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CES Asia 2018 Showcases the Bleeding Edge in Mobility Tech and More
Held in Shanghai over the course of three days, CES Asia 2018 brings the world’s hottest consumer electronics show to Asia. In its fourth instalment in the Chinese city, CES Asia refined and developed its goal of showcasing the tech of the region in one place. With the main show in Las Vegas held six...

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CES  Asia  2018  Showcases  the  Bleeding  Edge  in  Mobility  Tech  and  More 
4 days ago by vrzone
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 computing.....nor.ai, 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.
cloud_computing  decentralization  edge  future  Industrial_Internet  IT  artificial_intelligence  centralization  machine_learning  Microsoft  data_centers 
13 days ago by jerryking
How to Secure Edge Computing
So what are the steps to secure edge computing? (1) Encrypt Everything: By encrypting all data, even if data is stolen an attacker will have limited utility. (2) Use Secure Tunnels: As edge computing isn't all located within a secured data center, connectivity should be hardened with the use of VPNs and secure tunnels. (3) Constant Iteration Beyond Initial Setup: Organizations that are deploying edge computing need to have processes in place to enable constant iteration beyond the initial setup to deal with patching and emerging security issues. (4) Employ Pro-Active Threat Detection: Since edge computing by definition is not centralized, it's critically important for providers to employ proactive threat detection technologies to identify potential issues early. (5) Automated Patching and Assertion: Given that edge computing can potentially involve large numbers of distributed devices, there is a need to make sure that patching is automated that a given patch has been validated and properly implemented.
security  iot  iiot  edge 
19 days ago by dlkinney
Microsoft Is Losing Its Edge in the Browser Efficiency Race
Despite the growing ubiquity of competitors like Chrome in the past few years, Microsoft has been trying to shift more users to adopt Edge as their primary browser. Edge was launched along with Windows 10, back in 2015, replacing the venerable Internet Explorer as the default browser for Windows. While Microsoft retained Internet Explorer’s logo...

The post Microsoft Is Losing Its Edge in the Browser Efficiency Race appeared first on .
Microsoft  Is  Losing  Its  Edge  in  the  Browser  Efficiency  Race 
23 days ago by vrzone

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