This paper introduces MetaBGM, a groundbreaking framework for generating background music that adapts to dynamic scenes and real-time user interactions. We define multi-scene as variations in environmental contexts, such as transitions in game settings or movie scenes. To tackle the challenge of converting backend data into music description texts for audio generation models, MetaBGM employs a novel two-stage generation approach that transforms continuous scene and user state data into these texts, which are then fed into an audio generation model for real-time soundtrack creation. Experimental results demonstrate that MetaBGM effectively generates contextually relevant and dynamic background music for interactive applications.

This book uses the modern theory of artificial intelligence (AI) to understand human suffering or mental pain. Both humans and sophisticated AI agents process information about the world in order to achieve goals and obtain rewards, which is why AI can be used as a model of the human brain and mind. This book intends to make the theory accessible to a relatively general audience, requiring only some relevant scientific background. The book starts with the assumption that suffering is mainly caused by frustration. Frustration means the failure of an agent (whether AI or human) to achieve a goal or a reward it wanted or expected. Frustration is inevitable because of the overwhelming complexity of the world, limited computational resources, and scarcity of good data. In particular, such limitations imply that an agent acting in the real world must cope with uncontrollability, unpredictability, and uncertainty, which all lead to frustration. Fundamental in such modelling is the idea of learning, or adaptation to the environment. While AI uses machine learning, humans and animals adapt by a combination of evolutionary mechanisms and ordinary learning. Even frustration is fundamentally an error signal that the system uses for learning. This book explores various aspects and limitations of learning algorithms and their implications regarding suffering. At the end of the book, the computational theory is used to derive various interventions or training methods that will reduce suffering in humans. The amount of frustration is expressed by a simple equation which indicates how it can be reduced. The ensuing interventions are very similar to those proposed by Buddhist and Stoic philosophy, and include mindfulness meditation. Therefore, this book can be interpreted as an exposition of a computational theory justifying why such philosophies and meditation reduce human suffering.

With the emergence of widely available powerful LLMs, disinformation generated by large Language Models (LLMs) has become a major concern. Historically, LLM detectors have been touted as a solution, but their effectiveness in the real world is still to be proven. In this paper, we focus on an important setting in information operations -- short news-like posts generated by moderately sophisticated attackers. We demonstrate that existing LLM detectors, whether zero-shot or purpose-trained, are not ready for real-world use in that setting. All tested zero-shot detectors perform inconsistently with prior benchmarks and are highly vulnerable to sampling temperature increase, a trivial attack absent from recent benchmarks. A purpose-trained detector generalizing across LLMs and unseen attacks can be developed, but it fails to generalize to new human-written texts. We argue that the former indicates domain-specific benchmarking is needed, while the latter suggests a trade-off between the adversarial evasion resilience and overfitting to the reference human text, with both needing evaluation in benchmarks and currently absent. We believe this suggests a re-consideration of current LLM detector benchmarking approaches and provides a dynamically extensible benchmark to allow it (https://github.com/Reliable-Information-Lab-HEVS/dynamic_llm_detector_benchmark).

This paper investigates the RWKV model's efficacy in content moderation through targeted experimentation. We introduce a novel dataset specifically designed for distillation into smaller models, enhancing content moderation practices. This comprehensive dataset encompasses images, videos, sounds, and text data that present societal challenges. Leveraging advanced Large Language Models (LLMs), we generated an extensive set of responses -- 558,958 for text and 83,625 for images -- to train and refine content moderation systems. Our core experimentation involved fine-tuning the RWKV model, capitalizing on its CPU-efficient architecture to address large-scale content moderation tasks. By highlighting the dataset's potential for knowledge distillation, this study not only demonstrates RWKV's capability in improving the accuracy and efficiency of content moderation systems but also paves the way for developing more compact, resource-efficient models in this domain. Datasets and models can be found in HuggingFace: https://huggingface.co/modrwkv

