Electronic music artist and tech creator Look Mum No Computer has been chosen to represent the UK at this year's Eurovision Song Contest in Vienna, the BBC has announced. Look Mum No Computer is a solo artist, songwriter and YouTuber, who is also described as an inventor of unique musical machines. The singer first arrived on the music scene back in 2014 as Sam Battle, frontman of indie rock band Zibra. The group performed at Glastonbury in 2015 for BBC Introducing. Since then, he has been performing and recording under his solo name.

We propose a post-training method for lower-resource languages that preserves fluency of language models even when aligned by disfluent reward models. Preference-optimization is now a well-researched topic, but previous work has mostly addressed models for English and Chinese. Lower-resource languages lack both datasets written by native speakers and language models capable of generating fluent synthetic data. Thus, in this work, we focus on developing a fluent preference-aligned language model without any instruction-tuning data in the target language. Our approach uses an on-policy training method, which we compare with two common approaches: supervised finetuning on machine-translated data and multilingual finetuning. We conduct a case study on Norwegian Bokmål and evaluate fluency through native-speaker assessments. The results show that the on-policy aspect is crucial and outperforms the alternatives without relying on any hard-to-obtain data.

Feedback is New Scientist's popular sideways look at the latest science and technology news. You can submit items you believe may amuse readers to Feedback by emailing feedback@newscientist.com Saturday 17 May will see the final of this year's Eurovision Song Contest, which will be the most over-the-top evening of television since, well, the previous Eurovision. Feedback is deeply relieved that Feedback Jr appears not to be interested this year, so we might escape having to sit up and watch the entire thing. While we are deeply supportive of the contest's kind and welcoming vibe, most of the songs make our ears bleed.

Amid flamboyant performances, flashy costumes and pyrotechnics, the Eurovision Song Contest is probably one of the weirdest, most peculiar shows ever to grace our screens. It's the kind of event that an alien species or an emotionless android would have a hard time understanding, were they watching Europe tune into the annual celebration of kitsch, patriotism and unity. But could machines understand - and reproduce - such a uniquely human experience? The answer could be found at the AI Song Contest, a Eurovision-inspired music competition where all the songs are written by artificial intelligence. Since its creation in 2020, the song contest has been hosted every year by the Belgian city of Liège, where teams of data scientists, programmers, and musicians from all over the world participate with the compositions they have created with the help of AI.

In late April 2020, a company named OpenAI uploaded dozens of new tracks to SoundCloud, all of them matter-of-factly titled like "Hip-hop, in the style of Nas" or "Pop, in the style of Katy Perry." You'd be forgiven for initially thinking the songs were average YouTube covers. A few seconds spent listening to the gargled production, bizarre lyrics, and eerie vocals would definitely change your mind. The songs were all made using an artificial intelligence software called Jukebox, designed by OpenAI, a billion dollar research organization leading the field in AI research. Jukebox isn't your standard Elvis impersonator: After being trained on 1.2 million songs and other data about genres and artists, the neural net has learned to produce original music in the uncannily recognizable style of famous artists like Elton John and Rihanna.

Eurovision 2020 was unsurprisingly cancelled due to the pandemic, but AI has stepped in to fill its glittery shoes. Dutch broadcaster VPRO has just wrapped up a Eurovision-inspired AI Song Contest, with 13 teams from Europe and Australia training algorithms to become budding pop stars while experts judge their output. As BBC and Bloomberg point out, the results are a mix of surprisingly well-done and frighteningly dystopic tunes... a bit like the real thing, really. The winning entry came from Australian team Uncanny Valley, whose song "Beautiful the World" was built by an AI trained on a mix of Eurovision hits and local animals affected by wildfires, including koalas, kookaburras and Tasmanian devils. It has the same catchy dance pop riffs you'd expect to get the full douze points from a Eurovision vote, just with nonsensical lyrics.