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ARMs 31 billion takeover shows that information is king

SoftBank is getting a bargain

ARM Holdings, a chip design firm that doesnÕt manufacture or sell any chips, has just been bought by SoftBank for a cool $31.4 billion. ThatÕs four times as much as Microsoft paid for Nokia, close to three times GoogleÕs expenditure on Motorola, and an order of magnitude more than Palm cost HP. We think of these other companies as the authors of the mobile world weÕre living in, but itÕs ARMÕs invisible contribution that has proven more influential Ñ and now a lot more valuable Ñ than all of them.

The smartphone revolution of this century might as well be called the ARM takeover. Practically every single phone, tablet, and smartwatch out in the world today runs on a processor using the ARM architecture Ñ which means licensing ARMÕs designs and paying royalties for every chip sold. Yes, that includes iPhones, Galaxys, BlackBerrys, Droids, and Lumias: all but the most loyal of Intel acolytes are manufacturing ARM-powered mobile devices. ARMÕs portfolio extends beyond mobile processors to include graphics, wireless, and server chips along with physical design blueprints and software development tools. Simply put, if you want to build a mobile device of any kind, youÕll have to deal with ARM.

ARM IS AN INTELLECTUAL PROPERTY POWERHOUSE

ARMÕs product is information. The company spends its time and money on R&D, which it converts into successive generations of new mobile processor core and system designs. Its hardware partners would love to be able to build everything themselves, but ARMÕs depth and breadth of expertise is such that itÕs more efficient to license rather than compete with its technology. With more than 4,500 granted or pending patents, ARM is an intellectual property powerhouse Ñ like a patent troll that isnÕt actually trolling, it just develops smart production methods and designs and sells them.

An oft-cited aphorism from Tom Goodwin last year identified one of the prevailing trends of modern tech:

"Uber, the worldÕs largest taxi company, owns no vehicles. Facebook, the worldÕs most popular media owner, creates no content. Alibaba, the most valuable retailer, has no inventory. And Airbnb, the worldÕs largest accommodation provider, owns no real estate. Something interesting is happening."

The "something interesting" is happening behind the scenes of the tech world too. ARM is another of these prospering companies whose profits keep improving even in the absence of any tangible, physical assets. It isnÕt chasing consumers directly, but itÕs just as much a trader in information as Facebook, Uber, and Airbnb are. Consumers recompense ARM via the intermediary of a hardware-manufacturing partner, but the core mechanics are still the same: obtain valuable information, secure your control over it, sell it to a willing purchaser, and profit.

ARMs Holdings

ItÕs a simple formula that should be extremely familiar by now. Data and software might have high initial acquisition or production costs, but once you have them, the marginal cost of producing another unit to sell or license is zero. ARM has carved out its niche by continuously being ahead of the competition, nullifying IntelÕs Sisyphean efforts to break through into mobile, and developing a wide network of satisfied licensees.

The headline reason for SoftBankÕs acquisition of ARM today is the latter companyÕs instrumental role in developing the future Internet of Things. The pair have even set up a website dedicated to the deal, where they explain their rationale and talk up plans for world domination thatÕs even greater than the 90 billion ARM chips already out there. But the IoT future isnÕt here yet, and a seasoned investor like SoftBank CEO Masayoshi Son doesnÕt spend $31 billion purely on potential. He sees that ARM is an already profitable company with comparatively negligible expenses, he recognizes the massive discountthat BrexitÕs impact on the British pound has created, and he knows ARMÕs influence is far greater than its size. It just makes good business sense, especially at a time when debt is cheap to sustain and cash is more of a burden than an asset.

THE INFORMATION AGE IS DEFINED BY COMPANIES LIKE ARM, WHOSE ASSETS ARE INTANGIBLE

To casual observers, the idea of a company with no brand recognition Ñ anonymous to all but the geeky spec sheet explorers Ñ meriting an 11-figure price will seem absurd. But just like the more consumer-facing acquisitions of WhatsApp by Facebook and LinkedIn by Microsoft, this is a big investment into the information economy.

