A new exploit in the PC version of Grand Theft Auto Online is causing players to lose game progress and in-game currency, with some accounts becoming corrupted or banned. The exploit, a “remote code execution,” was distributed through the developer of the North Online GTA cheat mod.

The exploit can reportedly impact anyone, not just players in the same multiplayer lobby as the attacker, according toBleepingComputer. That means anyone currently online and playing the game on PC is at least theoretically vulnerable to attack. (Console players are unaffected.) Engadget reached out to Rockstar for comment, and we will update this article if we hear back.

The company tweeted this acknowledgment of the fiasco on Monday.

North's developer removed the abusive elements on January 21st and apologized (their changelog read “bad judgement on my part for adding this public.”) Although GTA Online doesn’t block harmless community-created mods, those distributing cheats or other hacks tilting the game’s competitive balance may face real-world consequences. Rockstar and parent company Take-Two Interactive have previously taken legal action against cheat makers, including the creator of an infinite-money hack who was ordered to pay $150,000 plus attorney fees in 2019.

A workaround for corrupted accounts, which some players have claimed works, is to delete the “Rockstar Games” folder from the Windows Documents folder before reloading the game. However, we recommend avoiding the PC version until Rockstar cleans things up.

Elon Musk wasn't lying last October when he told Bloomberg that 75 percent of the employees at his newly acquired toy, Twitter.com, wouldn't lose their jobs under his ownership, as The Washington Post had reported at the time. Turns out, it's closer to 80 percent. Of the roughly 7,500 people working there before Musk's takeover, CNBC reports Friday that barely 1,300 in total, and fewer than 550 full-time engineers, are left at the husk of a company, either through said layoffs or voluntary resignations.

CNBC also notes that 75 employees are currently on leave, 40 of which are engineers, while the Trust and Safety team, which oversees content moderation for the site, has been culled to fewer than 20 full-timers. This news comes at the end of a seemingly ceaseless string of blunders since Musk announced an unsolicited $44 billion bid to buy the social media site last April. 

Aside from firing everyone that wasn't nailed down, Musk has reinstated numerous far-right and fascist accounts that had previously been permanently banned without so much as a second glance at the "moderation council" he was supposedly going to establish. He's made critical operational decisions based on Twitter polls — and that's after trying weasel out of the deal to purchase Twitter in the first place on trumped up complaints regarding the prevalence of bot users and how easy it is to game Twitter polls. 

He's used the banhammer to silence critics ranging from journalists to college kids. Musk has brought in employees from his other, unrelated companies, including members of the SpaceX and Tesla teams; and fired employees for questioning his business acumen. His $8 blue check verification scheme has haltingly rolled out in fits and starts, this while ad revenue is reportedly down 40 percent as advertisers look to escape his sinking ship. His first interest payment on the $13 billion debt he leveraged to purchase Twitter, which is today valued at around $15 billion, is due at the end of the month.

But Twitter isn't the only company shedding staff like water off a wet dog's coat. Google laid off 12,000 employees this week, Amazon disemployeed 18,000 people globally, and Microsoft eliminated 10,000 positions. Between the three, they've put about 70,000 people out of work in the last year alone.   

It's been over 12 years since Tron: Legacy debuted and those who've been longing for a third entry in the classic sci-fi series may have wished for it on a monkey's paw. Tron: Ares, as the film may be called, could start filming this August with Jared Leto, ol' Morbius himself, reportedly set to star. Joachim Rønning (Maleficent: Mistress of Evil and Pirates of the Caribbean: Dead Men Tell No Tales) is in talks to direct, according to Deadline.

As Variety notes, Leto first signed on back in 2017, but Disney has had a third movie on the backburner since long before then. Tron: Legacy director Joseph Kosinski (who went on to make Top Gun: Maverick) said in an interview that he wrote and storyboarded a sequel "that takes place on the internet with Yahoo and Google and all those sites." Kosinski said he was close to moving forward with it in 2015 but suggested Disney "pulled the plug" as it had bigger, Marvel- and Star Wars-sized fish to focus on.

This time around, Tron: Ares could finally be happening. Unfortunately, it seems unlikely that Daft Punk will return to deliver another banger of a score. The iconic duo split up in 2021.

