Financial fraud is the cause of multi-billion dollar losses annually. Traditionally, fraud detection systems rely on rules due to their transparency and interpretability, key features in domains where decisions need to be explained. However, rule systems require significant input from domain experts to create and tune, an issue that rule induction algorithms attempt to mitigate by inferring rules directly from data. We explore the application of these algorithms to fraud detection, where rule systems are constrained to have a low false positive rate (FPR) or alert rate, by proposing RIFF, a rule induction algorithm that distills a low FPR rule set directly from decision trees. Our experiments show that the induced rules are often able to maintain or improve performance of the original models for low FPR tasks, while substantially reducing their complexity and outperforming rules hand-tuned by experts.

We've heard AI-generated songs mimic the work of AC/DC, Metallica and more. Now artificial intelligence software has generated "new" Jimi Hendrix and Nirvana tracks, along with other artists and bands with members who died at the age of 27, to help raise awareness for the importance of mental health support amongst musicians and members of the music industry. The Hendrix song, You're Gonna Kill Me, and the Nirvana track, Drowned In the Sun, are part of a new project by the Toronto-based organization, Over the Bridge, which has put together a compilation, all created via artificial intelligence, in the style of musicians who died at the age of 27. The release, titled Lost Tapes of the 27 Club, also features songs in the style of the Doors and Amy Winehouse, all made through Google's AI program Magenta, which analyses an artist's previous work in order to learn how to compose like them. An additional AI program was used to create the lyrics.

The recently launched Lost Tapes of the 27 Club project uses AI software to create songs in the style of musicians who died at the age of 27. One of the featured tracks is called "Drowned in the Sun", and it comes pretty close to replicating a Nirvana song written by Kurt Cobain himself. With opening guitars starting out restrained before reaching a crescendo on the chorus, the track is reminiscent of Nirvana's signature hit, "Come as You Are". Its chorus sounds like something Cobain might have written, too, with lyrics like, "I don't care/ I feel as one, drowned in the sun." As explained in a Rolling Stone feature, Google's AI program Magenta was used to analyze the pioneering grunge band's music and create the instrumental track.

Ever since Kurt Cobain's death in 1994, Nirvana fans have hypothesized about the music he would have made had he lived. But other than "You Know You're Right," the scabrous, throat-shredding meditation on confusion that Nirvana recorded a few months before his suicide, and a few comments he told confidants about potentially collaborating with R.E.M.'s Michael Stipe or going completely solo, he mainly left behind question marks. Now an organization has created a "new" Nirvana song using artificial-intelligence software to approximate the singer-guitarist's songwriting. The guitar riffs vary from quiet, "Come as You Are"–style plucking to raging, Bleach fury à la "Scoff." And lyrics like, "The sun shines on you but I don't know how," and a surprisingly anthemic chorus, "I don't care/I feel as one, drowned in the sun," bear evocative, Cobain-esque qualities.

If your kids aren't playing Fortnite – the colourful, cartoonish shooter that has recently become a massive after-school (and work lunch-break) craze – they are probably playing Roblox. Like Minecraft, which colonised the minds of basically all school-aged children around 2012-15, Roblox lets players get creative and build things. But it goes further than Minecraft in that you can create entire games in Roblox, from racers to haunted-house adventures to competitive battle arenas. According to the developer, it has 56 million players. It is an entirely online, social game: everything you play has been built by someone else.