will be well into its transformation into a computing company that manages all sorts of digital things: phones, satellite television and huge volumes of data, all sorted through software managed in the cloud.

.......“Everybody is going to go face to face with a Google, an Amazon, a Netflix,” he said. “You compete based on data, and based on customer insights you get with their permission. If we’re wrong, it won’t play well for anyone here.
Quentin_Hardy  AT&T  cloud_computing  data  retraining  reinvention  skills  self-education  virtualization  data_scientists  new_products  online_training  e-learning  customer_insights  Google  Amazon  Netflix  data_driven 
february 2016 by jerryking
Looking Beyond the Internet of Things
JAN. 1, 2016 | NYT | By QUENTIN HARDY.

Adam Bosworth is building what some call a “data singularity.” In the Internet of Things, billions of devices and sensors would wirelessly connect to far-off data centers, where millions of computer servers manage and learn from all that information.

Those servers would then send back commands to help whatever the sensors are connected to operate more effectively: A home automatically turns up the heat ahead of cold weather moving in, or streetlights behave differently when traffic gets bad. Or imagine an insurance company instantly resolving who has to pay for what an instant after a fender-bender because it has been automatically fed information about the accident.

Think of it as one, enormous process in which machines gather information, learn and change based on what they learn. All in seconds.... building an automated system that can react to all that data like a thoughtful person is fiendishly hard — and that may be Mr. Bosworth’s last great challenge to solve....this new era in computing will have effects far beyond a little more efficiency. Consumers could see a vast increase in the number of services, ads and product upgrades that are sold alongside most goods. And products that respond to their owner’s tastes — something already seen in smartphone upgrades, connected cars from BMW or Tesla, or entertainment devices like the Amazon Echo — could change product design.
Quentin_Hardy  Industrial_Internet  data  data_centers  data_driven  machine_learning  Google  Amazon  cloud_computing  connected_devices  BMW  Tesla  Amazon_Echo  product_design  Michael_McDerment  personalization  connected_cars 
january 2016 by jerryking
How SurveyMonkey Is Coping After the Death of Dave Goldberg - The New York Times
By QUENTIN HARDY JUNE 21, 2015.

SurveyMonkey’s top executives have had to avoid “strategic paralysis from a culture of mourning, and emotional revolt from telling people ‘get over it,’ ” said Jeffrey A. Sonnenfeld, a professor at the Yale School of Management. “There is a way to take a loss and make it into strength.”

SurveyMonkey was started in 1999 and remained small for a decade, offering online and email surveys on various topics. In 2009, private equity investors acquired it, and Mr. Goldberg, who had sold a small music company to Yahoo for $12 million in 2001, was brought in soon after to run the company. Starting with just 14 employees, Mr. Goldberg began his recruiting.
Quentin_Hardy  SurveyMonkey  Silicon_Valley  mourning  succession  paralyze  boards_&_directors_&_governance  executive_management 
june 2015 by jerryking
The Sensor-Rich, Data-Scooping Future - NYTimes.com
APRIL 26, 2015 | NYT | By QUENTIN HARDY.

Sensor-rich lights, to be found eventually in offices and homes, are for a company that will sell knowledge of behavior as much as physical objects....The Internet will be almost fused with the physical world. The way Google now looks at online clicks to figure out what ad to next put in front of you will become the way companies gain once-hidden insights into the patterns of nature and society.

G.E., Google and others expect that knowing and manipulating these patterns is the heart of a new era of global efficiency, centered on machines that learn and predict what is likely to happen next.

“The core thing Google is doing is machine learning,” Eric Schmidt....The great data science companies of our sensor-packed world will have experts in arcane reaches of statistics, computer science, networking, visualization and database systems, among other fields. Graduates in those areas are already in high demand.

Nor is data analysis just a question of computing skills; data access is also critically important. As a general rule, the larger and richer a data set a company has, the better its predictions become. ....an emerging area of computer analysis known as “deep learning” will blow away older fields.

While both Facebook and Google have snapped up deep-learning specialists, Mr. Howard said, “they have far too much invested in traditional computing paradigms. They are the equivalent of Kodak in photography.” Echoing Mr. Chui’s point about specialization, he said he thought the new methods demanded understanding of specific fields to work well.

