This article contains spoilers for the film Don't Look Up. Streaming just in time for Christmas, Adam McKay's decidedly uncheery Netflix comedy, Don't Look Up, finds Jennifer Lawrence and Leonardo DiCaprio playing a pair of intrepid astronomers as they try (and mostly fail) to warn the world about a planet-killing comet that's hurtling toward Earth. From the beginning, the scientists' efforts are marked by futility, encapsulated in an early scene in which Kate Dibiasky (Lawrence) and Randall Mindy (DiCaprio) are brought to the White House to debrief President Janie Orlean (Meryl Streep) on the impending extinction-level event. Predictably, the meeting goes disastrously. The president's son and chief of staff (played by Jonah Hill) lounges on the couch, nurses a bad case of coke sniffles, and proclaims to be "so bored" by all the world-ending comet talk.

Over the years, we have truly witnessed the giant leaps that technology has made. Probably one of the most astounding things science has come up with is Artificial Intelligence. It came into the world with a bang. Just a few years after conception, it was able to make its way into a lot of Hollywood movies, as a villain that humanity needs to face (Age of Ultron flashbacks). Well, while the movies might have been a bit of an exaggeration, there is no denying the limitless possibilities that Artificial Intelligence opens up for us.

he role of AI and ML in the media & entertainment industry will increase significantly in 2022, with revenue forecasted to surpass US$ 9.5 billion …

For the new sequel, "The Matrix Resurrections," filmmakers deployed much-higher-caliber technologies, including three-dimensional imagery made using artificial intelligence. But after 22 years of digital evolution, high-end movie effects are approaching a plateau near perfection. "We went from pulling off what seemed to be impossible, to a sort of inability to create surprise" in the movie industry, says John Gaeta, who helped craft the bullet-time effect. He was a visual-effects designer on the first three "Matrix" films; now he is making things for the metaverse. This year the movies presented us with a car slingshotting from cliff to cliff ("F9"); Ryan Reynolds running amok inside a videogame ("Free Guy"); and giant monsters crushing the Hong Kong skyline ("Godzilla vs. Kong").

AI software that spots duplicated images in research papers can work faster and on a larger scale than manual checkers -- but still needs editorial oversight.Credit: Laurence Dutton/Getty Just before a study appears in any of ten journals published by the American Association for Cancer Research (AACR), it undergoes an unusual extra check. Since January 2021, the AACR has been using artificial intelligence (AI) software on all manuscripts it has provisionally accepted after peer review. The aim is to automatically alert editors to duplicated images, including those in which parts have been rotated, filtered, flipped or stretched. The AACR is an early adopter in what could become a trend. Hoping to avoid publishing papers with images that have been doctored -- whether because of outright fraud or inappropriate attempts to beautify findings -- many journals have hired people to manually scan submitted manuscripts for issues, often using software to help check what they find. But Nature has learnt that in the past year, at least four publishers have started automating the process by relying on AI software to spot duplications and partial duplications before manuscripts are published.

Audiovisual scenes are pervasive in our daily life. It is commonplace for humans to discriminatively localize different sounding objects but quite challenging for machines to achieve class-aware sounding objects localization without category annotations, i.e., localizing the sounding object and recognizing its category. To address this problem, we propose a two-stage step-by-step learning framework to localize and recognize sounding objects in complex audiovisual scenarios using only the correspondence between audio and vision. First, we propose to determine the sounding area via coarse-grained audiovisual correspondence in the single source cases. Then visual features in the sounding area are leveraged as candidate object representations to establish a category-representation object dictionary for expressive visual character extraction. We generate class-aware object localization maps in cocktail-party scenarios and use audiovisual correspondence to suppress silent areas by referring to this dictionary. Finally, we employ category-level audiovisual consistency as the supervision to achieve fine-grained audio and sounding object distribution alignment. Experiments on both realistic and synthesized videos show that our model is superior in localizing and recognizing objects as well as filtering out silent ones. We also transfer the learned audiovisual network into the unsupervised object detection task, obtaining reasonable performance.

As the millennium was about to turn, The Matrix arrived in theaters like a speeding bullet--or maybe a very slow-moving one, filmed with the then-novel extreme-slo-mo special effect that would become known as "bullet time." Digital technology played a much smaller role in most people's lives in 1999. The internet was still a novelty, used by most people mainly for sending and receiving email. Smartphones were nonexistent, music was still mainly listened to on CD, and Netflix was a two-year-old company primarily in the business of mailing movies on DVD to people's houses. The idea that all of humanity was trapped in a simulation, our physical bodies parked in life-sustaining pods while our daily lives unfolded in a virtual space run by distant evil overlords, still sounded like a cool science-fiction metaphor, not a description of banal everyday reality.

Fox News Flash top entertainment and celebrity headlines are here. Check out what clicked this week in entertainment. "Wheel of Fortune" fans think a contestant on Monday's episode deserves a second chance after the show seemingly misspelled the name of rapper Yung Joc. It's rare that a show as well-known for its use of the written word as "Wheel of Fortune" would contain a gaffe as simple as a spelling error. However, that's exactly what many fans believe happened Monday when constant Kennise Miller was competing in the Bonus Round puzzle.

Starting from the mid/late 1980's, many aspiring musicians (like me…) used the legendary Commodore Amiga computer to learn and compose music. Amiga's sound and graphics capabilities were pretty incredible compared to other home computers available at the time, and it quickly became popular among gamers, coders, graphic artists and musicians all over the world, and especially in Europe. Many Amiga musicians used a tracker, a type of music software that produces modules, or mods for short. A mod is a single file that contains everything necessary to play back a full song: notation, arrangement, song structure and instruments. As you might have guessed, trackers and mods were quite primitive by today's standards.

Data and artificial intelligence (AI) are playing a key role in transforming home loan originations. And the big winner could be the customer.