Sega has at last revealed when folks will be able to snap up Endless Dungeon. The action-packed game is coming to Steam, Epic Games Store, Xbox Series X/S, PlayStation 4 and PlayStation 5 on May 18th. A Nintendo Switch version will be available later.

Endless Dungeon, from developer Amplitude Studios, was previously slated for a 2022 debut. It's a squad-based blend of a tower defense game and a twin-stick shooter. Players are tasked with both protecting a so-called crystal bot and progressing further into a dungeon.

You can team up with three friends or go it alone and control three characters by yourself (you'll have direct control over one and bark orders at the other two). Endless Dungeon is a roguelite, so you'll gradually unlock persistent upgrades, weapons and characters.

Alongside the release date announcement, Sega opened up pre-orders for most platforms. You'll get early access two days before the official launch, as well as some extra goodies, by pre-ordering the “Last Wish” digital edition. A physical Day One edition with a card game and art book is available too. Sega also released a new trailer which shows some more chaotic gameplay:

Adobe's Camera to Cloud system, which can upload footage from cameras to the cloud (shockingly enough), is now available without the need for additional hardware. In what the company is calling an industry first, the tech is integrated into RED's V-Raptor and V-Raptor XL cinema camera systems, which can directly upload 8K RAW footage to Frame.io. The only other thing you'll really need is a high-bandwidth internet connection.

Swift cloud uploads should let post-production teams start work on the footage quickly, wherever they may be located. Adobe suggests this can save production companies time and money. It previewed the RED Camera to Cloud integration at Adobe Max in October, noting at the time that Fujifilm's X-H2S mirrorless camera would also be able to upload RAW photos to Frame.io directly.

Adobe says more than 6,000 productions are already using Camera to Cloud, which until the RED integration required another piece of gear. Now, anyone who happens to have a V-Raptor camera can try it out. Direct Camera to Cloud uploads will likely remain the domain of professionals for now (the V-Raptor starts at $24,500), but here's hoping Adobe brings the integration to other cameras soon.

In addition, Adobe announced at the Sundance Film Festival that a beta version of an AI-powered video editing tool is opening up to more users, but not everyone just yet. The web-based Project Blink pinpoints people, objects, dialogue, actions and sounds in video and makes them all searchable. When the AI finds the relevant section, it creates a new clip. You can copy and paste text and the tool will slot in that part of the video.

Among the new features and upgrades include more audio tags (which flag elements like applause and laughter) and the option for users to upload as many files as they wish thanks to infinite scrolling in the library. Project Blink isn't the only text-based video editing tool around, however. Other companies, such as Descript and Runway, have developed their own versions.

Twitter is now offering a yearly discount on its Blue subscription service, according to a new support page spotted by The Verge. Web users can now sign up for $84 per year ($7 per month) and save a buck over the monthly $8 price. Similar discounts are available in other countries that offer Twitter Blue, including the UK, Canada, Australia, New Zealand and Japan. 

Until now, Twitter Blue users only had the option of an $8 per month subscription via the web, or $11 month on iOS (passing Apple's 30 percent fee onto the user). However, iOS users can still sign up on the web to save the extra $3. In that case, the new yearly subscription would save them 36 percent compared to signing up directly on iOS. 

A Twitter Blue subscription offers a number of perks, including a blue "verified" checkmark, higher ranking replies, 60-minute video uploads and more. Users can also undo and edit tweets, customize app icons, themes and navigations, bookmark tweets and more. You'll need a phone number to sign up, and Twitter is supposed to verify your account to assure it's not fraudulent or fake — something it failed at recently. 

The Elon Musk-owned social media network seems to need as many subscriptions as possible. According to a recent report on The Information, more than 500 of Twitter's advertisers have paused spending on the site, and daily revenue on January 17th was down 40 percent compared to last year. 

In the first quarter of 2022 before Musk's acquisition was finalized, Twitter reported sales of $1.2 billion, with $1.1 billion of that in advertising, and subscriptions (plus other revenue) making up the rest. 

