Biz & IT

inside-a-violent-gang’s-ruthless-crypto-stealing-home-invasion-spree

Inside a violent gang’s ruthless crypto-stealing home invasion spree

Biz & IT, Cryptocurrency, extortion, Security, syndication / /

brutal extortion —

More than a dozen men threatened, assaulted, tortured, or kidnapped 11 victims.

–

photo illustration of Cyber thieves stealing Bitcoin on laptop screen

Cryptocurrency has always made a ripe target for theft—and not just hacking, but the old-fashioned, up-close-and-personal kind, too. Given that it can be irreversibly transferred in seconds with little more than a password, it’s perhaps no surprise that thieves have occasionally sought to steal crypto in home-invasion burglaries and even kidnappings. But rarely do those thieves leave a trail of violence in their wake as disturbing as that of one recent, ruthless, and particularly prolific gang of crypto extortionists.

The United States Justice Department earlier this week announced the conviction of Remy Ra St. Felix, a 24-year-old Florida man who led a group of men behind a violent crime spree designed to compel victims to hand over access to their cryptocurrency savings. That announcement and the criminal complaint laying out charges against St. Felix focused largely on a single theft of cryptocurrency from an elderly North Carolina couple, whose home St. Felix and one of his accomplices broke into before physically assaulting the two victims—both in their seventies—and forcing them to transfer more than $150,000 in bitcoin and ether to the thieves’ crypto wallets.

In fact, that six-figure sum appears to have been the gang’s only confirmed haul from its physical crypto thefts—although the burglars and their associates made millions in total, mostly through more traditional crypto hacking as well as stealing other assets. A deeper look into court documents from the St. Felix case, however, reveals that the relatively small profit St. Felix’s gang made from its burglaries doesn’t capture the full scope of the harm they inflicted: In total, those court filings and DOJ officials describe how more than a dozen convicted and alleged members of the crypto-focused gang broke into the homes of 11 victims, carrying out a brutal spree of armed robberies, death threats, beatings, torture sessions, and even one kidnapping in a campaign that spanned four US states.

In court documents, prosecutors say the men—working in pairs or small teams—threatened to cut toes or genitalia off of one victim, kidnapped and discussed killing another, and planned to threaten another victim’s child as leverage. Prosecutors also describe disturbing torture tactics: how the men inserted sharp objects under one victim’s fingernails and burned another with a hot iron, all in an effort to coerce their targets to hand over the devices and passwords necessary to transfer their crypto holdings.

“The victims in this case suffered a horrible, painful experience that no citizen should have to endure,” Sandra Hairston, a US attorney for the Middle District of North Carolina who prosecuted St. Felix’s case, wrote in the Justice Department’s announcement of St. Felix’s conviction. “The defendant and his coconspirators acted purely out of greed and callously terrorized those they targeted.”

The serial extortion spree is almost certainly the worst of its kind ever to be prosecuted in the US, says Jameson Lopp, the cofounder and chief security officer of Casa, a cryptocurrency-focused physical security firm, who has tracked physical attacks designed to steal cryptocurrency going back as far as 2014. “As far as I’m aware, this is the first case where it was confirmed that the same group of people went around and basically carried out home invasions on a variety of different victims,” Lopp says.

Lopp notes, nonetheless, that this kind of crime spree is more than a one-off. He has learned of other similar attempts at physical theft of cryptocurrency in just the past month that have escaped public reporting—he says the victims in those cases asked him not to share details—and suggests that in-person crypto extortion may be on the rise as thieves realize the attraction of crypto as a highly valuable and instantly transportable target for theft. “Crypto, as this highly liquid bearer asset, completely changes the incentives of doing something like a home invasion,” Lopp says, “or even kidnapping and extortion and ransom.”

Inside a violent gang’s ruthless crypto-stealing home invasion spree Read More »

researchers-craft-smiling-robot-face-from-living-human-skin-cells

Researchers craft smiling robot face from living human skin cells

AI, Biz & IT, foreskin, Harvard, human skin, human skin cells, PromoCell, robot, Science, skin cells, slimy, Tech, University of Tokyo / /
A movable robotic face covered with living human skin cells.

Enlarge / A movable robotic face covered with living human skin cells.