It is of course possible that both things are true: Big companies like Google and Amazon will have lots of commodity data analysis, and specialists will find niches. That means for most of us, the answer to the future will be in knowing how to ask the right kinds of questions.
sensors  GE  GE_Capital  Quentin_Hardy  data  data_driven  data_scientists  massive_data_sets  machine_learning  automated_reasoning  predictions  predictive_analytics  predictive_modeling  layer_mastery  core_competencies  Enlitic  deep_learning  niches  patterns  analog  insights  latent  hidden  questions  Google  Amazon  aftermath  physical_world  specialization  consumer_behavior  cyberphysical  arcane_knowledge  artificial_intelligence  test_beds 
april 2015 by jerryking
Amazon to Sell Predictions in Cloud Race Against Google and Microsoft - NYTimes.com
By QUENTIN HARDY APRIL 9, 2015

Amazon Web Services announced that it was selling to the public the same kind of software it uses to figure out what products Amazon puts in front of a shopper, when to stage a sale or who to target with an email offer.

The techniques, called machine learning, are applicable for technology development, finance, bioscience or pretty much anything else that is getting counted and stored online these days. In other words, almost everything.
Quentin_Hardy  Amazon  Google  machine_learning  cloud_computing  AWS  Microsoft  Azure  predictions  predictive_analytics  predictive_modeling  automated_reasoning 
april 2015 by jerryking
What Cars Did for Today's World, Data May Do for Tomorrow's - NYTimes.com
August 10, 2014 | NYT | Quentin Hardy.

General Electric plans to announce Monday that it has created a “data lake” method of analyzing sensor information from industrial machinery in places like railroads, airlines, hospitals and utilities. G.E. has been putting sensors on everything it can for a couple of years, and now it is out to read all that information quickly.

The company, working with an outfit called Pivotal, said that in the last three months it has looked at information from 3.4 million miles of flights by 24 airlines using G.E. jet engines. G.E. said it figured out things like possible defects 2,000 times as fast as it could before.....Databricks, that uses new kinds of software for fast data analysis on a rental basis. Databricks plugs into the one million-plus computer servers inside the global system of Amazon Web Services, and will soon work inside similar-size megacomputing systems from Google and Microsoft....If this growing ecosystem of digital collection, shipment and processing is the new version of cars and highways, what are the unexpected things, the suburbs and fast-food joints that grew from cars and roads?

In these early days, businesses like Uber and Airbnb look like challengers to taxi fleets and hotels. They do it without assets like cars and rooms, instead coordinating data streams about the location of people, cars, and bedrooms. G.E. makes engines, but increasingly it coordinates data about the performance of engines and the location of ground crews. Facebook uses sensor data like location information from smartphones
Quentin_Hardy  data  data_driven  AWS  asset-light  massive_data_sets  resource_allocation  match-making  platforms  resource_management  orchestration  ecosystems  GE  sensors  unexpected  unforeseen  Databricks  Uber  Airbnb  data_coordination  instrumentation_monitoring  efficiencies 
august 2014 by jerryking
Wealth Managers Enlist Spy Tools to Map Portfolios - NYTimes.com
AUG. 3, 2014 | NYT | QUENTIN HARDY.

Karen White, Addepar’s president and chief operating officer, says a typical customer has investments at five to 15 banks, stockbrokers or other investment custodians.

Addepar charges based on how much data it is reviewing. Ms. White said Addepar’s service typically started at $50,000, but can go well over $1 million, depending on the money and investment variables involved.

And in much the way Palantir seeks to find common espionage themes, like social connections and bomb-making techniques, among its data sources,[jk: traffic_analysis] Mr. Lonsdale has sought to reduce financial information to a dozen discrete parts, like price changes and what percentage of something a person holds.

