The past few years have seen an explosion in applications of artificial intelligence to creative fields. A new generation of image and text generators is delivering impressive results. Now AI has also found applications in music, too. Last week, a group of researchers at Google released MusicLM -- an AI-based music generator that can convert text prompts into audio segments. With the music industry still adjusting to disruptions caused by the internet and streaming services, there's a lot of interest in how AI might change the way we create and experience music.

Leon The Cat contemplating CatGPT chat. ChatGPT has hit an estimated 100 million monthly active users making it the fastest growing consumer internet application in history according to a UBS study. UBS analysts peg its total addressable market to be $1 trillion, reported Yahoo Finance. Ever since its launch on Nov. 30, the clever ask-me-anything tool has been the go-to-resource for advice on just about any topic it's been trained on and can complete complex tasks like debugging code, doing research and writing articles in an endearing human-like tone. Some news organizations like BuzzFeed have embraced it, striking a $10 million deal with Meta to provide Facebook and Instagram with AI-generated content leveraging the technology, according to Reuters.

Data science research into fake news has gathered much momentum in recent years, arguably facilitated by the emergence of large public benchmark datasets. While it has been well-established within media studies that gender bias is an issue that pervades news media, there has been very little exploration into the relationship between gender bias and fake news. In this work, we provide the first empirical analysis of gender bias vis-a-vis fake news, leveraging simple and transparent lexicon-based methods over public benchmark datasets. Our analysis establishes the increased prevalance of gender bias in fake news across three facets viz., abundance, affect and proximal words. The insights from our analysis provide a strong argument that gender bias needs to be an important consideration in research into fake news.

A New cross-domain strategy based XAI models for fake news detection v0.1.1 ABSTRACT The Advancement in technology and rapid usage of social media has made communication easier and faster than ever before. Fake news threatens the community, democracy, egalitarianism and people's trust. Cross-domain text classification is a task of a model adopting a target domain by using the knowledge of the source domain. Natural Language Processing and Deep Learning models are used to identify misleading information. Explainability is crucial in understanding the behaviour of these complex models. In this study, we propose a four-level cross-domain strategy to study the impact of explainability on cross-domain models. The latest findings in the natural language process, the "Bidirectional Encoder Representations from Transformers" (BERT) model published by Devlin et al. (2018) google used to implement the concept of transfer learning. A fine-tune BERT model is used to perform cross-domain classification. Using this model, we conducted four experiments using datasets from different domains. Explanatory models like Anchor, ELI5, LIME and SHAP are used to design a novel explainable approach to cross-domain levels. The experimental analysis has given an ideal pair of XAI models on different levels of cross-domain. INTRODUCTION Nowadays, social media has become a potential influencing tool. According to the statistics published by Datareportal in July 2022, there is exponential growth in social media platforms, declaring that more than half of the world's population (59 per cent) is using them. Consequently, these platforms have deterministic effects on people's lives and the integrity of societies and local communities. Groups of people forming social media clusters use, unfortunately, these tools to spread speculation - so-called "fake news". In 2008, a journalist posted a report about Steve jobs medical condition. It has created massive confusion and controversy within societies and led to fluctuations in the stock price of Apple Inc. Rubin (2017). During the Covid-19 pandemic, fake news was largely spread among people and has created panic within societies. Recent statistics published by the United States support receiving reports from 80 per cent of consumers about the fake news outbreak. Insufficient data is one of the reasons behind unreliable communication, making it difficult to distinguish fake from real news. In 2016, fake news was popular mainly during the United States elections. They have created a great source of influence on people's opinions about two constants.

What is the impact of taking all the musical know-how and ingesting into an AI brain with only asking questions expressing your musical tastes? Who needs to be a musician to entertain when we will soon be able to create our own music even more easily and tap into the human genius of every muscian that has a recording? Google researchers say MusicLM is based on a model generating high-fidelity music from text descriptions such as "a calming violin melody backed by a distorted guitar riff". You can find the details on GitHub. MusicLM is built on a neural network, and trained on a large music data set of over280,000 hours of music, enabling it to automatically produce innovative music tracks of diverse instruments, genres, and concepts based on text descriptions.

For a product that its own creators, in a marketing pique, once declared "too dangerous" to release to the general public, OpenAI's ChatGPT is seemingly everywhere these days. The versatile automated text generation (ATG) system, which is capable of outputting copy that is nearly indistinguishable from a human writer's work, is officially still in beta but has already been utilized in dozens of novel applications, some of which extend far beyond the roles ChatGPT was originally intended for -- like that time it simulated an operational Linux shell or that other time when it passed the entrance exam to Wharton Business School. The hype around ChatGPT is understandably high, with myriad startups looking to license the technology for everything from conversing with historical figures to talking to historical literature, from learning other languages to generating exercise routines and restaurant reviews. But with these technical advancements come with a slew of opportunities for misuse and outright harm. And if our previous hamfisted attempts at handling the spread of deepfake video and audio technologies were any indication, we're dangerously underprepared for the havoc that at-scale, automated disinformation production will wreak upon our society.

That's because AI is able to read, write, and understand text-based data well, she added. "Analyzing and interpreting vast amounts of language based data and information is a skill that you'd expect generative AI technologies to ramp up on," Madgavkar said. Economist Paul Krugman said in a New York Times op-ed that ChatGPT may be able to do tasks like reporting and writing "more efficiently than humans." The media industry is already beginning to experiment with AI-generated content. Tech news site CNET used an AI tool similar to ChatGPT to write dozens of articles -- though the publisher has had to issue a number of corrections -- and BuzzFeed announced that it will use tech from the ChatGPT maker to generate new forms of content.

The publisher of Sports Illustrated and other outlets is using artificial intelligence to help produce articles and pitch journalists potential topics to follow, the latest example of a media company investing in the emerging technology. The Arena Group Holdings, whose publications include TheStreet, Men's Journal and Dealbreaker, said it is working with AI startups Jasper and Nota as part of an effort to generate stories that pull information from its own library of content. The company is also using technology from OpenAI, the creator of ChatGPT, a chatbot that has generated considerable buzz among consumers and businesses due to its humanlike, content-producing capabilities.

An impressive new AI system from Google can generate music in any genre given a text description. But the company, fearing the risks, has no immediate plans to release it. Called MusicLM, Google's certainly isn't the first generative artificial intelligence system for song. There have been other attempts, including Riffusion, an AI that composes music by visualizing it, as well as Dance Diffusion, Google's own AudioML and OpenAI's Jukebox. But owing to technical limitations and limited training data, none have been able to produce songs particularly complex in composition or high-fidelity.

In brief Joshua Browder, CEO of DoNotPay, made headlines for claiming an AI chatbot was due to defend a man in an upcoming court hearing, but has pulled out of the stunt. Browder runs a consumer rights startup that was originally built to help people appeal parking tickets more easily, and has since grown with the aim of building "the world's first robot lawyer." He wanted to show AI could replace expensive human lawyers, using language models to form legal arguments. Earlier this month he claimed to have convinced a man to wear headphones during a court case and recite the output of an AI chatbot in a court hearing scheduled to take place over Zoom. But his behavior caught the attention of prosecutors irked by his reckless antics.