In a new study, researchers from the University of Tokyo, Harvard University, and the International Research Center for Neurointelligence have unveiled a technique for creating lifelike robotic skin using living human cells. As a proof of concept, the team engineered a small robotic face capable of smiling, covered entirely with a layer of pink living tissue.

The researchers note that using living skin tissue as a robot covering has benefits, as it’s flexible enough to convey emotions and can potentially repair itself. “As the role of robots continues to evolve, the materials used to cover social robots need to exhibit lifelike functions, such as self-healing,” wrote the researchers in the study.

Shoji Takeuchi, Michio Kawai, Minghao Nie, and Haruka Oda authored the study, titled “Perforation-type anchors inspired by skin ligament for robotic face covered with living skin,” which is due for July publication in Cell Reports Physical Science. We learned of the study from a report published earlier this week by New Scientist.

The study describes a novel method for attaching cultured skin to robotic surfaces using “perforation-type anchors” inspired by natural skin ligaments. These tiny v-shaped cavities in the robot’s structure allow living tissue to infiltrate and create a secure bond, mimicking how human skin attaches to underlying tissues.

To demonstrate the skin’s capabilities, the team engineered a palm-sized robotic face able to form a convincing smile. Actuators connected to the base allowed the face to move, with the living skin flexing. The researchers also covered a static 3D-printed head shape with the engineered skin.

Enlarge / “Demonstration of the perforation-type anchors to cover the facial device with skin equivalent.”

Takeuchi et al. created their robotic face by first 3D-printing a resin base embedded with the perforation-type anchors. They then applied a mixture of human skin cells in a collagen scaffold, allowing the living tissue to grow into the anchors.

Researchers craft smiling robot face from living human skin cells Read More »

openai’s-new-“criticgpt”-model-is-trained-to-criticize-gpt-4-outputs

OpenAI’s new “CriticGPT” model is trained to criticize GPT-4 outputs

AI, Biz & IT, chatgpt, chatgtp, CriticGPT, GPT-4, GPT-4-turbo, GPT-4o, machine learning, openai / /

automated critic —

Research model catches bugs in AI-generated code, improving human oversight of AI.

–

An illustration created by OpenAI.

Enlarge / An illustration created by OpenAI.

On Thursday, OpenAI researchers unveiled CriticGPT, a new AI model designed to identify mistakes in code generated by ChatGPT. It aims to enhance the process of making AI systems behave in ways humans want (called “alignment”) through Reinforcement Learning from Human Feedback (RLHF), which helps human reviewers make large language model (LLM) outputs more accurate.

As outlined in a new research paper called “LLM Critics Help Catch LLM Bugs,” OpenAI created CriticGPT to act as an AI assistant to human trainers who review programming code generated by the ChatGPT AI assistant. CriticGPT—based on the GPT-4 family of LLMS—analyzes the code and points out potential errors, making it easier for humans to spot mistakes that might otherwise go unnoticed. The researchers trained CriticGPT on a dataset of code samples with intentionally inserted bugs, teaching it to recognize and flag various coding errors.

The researchers found that CriticGPT’s critiques were preferred by annotators over human critiques in 63 percent of cases involving naturally occurring LLM errors and that human-machine teams using CriticGPT wrote more comprehensive critiques than humans alone while reducing confabulation (hallucination) rates compared to AI-only critiques.

Developing an automated critic

The development of CriticGPT involved training the model on a large number of inputs containing deliberately inserted mistakes. Human trainers were asked to modify code written by ChatGPT, introducing errors and then providing example feedback as if they had discovered these bugs. This process allowed the model to learn how to identify and critique various types of coding errors.

In experiments, CriticGPT demonstrated its ability to catch both inserted bugs and naturally occurring errors in ChatGPT’s output. The new model’s critiques were preferred by trainers over those generated by ChatGPT itself in 63 percent of cases involving natural bugs (the aforementioned statistic). This preference was partly due to CriticGPT producing fewer unhelpful “nitpicks” and generating fewer false positives, or hallucinated problems.

The researchers also created a new technique they call Force Sampling Beam Search (FSBS). This method helps CriticGPT write more detailed reviews of code. It lets the researchers adjust how thorough CriticGPT is in looking for problems, while also controlling how often it might make up issues that don’t really exist. They can tweak this balance depending on what they need for different AI training tasks.