As a computer system learns the behavior of a certain asset, it begins to build a database of probable relationships, like what a bond market crisis might mean for European equities. “A lot of computer science, machine learning, can be applied to that,” Mr. Lonsdale said. “There are lessons from Palantir about how to do this.”
wealth_management  software  valuations  Quentin_Hardy  Addepar  Palantir  money_management  social_connectivity  machine_learning  correlations  portfolio_management  investment_custodians  tools 
august 2014 by jerryking
Start-Ups Are Mining Hyperlocal Information for Global Insights - NYTimes.com
November 10, 2013 | WSJ | By QUENTIN HARDY

By analyzing the photos of prices and the placement of everyday items like piles of tomatoes and bottles of shampoo and matching that to other data, Premise is building a real-time inflation index to sell to companies and Wall Street traders, who are hungry for insightful data.... Collecting data from all sorts of odd places and analyzing it much faster than was possible even a couple of years ago has become one of the hottest areas of the technology industry. The idea is simple: With all that processing power and a little creativity, researchers should be able to find novel patterns and relationships among different kinds of information.

For the last few years, insiders have been calling this sort of analysis Big Data. Now Big Data is evolving, becoming more “hyper” and including all sorts of sources. Start-ups like Premise and ClearStory Data, as well as larger companies like General Electric, are getting into the act....General Electric, for example, which has over 200 sensors in a single jet engine, has worked with Accenture to build a business analyzing aircraft performance the moment the jet lands. G.E. also has software that looks at data collected from 100 places on a turbine every second, and combines it with power demand, weather forecasts and labor costs to plot maintenance schedules.
start_ups  data  data_driven  data_mining  data_scientists  inflation  indices  massive_data_sets  hyperlocal  Premise  Accenture  GE  ClearStory  real-time  insights  Quentin_Hardy  pattern_recognition  photography  sensors  maintenance  industrial_Internet  small_data 
november 2013 by jerryking
Why Big Data Is Not Truth - NYTimes.com
June 1, 2013, 8:00 am 25 Comments
Why Big Data Is Not Truth
By QUENTIN HARDY
massive_data_sets  data  contrarians  Quentin_Hardy 
june 2013 by jerryking
Jeff Hawkins Develops a Brainy Big Data Company - NYTimes.com
November 28, 2012, 12:13 pmComment
Jeff Hawkins Develops a Brainy Big Data Company
By QUENTIN HARDY

Jeff Hawkins, who helped develop the technology in Palm, an early and successful mobile device, is a co-founder of Numenta, a predictive software company....Numenta’s product, called Grok, is a cloud-based service that works much the same way. Grok takes steady feeds of data from things like thermostats, Web clicks, or machinery. From initially observing the data flow, it begins making guesses about what will happen next. The more data, the more accurate the predictions become.
massive_data_sets  Grok  pattern_recognition  start_ups  streaming  aftermath  cloud_computing  predictions  predictive_analytics  Quentin_Hardy 
november 2012 by jerryking
H.P.’s Misstep Shows Risk in the Push for Big Ideas - NYTimes.com
November 21, 2012 | NYT | By QUENTIN HARDY.

The ill-fated marriage of the companies is a lesson for H.P. and other older technology giants as they throw billions at supposedly game-changing acquisitions, trying to gain a foothold in the future.

In that future, smartphones and tablets, connected to cloud-computing data centers, are the essential tools of work and play. Companies rent software over the air, rather than buying it with expensive maintenance contracts.

And vast streams of data are continually analyzed to find new patterns and make predictions about consumer behavior and product design. Autonomy, for instance, makes software that can analyze marketing patterns and advise a company on matters like where it should increase marketing resources.

These forces threaten older businesses, like H.P.’s traditional personal computer and data storage products. Other companies, like Oracle, Microsoft and Cisco, also face pressure. They are all trying to buy the future — and have the cash to do it..... But identifying the next big thing can be difficult, said Jeffrey Sonnenfeld, a professor of management at Yale University. Likely as not, he said, deals like the one for Autonomy have “maybe a 40 percent success, 60 percent failure rate.”

He added, “The odds are against you succeeding, but the odds are also worth taking.”

The real hazard, he said, is in the way companies describe these acquisitions as “natural, inevitable victories.” They should be seen, he said, as “an investment, like in research and development.”
Autonomy  big_bets  breakthroughs  cloud_computing  cultural_clash  failure  game_changers  HP  ideas  M&A  Meg_Whitman  mergers_&_acquisitions  mistakes  missteps  moonshots  Quentin_Hardy  risks  SaaS  subscriptions  success_rates 
november 2012 by jerryking

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