computing


The Top 30 Emerging Technologies (2018–2028) – Sean Moffitt – Medium

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As part of Wikibrands' Digital Periscope study and surveys (see currently open 2018 studies Current Practices and Future Trends), we have ranked the 30 emerging technologies that will impact culture, the marketplace and society the most over the next decade. With no further adieu, here is our list. We'll also admit that as much as we like to keep each of these technologies distinct and separate, many of them are interacting and blending with each other (and that's okay). We plan on evolving the 30 list and using it as a benchmark and basis for all future analysis and thought leadership to bridge the gap between holders of technology and those to put it to work. Part of our three year old odyssey to put digital transformation deeper, wider and faster inside organizations through our help and interventions.


Philosophy and the quantum computer

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The events of the past few weeks have provided much fodder to this columnist. First, there was the American grandstanding on immigration, and then the events at Cognizant Technology Solutions Corp., Infosys Ltd and Tata Consultancy Services Ltd. More recently, Cloudflare Inc., which hosts information for close to two million websites, including Uber Technologies Inc. and OKCupid, had an Internet security disaster that saw the leak of passwords, cookies, and private messages from adult dating sites. This "Cloudbleed" was discovered on 17 February, 2017, but has evidently been around for many months. Decisions, decisions--what does one chew on first?


Fog Computing Test Bed: Cutting Costs and Latency in Data Transmission

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Fabs Meet Machine Learning

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Aki Fujimura, chief executive of D2S, sat down with Semiconductor Engineering to discuss Moore's Law and photomask technology. Fujimura also explained how artificial intelligence and machine learning are impacting the IC industry. What follows are excerpts of that conversation. SE: For some time, you've said we need more compute power. So we need faster chips at advanced nodes, but cost and complexity are skyrocketing. Fujimura: Moore's Law is definitely slowing down, but I'm confident there will be continued innovation everywhere to keep it going for a while. There's a lot that every discipline of the eco-system is working on to make incremental and breakthrough improvements.


AI Companies & Cybersecurity:The Race To Build Artificial Intelligence Defenses

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Artificial intelligence, for all its mind-boggling potential, is a double-edged sword. Sure, AI might save lives through early cancer or heart disease detection. In cybersecurity, though, even AI companies worry that the bad guys will use artificial intelligence to launch more potent attacks. Little wonder, then, that computer security has become an AI hot spot. Venture capital firms are throwing money into "machine learning" startups.


How to Make an AI Project More Likely to Succeed

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A recent survey by Deloitte of "aggressive adopters" of cognitive technologies found that 76% believe that they will "substantially transform" their companies within the next three years. There probably hasn't been this much excitement about a new technology since the dotcom boom years in the late 1990s. The possibilities would seem to justify the hype. In the future, we will see new computing architectures, like quantum computing and neuromorphic chips, propel capabilities even further. Still, there remains a large gap between aspiration and reality.


Why Most of Us Fail to Grasp Coming Exponential Gains in AI

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By now, most of us are familiar with Moore's Law, the famous maxim that the development of computing power follows an exponential curve, doubling in price-performance (that is, speed per unit cost) every 18 months or so. When it comes to applying Moore's Law to their own business strategies, however, even visionary thinkers frequently suffer from a giant "AI blind spot." I give a lot of talks to successful, strategically-minded business people who can see around corners in their own industries, yet they struggle to grasp what exponential improvement really means. And a lot is riding on this exponential curve, but one technology that is particularly benefiting from it is artificial intelligence. One reason people do not grasp how rapidly artificial intelligence is developing is so simple it's almost laughable: Exponential curves don't fare well when we humans try to capture them on paper.


Robotics in business: Everything humans need to know

ZDNet

One kind of robot has endured for the last half-century: the hulking one-armed Goliaths that dominate industrial assembly lines. These industrial robots have been task-specific -- built to spot weld, say, or add threads to the end of a pipe. They aren't sexy, but in the latter half of the 20th century they transformed industrial manufacturing and, with it, the low- and medium-skilled labor landscape in much of the U.S., Asia, and Europe. You've probably been hearing a lot more about robots and robotics over the last couple years. That's because for the first time since the 1961 debut of GM's Unimate, regarded as the first industrial robot, the field is once again transforming world economies. Only this time the impact is going to be broader.


The Industrial Era Ended, and So Will the Digital Era

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In a famous scene in the 1967 movie The Graduate, a family friend takes aside Dustin Hoffman's character, Benjamin Braddock, and whispers in a conspiratorial tone, "Plastics….There's a great future in plastics." It seems quaint today, but back then plastics really were new and exciting. If the movie had been set in another age, the advice to young Braddock would have been different. He might have been counseled to go into railroads or electronics or simply to "Go West, young man!" Every age has things that seem novel and wonderful at the time, but tepid and banal to future generations. Today digital technology is all the rage because after decades of development it has become incredibly useful.


Building AI: Key Steps For Adoption And Scaling Up

Forbes Technology

And yet according to 313 executives recently surveyed by Forbes Insights--63% of whom were in the C-Suite--almost all (95%) believe that AI will play an important role in their responsibilities in the near-future. The majority of CEOs today are not drivers of AI adoption--that responsibility falls on C-level technology leaders who need to build a strong business case and show results that encourage a deeper dive into change. With that firmly in mind, Forbes Insights and Intel have taken their combined experience covering and developing technology to produce this introductory guide to AI adoption, from buy-in and deployment to building a corporate culture around data. Consider the below three steps your beginner's guide to AI. It's important to see beyond the swirl of hype and expectations around AI technologies and view them for what they really are--massive accelerators of processes and insights and profound amplifiers of human capability.