Interestingly, the researchers found that CriticGPT’s capabilities extend beyond just code review. In their experiments, they applied the model to a subset of ChatGPT training data that had previously been rated as flawless by human annotators. Surprisingly, CriticGPT identified errors in 24 percent of these cases—errors that were subsequently confirmed by human reviewers. OpenAI thinks this demonstrates the model’s potential to generalize to non-code tasks and highlights its ability to catch subtle mistakes that even careful human evaluation might miss.

Despite its promising results, like all AI models, CriticGPT has limitations. The model was trained on relatively short ChatGPT answers, which may not fully prepare it for evaluating longer, more complex tasks that future AI systems might tackle. Additionally, while CriticGPT reduces confabulations, it doesn’t eliminate them entirely, and human trainers can still make labeling mistakes based on these false outputs.

The research team acknowledges that CriticGPT is most effective at identifying errors that can be pinpointed in one specific location within the code. However, real-world mistakes in AI outputs can often be spread across multiple parts of an answer, presenting a challenge for future iterations of the model.

OpenAI plans to integrate CriticGPT-like models into its RLHF labeling pipeline, providing its trainers with AI assistance. For OpenAI, it’s a step toward developing better tools for evaluating outputs from LLM systems that may be difficult for humans to rate without additional support. However, the researchers caution that even with tools like CriticGPT, extremely complex tasks or responses may still prove challenging for human evaluators—even those assisted by AI.

OpenAI’s new “CriticGPT” model is trained to criticize GPT-4 outputs Read More »

mac-users-served-info-stealer-malware-through-google-ads

Mac users served info-stealer malware through Google ads

Biz & IT, Security / /

MOAR MALVERTISING —

Full-service Poseidon info stealer pushed by “advertiser identity verified by Google.”

–

Mac users served info-stealer malware through Google ads

Getty Images

Mac malware that steals passwords, cryptocurrency wallets, and other sensitive data has been spotted circulating through Google ads, making it at least the second time in as many months the widely used ad platform has been abused to infect web surfers.

The latest ads, found by security firm Malwarebytes on Monday, promote Mac versions of Arc, an unconventional browser that became generally available for the macOS platform last July. The listing promises users a “calmer, more personal” experience that includes less clutter and distractions, a marketing message that mimics the one communicated by The Browser Company, the start-up maker of Arc.

When verified isn’t verified

According to Malwarebytes, clicking on the ads redirected Web surfers to arc-download[.]com, a completely fake Arc browser page that looks nearly identical to the real one.

Malwarebytes

Digging further into the ad shows that it was purchased by an entity called Coles & Co, an advertiser identity Google claims to have verified.

Malwarebytes

Visitors who click the download button on arc-download[.]com will download a .dmg installation file that looks similar to the genuine one, with one exception: instructions to run the file by right-clicking and choosing open, rather than the more straightforward method of simply double clicking on the file. The reason for this is to bypass a macOS security mechanism that prevents apps from being installed unless they’re digitally signed by a developer Apple has vetted.

Malwarebytes

An analysis of the malware code shows that once installed, the stealer sends data to the IP address 79.137.192[.]4. The address happens to host the control panel for Poseidon, the name of a stealer actively sold in criminal markets. The panel allows customers to access accounts where data collected can be accessed.

Malwarebytes

“There is an active scene for Mac malware development focused on stealers,” Jérôme Segura, lead malware intelligence analyst at Malwarebytes, wrote. “As we can see in this post, there are many contributing factors to such a criminal enterprise. The vendor needs to convince potential customers that their product is feature-rich and has low detection from antivirus software.”

Poseidon advertises itself as a full-service macOS stealer with capabilities including “file grabber, cryptocurrency wallet extractor, password stealer from managers such as Bitwarden, KeePassXC, and browser data collector.” Crime forum posts published by the stealer creator bill it as a competitor to Atomic Stealer, a similar stealer for macOS. Segura said both apps share much of the same underlying source code.

The post author, Rodrigo4, has added a new feature for looting VPN configurations, but it’s not currently functional, likely because it’s still in development. The forum post appeared on Sunday, and Malwarebytes found the malicious ads one day later. The discovery comes a month after Malwarebytes identified a separate batch of Google ads pushing a fake version of Arc for Windows. The installer in that campaign installed a suspected infostealer for that platform.