As much as hardware companies like Apple and Samsung might dominate news coverage and peopleÕs wish lists, itÕs the software and service providers that load those devices up and make them truly desirable. In ARMÕs case, its information provides the blueprint and architecture atop which everything is built. Hardware manufacturers may come and go, but the one essential and irreplaceable aspect of modern mobile computing is ARMÕs portfolio of intellectual property. ThatÕs where the value is.

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Anwsered 64bit system is attempting to install 32bit updates

64bit system is attempting to install 32bit updates

my pc keeps wanting me to install new window updates,but my pc is a 64 bit system and the updates that are trying to install are 32 bit?why is windows not detecting automatically?

Keys to the Problem 64bit system is attempting to install 32bit updates

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If Office 2010 64-bit isÊNOTÊinstalled, the Office 32-bit updates are appropriate for your system.

~Robear Dyer (PA Bear) ~ MS MVP (IE, Mail, Security, Windows & Update Services) since 2002 ~ Disclaimer: MS MVPs neither represent nor work for Microsoft

Use the System File Checker tool to repair corrupted or missing system files:

1. Click Start.
2. Type cmd, and then press CTRL+SHIFT+ENTER to open the elevated command prompt (I.e. Command prompt with administrative rights).
3. The User Account Control window should appear, be sure that the action it exhibits is correct, and then press the Continue button.
4. Type or copy paste the below command line into it without quotes:
5. "Sfc /scannow"

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Achievement unlocked NASA‰Ûªs Juno spaceship is now in Jupiter‰Ûªs orbit

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Nearly five years after it was first launched in August 2011, NASAÕs Juno spaceship has finally entered JupiterÕs orbit. At 11:53PM ET/8:53PM PT, the space agency received confirmation that the spacecraft had turned on its main engine, which burned for 35 minutes to slow down and allow Juno to be drawn in by JupiterÕs gravitational pull.

ItÕs a monumental achievement for NASA: the feat saw Juno cover 445 million miles in space to get closer to Jupiter than any other spaceship in the history of mankind. It is now in a highly elliptical 53-day orbit around the giant planet.

Broadcast live streaming video on Ustream

The goal of this mission is to determine how much water is in JupiterÕs atmosphere, in an effort to learn about which planet formation theory is correct. NASA also wants to measure the composition and temperature of JupiterÕs atmosphere, and how its magnetic force field affects the atmosphere there.

Jupiter emits massive amounts of radiation and flings debris with great force; Juno will avoid these belts for most of its time in the planetÕs orbit. But at the end of the 53-day cycle, it will be within close proximity of the planetÕs equator Ð close enough to study the atmosphere and magnetic field.

At 12:30AM ET, the spaceship is scheduled to re-orient itself toward the sun to recharge its batteries. If the maneuver is successful, itÕs in the clear. You can follow along by tuning into the livestream above.

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5 Ways Voice Recognition Is Now A Part of Our Everyday Lives

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10 ways IoT is making successful inroads into business

The Internet of Things is finding its way into a host of industries, from transportation to health care to factory maintenance.

Many companies are still engaged in proofs of concept to see where the Internet of Things (IoT) can bring value to their operations and strategies, but a number of IoT apps have already taken root in a cross-section of industry sectors and are producing favorable business impact. Here are 10 good examples.

1: Transportation infrastructure

The insertion of sensors at key points of highways and railways is enabling cities to monitor the wellness of their transportation infrastructures, along with events like traffic flow and congestion. The information these IoT sensors send back to headquarters is used to notify motorists of heavy congestion points and alternate routes. It also serves as a predictive means of showing where equipment failures are imminent, so repair crews can be dispatched to fix vulnerable equipment before actual failures (and traffic stoppages) result.

2: Safety of sensitive goods during transport

Foodstuffs and medical supplies often require stringent temperature and humidity controls during storage and shipment. To facilitate climate control, logistics companies use environmentally controlled, sealed containers. The containers are equipped with sensors that emit status reports to a central network so they can be monitored for adherence to humidity and temperature controls. If the environmentals within a container begin to fail or if tampering with a closed container seal is detected, the sensors immediately send out alerts to the central network so appropriate steps can be taken. The use of IoT reduces spoilage of sensitive goods and also prevents tampering.

