Fake news is fake material in a news media format but is not processed properly by news agencies. The fake material can provoke or defame significant entities or individuals or potentially even for the personal interests of the creators, causing problems for society. Distinguishing fake news and real news is challenging due to limited of domain knowledge and time constraints. According to the survey, the top three areas most exposed to hoaxes and misinformation by residents are in Banten, DKI Jakarta and West Java. The model of transformers is referring to an approach in the field of artificial intelligence (AI) in natural language processing utilizing the deep learning architectures. Transformers exercise a powerful attention mechanism to process text in parallel and produce rich and contextual word representations. A previous study indicates a superior performance of a transformer model known as BERT over and above non transformer approach. However, some studies suggest the performance can be improved with the use of improved BERT models known as ALBERT and RoBERTa. However, the modified BERT models are not well explored for detecting fake news in Bahasa Indonesia. In this research, we explore those transformer models and found that ALBERT outperformed other models with 87.6% accuracy, 86.9% precision, 86.9% F1-score, and 174.5 run-time (s/epoch) respectively. Source code available at: https://github.com/Shafna81/fakenewsdetection.git

Music generation has attracted growing interest with the advancement of deep generative models. However, generating music conditioned on textual descriptions, known as text-to-music, remains challenging due to the complexity of musical structures and high sampling rate requirements. This paper introduces JEN-1, a universal high-fidelity model for text-to-music generation. JEN-1 is a diffusion model incorporating both autoregressive and non-autoregressive training. Through incontext learning, JEN-1 performs various generation tasks including text-guided music generation, music inpainting, and continuation. Evaluations demonstrate JEN-1's superior performance over state-of-the-art methods in text-music alignment and music quality while maintaining computational efficiency. Our demos are available at https://www.futureverse.com/research/jen/ "Music is the universal language of mankind." - Henry Wadsworth Longfellow Music, as an artistic expression comprising harmony, melody and rhythm, holds great cultural significance and appeal to humans. Recent years have witnessed remarkable progress in music generation with the rise of deep generative models (Liu et al., 2023; Kreuk et al., 2022; Agostinelli et al., 2023).

In 1950, the British computer scientist Alan Turing disputed whether human reasoning can be matched by computers: "Can machines think?" (TURING, 1950). Subsequently, he proposed the Turing Test to measure computer or artificial intelligence. In a Turing test, a human interrogator is presented with responses from a human and a computer (with the ability to generate written texts in real-time). If the interrogator cannot distinguish between the answers, the computer system passes the Turing Test. Although several computer programs and chatbots like Eliza demonstrated success in the Turing test ((Weizenbaum, 1966) (Güzeldere & Franchi, 1995)), these programs arguably used certain tricks to pass the test (Pinar Saygin et al., 2000) rather than demonstrating any significant intelligence. With the advancement in machine learning and natural language processing (NLP), chatbots have gained significant research attention and have been used for a variety of commercial and non-commercial applications ((Luo et al., 2022), (Adamopoulou & Moussiades, 2020), (Ranoliya et al., 2017), (Rahman et al., 2017), (Zhou et al., 2020)). Despite their vast adoption, most chatbots do not have personalization, and user satisfaction remains questionable (Følstad & Brandtzaeg, 2020). This limitation prompted researchers and developers to focus on chatbot engagement in making chatbots more conversational.

Generative models have emerged as an essential building block for many image synthesis and editing tasks. Recent advances in this field have also enabled high-quality 3D or video content to be generated that exhibits either multi-view or temporal consistency. With our work, we explore 4D generative adversarial networks (GANs) that learn unconditional generation of 3D-aware videos. By combining neural implicit representations with time-aware discriminator, we develop a GAN framework that synthesizes 3D video supervised only with monocular videos. We show that our method learns a rich embedding of decomposable 3D structures and motions that enables new visual effects of spatio-temporal renderings while producing imagery with quality comparable to that of existing 3D or video GANs.

Publishers should be able to opt out of having their works mined by generative artificial intelligence systems, according to Google, but the company has not said how such a system would work. The call for a fair use exception for AI systems is a view the company has expressed to the Australian government in the past, but the notion of an opt-out option for publishers is a new argument from Google. When asked how such a system would work, a spokesperson pointed to a recent blog post by Google where the company said it wanted a discussion around creating a community-developed web standard similar to the robots.txt Google's comments come as news companies such as News Corp have already reportedly been initiating conversations with AI companies about payment for scraping news articles. Toby Murray, associate professor at the University of Melbourne's computing and information systems school, said Google's proposal would put the onus on content creators to specify whether AI systems could absorb their content or not, but he indicated existing licensing schemes such as Creative Commons already allowed creators to mark how their works can be used.

The beta version of Spotify's AI-enhanced DJ feature is coming to 50 new countries, after soft-launching in the US and Canada back in February. In recent months, it's rolled out in the UK and Ireland, but now the robotic Wolfman Jack is headed to more countries in Europe, Asia and Africa, in addition to Australia and New Zealand. There's a caveat, but it depends on some initial understanding of what this tool actually does. The Spotify DJ is available to premium subscription members and provides algorithmic recommendations of what to listen to, just like any music streaming app. However, these recommendations are accompanied by AI-generated DJ commentary on what you're listening to. The DJ, based on Spotify's Xavier Jernigan, only speaks English, no matter where you live.

People's hair in animated movies and video games could start to look far more realistic, thanks to artificial intelligence. For decades, hair in video games and animated movies has looked unnatural because of the complexity of modelling its movement. "Almost all works that exist today consider hair as a mesh," says Vanessa Sklyarova at the Samsung AI Centre in Moscow, Russia. The graphical texture is then laid on top of this mesh, she says.

You can create text shorts on iPhones and Android phones. You know what they say about the American dream, right? Think about it -- a decently sized home, kids playing in the yard, neighbors discussing last night's game across white picket fences. But hold onto your remote controls because the American neighborhood is getting a plot twist. CLICK TO GET KURT'S FREE CYBERGUY NEWSLETTER WITH SECURITY ALERTS, QUICK TIPS, TECH REVIEWS AND EASY HOW-TO'S TO MAKE YOU SMARTER The folks there would've once waved hello to the postman; now they're sharing their neighborhood skyline with a monstrous Amazon data center.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. Pope Francis issued a warning on artificial intelligence Tuesday, urging those behind the technology to "be vigilant" during their work. The Pope made the statement in his message marking New Year's Day, which the Vatican traditionally releases far in advance. Francis, 86, has joked in the past that he is far from technologically savvy, but said Tuesday that AI must be used in a "responsible way." "Pope Francis calls for an open dialogue on the meaning of these new technologies, endowed with disruptive possibilities and ambivalent effects. He recalls the need to be vigilant and to work so that a logic of violence and discrimination does not take root in the production and use of such devices, at the expense of the most fragile and excluded," the message read.

We study Socially Unacceptable Discourse (SUD) characterization and detection in online text. We first build and present a novel corpus that contains a large variety of manually annotated texts from different online sources used so far in state-of-the-art Machine learning (ML) SUD detection solutions. This global context allows us to test the generalization ability of SUD classifiers that acquire knowledge around the same SUD categories, but from different contexts. From this perspective, we can analyze how (possibly) different annotation modalities influence SUD learning by discussing open challenges and open research directions. We also provide several data insights which can support domain experts in the annotation task.