Malwarebytes

Like most other large advertising networks, Google Ads regularly serves malicious content that isn’t taken down until third parties have notified the company. Google Ads takes no responsibility for any damage that may result from the oversights. The company said in an email it removes malicious ads once it learns of them and suspends the advertiser and has done so in this case.

People who want to install software advertised online should seek out the official download site rather than relying on the site linked in the ad. They should also be wary of any instructions that direct Mac users to install apps through the double-click method mentioned earlier. The Malwarebytes post provides indicators of compromise people can use to determine if they’ve been targeted.

Mac users served info-stealer malware through Google ads Read More »

ai-generated-al-michaels-to-provide-daily-recaps-during-2024-summer-olympics

AI-generated Al Michaels to provide daily recaps during 2024 Summer Olympics

2024 Summer Olympics, AI, Al Michaels, Biz & IT, chatgpt, chatgtp, Deepfakes, machine learning, nbc, nfl, olympic games, Olympics, speech synthesis, sports, sports commentators, Summer Olympics, voice synthesis / /

forever young —

AI voice clone will narrate daily Olympics video recaps; critics call it a “code-generated ghoul.”

–

Al Michaels looks on prior to the game between the Minnesota Vikings and Philadelphia Eagles at Lincoln Financial Field on September 14, 2023 in Philadelphia, Pennsylvania.

Enlarge / Al Michaels looks on prior to the game between the Minnesota Vikings and Philadelphia Eagles at Lincoln Financial Field on September 14, 2023, in Philadelphia, Pennsylvania.

On Wednesday, NBC announced plans to use an AI-generated clone of famous sports commentator Al Michaels‘ voice to narrate daily streaming video recaps of the 2024 Summer Olympics in Paris, which start on July 26. The AI-powered narration will feature in “Your Daily Olympic Recap on Peacock,” NBC’s streaming service. But this new, high-profile use of voice cloning worries critics, who say the technology may muscle out upcoming sports commentators by keeping old personas around forever.

NBC says it has created a “high-quality AI re-creation” of Michaels’ voice, trained on Michaels’ past NBC appearances to capture his distinctive delivery style.

The veteran broadcaster, revered in the sports commentator world for his iconic “Do you believe in miracles? Yes!” call during the 1980 Winter Olympics, has been covering sports on TV since 1971, including a high-profile run of play-by-play coverage of NFL football games for both ABC and NBC since the 1980s. NBC dropped him from NFL coverage in 2023, however, possibly due to his age.

Michaels, who is 79 years old, shared his initial skepticism about the project in an interview with Vanity Fair, as NBC News notes. After hearing the AI version of his voice, which can greet viewers by name, he described the experience as “astonishing” and “a little bit frightening.” He said the AI recreation was “almost 2% off perfect” in mimicking his style.

The Vanity Fair article provides some insight into how NBC’s new AI system works. It first uses a large language model (similar technology to what powers ChatGPT) to analyze subtitles and metadata from NBC’s Olympics video coverage, summarizing events and writing custom output to imitate Michaels’ style. This text is then fed into an unspecified voice AI model trained on Michaels’ previous NBC appearances, reportedly replicating his unique pronunciations and intonations.

NBC estimates that the system could generate nearly 7 million personalized variants of the recaps across the US during the games, pulled from the network’s 5,000 hours of live coverage. Using the system, each Peacock user will receive about 10 minutes of personalized highlights.

A diminished role for humans in the future?

Al Michaels reports on the Sweden vs. USA men's ice hockey game at the 1980 Olympic Winter Games on February 12, 1980.

Enlarge / Al Michaels reports on the Sweden vs. USA men’s ice hockey game at the 1980 Olympic Winter Games on February 12, 1980.

It’s no secret that while AI is wildly hyped right now, it’s also controversial among some. Upon hearing the NBC announcement, critics of AI technology reacted strongly. “@NBCSports, this is gross,” tweeted actress and filmmaker Justine Bateman, who frequently uses X to criticize technologies that might replace human writers or performers in the future.

A thread of similar responses from X users reacting to the sample video provided above included criticisms such as, “Sounds pretty off when it’s just the same tone for every single word.” Another user wrote, “It just sounds so unnatural. No one talks like that.”

The technology will not replace NBC’s regular human sports commentators during this year’s Olympics coverage, and like other forms of AI, it leans heavily on existing human work by analyzing and regurgitating human-created content in the form of captions pulled from NBC footage.