3: Logistics tracking and performance

Major logistics carriers now use trucks that are sensor equipped so shipments can be tracked along routes, optimum delivery routes can be used, and timeliness can be tracked. In some cases, sensors are also used to track speeds, braking habits, etc., of drivers to ensure that the safest and most environmentally friendly driving practices are used.

4: Equipment diagnostics and preventive maintenance on the factory floor

As manufacturers adopt new 21st century practices, equipment within the factory is being outfitted with sensors that automatically flash an alert into the central factory operations monitoring network when a weakening component or other failure-inducing condition is detected. In this way, manufacturers can take a machine offline, reroute manufacturing operations and repair the faulty equipment before a total failure occurs that stops production.

5: Smart street lights

Street lights with IoT capability now "communicate" with city utility managers who are miles away, sending IoT data on energy usage and enabling remote adjustments to lighting to compensate for local environmental conditionsÑsuch as dimming the lights on a moonlit night or increasing lighting during rainstorms and fog. The ability to climate-adjust street lighting economizes energy usage and reduces energy costs.

6: Unmanned aerial vehicles (UAVs)

Aerial drones equipped with IoT sensors are being used by oil and gas exploration companies, mining companies, and agribusiness to chart and monitor remote, difficult to access areas and to measure elements such as soil composition and moisture content. The ability to perform these operations remotely saves field time and reduces the safety risk incurred when personnel are dispatched to remote and uncharted areas.

7: Inventory tracking during shipment

In areas of the world where the theft of inventory from trucks in transit for sale on the black market is widespread, transportation companies are attaching IoT sensors to packages and are making the practice known to locals. In one case, a transporter reported that the theft rate had fallen from 50% of inventory to 4% after IoT sensors were installed.

8: Home and business energy monitoring

Homeowners and companies are employing environmental energy monitoring with the help of IoT sensors. The devices assist them in controlling energy consumptionÑwhether it be for an individual home, a business, or a data center.

9: Mobile device tracking

In 2014 alone, more than 10 million mobile devices were lost in the UK. The worldwide total of lost or stolen mobile devices is undoubtedly staggering. Enter IoT sensors that can be activated on these devices to at least prevent data breachesÑand to possibly facilitate device retrievals.

10: Safety monitoring/tracking of Alzheimers patients

Individuals suffering from Alzheimers or other mentally debilitating disorders can now be tracked via IoT sensors in case they leave the home and cant find their way back. In addition, IoT sensors can serve as a safety net for potentially dangerous situations. For example they can be attached to stove gas burners in case a burner is turned on and left unattended.

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Anwsered All the AVG anti virus download failed the message was there is virus and were deleted

All the AVG anti-virus download failed, the message was there is virus and were deleted.

WhenÊthe AVG antivirus was notÊworking properly, I deleted it.
AndÊinstall the latest AVG anti-virus 2012.
But unsuccessful.
Ê
The download was unsuccessful.
The message showed thatÊthere is virusÊand wasÊdeleted.ÊI tried to download a few AVG, Norton anti-virus,Ê all turned out to haveÊ the same message.
Now how to solve this problem.

Ê
Thank you
Ê
Best Regards
Mei

Anwsers to the Problem All the AVG anti-virus download failed, the message was there is virus and were deleted.

