Another Samsung smartphone explodes, this time it’s the Galaxy S7

By tech2 News Staff /  16 Nov 2016 , 10:44

Just when you thought the exploding smartphones (Galaxy Note 7) were taken care of, a new smartphone has been reported to blow up. According to Amarjit Mann, he felt his Galaxy S7 phone getting warm in his pocket while he was driving. As soon as he took it out, it exploded in his hand causing second degree burns on his hands and third-degree burns on his wrist.

The owner of the smartphone added that the burning handset was stuck to his hand before he was able to throw it out of his car’s window, “This is a nightmare for me, I’ve never seen anything like this. I should’ve lost my eyes, or my cheeks or anything could have happened. I luckily threw it outside. It should have damaged my whole car. I just saw smoke and nothing else.”

Now before you panic, let us tell you that not all Galaxy S7 smartphone are exploding. It was probably one of the few unlucky units that faced an unprecedented battery failure. For that matter, even a few iPhone devices have been reported to explode.

However the news is something that the company should worry about as it recently issues a worldwide recall and halted production of the Galaxy Note 7 as the smartphone was catching on fire as well as exploding. Samsung also had reportedly recalled 2.8 million washing machines in the US as they were falling apart and hurting consumers during usage. If the exploding cases continue, Samsung is going to have a rough time.

WhatsApp temporarily pauses user data sharing with Facebook in Europe

Representational image: Reuters

  16 Nov 2016 , 10:31

WhatsApp has temporarily suspended giving parent company Facebook information about users in Europe for ad targeting, responding to concerns there over privacy, a source close to the matter said Tuesday. Conversations with officials in Europe over the past few months resulted in the social network deciding to only tapping into WhatsApp user data there for purposes such as fighting spam, according to the source.

The break was described as an effort to give regulators time to share privacy concerns and for Facebook to consider ways to address them. German data protection authorities in September cited privacy concerns when they blocked Facebook from collecting subscriber data from WhatsApp there.

“It has to be (the users’) decision whether they want to connect their account with Facebook,” Hamburg’s Commissioner for Data Protection and Freedom of Information Johannes Caspar said at the time. “Facebook has to ask for their permission in advance.”

WhatsApp announced in August that it would begin sharing data with Facebook, in a bid to allow better targeted advertising and to combat spam on the platform. Users of the instant messenger were given the ability to opt out of sending information to Facebook through settings in WhatsApp’s applications on smartphones.

European data protection group G29 formally expressed its concerns at the end of October. The G29 sent letters asking Facebook and WhatsApp to stop sharing data until appropriate legal safeguards were in place. The sharing of WhatsApp user information with Facebook went beyond what subscribers consented to in the original terms of service, the G29 reasoned.

Facebook bought WhatsApp about two years ago in a deal valued about $19 billion. In mid-September, the European Commission recommended tighter privacy and security requirements for services including WhatsApp and Microsoft-owned video calling service Skype, saying they should be regulated more like traditional telecoms.

Under the proposal, the commission would require companies like WhatsApp or Skype to offer emergency-calling services when customers dial traditional phone numbers as well as obey stricter privacy rules.

AFP

Google announces major investment in London assuring commitment to post-Brexit UK

Image Credits: Reuters

  16 Nov 2016 , 09:34

Google delivered a vote of confidence in London’s future as a technological hub after the Brexit vote on Tuesday by announcing plans for a new building in the King’s Cross area of the city that will house thousands of extra engineers. Google’s Chief Executive Sundar Pichai said computer science had a great future in Britain, citing the talent pool, educational institutions, and passion for innovation present in the country.

“That’s why we are investing in London in both engineering talent and infrastructure,” he said. The 10-storey building, Google’s first wholly owned and designed outside the United States, will increase its presence in King’s Cross to more than 1 million square feet, enough for more than 7,000 employees in total, the company said.

Google has 5,700 employees and contractors in the UK, including about 2,000 engineers housed in the recently opened building in King’s Cross where Pichai announced the expansion. Pichai, who became CEO in October 2015 when parent company Alphabet Inc was created, said he was optimistic about Britain’s future, despite the uncertainty caused by June’s vote to leave the European Union.