Looking down the line, due to AI media cloning technologies like voice, video, and image synthesis, today’s celebrities may be able to attain a form of media immortality that allows new iterations of their likenesses to persist through the generations, potentially earning licensing fees for whoever holds the rights.

We’ve already seen it with James Earl Jones playing Darth Vader’s voice, and the trend will likely continue with other celebrity voices, provided the money is right. Eventually, it may extend to famous musicians through music synthesis and famous actors in video-synthesis applications as well.

The possibility of being muscled out by AI replicas factored heavily into a Hollywood actors’ strike last year, with SAG-AFTRA union President Fran Drescher saying, “If we don’t stand tall right now, we are all going to be in trouble. We are all going to be in jeopardy of being replaced by machines.”

For companies that like to monetize media properties for as long as possible, AI may provide a way to maintain a media legacy through automation. But future human performers may have to compete against all of the greatest performers of the past, rendered through AI, to break out and forge a new career—provided there will be room for human performers at all.

“Al Michaels became Al Michaels because he was brought in to replace people who died, or retired, or moved on,” tweeted a writer named Geonn Cannon on X. “If he can’t do the job anymore, it’s time to let the next Al Michaels have a shot at it instead of just planting a code-generated ghoul in an empty chair.“

AI-generated Al Michaels to provide daily recaps during 2024 Summer Olympics Read More »

toys-“r”-us-riles-critics-with-“first-ever”-ai-generated-commercial-using-sora

Toys “R” Us riles critics with “first-ever” AI-generated commercial using Sora

AI, Air Head, Biz & IT, Joe Russo, machine learning, Mike Drucker, Native Foreign, Patrick Cederberg, shy kids, Toys, Toys"R"Us, video synthesis / /
A screen capture from the partially AI-generated Toys

Enlarge / A screen capture from the partially AI-generated Toys “R” Us brand film created using Sora.

Toys R Us

On Monday, Toys “R” Us announced that it had partnered with an ad agency called Native Foreign to create what it calls “the first-ever brand film using OpenAI’s new text-to-video tool, Sora.” OpenAI debuted Sora in February, but the video synthesis tool has not yet become available to the public. The brand film tells the story of Toys “R” Us founder Charles Lazarus using AI-generated video clips.

“We are thrilled to partner with Native Foreign to push the boundaries of Sora, a groundbreaking new technology from OpenAI that’s gaining global attention,” wrote Toys “R” Us on its website. “Sora can create up to one-minute-long videos featuring realistic scenes and multiple characters, all generated from text instruction. Imagine the excitement of creating a young Charles Lazarus, the founder of Toys “R” Us, and envisioning his dreams for our iconic brand and beloved mascot Geoffrey the Giraffe in the early 1930s.”

The company says that The Origin of Toys “R” Us commercial was co-produced by Toys “R” Us Studios President Kim Miller Olko as executive producer and Native Foreign’s Nik Kleverov as director. “Charles Lazarus was a visionary ahead of his time, and we wanted to honor his legacy with a spot using the most cutting-edge technology available,” Miller Olko said in a statement.

In the video, we see a child version of Lazarus, presumably generated using Sora, falling asleep and having a dream that he is flying through a land of toys. Along the way, he meets Geoffery, the store’s mascot, who hands the child a small red car.

Many of the scenes retain obvious hallmarks of AI-generated imagery, such as unnatural movement, strange visual artifacts, and the irregular shape of eyeglasses. In February, a few Super Bowl commercials intentionally made fun of similar AI-generated video defects, which became famous online after fake AI-generated beer commercial and “Pepperoni Hug Spot” clips made using Runway’s Gen-2 model went viral in 2023.

  • A screen capture from the partially AI-generated Toys “R” Us brand film created using Sora.

    Toys “R” Us

  • A screen capture from the partially AI-generated Toys “R” Us brand film created using Sora.

    Toys “R” Us

  • A screen capture from the partially AI-generated Toys “R” Us brand film created using Sora.

    Toys “R” Us

  • A screen capture from the partially AI-generated Toys “R” Us brand film created using Sora.

    Toys R Us

  • A screen capture from the partially AI-generated Toys “R” Us brand film created using Sora.

    Toys R Us

  • A screen capture from the partially AI-generated Toys “R” Us brand film created using Sora.

