2 research outputs found

    A Vision for the future

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    For the past 40 years, computer scientists and engineers have been building technology that has allowed machine vision to be used in high value applications from factory automation to Mars rovers. However, until now the availability of computational power has limited the application of these technologies to niches with a strong enough need to overcome the cost and power hurdles. This is changing rapidly as the computational means have now become available to bring computer vision to mass market applications in mobile phones, tablets, wearables, drones and robots enabling brand new user-experiences within the cost, power and volumetric constraints of mobile platforms

    Generating Indicators of Disruptive Innovation using Big Data: Can big data approaches exploit the wealth of information on the internet help in prediction of disruption relating to innovation of disruption relating to innovation

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    Technological evolution and its potential impacts are of significant interest to govern-10 ments, corporate organizations and for academic enquiry; but assessments of technology progres-11 sion are often highly subjective. This paper prototypes potential objective measures to assess tech-12 nology progression using internet-based data. These measures may help reduce the subjective na-13 ture of such assessments and, in conjunction with other techniques, reduce the uncertainty of tech-14 nology progression assessment. The paper examines one part of the technology ecosystem, namely, 15 academic research and publications. It uses analytics performed against a large body of academic 16 paper abstracts and metadata published over 20 years to propose and demonstrate candidate indi-17 cators of technology progression. Measures prototyped are: (i) overall occurrence of technologies 18 used over time in research, (ii) the fields in which this use was made; (iii) the geographic spread of 19 specific technologies within research and (iv) the clustering of technology research over time. An 20 outcome of the analysis is an ability to assess the measures of technology progression against a set 21 of inputs and a set of commentaries and forecasts made publicly in the subject area over the last 20 22 years. The potential automated indicators of research are discussed together with other indicators 23 which might help working groups in assessing technology progression using more quantitative 24 methods. 2
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