recentpopularlog in

jerryking : data_centers   8

Hey Siri. Why did Apple pay $200m for an AI start-up?
JANUARY 15 2020 | Financial Times | Richard Waters and Patrick McGee in San Francisco.

For Apple, better on-device AI would allow the company’s customers to keep full control of their personal data.

Apple has paid almost $200m for an AI start up, Seattle-based Xnor, that specialises in bringing intelligence to “smart” devices.....Xnor specialises in running complex machine learning models on so-called edge devices — the wide range of gadgets, from smartphones to smart home devices and cars, that operate beyond the reach of the cloud data centres that currently handle most artificial intelligence processing.  Running machine learning on-device, rather than in the cloud, has become one of the most important technology frontiers in the spread of AI. For Apple, better on-device AI would allow the company’s customers to keep full control of their personal data......That has become an important part of the company’s marketing pitch as it tries to distinguish itself from Google and Facebook.

Xnor had developed a way to run large machine learning models without requiring the computing resources and power normally needed for such data-intensive work (e.g. the technology reduces network demands caused by AI aka latency). .....This means that critical applications can continue to run even when they lose a connection to the cloud, such as in driverless cars.
Apple  artificial_intelligence  cloud_computing  connected_devices  data_centers  decentralization  edge  Facebook  Google  latency  M&A  machine_learning  on-device  personal_data  Richard_Waters  Siri  start_ups  Xnor 
4 weeks ago by jerryking
The Morning Download: Computing’s Future Lies at Edge of Network, Just Before the Cloud - CIO Journal. - WSJ
By Steve Rosenbush
Jun 20, 2018

For years, computing has been centralized in one place or another. First, the data center, and later massive clouds. Now, networks are taking a more decentralized structure, with power located at the so-called edge, be it a retail environment, an oil rig or an automobile. On Tuesday, Hewlett Packard Enterprise Co. said it will invest $4 billion during the next four years to accelerate innovation in what HPE calls “the intelligent edge.”

Edge of opportunity. “We see significant areas for growth … (as) more assets and ‘things’ come online and the amount of data generated continues to grow exponentially,” HPE CEO Antonio Neri told CIO Journal’s Sara Castellanos in an email. The number of devices connected to the internet will reach 20.4 billion by 2020, up from 8.4 billion in 2017, according to Gartner Research Inc. By 2021, 40% of enterprises will have an edge computing strategy in place, up from about 1% in 2017, Gartner says.

The payoff. Stewart Ebrat, CIO at bridal gown and fashion company Vera Wang Co., an HPE customer, maintains that with data analytics and Bluetooth-enabled beacon devices at the edge, a salesperson could know more about a prospective customer’s preferences as soon as they walk into a brick-and-mortar store. Says Mr. Ebrat: “The customer has always been number one (at Vera Wang), but technology is going to enhance that experience even further.”
cloud_computing  decentralization  edge  future  Industrial_Internet  IT  artificial_intelligence  centralization  machine_learning  HPE  HP  data_centers 
june 2018 by jerryking
The future of computing is at the edge
June 6, 2018 | FT | by Richard Waters in San Francisco.

With so much data being produced, sending it all to cloud does not make economic sense.

The economics of big data — and the machine learning algorithms that feed on it — have been a gift to the leading cloud computing companies. By drawing data-intensive tasks into their massive, centralised facilities, companies such as Amazon, Microsoft and Google have thrived by bringing down the unit costs of computing.

But artificial intelligence is also starting to feed a very different paradigm of computing. This is one that pushes more data-crunching out to the network “edge” — the name given to the many computing devices that intersect with the real world, from internet-connected cameras and smartwatches to autonomous cars. And it is fuelling a wave of new start-ups which, backers claim, represent the next significant architectural shift in, an early-stage AI software start-up that raised $12m this month, is typical of this new wave. Led by Ali Farhadi, an associate professor at University of Washington, the company develops machine learning algorithms that can be run on extremely low-cost gadgets. Its image recognition software, for instance, can operate on a Raspberry Pi, a tiny computer costing just $5, designed to teach the basics of computer science......That could make it more economical to analyse data on the spot rather than shipping it to the cloud. One possible use: a large number of cheap cameras around the home with the brains to recognise visitors, or tell the difference between a burglar and a cat.

The overwhelming volume of data that will soon be generated by billions of devices such as these upends the logic of data centralisation, according to Mr Farhadi. “We like to say that the cloud is a way to scale AI, but to me it’s a roadblock to AI,” he said. “There is no cloud that can digest this much data.”

