The Future


Take 5: How Humans Benefit as Machines Get Smarter

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In a recent study, Kellogg's Eli Finkel and colleagues had participants share a difficult personal story to a robot named Travis. When Travis reacted by moving and displaying supportive text, participants rated it as more social and competent. In a recent podcast, Ferrucci describes a future where humans and computers grow up together. The team found that traders made less lucrative trades when they were in a highly emotional state or a low emotional state.


The Future of Artificial Intelligence and Cybernetics

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For example, if the robot brain has roughly the same number of human neurons as a typical human brain, then could it, or should it, have rights similar to those of a person? Also, if such robots have far more human neurons than in a typical human brain--for example, a million times more neurons--would they, rather than humans, make all future decisions? With those cases, the situation isn't straightforward, as patients receive abilities that normal humans don't have--for example, the ability to move a cursor on a computer screen using nothing but neural signals. It's clear that connecting a human brain with a computer network via an implant could, in the long term, open up the distinct advantages of machine intelligence, communication, and sensing abilities to the individual receiving the implant.


What My 90-Year-Old Mom Taught Me About The Future Of AI In Health Care

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The plan was to have her watch her weight daily, and every time there was any sign of increased fluid, to recommend an extra dose -- an extra pill -- of Lasix, to restore her fluid balance. On the other hand, a friend's father, a physician, had defied the odds and lived for decades with severe heart failure by weighing himself daily and adjusting his medications accordingly. If her weight increases by more than 1 pound in one day, recommend one extra Lasix pill. If the weight does not return to normal by the second day after the extra dose, then give one additional dose the third day.


The Future of Artificial Intelligence and Cybernetics

#artificialintelligence

For example, if the robot brain has roughly the same number of human neurons as a typical human brain, then could it, or should it, have rights similar to those of a person? Also, if such robots have far more human neurons than in a typical human brain--for example, a million times more neurons--would they, rather than humans, make all future decisions? With those cases, the situation isn't straightforward, as patients receive abilities that normal humans don't have--for example, the ability to move a cursor on a computer screen using nothing but neural signals. It's clear that connecting a human brain with a computer network via an implant could, in the long term, open up the distinct advantages of machine intelligence, communication, and sensing abilities to the individual receiving the implant.


6 Things CMOs Can Do Now To Prepare For The Future Of AI-Powered Marketing

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I've called this human-to-machine-to-human (H2M2H) marketing and AI-powered systems will make these processes better for both customers and marketers. According to Jake Sorofman of Gartner, "We've understood modern marketing to be using machines as the basis for taking a manual process, standardizing it, and automating it for execution at scale. A good example of this would be programmatic media and real-time bidding, where a market is made in the moment in a way that's fully automated, removing human beings from the equation. Human beings are defining parameters and they're defining budgets, they're defining goals and leaving the machines to figure out the right match."


What the Future of Artificial Intelligence in Government Could Look Like

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This piece is adapted from their new study, How much time and money can AI save government? At the high end, we estimate within the next 5-7 years, as many as 1.1 billion working hours could be freed up in the federal government every year, saving a whopping $37 billion annually. Ultimately, AI could potentially free up 30 percent of federal employees' time. The enormous potential of AI to liberate resources offers tremendous promise for public managers faced with limited resources and expanding backlogs.


Rise of the robot

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Since GE Aviation's Bromont plant started using automation in the 1990s, the number of human hours needed to produce output has dropped an average of five per cent per year. The Bromont experience is a small example of a larger trend occurring in industries ranging from manufacturing to energy to banking: Automation unleashes gains in productivity that can actually boost employment and benefit the economy as a whole, though the experience will no doubt be disruptive for many of those who initially lose their jobs. A study by the University of Toronto's Mowat Centre found that in the 10 years leading up to 2014, the number of people working in the province's manufacturing sector fell to just over 10 per cent, down from nearly 16 per cent. But subject to business cycles, the Mowat Centre study found that Ontario's higher productivity jobs remained in place.


The Future of AI is Here - PwC

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AI, as a true change agent, is coming, and in many ways, its early rumblings are already being felt. It's clear that some people will eagerly adopt and integrate the new tools and ways of working it makes possible, while others will be more cautious or even oppose the changes it brings to their life or work. An open mind will be the biggest asset in the near future, as the technology advances and we continue to experiment with how to use AI to solve problems--in our personal lives, professional lives, and society at large. Those who think practically and critically will ride the waves of these advancements instead of being left behind.



The Future of AI is Analog!

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The perceptual process (or the process of coping with situations in general) amounts to collapsing vast clouds of hypotheses aroused by initial evidence, leaving active only tiny subsets that support each other by mutual arguments. It creates well-organized connectivity patterns called net fragments. Apply this to perception: The sensory input is highly ambiguous and creates a large cloud of hypotheses. All these nano-processors are connected by axons, ionic wires, but very little information is actually moved around: not the values of quantities (synaptic weights, membrane potentials etc.)