If you enjoyed HBO's take on The Last of Us, you're far from alone. WarnerMedia has revealed that the video game adaptation racked up 4.7 million viewers on conventional and streaming TV for its January 15th premiere, making it HBO's third largest debut of the streaming era. Only the Game of Thrones spinoff House of the Dragon rated higher with a crowd topping 9.9 million, and Boardwalk Empire's 4.81 million-viewer launch from 2010 (when HBO Go arrived) was only slightly stronger.

The Last of Us "nearly doubled" the audience for Euphoria's season two opener, WarnerMedia says. While it's not yet clear how well the game series will fare in the long term, the company notes that Sunday night viewing for an HBO show tends to account for 20 to 40 percent of the total gross viewership per episode.

The strong initial performance isn't surprising. On top of the long hype campaign, The Last of Us has well-known names (including Pedro Pascal, Bella Ramsey and Chernobyl creator Craig Mazin) as well as the benefit of an established fan base from Naughty Dog's game franchise. Include HBO Max availability and a good early critical response and there were many people willing to tune in.

It's too soon to say if The Last of Us will be the most popular game-based TV series to date. It has to compete with successes like Netflix's League of Legends series Arcane, among others. However, the initial viewing data suggests this bet on a lavish production has paid off for everyone involved. In that light, it's easy to see why Sony was willing to commit to TV shows for God of War and Horizon. As with rival shows like Halo, this is a chance to expand interest in a franchise to many more people.

Disney+ has released a new trailer for The Mandalorian during the NFL Wild Card Game on ESPN and ABC Network. It shows Pedro Pascal's character Din Djarin and Grogu reunited and going on their next adventure. Din also reveals in the trailer that he's going back to the planet Mandalore in an effort to redeem himself after removing his helmet and showing his face to other people by the end of season 2. As revealed in previous episodes, Din is a member of the religious sect Children of the Watch that views removing one's helmet in the presence of others a serious transgression.

While Din is dealing with the consequences of his decision, the New Republic is struggling: "There's something dangerous happening out there," Captain Carson Teva warned. "And by the time it becomes big enough for you to act, it'll be too late." The trailer also shows Grogu exhibiting better control of the Force after leaving with Luke Skywalker in the previous season to train at his Jedi Temple. 

Disney released its first teaser trailer for the show at last year's D23 Expo, showing us that everybody's favorite Star Wars family will indeed get reunited for season 3. Now this newer trailer gives us a taste of what Din and Grogu will encounter. Not that we have long to wait for the next season to drop — season 3 will be available for streaming on Disney+ starting on March 1st.

As of October, singers, songwriters and music makers are uploading 100,000 new songs every day to streaming services like Spotify. That is too much music. There's no reality, alternate or otherwise, wherein someone could conceivably listen to all that even in a thousand lifetimes. Whether you're into Japanese noise, Russian hardcore, Senegalese afro-house, Swedish doom metal, or Bay Area hip hop, the sheer scale of available listening options is paralyzing. It's a monumental problem that data scientist Glenn McDonald is working to solve. In the excerpt below from Computing Taste: Algorithms and the Makers of Music Recommendation, author and Tuft's University anthropologist Nick Seaver explores McDonald's unique landscape-based methodology for surfacing all the tracks you never knew you couldn't live without.       

University of Chicago Press

Reprinted with permission from Computing Taste: Algorithms and the Makers of Music Recommendation by Nick Seaver, published by The University of Chicago Press. © 2022 by The University of Chicago. All rights reserved.

The World of Music

“We are now at the dawn of the age of infinitely connected music,” the data alchemist announced from beneath the Space Needle. Glenn McDonald had chosen his title himself, preferring “alchemy,” with its esoteric associations, over the now-ordinary “data science.” His job, as he described it from the stage, was “to use math and typing and computers to help people understand and discover music.” 

McDonald practiced his alchemy for the music streaming service Spotify, where he worked to transmute the base stuff of big data — logs of listener interactions, bits of digital audio files, and whatever else he could get his hands on — into valuable gold: products that might attract and retain paying customers. The mysterious power of McDonald’s alchemy lay in the way that ordinary data, if processed correctly, appeared to transform from thin interactional traces into thick cultural significance.