Detecting false information on social media is critical in mitigating its negative societal impacts. To reduce the propagation of false information, automated detection provide scalable, unbiased, and cost-effective methods. However, there are three potential research areas identified which once solved improve detection. First, current AI-based solutions often provide a uni-dimensional analysis on a complex, multi-dimensional issue, with solutions differing based on the features used. Furthermore, these methods do not account for the temporal and dynamic changes observed within the document's life cycle. Second, there has been little research on the detection of coordinated information campaigns and in understanding the intent of the actors and the campaign. Thirdly, there is a lack of consideration of cross-platform analysis, with existing datasets focusing on a single platform, such as X, and detection models designed for specific platform. This work aims to develop methods for effective detection of false information and its propagation. To this end, firstly we aim to propose the creation of an ensemble multi-faceted framework that leverages multiple aspects of false information. Secondly, we propose a method to identify actors and their intent when working in coordination to manipulate a narrative. Thirdly, we aim to analyse the impact of cross-platform interactions on the propagation of false information via the creation of a new dataset.

In case the many books and films from the Twilight universe haven't provided enough fodder for your fandom, there's a new TV project in the works about the love-em-or-hate-em sparkly vampires of the Pacific Northwest. An animated series adaptation of Midnight Sun is currently in development at Netflix. Published in 2020, Midnight Sun is a companion to the original Twilight novel, telling the same events of that book from the perspective of Edward Cullen. Yes, the sick, masochistic lion gets to share his side of the story of how he falls for the stupid lamb known as Bella Swan. Author Stephanie Meyer will be an executive producer for the series, as she has been for most other projects in the Twilight realm.

With a name that sounds like something a parent would slowly mouth to their infant, NaNoWriMo is an annual "challenge" in which many thousands of seemingly well-adjusted people decide to write a novel in a month. "Do I need something special to write a novel?" the nonprofit that puts on this exquisite torture reasonably asks on its website. National Novel Writing Month began in 1999 with 21 participants, and now nearly half a million take part every November. The event is also the name of the organization that gamifies the exercise, hosting participants on its online platform. To "win" NaNoWriMo, you need to produce a minimum of 50,000 words in a month (about the length of The Great Gatsby)--or 1,667 words a day, a number, NaNoWriMo tells us, that "scientists have determined to be the perfect amount to boost your creativity."

Fox News chief political anchor Bret Baier has the latest on the pros and cons of the bombshell developments on'Special Report.' The Vatican flag flies outside the United Nations headquarters on Sept. 25, 2015, in New York City. 'PROPER HUMAN CONTROL': A delegation representing the Holy See urged the United Nations this week to put a moratorium on autonomous weapons designed to kill without human decision-making. 'INSANE': Canva is facing pushback from customers over plans to increase subscription prices by more than 300% in some instances. United Nations Headquarters in New York City is seen flanked by Hamas and Hezbollah fighters.

It took a decade, but we finally have a teaser for the live-action A Minecraft Movie. The first look comes courtesy of a video released by Warner Bros. today that clocks in at just over one minute -- but, hey, we'll take it. The film studio has confirmed its previous target, April 4, 2025, is moving forward with a theater-only release. Yes, once upon a time, it had release dates for May 2019 and March 2022, but the existence of a teaser makes us feel a little more hopeful (gullible?) After a series of directors joined and left the project, A Minecraft Movie is led by filmmaker Jared Hess.

Even after a century beneath the water, the Titanic's bow remains one of the most magnificent and haunting sights in the ocean. However, a new survey of the wreck site has revealed that the railing, made famous by Jack and Rose, has now collapsed into rust. Haunting images snapped by underwater robots through the years show the great ship's bow has gradually eroded. Experts say that its metal construction and frequent human visits mean it is only a matter of time before the Titanic collapses. Dr Rodrigo Pacheco-Ruiz, archaeological data manager for HMS Victory and maritime archaeologist from the University of Southampton, told MailOnline: 'The realistic view is that because she's such a big metal object, she won't be there for very long.' Haunting pictures reveal how the Titanic's iconic bow has decayed in the 37 years between 1987 and 2010 Earlier this week, RMS Titanic Inc, the company which holds the salvage rights for the ship, released new images and footage of the sunken liner.