...Fabian Offert [email protected] “Intriguing Properties of Neural Networks.” By Christian Szegedy , Wojciech Zaremba , Ilya Sutskever , Joan Bruna , Dumitru Erhan , Ian Goodfellow , and Rob Fergus . arXiv preprint. 2013 . https://arxiv.org/abs/1312.6199...

... games, which depend on character-based scripting and pathfinding algorithms, are more basic than the supervised and unsupervised learning of later neural networks. Historically, developers have often spent more resources on graphics than AI systems in order to appeal to consumers through visual delights...

..., [ . . . ] there is great promise in it, for non-linearity means that the art of playing the game has a way of changing the rules” (71). As I will show, the narrator’s altered neural pathways enable him to “play the game” of identity formation in ways that subvert the “rules” of white supremacy. 13 The narrator’s...

... autodidactic neural networks, more generally, hold for the future of the humanities—and, to the degree that Dimock’s piece identifies a shifting in the profession, for the future of work in the humanities. 26 Thus, the initial dismissal by many that GPT-3 does not remotely approximate literature, let...

... to the hacker’s body even as they enter into the disembodied matrix. To “jack in” involves plugging the cyberspace deck into a neural interface; it establishes a physical connection between the plug of the deck (an early model computer) and the “jack” of the hacker’s neural interface (Gibson 1987 : 17). All...

..., then, is a problem of transmission even before we hurt. The source of pain need not be injury or disease; other “noxious stimuli” such as stretching or pressure may also produce nociceptive (harm-identifying) neural signals (Bogduk 2009 : 17). 8 In response the brain generates what neurology calls...

... Lentz, the Frankensteinian creator of a neu- ral net, to train a supercomputer in the field of literary studies to the point that it can outperform a student on a master’s exam. Another similarity between Roger’s Version and Galatea 2.2 is the emphasis on teaching. Richard learns about neural nets...

... model of image transmission. New ideas about the apprehension of reality—such as the indexical reception of reality-impressions in neural tissue or the furrowing of memory pathways in brain circuits—dislodged the image of the cool, untouched, representing consciousness. And ultimately the model...

... authority has complete knowledge of the world. This critique of liberal reason was one of the bedrocks for both the finance capital and algorithmic trading of our present and the layered neural network model now heavily in use. It also makes us recognize that AI is not a technology—it is an epistemology...

... is massive. With ninety-six layers of neurons, it may lay claim to being the largest and most sophisticated neural net ever created: GPT-3 “has about 175 billion parameters, and it was trained on about 45 terabytes of text data from different datasets, with 60% coming from Common Crawl’s archive of web...

... lesson, the brains of individuals with Capgras-­type neural damage continue their primary task of ensuring consistency despite contradictory input from the outside world. Capgras is an irresist- ible case for Weber because the brain insists on self-familiarity­ in the absence...

... in the early modern period yielded an expansion of available calories for human consumption, which allowed for an increase in the density of human settlements. This density in turn spurred the development of leisure activities and the neural stimulation they provide. Together, these changes created...

... a vision of designing a computer system they called the Dynamic Modeling System, dedicated to building scientific models across a range of fields and equipped with ready-to-use data sets and modeling tools (110). Early group members anticipated using it to model phenomena from neural activity to urban...

...-Richer locates an abiding concern with managing uncertainty in neural models and Cold War cybernetics; this, he claims, paved the way for a wider “adversarial epistemology” that recasts failure as an “opportunity” to improve models (218). In contrast, Ceyda Yolgörmez draws from Alan Turing and George...

... to be accountable for the results of their use, and for the most harmful outputs to be regulated are insufficient (5). “One could imagine a world,” she writes, in which the deep neural networks used in cities like Baltimore are scrutinized and rendered compliant with rules and yet continue to learn to recognize...

... by Duke University Press 2023 The ethics of artificial intelligence (AI) have become a matter of public concern. According to a recent Stanford report, the number of research papers in the area given at major conferences such as the annual Conference on Neural Information Processing Systems has...

... of a human in pain crashes their neural networks and can cause death. Ashby thus goes even further than Isaac Asimov’s famous laws of robotics (designed to ensure robots cannot harm humans), requiring vNs to love their human masters, a psychological orientation she presents as analogous to emotional...

... herself inside out when experiencing pleasure, making even her neural pathways visible to the attentive viewer. Instead of a process that unfolds internally, neural conduction for her radiates outward so that sensory reactions are perceptibly etched on the physical surface of her body. One effect...

... ,” the neural programs whose inflexibility, within the novel’s logic, evokes primitiveness. The white(y)ness that is the name of Snow Crash’ s narrative universe is thus always already a misprized and supplementary derivation of the blackness that the narrative attempts but fails to subordinate by constraining...

..., big data, and computation at large as about deep learning, neural networks, or advanced inference techniques normally associated with the term AI . Roughly, these books help us visualize the AI scene today; one can draw concentric circles, and AI will be the innermost: a tiny subset of soft...