It was 2014, and McDonald was presenting at the Pop Conference, an annual gathering of music critics and academics held in a crumpled, Frank Gehry–designed heap of a building in the center of Seattle. I was on the other side of the country, and I followed along online. That year, the conference’s theme was “Music and Mobility,” and Mc Donald started his talk by narrating his personal musical journey, playing samples as he went. “When I was a kid,” he began, “you discovered music by holding still and waiting.” As a child at home, he listened to the folk music his parents played on the stereo. But as he grew up, his listening expanded: the car radio offered heavy metal and new wave; the internet revealed a world of new and obscure genres to explore. Where once he had been stuck in place, a passive observer of music that happened to go by, he would eventually measure the progress of his life by his ever broadening musical horizons. McDonald had managed to turn this passion into a profession, working to help others explore what he called “the world of music,” which on-demand streaming services had made more accessible than ever before.

Elsewhere, McDonald (2013) would describe the world of music as though it were a landscape: “Follow any path, no matter how unlikely and untrodden it appears, and you’ll find a hidden valley with a hundred bands who’ve lived there for years, reconstructing the music world in methodically- and idiosyncratically-altered miniature, as in Australian hip hop, Hungarian pop, microhouse or Viking metal.” 

Travelers through the world of music would find familiarity and surprise — sounds they never would have imagined and songs they adored. McDonald marveled at this new ability to hear music from around the world, from Scotland, Australia, or Malawi. “The perfect music for you may come from the other side of the planet,” he said, but this was not a problem: “in music, we have the teleporter.” On-demand streaming provided a kind of musical mobility, which allowed listeners to travel across the world of music instantaneously.

However, he suggested, repeating the common refrain, the scale of this world could be overwhelming and hard to navigate. “For this new world to actually be appreciable,” McDonald said, “we have to find ways to map this space and then build machines to take you through it along interesting paths.” The recommender systems offered by companies like Spotify were the machines. McDonald’s recent work had focused on the maps, or as he described them in another talk: a “kind of thin layer of vaguely intelligible order over the writhing, surging, insatiably expanding information-space-beast of all the world’s music.”

Although his language may have been unusually poetic, McDonald was expressing an understanding of musical variety that is widely shared among the makers of music recommendation: Music exists in a kind of space. That space is, in one sense, fairly ordinary — like a landscape that you might walk through, encountering new things as you go. But in another sense, this space is deeply weird: behind the valleys and hills, there is a writhing, surging beast, constantly growing and tying points in the space together, infinitely connected. The music space can seem as natural as the mountains visible from the top of the Space Needle; but it can also seem like the man-made topological jumble at its base. It is organic and intuitive; it is technological and chaotic.

Spatial metaphors provide a dominant language for thinking about differences among the makers of music recommendation, as they do in machine learning and among Euro-American cultures more generally. Within these contexts, it is easy to imagine certain, similar things as gathered over here, while other, different things cluster over there. In conversations with engineers, it is very common to find the music space summoned into existence through gestures, which envelop the speakers in an imaginary environment populated by brief pinches in the air and organized by waves of the hand. One genre is on your left, another on your right. On whiteboards and windows scattered around the office, you might find the music space rendered in two dimensions, containing an array of points that cluster and spread across the plane.

In the music space, music that is similar is nearby. If you find yourself within such a space, you should be surrounded by music that you like. To find more of it, you need only to look around you and move. In the music space, genres are like regions, playlists are like pathways, and tastes are like drifting, archipelagic territories. Your new favorite song may lie just over the horizon.

But despite their familiarity, spaces like these are strange: similarities can be found anywhere, and points that seemed far apart might suddenly become adjacent. If you ask, you will learn that all of these spatial representations are mere reductions of something much more complex, of a space comprising not two or three dimensions but potentially thousands of them. This is McDonald’s information-space-beast, a mathematical abstraction that stretches human spatial intuitions past their breaking point.

Spaces like these, generically called “similarity spaces,” are the symbolic terrain on which most machine learning works. To classify data points or recommend items, machine-learning systems typically locate them in spaces, gather them into clusters, measure distances among them, and draw boundaries between them. Machine learning, as the cultural theorist Adrian Mackenzie (2017, 63) has argued, “renders all differences as distances and directions of movement.” So while the music space is in one sense an informal metaphor (the landscape of musical variation) in another sense it is a highly technical formal object (the mathematical substrate of algorithmic recommendation).

