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Departing eclipse watchers are causing traffic jams from Portland to Charleston.
No special filtered glasses required to stare at the sun in a Gear VR headset.
Only about 6 percent of Americans will see the totality today.
Even if itrsquo;s cloudy, even if itrsquo;s not total near you, itrsquo;s worth experiencing.
Ahead of the rare solar event, eye doctors describe the dangers of risky viewing.
There is a great deal of interest from those with traditional IT skillsmdash;such as enterprise architects, developers, and networking engineersmdash;to steer themselves into a cloud computing career that will not only provide job protection, but pay better as well.However, the path to cloud computing riches is not that clear for most.[ What is cloud computing? Everything you need to know now. | Download the public cloud megaguide PDF: Amazon, Microsoft, Google, IBM, and Joyent compared. | Stay up on the cloud with InfoWorldrsquo;s Cloud Computing Report newsletter. ]The good news: There is a path for many IT pros into the cloud.

This article shows you how to map a path to those jobs from your current state if you are an enterprise architect, database admin, application developer, system admin, test-and-acceptance engineer, or networking engineer.To read this article in full or to leave a comment, please click here
European retail leader will prioritise customer experience for their online store[LONDON] --- [10 AUGUST 2017] Carpetright, UKrsquo;s leading flooring and beds retailer, has partnered with Qubit, a leader in marketing personalisation technology, to help drive in-store sales through tailored online experiences.

The company is now prioritising online personalisation; recognising that the path to purchase often starts long before a customer walks into a store.

Carpetright trade from 434 stores and concessions in the UK as... Source: RealWire
Today, a dangerous new trend is emerging: steganography is increasingly being used by actors creating malware and cyber-espionage tools. Most modern anti-malware solutions provide little, if any, protection from steganography, while any carrier in which a payload can be secretly carried poses a potential threat.

SambaCry is coming

Not long ago, news appeared online of a younger sibling for the sensational vulnerability EternalBlue.

The story was about a new vulnerability for *nix-based systems – EternalRed (aka SambaCry). On May 30th our honeypots captured the first attack to make use of this particular vulnerability, but the payload in this exploit had nothing in common with the Trojan-Crypt that was EternalBlue and WannaCry.
For decades, industrial control systems have been generating enormous volumes of data, but in many cases that data hasnrsquo;t been fully employed to help companies reduce operating costs, improve reliability, and increase productivitymdash;three goals that amount to the holy grail of manufacturing. Until recently, the path forward has been blocked by insufficient compute power, storage, and machine learning technologies to allow companies to harness the richness of the data they generate.Today, all of this is changing.

Thanks to the rise of the Industrial Internet of Things, dramatic advances in computing systems, and the rapid maturation of machine learning algorithms, manufacturers now have the ability to collect, store, and analyze huge amounts of data in real time to turn it into actionable information.

They can use this information to enhance operations, remedy equipment issues proactively, improve plant availability, and meet countless other goals that drive toward better margins for the business.To read this article in full or to leave a comment, please click here
Ars' Sean Gallagher remembers his singular contribution to drone warfare's development.
In todayrsquo;s digitally driven world, enterprises have gotten pretty good at the business of capturing and storing enormous amounts of data. Now they are challenged to unearth the business value that is buried in all of that data by using advanced analytics techniques.For many organizations, the hard part is figuring out how to move forward in a strategic manner.

They have the data, they have business analysts, and they have the IT infrastructure. Now they are asking: Whatrsquo;s possible with all this data? How do we get started down the path to advanced analytics and machine learning? How do we cultivate the expertise we need?This really isnrsquo;t a technology problem.

This is a people problem.

At a technology level, powerful, easy-to-use analytical platforms and solutions are now more accessible than ever before.

The real organizational challenge is one of cultivating the expertise and experience needed to capitalize on data analytics.

This challenge is exacerbated by the speed at which analytics tools and platforms are evolving.

Even if you have bona fide data scientists on your team, they will need help keeping up with the latest methods.To read this article in full or to leave a comment, please click here