Download Error Fixer for Free Now

http://www.avg.com/us-en/support
Ê
http://us.norton.com/support/
Ê
Your computer may now be infected and you may be unable to install an antimalware program.
Ê
You should never have more than one security product installed on the PC providing active protection/scanning.
This can cause performance issues, system instability and conflicts between programs, and can hinder the effectiveness all installed antivirus
products.
Ê
If you are NOT using Microsoft Security Essentials, you can get free help with malware removal here:

http://supportservices.microsoft.com/support/services/virus_malware_removal
If you are in North America, you can call MS Support at 866-727-2338 for help with virus and spyware infections.
For international information see your
local subsidiary support site.
Or, obtain assistance from your antimalware provider (Avast, AVG, Avira, McAfee, Norton, Trend Micro, etc).
Alternatively
Go to www.malwarebytes.org and download, install, update and run the free version Ð just follow the prompts.You may need to rename the installation file
to 123.exe or something similar to prevent the malware from disabling/blocking the installation.
and/or
Try Superantispyware Portable at: http://www.superantispyware.com/portablescanner.html
and/or
Try Eset Online Scanner:
http://go.eset.com/us/online-scanner
Ê
Good luck...
Ê
http://voices.washingtonpost.com/securityfix/2009/09/what_to_do_when_rogue_anti-vir.html#more
Ê
http://ask-leo.com/i_run_antivirus_software_why_do_i_still_sometimes_get_infected.html
Ê
http://www.av-comparatives.org/
Ê
http://www.dslreports.com/forum/r25776413-2011-Anti-Virus-Poll

Make Sure that your Hardware Meets the System Requirements

Microsoft Windows Requirements :

• 1 gigahertz (GHz) or faster 32-bit (x86) or 64-bit (x64) processor
• 1 gigabyte (GB) RAM (32-bit) or 2 GB RAM (64-bit)
• 16 GB available hard disk space (32-bit) or 20 GB (64-bit)

You need to double-check your computers hardware configuration against the following Microsoft requirements. If your PC hardware is not up to par, then make sure you upgrade where necessary before continuing.

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AI Is Transforming Google Search The Rest of the Web Is Next

YESTERDAY, THE 46-YEAR-OLD Google veteran who oversees the companyÕs search engine, Amit Singhal, announced his retirement. And in short order, Google revealed that SinghalÕs rather enormous shoes would be filled by a man named John Giannandrea. On one level, these are just two guys doing something new with their lives. But you can also view the pair as the ideal metaphor for a momentous shift in the way things work inside GoogleÑand across the tech world as a whole.

Giannandrea, you see, oversees GoogleÕs work in artificial intelligence. This includes deep neural networks, networks of hardware and software that approximate the web of neurons in the human brain. By analyzing vast amounts of digital data, these neural nets can learn all sorts of useful tasks, like identifying photos, recognizing commands spoken into a smartphone, and, as it turns out, responding to Internet search queries. In some cases, they can learn a task so well that they outperform humans. They can do it better. They can do it faster. And they can do it at a much larger scale.

This approach, called deep learning, is rapidly reinventing so many of the InternetÕs most popular services, from Facebook to Twitter to Skype. Over the past year, it has also reinvented Google Search, where the company generates most of its revenue. Early in 2015, as Bloomberg recently reported, Google began rolling out a deep learning system called RankBrain that helps generate responses to search queries. As of October, RankBrain played a role in Òa very large fractionÓ of the millions of queries that go through the search engine with each passing second.

As Bloomberg says, it was Singhal who approved the roll-out of RankBrain. And before that, he and his team may have explored other, simpler forms of machine learning. But for a time, some say, he represented a steadfast resistance to the use of machine learning inside Google Search. In the past, Google relied mostly on algorithms that followed a strict set of rules set by humans. The concernÑas described by some former Google employeesÑwas that it was more difficult to understand why neural nets behaved the way it did, and more difficult to tweak their behavior.

These concerns still hover over the world of machine learning. The truth is that even the experts donÕt completely understand how neural nets work. But they do work. If you feed enough photos of a platypus into a neural net, it can learn to identify a platypus. If you show it enough computer malware code, it can learn to recognize a virus. If you give it enough raw languageÑwords or phrases that people might type into a search engineÑit can learn to understand search queries and help respond to them. In some cases, it can handle queries better than algorithmic rules hand-coded by human engineers. Artificial intelligence is the future of Google Search, and if itÕs the future of Google Search, itÕs the future of so much more.

