Many attempts have been made to build an artificial brain. This paper aims to contribute to the conceptualization of an artificial learning system that functionally resembles an organic brain in a number of important neuropsychological aspects. Probably the techniques (algorithms) required are already available in various fields of artificial intelligence. However, the question is how to combine those techniques. The combination of truly autonomous learning, in which "accidental" findings (serendipity) can be used without supervision, with supervised learning from both the surrounding and previous knowledge, is still very challenging. In the event of changed circumstances, network models that can not utilize previously acquired knowledge must be completely reset, while in representation-driven networks, new formation will remain outside the scope, as we will argue. In this paper considerations to make artificial learning functionally similar to organic learning, and the type of algorithm that is necessary in the different hierarchical layers of the brain are discussed. To this end, algorithms are divided into two types: conditional algorithms (CA) and completely unsupervised learning. It is argued that in a conceptualisation of an artificial device that is functional similar to an organic learning system, both conditional learning (by applying CA’s), and non-conditional (supervised) learning must be applied.
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Working as speech acts that delineate online communities, claims to victimhood tend to evoke contestation. Their inherent political nature spurs user engagement in the shape of clicks, shares, emojis, and so on. TikTok’s multimodality has given rise to new practices of engagement that significantly shape how victimhood is communicated and negotiated. This study draws attention to the platform vernacular practice of the ‘stitch.’ Allowing users to respond to someone else by ‘remixing’ social media content of others, the stitch is a platform practice designed for commentary. We zoom in on stitched videos networked by hashtags, published in relation to the Israel-Hamas war. TikTok’s multimodality expands user pathways that connect claimants and those who contest them. Moving beyond hashtag hijacking the stitch elevates a practice of commentary that turns victimhood politics into a spectacle that politicizes formerly less political realms, and that further blurs the boundaries between on- and offline spaces. The analysis shows how stitched videos are especially used for antagonist encounters where they crowd out the ‘original’ post to which they respond. In this way, stitches can be seen as tools that aid platformed ‘regimes’ of visibility that prioritize the antagonist encounter in order to commodify them.
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