Social networking and micro-blogging services, such as Twitter, play an important role in sharing digital information. Despite the popularity and usefulness of social media, they are regularly abused by corrupt users. One of these nefarious activities is so-called fake news -- a "virus" that has been spreading rapidly thanks to the hospitable environment provided by social media platforms. The extensive spread of fake news is now becoming a major problem with far-reaching negative repercussions on both individuals and society. Hence, the identification of fake news on social media is a problem of utmost importance that has attracted the interest not only of the research community but most of the big players on both sides - such as Facebook, on the industry side, and political parties on the societal one. In this work, we create a model through which we hope to be able to offer a solution that will instill trust in social network communities. Our model analyses the behaviour of 50,000 politicians on Twitter and assigns an influence score for each evaluated user based on several collected and analysed features and attributes. Next, we classify political Twitter users as either trustworthy or untrustworthy using random forest and support vector machine classifiers. An active learning model has been used to classify any unlabeled ambiguous records from our dataset. Finally, to measure the performance of the proposed model, we used accuracy as the main evaluation metric.

Electronic music artists and sound designers have unique workflow practices that necessitate specialized approaches for developing music information retrieval and creativity support tools. Furthermore, electronic music instruments, such as modular synthesizers, have near-infinite possibilities for sound creation and can be combined to create unique and complex audio paths. The process of discovering interesting sounds is often serendipitous and impossible to replicate. For this reason, many musicians in electronic genres record audio output at all times while they work in the studio. Subsequently, it is difficult for artists to rediscover audio segments that might be suitable for use in their compositions from thousands of hours of recordings. In this paper, we describe LyricJam Sonic -- a novel creative tool for musicians to rediscover their previous recordings, re-contextualize them with other recordings, and create original live music compositions in real-time. A bi-modal AI-driven approach uses generated lyric lines to find matching audio clips from the artist's past studio recordings, and uses them to generate new lyric lines, which in turn are used to find other clips, thus creating a continuous and evolving stream of music and lyrics. The intent is to keep the artists in a state of creative flow conducive to music creation rather than taking them into an analytical/critical state of deliberately searching for past audio segments. The system can run in either a fully autonomous mode without user input, or in a live performance mode, where the artist plays live music, while the system "listens" and creates a continuous stream of music and lyrics in response.

Believe is above all a passion for music, tech, and digital marketing, shared by over 1,500 talented people in more than 50 countries. It is a visionary and entrepreneurial spirit that drives us and makes us one of the world's leading digital music companies whose moto is to shape the future of music. Believe's mission is to develop independent artists and labels in the digital world by providing them the solutions they need to grow their audience at each stage of their career and development, in all local markets around the world, with respect, fairness and transparency. Believe is a tribe of experts who successfully meet the challenges of the transformation of our music industry every day. It's an adventure, a human adventure, and one that is propitious and stimulating for all of us. Finally, Believe is a story that began in 2005 and that we must continue to narrate, now, and with you.

But this is not going to be an easy journey and there is a real danger that if do not consciously put a real effort into this evolution, we very well may end up living in a real-life Hollywood movie where we become slaves to our machines. We continue to place more and more emphasis on the sciences, finance, production and data processing, and in doing so we are becoming more machine-like and less human ourselves. We equate success with machine-like productivity and evaluate progress through the equation of output of goods and services that have a material or monetary value. We need to stop this obsession and learn how to balance it better with our humanness. This is not going to come automatically, for this requires us to learn the techniques and put in the hard work and commitment required to understand our own humanity first.

As a writer collective, we've had AI on the brain--from my last piece on AI companion bots to Evan's excellent essay on the AI value chain to Nathan's exploration of the infinite AI article. Every has also been building Lex, a word processor with AI baked in. I started working on this piece before we launched Lex, but testing out this tool (among others) has shaped my perspective on the role of AI writing assistants for creatives. Try it for yourself: watch the demo and sign-up to join the waitlist (Every's paid subscribers have priority access, so subscribe to skip the line). In 2016, filmmaker Oscar Sharp and AI researcher Ross Goodwin created an experimental short sci-fi film written entirely by a neural network.

On 8 July 2022, former Japanese Prime Minister Shinzo Abe was delivering a political campaign speech outside the Yamato-Saidaiji Station in Nara City, Japan, when a man approached and shot him in the back using a homemade firearm. Even before Abe died from his injuries, footage of the assassination had been posted online. Social media users began to speculate as to the identity and motive of the killer. On the internet forum 4chan, a site notorious for its anarchic, often hateful trolling, an anonymous user posted a photograph of the video game director Hideo Kojima, claiming this "left-wing extremist" was the perpetrator. If the post was intended to bait the gullible, it worked.

… 2.0 includes the new Model Summary view that shows how a machine learning model performs against a battery of AI Quality performance tests.

Artificial intelligence and machine learning can do wonders, from making art to automating admin jobs. But they're also a risk as they can empower bad actors with tricks like deepfake. As this particular technology evolves, it's a good idea to learn how deepfakes actually work and who would even want to use them--both legitimately and illegally. Mainstream applications of deepfake technology mainly revolve around funny, pornographic, or cinematic materials, but a study proved that deepfakes can fool facial recognition. This alone is a reason to worry and put your guard up.

And coming to terms with "robot writing" might just improve writing instruction, S. Scott Graham writes. September 2022 was apparently the month artificial intelligence essay angst boiled over in academia, as various media outlets published opinion pieces lamenting the rise of AI writing systems that will ruin student writing and pave the way toward unprecedented levels of academic misconduct. Then, on Sept. 23, academic Twitter exploded into a bit of a panic on this topic. The firestorm was prompted by a post to the OpenAI subreddit where user Urdadgirl69 claimed to be getting straight A's with essays "written" using artificial intelligence. Professors on Reddit and Twitter alike expressed frustration and concern about how best to address the threat of AI essays.

Photo credit: Evoluted Artificial intelligence showed us what cartoon characters characters look like as humans, and now, it has reimagined some famous horror movie posters. The team over at Evoluted thought of relevant keywords from each of these films and inputted into an AI tool, what they ended up with are a batch of movie posters that put a fresh twist on things. One of our favorite is Jaws, which was released on June 20, 1975 in theaters, directed by Steven Spielberg. It follows police chief Martin Brody (Roy Scheider) and marine biologist / professional shark hunter (Robert Shaw) who join forces to hunt a man-eating great white shark that attacks beachgoers at Amity Island. Other films that received an AI movie poster makeover include Friday the 13th, Dracula, Silence of the Lambs, IT, and The Birds.