Spatial understandings of data travel through technical infrastructures and everyday conversation; they are at once a form of metaphorical expression and a concrete computational practice. In other words, “space” here is both a formalism — a restricted, technical concept that facilitates precision through abstraction — and what the anthropologist Stefan Helmreich (2016, 468) calls an informalism — a less disciplined metaphor that travels alongside formal techniques. In practice, it is often hard or impossible to separate technical specificity from its metaphorical accompaniment. When the makers of music recommendation speak of space, they speak at once figuratively and technically.

For many critics, this “geometric rationality” (Blanke 2018) of machine learning makes it anathema to “culture” per se: it quantifies qualities, rationalizes passions, and plucks cultural objects from their everyday social contexts to relocate them in the sterile isolation of a computational grid. Mainstream cultural anthropology, for instance, has long defined itself in opposition to formalisms like these, which seem to lack the thickness, sensitivity, or adequacy to lived experience that we seek through ethnography. As the political theorists Louise Amoore and Volha Piotukh (2015, 361) suggest, such analytics “reduce heterogeneous forms of life and data to homogeneous spaces of calculation.”

To use the geographer Henri Lefebvre’s (1992) terms, similarity spaces are clear examples of “abstract space” — a kind of representational space in which everything is measurable and quantified, controlled by central authorities in the service of capital. The media theorist Robert Prey (2015, 16), applying Lefebvre’s framework to streaming music, suggests that people like McDonald — “data analysts, programmers and engineers” — are primarily concerned with the abstract, conceived space of calculation and measurement. Conceived space, in Lefebvrian thought, is parasitic on social, lived space, which Prey associates with the listeners who resist and reinterpret the work of technologists. The spread of abstract space under capitalism portends, in this framework, “the devastating conquest of the lived by the conceived” (Wilson 2013).

But for the people who work with it, the music space does not feel like a sterile grid, even at its most mathematical. The makers of music recommendation do not limit themselves to the refined abstractions of conceived space. Over the course of their training, they learn to experience the music space as ordinary and inhabitable, despite its underlying strangeness. The music space is as intuitive as a landscape to be walked across and as alien as a complex, highly dimensional object of engineering. To use an often- problematized distinction from cultural geography, they treat “space” like “place,” as though the abstract, homogeneous grid were a kind of livable local environment.

Similarity spaces are the result of many decisions; they are by no means ``natural,” and people like McDonald are aware that the choices they make can profoundly rearrange them. Yet spatial metaphorizing, moving across speech, gesture, illustration, and computation, helps make the patterns in cultural data feel real. A confusion between maps and territories— between malleable representations and objective terrains— is productive for people who are at once interested in creating objective knowledge and concerned with accounting for their own subjective influence on the process. These spatial understandings alter the meaning of musical concepts like genre or social phenomena like taste, rendering them as forms of clustering.

Twitter’s “For You” tab, which debuted on iOS devices earlier this week, has begun rolling out to desktop web browsers. The new interface replaces the “sparkle” icon that previously allowed you to toggle between the platform’s algorithmically generated and reverse chronological feeds.

As The Verge notes, the For You tab is now the default view you see when you first visit Twitter after the update is available on your web browser. That said, the desktop version doesn’t appear to force you to stick with the For You feed like Twitter’s updated iOS app does. When I visited the website on my computer, I switched to the “Following” view and then closed the tab where I was viewing my feed. When I opened a new tab and navigated back to Twitter, the site defaulted to the Following view.

On Friday, Twitter said the new interface would roll out to Android devices “soon.” Twitter introduced a similar feature in 2022, only to abandon the idea days after a chorus of users complained they didn’t want the previously named Home feed imposed on them. However, at the end of last year, Musk tweeted that Twitter would move forward with the change. “Main timeline should allow for an easy sideways swipe between the top, latest, trending and topics that follow," he said at the time. "Twitter search nav already sorta does this after you search."