“Historically, the UK has been an open and connected economy, and like a lot of businesses we are proud of and rely on the fact that we recruit the best talent from around world,” he said. “We are optimistic that this situation will continue.” “We understand there is uncertainty and even concerns about topics like Brexit and the pace of technological change in our times, but we know for certain that web and digital technology will be an engine of growth for the UK for years to come.”

British Finance Minister Philip Hammond said the investment showed leading firms were still choosing to invest in Britain, while the Mayor of London Sadiq Khan said inflows remain “robust” post-Brexit. “London isn’t just the tech capital of Europe, we are on the shoulder of New York and we are catching up with Silicon Valley,” Khan said at the event.

“Investment into the capital post-Brexit remains robust, so Google’s expansion will further strengthen our city’s reputation as a global leader in digital technology.” Pichai made reference in his speech to another event that exposed a division in a western society: the U.S. election. “Recent events, including the election in the U.S., have clearly surfaced challenges with inequality and people feeling marginalized,” he said.

These were “long-term and difficult” problems to solve, he said, but it was his hope that Google would play a constructive role in addressing some of these challenges. The company, along with Facebook, on Monday announced measures aimed at halting the spread of “fake news” on the internet by targeting how some purveyors of phony content make money: advertising. The shifts comes as Google, Facebook and Twitter Inc face a backlash over the role they played in the U.S. presidential election by allowing the spread of false and often malicious information that might have swayed voters toward Republican candidate Donald Trump, who won the Nov. 8 vote.

Reuters

Google uses machine learning to upscale and enhance low quality photos

Image: Google

By Aditya Madanapalle /  15 Nov 2016 , 18:36

Image upscaling is often made fun of in movies and television series, for extracting impossible levels of image information from low quality, blurry photos. Typically law enforcement agencies approach a technician with blurry images, and after a few keystrokes, a high resolution images suddenly emerges. Google has developed technology called Rapid and Accurate Image Super-Resolution (RAISR), that actually works similar to what is shown in this clip from CSI.

The technology is not just for law enforcement agencies. The rapid evolution of both cameras and screens means that all of us have collections of older low resolution photos that we look at in newer high resolution screens. While there are upscaling and enhancing techniques around, none of them can fill in the missing information. Mostly, these algorithms work by guessing pixels based on the pixels nearby, creating aliasing artifacts. Google has a machine learning approach that does not directly bring in the missing image information, but does preserve and build on the underlying structure.

Google RAISR in action. Image: Google.

The technique uses machine learning to train on two sets of images, a high resolution version, and a low resolution version. The machine generates a set of filters that compares the two versions, and then enhances the low resolution image with the filters. If a high resolution image is not available, the technique can still be used. The AI is trained on the upscaled image based on traditional linear upscaling techniques.

Image: Google

RAISR can be used on mobile phones as well, and processes the images 10 to 100 times faster than traditional methods. The enhanced images are less blurry than current approaches. The RAISR technique can be used to improve pinch to zoom functionality in mobile phones. Lower resolution images can be sent over communication services to conserve on bandwidth, and these images can be restored to the original quality by the recipient.

You can see more examples of RAISR in action here.

How to quickly deploy an OpenVPN server

VPN

Don't let a VPN server deployment bog you down. See how to get one up and running quickly with a TurnKey Linux solution.

By Jack Wallen | November 14, 2016, 12:20 PM PST
If your business has grown to the point where you need to offer a VPN to your employees, the thought of spending either the money or the time deploying such a solution might send you into apoplectic fits. It doesn't have to—there are so many incredible solutions available, some of which are free and even easy to unleash.


One such solution is OpenVPN. With this server software, you can either install it onto an existing platform, or you can opt to go the virtual route with a virtual appliance. I find that the easiest path to success is to use the TurnKey Linux OpenVPN virtual appliance. With this solution, you can spin up a VPN in a few minutes.

Let's walk through the process of launching the OpenVPN VM with the help of VirtualBox.

Importing the virtual appliance

The first thing you must do is download the appliance file. Once you have that file on your host machine, unzip it. Now you must import the .ova file into VirtualBox. To do this, open VirtualBox and click File | Import Appliance. When prompted, click the File icon and, from your file manager, navigate to and select the turnkey-openvpn-XXX-jessie-amd64.ova file (XXX is the release number). Click Next in the import wizard and then go through the default settings (Figure A).


