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My purpose here is primarily to elicit discussion. I realize that making such choices may be audacious, but it is meant to be merely a personal statement. Each of them can be reduced to a generalization that, let us hope, is both gracefully simple and exceedingly far-reaching. I present here examples of what in my mind constitute paradigm shifts and drifts in microbiology. The definition does not readily lend itself to quantitative analysis, and I will use a personal reading of Kuhn's terms. Borrowing from the language of influenza virology, I will call the latter "paradigm drifts." How do these concepts apply to the microbial sciences?Ī paradigm shift, in the Kuhnian view, must have these attributes: unprecedented, open-ended, broad, simple, and fruitful.
#SOCIAL PARADIGM SHIFT SERIES#
In 1962, Thomas Kuhn wrote a book of seminal importance, The Structure of Scientific Revolutions, wherein he introduced the concept of "paradigm shift." Kuhn proposed that science advances through a " series of peaceful interludes punctuated by intellectually violent revolutions," in which "one conceptual world view is replaced by another." Paradigm shifts occur rapidly other significant insights take their time in developing and are the stuff of "normal" science. We are witnessing in real time the changes that could potentially rethink every industry and area of human activity.The original version of this essay appeared in a 2009 issue of ASM's magazine, Microbe. It seems that both corporates and other sector players are starting to consolidate across verticals. This sector is perhaps the hottest in terms of exits and acquisitions, with over 133 such deals in 2017 and over $18bn invested. A process fuelled by the exponential increase of investment across AI, culminating with 2017, when over $11bn was invested across 1174 deals, doubling from 2016 in absolute and relative terms ( data from Pitchbook AI Report 2018).
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It is expected that many such AI technologies will start to be applied across sectors, commercialised, and later upgraded. Further enhanced by established statistical analysis, an evolution from probability to Markov simulations pattern recognition, and decision systems as a subset. Cloud computing, lowering costs of data storage, the adoption of smart devices and the exponential increase in data generated, made this an even better momentum.Įvolution Data technologies and data systems. The economics of bytes interacting with the world of atoms. The cost of computational power (Moore’s law), had a positive effect of lowering the entry barriers for entrepreneurs and researchers, leading to an acceleration of innovation across the globe. There are broadly 5 trends that are converging, creating a nurturing platform for experimentation and innovation:
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The technologies have been around for a while, but why are we getting excited about it now. Further, it is moving closer to simulate emotions such as empathy. It is uncertain which of these scenarios or a mix of potential realities will unfold of the next three decades, what it is clearer than before is that AI technology is now emulating human characteristics and qualities, such as creativity, vision, speech, analytical abilities with multiple streams of data (structured or not).
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From technological socialism to a singularity where we all enjoy the endless potential of General AI, all the way to a dystopic landscape of radical selection, a rise of robots, a contraction of the global population and world where being human will not be a quality. These headlines lead many experts in our space to imagine very different realities for the next generations. There is an associated fear, and growing body of literature and research trying to quantify the side effects of AI and automation more broadly, as those technological advancements reach their respective tipping points.Īmong some of the findings of such studies are systemic unemployment, widening income gap, optimal consumption and an attack on the open competitive market. At the World Economic Forum 2018, in Davos, AI was one of the two major discussion topics, with clear ramification across industry sectors, with a potential for disruption at national, regional and global level. This is not just a popular topic in the investment ecosystem.
#SOCIAL PARADIGM SHIFT HOW TO#
How To Choose Between Angular And React For Your Next Project TensorFlow Object Detection API tutorialģ. AI, Machine Learning, & Deep Learning Explained in 5 MinutesĢ. Source: Thompson Reuters Trending AI Articles:ġ.
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