We present a novel approach to neural response prediction that incorporates higher-order operations directly within convolutional neural networks (CNNs). Our model extends traditional 3D CNNs by embedding higher-order operations within the convolutional operator itself, enabling direct modeling of multiplicative interactions between neighboring pixels across space and time. Our model increases the representational power of CNNs without increasing their depth, therefore addressing the architectural disparity between deep artificial networks and the relatively shallow processing hierarchy of biological visual systems. We evaluate our approach on two distinct datasets: salamander retinal ganglion cell (RGC) responses to natural scenes, and a new dataset of mouse RGC responses to controlled geometric transformations. Our higher-order CNN (HoCNN) achieves superior performance while requiring only half the training data compared to standard architectures, demonstrating correlation coefficients up to 0.75 with neural responses (against 0.80$\pm$0.02 retinal reliability). When integrated into state-of-the-art architectures, our approach consistently improves performance across different species and stimulus conditions. Analysis of the learned representations reveals that our network naturally encodes fundamental geometric transformations, particularly scaling parameters that characterize object expansion and contraction. This capability is especially relevant for specific cell types, such as transient OFF-alpha and transient ON cells, which are known to detect looming objects and object motion respectively, and where our model shows marked improvement in response prediction. The correlation coefficients for scaling parameters are more than twice as high in HoCNN (0.72) compared to baseline models (0.32).

Tom Newhouse, vice president of Convergence Media, discusses the potential impact of artificial intelligence on elections after an RNC AI ad garnered attention. As Elon Musk and others continue to sound the alarm about the potential dangers of artificial intelligence, an unlikely duo of a data scientist and a political philosopher is teaming up to use AI with a different purpose in mind: bridging society's increasingly stark political divisions. The project stemmed from the research of David Rozado, a professor at Te Pūkenga -- the New Zealand Institute of Skills and Technology, who's recent work has drawn attention to political bias in ChatGPT and the potential for such bias in other AI systems. Rozado found that in 14 out of 15 political orientation test answers from ChatGPT, a product of the company OpenAI, were deemed as giving left-leaning viewpoints. At the same time, however, the AI language processing tool denied having any political bias or orientation, maintaining that it was just providing objective and accurate information to users. "The system would flag as hateful comments about certain groups but not others," Rozado told Fox News Digital, noting for example that the system would say it's hateful to call women dishonest but not men.

This study is devoted to two of the oldest known manuscripts in which the oeuvre of the medieval mystical author Hadewijch has been preserved: Brussels, KBR, 2879-2880 (ms. On the basis of codicological and contextual arguments, it is assumed that the scribe who produced B used A as an exemplar. While the similarities in both layout and content between the two manuscripts are striking, the present article seeks to identify the differences. After all, regardless of the intention to produce a copy that closely follows the exemplar, subtle linguistic variation is apparent. Divergences relate to spelling conventions, but also to the way in which words are abbreviated (and the extent to which abbreviations occur). The present study investigates the spelling profiles of the scribes who produced mss. In the first part of this study, we will present both manuscripts in more detail, after which we will consider prior research carried out on scribal profiling. The current study both builds and expands on Kestemont (2015). Next, we outline the methodology used to analyse and measure the degree of scribal appropriation that took place when ms. B was copied off the exemplar ms. A. After this, we will discuss the results obtained, focusing on the scribal variation that can be found both at the level of individual words and n-grams. To this end, we use machine learning to identify the most distinctive features that separate manuscript A from B. Finally, we look at possible diachronic trends in the appropriation by B's scribe of his exemplar. We argue that scribal takeovers in the exemplar impacts the practice of the copying scribe, while transitions to a different content matter cause little to no effect. INTRODUCTION Among the Royal Library of Belgium's (KBR) extraordinarily rich collection are two fourteenth-century manuscripts that are of great importance to the field of medieval Dutch literature in general, and that of mysticism in the Low Countries in particular: KBR 2879-80 and KBR 2877-78. Both manuscripts contain the complete oeuvre - consisting of letters, visions, songs, and poems - of the mystical writer Hadewijch. Since unambiguous biographical data are lacking, the historical figure of Hadewijch is largely shrouded in mystery. Through her work, however, one can get a modest glimpse of who she was and when she lived. Researchers who undertook this quest situate Hadewijch in the religious women's movement (mulieres religiosae) of the thirteenth century [Mommaers, 2003; Fraeters & Willaert, 2009, p. 13-19; Fraeters, 2013; Willaert, 2013].

A chilling drone video shows a hammerhead shark circling a seemingly oblivious swimmer off a Miami beach. The video was posted to Instagram by drone operator and photographer Jason McIntosh. The Miami Herald reports that the close encounter was captured off South Beach on Sunday. McIntosh captioned the video, "Hammer Time," and used MC Hammer's famous song "U Can't Touch This" as the soundtrack. The video has been viewed more than 29,000 times since it was posted last week.

Thirteen years ago, the Fred Hutchinson Cancer Research Center spun out a small startup with a mission to help researchers get a handle on all the data that medical devices were generating. That company, LabKey, has since grown from six to 50 employees and counts Merck, MIT and Britain's public health agency as clients. But the company never strayed far from home, now occupying an office a few blocks from where it was born in Fred Hutch's Seattle headquarters. LabKey's story contrasts sharply with that of Juno Therapeutics, an immunotherapy company that spun out of Fred Hutch, raised millions in venture capital, and was bought by Celgene for $9 billion in January 2018. To this day, LabKey hasn't raised outside funding, following its own path to success in a competitive area of technology and life sciences.

Texting and chatting have become so ingrained in our daily lives that, these days, most people get genuinely upset when they receive phone calls. The convenience of mobile communication has made us greedy about our time, and spending minutes on the phone for something that can be accomplished via text has become just downright offensive. For that reason, marketers are now turning to messaging platforms to improve communication channels for sales and customer service conversations. In fact, a report by Twilio found that 9 out of 10 consumers want to use messaging to communicate with brands. "[The] report highlights a growing divide between consumers and brands," said Manav Khurana, VP of Product Marketing at Twilio.