“The need for this is being driven by the mass of information being collected at the edge,” added Peter Levine, a partner at Silicon Valley venture capital firm Andreessen Horowitz and investor in a number of “edge” start-ups. “The real expense is going to be shipping all that data back to the cloud to be processed when it doesn’t need to be.”

Other factors add to the attractions of processing data close to where it is collected. Latency — the lag that comes from sending information to a distant data centre and waiting for results to be returned — is debilitating for some applications, such as driverless cars that need to react instantly. And by processing data on the device, rather than sending it to the servers of a large cloud company, privacy is guaranteed.

Tobias Knaup, co-founder of Mesosphere, another US start-up, uses a recent computing truism to sum up the trend: “Data has gravity.”....Nor are the boundaries between cloud and edge distinct. Data collected locally is frequently needed to retrain machine learning algorithms to keep them relevant, a computing-intensive task best handled in the cloud. Companies such as Mesosphere — which raised $125m this month, taking the total to more than $250m — are betting that this will give rise to technologies that move information and applications to where they are best handled, from data centres out to the edge and vice versa...Microsoft unveiled image-recognition software that was capable of running on a local device rather than its own data centres.
Andreessen_Horowitz  artificial_intelligence  centralization  cloud_computing  computer_vision  data_centers  decentralization  edge  future  Industrial_Internet  IT  latency  low-cost  machine_learning  Microsoft  Richard_Waters 
june 2018 by jerryking
‘You’re Stupid If You Don’t Get Scared’: When Amazon Goes From Partner to Rival - WSJ
By Jay Greene and Laura Stevens
June 1, 2018

The data weapon
One Amazon weapon is data. In retail, Amazon gathered consumer data to learn what sold well, which helped it create its own branded goods while making tailored sales pitches with its familiar “you may also like” offer. Data helped Amazon know where to start its own delivery services to cut costs, an alternative to using United Parcel Service Inc. and FedEx Corp.

“In many ways, Amazon is nothing except a data company,” said James Thomson, a former Amazon manager who advises brands that work with the company. “And they use that data to inform all the decisions they make.”

In web services, data across the broader platform, along with customer requests, inform the company’s decisions to move into new businesses, said former Amazon executives.

That gives Amazon a valuable window into changes in how corporations in the 21st century are using cloud computing to replace their own data centers. Today’s corporations frequently want a one-stop shop for services rather than trying to stitch them together. A food-services firm, say, might want to better track data it collects from its restaurants, so it would rent computing space from Amazon and use a data service offered by a software company on Amazon’s platform to better analyze what customers order. A small business might use an Amazon partner’s online services for password and sign-on functions, along with other business-management programs.
21st._century  Amazon  AWS  brands  cloud_computing  contra-Amazon  coopetition  data  data_centers  data_collection  data_driven  delivery_services  fear  new_businesses  one-stop_shop  partnerships  platforms  private_labels  rivalries  small_business  strengths  tools  unfair_advantages 
june 2018 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
WSJ: The War for the Web
May 06, 2008 | THE WSJ | Andy Kessler:

The Cloud. The desktop computer isn't going away. But as bandwidth speeds increase, more and more computing can be done in the network of computers sitting in data centers – aka the "cloud."

There, search results can be calculated, companies' payrolls processed, even the complex graphics for video games can be drawn. But it's not cheap. These clouds are multibillion-dollar investments. Google spent $842 million in the last three months on servers, data centers and fiber optics.

Not only hasn't the Internet yet matured, it's becoming an ever-more high stakes game

Today, there are several major clouds: Google, Yahoo, Microsoft, Amazon and smaller players IBM and Sun. Can there be more? Sure, but it would require a business model that could not only pay for it, but could rip it out every few years and modernize it. Google's $20 billion Web advertising business gives it the cash flow to do so. Advantage Google.
Andy_Kessler  cloud_computing  platforms  FAANG  Microsoft  cash_flows  Yahoo!  high-stakes  Google  advertising  data_centers 
october 2011 by jerryking
Unboxed - Who Says Innovation Belongs to the Small? -
May 23, 2009 | New York Times | By STEVE LOHR. Technology
trends also contribute to the rising role of large companies. The lone
inventor will never be extinct, but W. Brian Arthur, an economist at the
Palo Alto Research Center, says that as digital technology evolves,
step-by-step innovations are less important than linking all the
sensors, software and data centers in systems.
innovation  size  Steve_Lohr  Clayton_Christensen  large_companies  W._Brian_Arthur  sensors  software  interconnections  Fortune_500  brands  back-office  data_centers  systematic_approaches  systems  systems_integration  Xerox 
october 2009 by jerryking

Copy this bookmark:

to read