The most used buzzwords so far in 2017 are Artificial Intelligence (AI) and Machine Learning (ML) but it is becoming clear that their use covers widely disparate situations including analytics, autonomous cars, cyber security, IoT, marketing, digital assistants and the father of it all – big data.
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Certainly by now we’ve all seen enough empirical and anecdotal evidence in support of the value to the business of diversity in the workplace to dispel any notion that it’s just another HR inconvenience to deal with.
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Intelligent machines, long promised and never delivered, are finally on the horizon. Sufficiently intelligent robots will be able to operate autonomously from human control. They will be able to make genuine choices.
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So many of the tasks that we now take for granted once had to be done manually. Washing a load of laundry no longer takes all day; our phone calls are directed to the correct departments by automated recordings; and many of our online orders are now selected and packed by robots.
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What distinguishes Elon Musk’s reputation as an entrepreneur is that any venture he takes on comes from a bold and inspiring vision for the future of our species. Not long ago, Musk announced a new company, Neuralink, with the goal of merging the human mind with AI.
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If you look past the hype, existential concerns, and fear that Alexa is a CIA mole, there are some genuinely exciting developments happening in the world of artificial intelligence.
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Many leaders are now aware of the dangers of collaboration overload and collaboration-tool overload in the workplace. The evidence continues to mount that, for many organizations, the costs associated with meetings, emails, IMs and other forms of workforce collaboration now exceed the benefits.
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TL;DR The most accurate machine learning systems to date are those that use a “human-in-the-loop” computing paradigm. Though we have seen huge advances in the quality and accuracy of pure machine-driven systems, they tend to fall short of acceptable accuracy rates.
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In 2013, the Oxford Martin School released a report that looked at the automation of work, assessing the likelihood that robots and other technologies would replace humans. It concluded that of the 702 job categories examined, 47% were susceptible to automation within the next 20 years.
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IN THE early 20th century the future seemed bright for horse employment. Within 50 years cars and tractors made short work of equine livelihoods. Some futurists see a cautionary tale for humanity in the fate of the horse: it was economically indispensable until it wasn’t.
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