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jerryking : data_coordination   3

Apple’s drive for world auto dominance spooks the industry - The Globe and Mail
GREG KEENAN, BRIAN MILNER AND OMAR EL AKKAD
The Globe and Mail
Published Friday, Mar. 20 2015,

Apple’s big advantage over traditional car makers is simple, yet hard to overcome, and it lies in the cloud.

The cloud consists of remote servers that store vast amounts of data and run applications, giving everyone on the planet with a connected device access to unlimited computing power essentially for free. It is also revolutionizing the way companies do business by instantly providing them with vast amounts of customer data. And it means Apple would not need to acquire car manufacturing capacity or build assembly and distribution networks in order to create chaos in the club.

It’s an advantage few traditional manufacturers, including auto makers, fully grasp, let alone have the ability to exploit.....“Apple thinks from the cloud out,” says Mr. McInerney, who would definitely line up for an Apple vehicle. At least then, he says, he would be assured of a better communications interface than the clunky one in his new upscale German model.

“If you’re an Apple or a Google, it allows you to use the same power to manage your supply chain that you use to manage your customers,” he says.

“That’s a revolution in thinking that allows you to identify all the cash-wait states [where money sits idle] and to collect a stunning amount of customer information in real time. Put the two together and you’re turning that information into cash at an accelerated rate. Car companies don’t think like that.”
automotive_industry  automobile  Apple  batteries  autonomous_vehicles  cloud_computing  connected_devices  layer_mastery  digital_first  data_coordination  incumbents  monetization  cash  customer_data  idle_funds  SMAC_stack  connected_cars 
march 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
Max Levchin talks about data, sensors and the plan for his new startup(s) — Tech News and Analysis
Jan. 30, 2013 | GigaOm |By Om Malik.

“The world of real things is very inefficient: slack resources are abundant, so are the companies trying to rationalize their use. Über, AirBnB, Exec, GetAround, PostMates, ZipCar, Cherry, Housefed, Skyara, ToolSpinner, Snapgoods, Vayable, Swifto…it’s an explosion! What enabled this? Why now? It’s not like we suddenly have a larger surplus of black cars than ever before.

Examine the DNA of these businesses: resource availability and demand requests — highly analog, as this is about cars, drivers, and passengers — is captured at the edge, automatically where possible, then transmitted and stored, then processed centrally. Requests are queued at the smart center, and a marketplace/auction is used to allocate them, matches are made and feedback is given in real time.

A key revolutionary insight here is not that the market-based distribution of resources is a great idea — it is the digitalization of analog data, and its management in a centralized queue to create amazing new efficiencies.”
massive_data_sets  data  Max_Levchin  sensors  start_ups  incubators  San_Francisco  sharing_economy  slack_resources  analog  efficiencies  meat_space  data_coordination  match-making  platforms  Om_Malik  resource_management  underutilization  resource_allocation  auctions  SMAC_stack  algorithms  digitalization  radical_ideas 
february 2013 by jerryking

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