After three weeks of a punishing Israeli bombardment of Gaza, Israel is still refusing to allow international journalists in. News outlets and audiences are entirely reliant on local Palestinian reporters, who risk their lives to provide a window into the war. Meenakshi Ravi reports on how Israelis are documenting and sharing the evidence online. Tariq Nafi examines Israel's use of AI-powered surveillance in Hebron, which has entrenched the Israeli government's control over Palestinians.

Actor Sarah Snook says the film industry should "set a precedent" on the use of artificial intelligence (AI). Snook, best known for her role as Shiv in the TV show Succession, said the use of AI is an "uncharted landscape". She spoke to Laura Kuenssberg ahead of her role in a London stage adaptation of The Picture of Dorian Gray. She wasn't able to talk about her time on Succession because of the Hollywood writer's strike. Many Hollywood screen actors are on strike, demanding better safeguards against the use of AI in TV and movie productions.

Francesca Mani and her mother Dorota join'The Ingraham Angle' to demand accountability for victims. Francesca Mani told "The Ingraham Angle" that the principal at Westfield High School recently notified her that she was one of multiple victims. "After that, I just felt, like, betrayed because I never thought it'd be my classmate, and when I came home, I told my mom and I said, 'We need to do something about this because it's not OK, and people are making it seem like it is.'" Mani said she never personally witnessed the explicit images, but that she felt betrayed. Mani said she believes she knows who the main culprit in the dissemination of the images is, but did not mention their name on air.

Several recent papers have published good solutions for language identification (LID) for about 300 high-resource and medium-resource languages. However, there is no LID available that (i) covers a wide range of low-resource languages, (ii) is rigorously evaluated and reliable and (iii) efficient and easy to use. Here, we publish GlotLID-M, an LID model that satisfies the desiderata of wide coverage, reliability and efficiency. It identifies 1665 languages, a large increase in coverage compared to prior work. In our experiments, GlotLID-M outperforms four baselines (CLD3, FT176, OpenLID and NLLB) when balancing F1 and false positive rate (FPR). We analyze the unique challenges that low-resource LID poses: incorrect corpus metadata, leakage from high-resource languages, difficulty separating closely related languages, handling of macrolanguage vs varieties and in general noisy data. We hope that integrating GlotLID-M into dataset creation pipelines will improve quality and enhance accessibility of NLP technology for low-resource languages and cultures. GlotLID-M model, code, and list of data sources are available: https://github.com/cisnlp/GlotLID.

Simulating realistic interaction and motions for physics-based characters is of great interest for interactive applications, and automatic secondary character animation in the movie and video game industries. Recent works in reinforcement learning have proposed impressive results for single character simulation, especially the ones that use imitation learning based techniques. However, imitating multiple characters interactions and motions requires to also model their interactions. In this paper, we propose a novel Multi-Agent Generative Adversarial Imitation Learning based approach that generalizes the idea of motion imitation for one character to deal with both the interaction and the motions of the multiple physics-based characters. Two unstructured datasets are given as inputs: 1) a single-actor dataset containing motions of a single actor performing a set of motions linked to a specific application, and 2) an interaction dataset containing a few examples of interactions between multiple actors. Based on these datasets, our system trains control policies allowing each character to imitate the interactive skills associated with each actor, while preserving the intrinsic style. This approach has been tested on two different fighting styles, boxing and full-body martial art, to demonstrate the ability of the method to imitate different styles.

The digitisation of historical documents has provided historians with unprecedented research opportunities. Yet, the conventional approach to analysing historical documents involves converting them from images to text using OCR, a process that overlooks the potential benefits of treating them as images and introduces high levels of noise. To bridge this gap, we take advantage of recent advancements in pixel-based language models trained to reconstruct masked patches of pixels instead of predicting token distributions. Due to the scarcity of real historical scans, we propose a novel method for generating synthetic scans to resemble real historical documents. We then pre-train our model, PHD, on a combination of synthetic scans and real historical newspapers from the 1700-1900 period. Through our experiments, we demonstrate that PHD exhibits high proficiency in reconstructing masked image patches and provide evidence of our model's noteworthy language understanding capabilities. Notably, we successfully apply our model to a historical QA task, highlighting its usefulness in this domain.

David Cronenberg has directed more than 20 feature films in a wide variety of genres, but he remains best known for provocative '80s sci-fi films like The Fly and Videodrome. Humor writer Tom Gerencer is a lifelong fan of Cronenberg's artistic vision. "He is an absolute genius, and he has merged that with an absolute mastery of craft," Gerencer says in Episode 533 of the Geek's Guide to the Galaxy podcast. "Often you see one or the other. You see someone who's very workmanlike and can produce a good movie, or you see someone who is a genius and is just all over the place, and there are good ones and bad ones. But he is both, and that's rare."

Following a lot of hype--and a quarter-century of work--"Now and Then," presumably the last song to feature all four original Beatles, is here. The track dropped Thursday and the music video, directed by Peter Jackson, hit YouTube on Friday. Sweet and haunting, it's full of piano and strings, and it wouldn't have been possible without the machine learning technology Jackson used on the docuseries Get Back. How the AI technology became the thing that saved the song is a bit of a journey. Years after John Lennon died in 1980, his wife, the musician and multimedia artist Yoko Ono, told his bandmate Paul McCartney that she had a demo tape Lennon had recorded at their apartment in the Dakota in New York City.

The Beatles have released another song, the first since 1995. "Now and Then" is being advertised as the final Beatles track, given that two of the members have passed and the other two are well over 80 years old. But then again, millionaires do love money. The song grew from a John Lennon demo track dating back to the 1970s and a 1995 guitar track from George Harrison. The surviving Beatles, Paul McCartney and Ringo Starr, then finished the tune using machine learning technology. The song was meant to come out back in 1995, along with "Free as a Bird" and "Real Love," two other tracks culled from old Lennon demos.

Kathy Ireland, CEO of Kathy Ireland Worldwide, spoke about the rapid growth of artificial intelligence and wants people to be aware of its potential impacts. As a businesswoman, Kathy Ireland is watching the rapid advancement of artificial intelligence with keen interest. "It's very interesting -- definitely moving rapidly -- and we've got to be alert to it," she told Fox News Digital. "As with all technology there, it can be used for good or evil. So, we've got to be alert to it and be on it. And I just can't stress enough the alertness and the protection that we all need. "Let's seek to use it for good and protect ourselves against any negative impacts that it could have." WHAT IS ARTIFICIAL INTELLIGENCE (AI)? Kathy Ireland told Fox News Digital she "can't stress enough the alertness and the protection that we all need" when it comes to artificial intelligence. Since founding her business, Kathy Ireland Worldwide, in 1993, Ireland has steadily added to her portfolio to establish a $500 million company. "[It] started with a single pair of socks, moved into apparel, fashion, fashion for the home, health and wellness, telemedicine, Fintech [financial technology], merchant services, wonderful companies, entertainment.