Figure A


The default settings for the OpenVPN virtual appliance.

The one setting you'll probably want to change is the default allocated RAM (the default is only 512MB). Double-click that entry and bump it up to what you feel is adequate for your needs. Once you've done that, click Import, and the process will complete.
Starting the VM

Select the TURNKEY OPENVPN from the left navigation and click Start. During the startup process, you'll be asked to enter a password for the root user (Figure B). Type in a password (make it challenging) and hit Enter on your keyboard.


Figure B


Setting a password for the root user account.

Next you'll be required to select a profile for the server (Figure C). You can select from:
Server: This profile accepts VPN connections from clients and optionally configures a private subnet behind the OpenVPN enabling client access.
Gateway: This profile accepts VPN connections from clients and automatically configures connecting clients to route all their traffic through the VPN.
Client: This profile initiates VPN connections to an OpenVPN server.

Figure C


Select your choice of Server, Gateway, or Client.

Your selection will depend upon the needs of your network and your clients, but more than likely the Server option will suffice.

Now follow these steps.
Enter an email address for the OpenVPN server key.
Configure an IP address or FQDN that will enable clients to reach the VPN.
Enter a Classless Inter-Domain Routing (CIDR) subnet address pool to be used by your VPN. (This will be in the form of 192.168.1.0/24. Make sure that entry is specific to your networking needs.)
Supply the CIDR subnet that will exist behind the server that the clients will reach (this address will be in the same form as the previous CIDR address).

Once you hit Enter after setting the second CIDR address, walk away from the machine, as it will take awhile to complete the final phase of the process. When you're presented with the TurnKey Backup and Migration page, tab down to Skip and hit Enter. The last thing to do is enter an email address that will receive all local system notifications; type the address and hit Enter (you can skip this step).

Before you can log into your OpenVPN server, you'll be prompted to either install or skip any available updates to the system. I highly recommend you install these updates. This process can take quite awhile, so step away again and allow the updates to complete. When the updates finish, reboot the machine. Once the machine reboots, you'll be presented with all the information you need to connect to your VPN (Figure D). Your OpenVPN server is up and running and ready for configuration.

Figure D


Your connection information for your OpenVPN server.
Final steps

I highly recommend you log into the Webmin address (with username root and the password you set during installation), so you can further configure the virtual appliance. You will not find a GUI frontend for configuring the OpenVPN server here—for this, check out the /etc/openvpn/server.conf file. To do that, you'll need to secure shell into the server (information on connecting is presented to you once boot up has finished). Once logged in, you can edit the config file and add users with the openvpn-addclient USER EMAIL_ADDRESScommand (USER is a username and EMAIL_ADDRESS is the client's email address)

How to connect a Linux machine to Google Cloud Print

connect a Linux machine to Google Cloud Print

By Jack Wallen | November 14, 2016, 8:55 AM PST

For a quick and easy way to extend your Linux printer server to your Google Cloud Print account, follow the steps in this tutorial.

If you have a Linux printer server, and you need to enable users to be able to print to your cloud-based printers, one easy method is to attach CUPS to a Google Account for use with Google Cloud Print. Great solution, right? But how do you pull that off?


Someone in the Linux community has made it not only possible, but easy. Let me walk you through the steps of connecting your CUPS printer server to a Google Cloud Print account.

I will be doing this on a Ubuntu 16.10 machine. The necessary software is available for Ubuntu as well as rpm-based distributions, Arch Linux, Gentoo, Portage ebuild, OS X, FreeBSD, and more.
Installation

The first thing you must do is install the necessary package. To do this, we must add a repository. Open your terminal window and issue the command:sudo add-apt-repository ppa:simon-cadman/niftyrepo

Now, update apt with the command:sudo apt-get update



Finally, install the software with the command:sudo apt-get install cupscloudprint


Once the installation is ready, you can connect your server to the Google Cloud Print account.

Connecting to your account


The developer of cupscloudprint has made this task incredibly simple. Go back to your terminal window and issue the command:sudo /usr/share/cloudprint-cups/setupcloudprint.py

The first thing that will happen is you'll be prompted to enter the email address associated with the cloud account. Type that address and hit enter. Next you'll be given a link to copy and paste into your browser (Figure A).

