According to the World Economic Forum’s Future of Jobs report, some jobs will be wiped out, others will be in high demand, but all in all, around 5 million jobs will be lost. The real question is then, how many jobs will be made redundant in the 2020s? Many futurists including Google’s Chief Futurist believe this will necessitate a universal human stipend that could become globally ubiquitous as early as the 2030s.
How to Think Exponentially and Better Predict the Future - 0 views
Will AI replace Humans? - FutureSin - Medium - 0 views
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AI will optimize many of our systems, but also create new jobs. We don’t know the rate at which it will do this. Research firm Gartner further confirms the hypothesis of AI creating more jobs than it replaces, by predicting that in 2020, AI will create 2.3 million new jobs while eliminating 1.8 million traditional jobs.
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In an era where it’s being shown we can’t even regulate algorithms, how will we be able to regulate AI and robots that will progressively have a better capacity to self-learn, self-engineer, self-code and self-replicate? This first wave of robots are simply robots capable of performing repetitive tasks, but as human beings become less intelligent trapped in digital immersion, the rate at which robots learn how to learn will exponentially increase.How do humans stay relevant when Big Data enables AI to comb through contextual data as would a supercomputer? Data will no longer be the purvey of human beings, neither medical diagnosis and many other things. To say that AI “augments” human in this respect, is extremely naive and hopelessly optimistic. In many respects, AI completely replaces the need for human beings. This is what I term the automation economy.
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Machines Teaching Each Other Could Be the Biggest Exponential Trend in AI - 0 views
18 exponential changes we can expect in the year ahead - 0 views
Optimization is as hard as approximation - Machine Learning Research Blog - 0 views
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Optimization is a key tool in machine learning, where the goal is to achieve the best possible objective function value in a minimum amount of time. Obtaining any form of global guarantees can usually be done with convex objective functions, or with special cases such as risk minimization with one-hidden over-parameterized layer neural networks (see the June post). In this post, I will consider low-dimensional problems (imagine 10 or 20), with no constraint on running time (thus get ready for some running-times that are exponential in dimension!).
Socio-Cultural Longitude - 0 views
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People the world over have acquired a passing familiarity with epidemic models, critical threshold values for transmission (R0), comorbidities, and exponential growth. But these insights into the pandemic are like Harrison's H1-3; they focus on a few elements of the problem. The pandemic is every bit as much a problem of the non-linear dynamics of markets, the cognitive biases of decision-makers, the collective dynamics of groups, and the coevolution of biological species - humans, mammalian food sources, and viral agents.
The Rise and Fall of Networks - 0 views
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But on this side of the ride the network has a problem: it is now burdened with the 'extractive repulsor.' So unless the folks in charge of the platform can figure out a way to reduce the extraction at an exponential rate, even a small number of people leaving the network will quickly lead to a torrent.
Exponential growth is a pipe dream - 0 views
Newsletter - The Exponential View - 0 views
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