Advances in AI-generated content have led to wide adoption of large language models, diffusion-based visual generators, and synthetic audio tools. However, these developments raise critical concerns about misinformation, copyright infringement, security threats, and the erosion of public trust. In this paper, we explore an extensive range of methods designed to detect and mitigate AI-generated textual, visual, and audio content. We begin by discussing motivations and potential impacts associated with AI-based content generation, including real-world risks and ethical dilemmas. We then outline detection techniques spanning observation-based strategies, linguistic and statistical analysis, model-based pipelines, watermarking and fingerprinting, as well as emergent ensemble approaches. We also present new perspectives on robustness, adaptation to rapidly improving generative architectures, and the critical role of human-in-the-loop verification. By surveying state-of-the-art research and highlighting case studies in academic, journalistic, legal, and industrial contexts, this paper aims to inform robust solutions and policymaking. We conclude by discussing open challenges, including adversarial transformations, domain generalization, and ethical concerns, thereby offering a holistic guide for researchers, practitioners, and regulators to preserve content authenticity in the face of increasingly sophisticated AI-generated media.

The ability to summarize long documents succinctly is increasingly important in daily life due to information overload, yet there is a notable lack of such summaries for Spanish documents in general, and in the legal domain in particular. In this work, we present BOE-XSUM, a curated dataset comprising 3,648 concise, plain-language summaries of documents sourced from Spain's ``Bolet\'ın Oficial del Estado'' (BOE), the State Official Gazette. Each entry in the dataset includes a short summary, the original text, and its document type label. We evaluate the performance of medium-sized large language models (LLMs) fine-tuned on BOE-XSUM, comparing them to general-purpose generative models in a zero-shot setting. Results show that fine-tuned models significantly outperform their non-specialized counterparts. Notably, the best-performing model -- BERTIN GPT-J 6B (32-bit precision) -- achieves a 24\% performance gain over the top zero-shot model, DeepSeek-R1 (accuracies of 41.6\% vs.\ 33.5\%).

Who invented deep residual learning? Modern AI is based on deep artificial neural networks (NNs). As of 2025, the most cited scientific article of the 21st century is an NN paper on deep residual learning with residual connections . Here is the timeline of the evolution of deep residual learning: 1991: recurrent residual connections (weight 1.0) solve the vanishing gradient problem 1997 LSTM: plain recurrent residual connections (weight 1.0) 1999 LSTM: gated recurrent residual connections (gates initially open: 1.0) 2005: unfolding LSTM--from recurrent to feedforward residual NNs May 2015: very deep Highway Net--gated feedforward residual connections (initially 1.0) Dec 2015: ResNet--like an open-gated Highway Net (or an unfolded 1997 LSTM) His recurrent residual connection was mathematically derived from first principles to overcome the fundamental deep learning problem of vanishing or exploding gradients, first identified and analyzed in the very same thesis. That is, at every time step of information processing, this unit just adds its current input to its previous activation value. The invariant residual connections transport error signals back to typically highly nonlinear adaptive parts of the NN where they can cause appropriate weight changes.

The University of North Carolina has placed Asian and Middle Eastern Studies professor Dwayne Dixon on leave after his ties to the far-left gun club Redneck Revolt were exposed.

Things to Do in L.A. Tap to enable a layout that focuses on the article. Gov. Gavin Newsom holds a news conference at the Google office in San Francisco in August to announce new AI partnerships. This is read by an automated voice. Please report any issues or inconsistencies here . Gov. Gavin Newsom signed legislation Monday requiring AI companies to publicly disclose security protocols and report critical safety incidents.

The platform appears to closely resemble TikTok and is powered by Sora 2, OpenAI's latest video generation model. OpenAI is preparing to launch a stand-alone app for its video generation AI model Sora 2, WIRED has learned. The app, which features a vertical video feed with swipe-to-scroll navigation, appears to closely resemble TikTok--except all of the content is AI-generated . There's a For You-style page powered by a recommendation algorithm. On the right side of the feed, a menu bar gives users the option to like, comment, or remix a video.

Nigel Max Edge allegedly opened fire from a boat at American Fish Company in Southport, North Carolina, killing three people and injuring five in what police call a premeditated attack.

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'What we have seen from Croydon is that it works,' said Sarah Jones. 'What we have seen from Croydon is that it works,' said Sarah Jones. Policing minister says government will'put some parameters' around its deployment in England Labour plans to consult on the use of live facial recognition (LFR) technology before expanding it across England, the new policing minister has told the party's annual conference. Sarah Jones, a Home Office minister, said the government would "put some parameters" over when and where it could be used in future. Campaigners claim the police have been allowed to self-regulate their use of the technology because of the lack of a legal framework and deploy the technology's algorithm at lower settings that are biased against ethnic minorities and women.

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