Sticking to the Rules

This past fall, I sat down with a former Googler who asked that I withhold his name because he wasnÕt authorized to talk about the companyÕs inner workings, and we discussed the role of neural networks inside the companyÕs search engine. At one point, he said, the Google ads team had adopted neural nets to help target ads, but the Òorganic searchÓ team was reluctant to use this technology. Indeed, over the years, discussions of this dynamic have popped up every now and again on Quora, the popular question-and-answer site.

Edmond Lau, who worked on GoogleÕs search team and is the author of the book The Effective Engineer, wrote in a Quora post that Singhal carried a philosophical bias against machine learning. With machine learning, he wrote, the trouble was that ÒitÕs hard to explain and ascertain why a particular search result ranks more highly than another result for a given query.Ó And, he added: ÒItÕs difficult to directly tweak a machine learning-based system to boost the importance of certain signals over others.Ó Other ex-Googlers agreed with this characterization.

Yes, GoogleÕs search engine was always driven by algorithms that automatically generate a response to each query. But these algorithms amounted to a set of definite rules. Google engineers could readily change and refine these rules. And unlike neural nets, these algorithms didnÕt learn on their own. As Lau put it: ÒRule-based scoring metrics, while still complex, provide a greater opportunity for engineers to directly tweak weights in specific situations.Ó

But now, Google has incorporated deep learning into its search engine. And with its head of AI taking over search, the company seems to believe this is the way forward.

Losing Control

ItÕs true that with neural nets, you lose some control. But you donÕt lose all of it, says Chris Nicholson, the founder of the deep learning startup Skymind. Neural networks are really just mathÑlinear algebraÑand engineers can certainly trace how the numbers behave inside these multi-layered creations. The trouble is that itÕs hard to understand why a neural net classifies a photo or spoken word or snippet of natural language in a certain way.

ÒPeople understand the linear algebra behind deep learning. But the models it produces are less human-readable. TheyÕre machine-readable,Ó Nicholson says. ÒThey can retrieve very accurate results, but we canÕt always explain, on an individual basis, what led them to those accurate results.Ó

What this means is that, in order to tweak the behavior of these neural nets, you must adjust the math through intuition, trial, and error. You must retrain them on new data, with still more trial and error. ThatÕs doable, but complicated. And as Google moves search to this AI model, itÕs unclear how the move will affect its ability to defend its search results against claims of unfairness or change the results in the face of complaints.

These concerns arenÕt trivial. Today, Google is facing an European anti-trust investigation into whether it unfairly demoted the pages of certain competitors. What happens when itÕs really the machines making these decisions, and their rationale is indecipherable? Humans will still guide these machines, but not in the same way they were guided in the past.

In any event, deep learning has arrived on Google Search. And the company may have used other forms of machine learning in recent years, as well. Though these technologies sacrifice some control, Google believes, the benefits outweigh that sacrifice.

Deep Learnings

To be sure, deep learning is still just a part of how Google Search works. According to Bloomberg, RankBrain helps Google deal with about 15 percent of its daily queriesÑthe queries the system hasnÕt seen in the past. Basically, this machine learning engine is adept at analyzing the words and phrases that make up a search query and deciding what other words and phrases carry much the same meaning. As a result, itÕs better than the old rules-based system when handling brand new queriesÑqueries Google Search has never 

But over time, systems like this will play an even greater role inside Internet services like Google Search. At one point, Google ran a test that pitted its search engineers against RankBrain. Both were asked to look at various web pages and predict which would rank highest on a Google search results page. RankBrain was right 80 percent of the time. The engineers were right 70 percent of the time.

This doesnÕt detract from SinghalÕs work. He joined Google in 2000, and a year later was named a Google Fellow, the highest honor Google bestows on its engineers. For most of GoogleÕs history, he has ruled the companyÕs search engine, and that search engine pretty much ruled the Internet.

But machine learning is rapidly changing that landscape. ÒBy building learning systems, we donÕt have to write these rules anymore,Ó John Giannandrea told a room full of reporters inside Google headquarters this fall. ÒIncreasingly, weÕre discovering that if we can learn things rather than writing code, we can scale these things much better.Ó

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