Figure A


Copy and paste the provided link into the browser.

If you haven't logged into your Google account from this browser, you'll be prompted for that information; otherwise, you'll be asked to Allow CUPS Cloud Print to manage your printers.
Click Allow.
You'll be given a code; copy that code and paste it into the terminal window at the Code From Google: prompt.
The command will output the accounts you currently have configured for Cloud Print. If you're happy with that, type y and hit Enter.
You'll be asked if you want to add all the printers associated with your account. Type y and hit Enter.
Once the printers have been added, you'll be asked if you want to use a prefix for the printers. If you do, type y, hit Enter, and then enter the necessary prefix; otherwise, type n and hit Enter.

Any printer you have associated with Google Cloud Print is now available to your Linux printer server. Quite painless, wouldn't you say?
Extending your printer server


What better way to extend your Linux printer server than to connect it to your Google Cloud Print account? With this setup, you can easily print to different locations (even in different states), so you don't have to expend the resources connecting printers to VPNs or other, costlier and complex, solutions.

IBM, NVIDIA partner for 'fastest deep learning enterprise solution' in the world

IBM and NVIDIA

By Conner Forrest | November 14, 2016, 7:25 AM PST

IBM and NVIDIA recently teamed up to announce IBM PowerAI, a software toolkit that accelerates machine training for AI solutions and will boost IBM Watson's capabilities.

IBM PowerAI, a new deep learning software toolkit announced Monday, could help train computers for machine learning and AI tasks faster than ever before. The solution, a joint project from IBM and NVIDIA, runs on an IBM server built specifically for AI and uses NVIDIA NVLink as well.

According to a press email announcing the availability of the solution, IBM PowerAI is the "world's fastest deep learning enterprise solution," and it will "help train computers to think and learn in more human-like ways at a faster pace."

This new toolkit was designed to work with IBM's Power Systems LC lineup of Linux servers, specifically the IBM Power S822LC for High Performance Computing (HPC). That server has NVIDIA's latest GPU technology on board, which helps further its potential for use in deep learning and AI applications.


While this new product is geared toward "emerging computing methods of artificial intelligence" like deep learning, it also has implications for IBM's better-known cognitive computing project, Watson. IBM PowerAI will bolster Watson's enterprise AI skills by providing the platform with additional training.


"PowerAI democratizes deep learning and other advanced analytic technologies by giving enterprise data scientists and research scientists alike an easy to deploy platform to rapidly advance their journey on AI," Ken King, general manager for OpenPOWER, said in the email. "Coupled with our high performance computing servers built for AI, IBM provides what we believe is the best platform for enterprises building AI-based software, whether it's chatbots for customer engagement, or real-time analysis of social media data."

Of course, none of this matters if there aren't real-life applications for the technology. In the press email, IBM noted that technologies such as the deep learning this toolkit provides have been used for fraud protection in banks, facial recognition applications, and even in self-driving cars.

In the past, IBM Watson has been used in verticals like healthcare, legal, finance, retail, cybersecurity, and even fantasy football. So, it's possible that we will see IBM PowerAI in these fields as well.


Live Webcast: Red Bull Racing: the hard science behind Formula One

Formula One is an incredibly fast moving sport. There can be as little as a few hundredths of a second between first and second place. The speed of innovation is extreme - and with Formula One regulations becoming more stringent each year, increasing the volume and quality of simulations to test new designs becomes increasingly critical. Join Red Bull Racing as they discuss the high-tech innovations needed to achieve success and how IBM solutions help - from the drawing board to race day! And learn how you can translate this to achieve 30-50% greater throughput for your research, engineering and design workloads. Register for this webcast now!
Webcasts provided by IBM

Existing IBM customers who have IBM's Power S822LC for HPC server can access IBM PowerAI immediately at no additional charge, the email said.
The 3 big takeaways for TechRepublic readers


IBM and NVIDIA recently partnered on IBM PowerAI, a new software toolkit, to accelerate deep learning initiatives in business.
PowerAI is meant to run on the IBM Power S822LC for High Performance Computing and exists as a separate product, but will work with Watson.
IBM sees these deep learning technologies as important to verticals like healthcare, finance, retail, and self-driving cars.