Are we defenseless against AI, deepfake, and the rapid spread of disinformation? Join the first episode in our podcast series part of the Jean Monnet Chair EU-ACT DIGITAL, an initiative spotlighting EU digital policy. Our very first guest, Member of European Parliament Bart Groothuis (part of the Committee on Industry, Research and Energy), provides his expert insights on the state of digitalisation in the EU while being interviewed by European Impact’s Paul Schuchhard and European Studies students Francisco van Ruijven and Joana Pereira Grilo from The Hague University of Applied Sciences. Visit https://eu-act.digital/ to find out more about the Jean Monnet Chair EU-ACT DIGITAL.
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What’s online video today, fifteen years into its exponential growth? In the age of the smart phone, video accompanies, informs, moves, and distracts us. What started off with amateur prosumers on YouTube has spread to virtually all communication apps: say it with moving images. Are you addicted yet? Look into that tiny camera, talk and move the phone, show us around, and prove the others out there that you exist!With this third reader the Video Vortex community — initiated in 2007 by the Instituteof Network Cultures — proves that it is still alive and kicking. No matter its changes, the network is still driven by its original mission to develop a critical vocabulary for this rapidly spreading visual culture: what are the specific characteristics of online video in terms of aesthetics and political economy of image production and distribution, and how do they compare to film and television? Who is the Andre Bazin of the YouTube age? Honestly, why can’t we name a single online video critic? Can we face the fact that hardly anyone is using the internet? What are you going to do with that 4K camera in your smartphone? Have we updated Marshall McLuhan’s hot and cold media for our digital era yet? Who dares? We see the Woman with a Smartphone Camera in action, but who will be our Vertov and lead the avant-garde? Who stops us? Let us radically confront the technological presence as it is and forget the pathetic regression to past formats: radical acceptance of the beautiful mess called the net.
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We present a novel architecture for an AI system that allows a priori knowledge to combine with deep learning. In traditional neural networks, all available data is pooled at the input layer. Our alternative neural network is constructed so that partial representations (invariants) are learned in the intermediate layers, which can then be combined with a priori knowledge or with other predictive analyses of the same data. This leads to smaller training datasets due to more efficient learning. In addition, because this architecture allows inclusion of a priori knowledge and interpretable predictive models, the interpretability of the entire system increases while the data can still be used in a black box neural network. Our system makes use of networks of neurons rather than single neurons to enable the representation of approximations (invariants) of the output.
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