    Toys “R” Us

  • A screen capture from the partially AI-generated Toys “R” Us brand film created using Sora.

    Toys “R” Us

  • A screen capture from the partially AI-generated Toys “R” Us brand film created using Sora.

    Toys “R” Us

  • A screen capture from the partially AI-generated Toys “R” Us brand film created using Sora.

    Toys “R” Us

  • A screen capture from the partially AI-generated Toys “R” Us brand film created using Sora.

    Toys “R” Us

  • A screen capture from the partially AI-generated Toys “R” Us brand film created using Sora.

    Toys “R” Us

AI-generated artwork receives frequent criticism online due to the use of human-created artwork to train AI models that create the works, the perception that AI synthesis tools will replace (or are currently replacing) human creative jobs, and the potential environmental impact of AI models, which are seen as energy-wasteful by some critics. Also, some people just think the output quality looks bad.

On the social network X, comedy writer Mike Drucker wrapped up several of these criticisms into one post, writing, “Love this commercial is like, ‘Toys R Us started with the dream of a little boy who wanted to share his imagination with the world. And to show how, we fired our artists and dried Lake Superior using a server farm to generate what that would look like in Stephen King’s nightmares.'”

Other critical comments were more frank. Filmmaker Joe Russo posted: “TOYS ‘R US released an AI commercial and it fucking sucks.”

Toys “R” Us riles critics with “first-ever” AI-generated commercial using Sora Read More »

music-industry-giants-allege-mass-copyright-violation-by-ai-firms

Music industry giants allege mass copyright violation by AI firms

AI, AI lawsuit, audio synthesis, Biz & IT, generative ai, Google, machine learning, Michael Jackson, microsoft, music synthesis, openai, Policy, Reuters, sony music, Suno, Udio, Univeral Music Group, voice synthesis, Warner Records / /

No one wants to be defeated —

Suno and Udio could face damages of up to $150,000 per song allegedly infringed.

–

Michael Jackson in concert, 1986. Sony Music owns a large portion of publishing rights to Jackson's music.

Enlarge / Michael Jackson in concert, 1986. Sony Music owns a large portion of publishing rights to Jackson’s music.

Universal Music Group, Sony Music, and Warner Records have sued AI music-synthesis companies Udio and Suno for allegedly committing mass copyright infringement by using recordings owned by the labels to train music-generating AI models, reports Reuters. Udio and Suno can generate novel song recordings based on text-based descriptions of music (i.e., “a dubstep song about Linus Torvalds”).

The lawsuits, filed in federal courts in New York and Massachusetts, claim that the AI companies’ use of copyrighted material to train their systems could lead to AI-generated music that directly competes with and potentially devalues the work of human artists.

Like other generative AI models, both Udio and Suno (which we covered separately in April) rely on a broad selection of existing human-created artworks that teach a neural network the relationship between words in a written prompt and styles of music. The record labels correctly note that these companies have been deliberately vague about the sources of their training data.

Until generative AI models hit the mainstream in 2022, it was common practice in machine learning to scrape and use copyrighted information without seeking permission to do so. But now that the applications of those technologies have become commercial products themselves, rightsholders have come knocking to collect. In the case of Udio and Suno, the record labels are seeking statutory damages of up to $150,000 per song used in training.

In the lawsuit, the record labels cite specific examples of AI-generated content that allegedly re-creates elements of well-known songs, including The Temptations’ “My Girl,” Mariah Carey’s “All I Want for Christmas Is You,” and James Brown’s “I Got You (I Feel Good).” It also claims the music-synthesis models can produce vocals resembling those of famous artists, such as Michael Jackson and Bruce Springsteen.

Reuters claims it’s the first instance of lawsuits specifically targeting music-generating AI, but music companies and artists alike have been gearing up to deal with challenges the technology may pose for some time.

In May, Sony Music sent warning letters to over 700 AI companies (including OpenAI, Microsoft, Google, Suno, and Udio) and music-streaming services that prohibited any AI researchers from using its music to train AI models. In April, over 200 musical artists signed an open letter that called on AI companies to stop using AI to “devalue the rights of human artists.” And last November, Universal Music filed a copyright infringement lawsuit against Anthropic for allegedly including artists’ lyrics in its Claude LLM training data.

Similar to The New York Times’ lawsuit against OpenAI over the use of training data, the outcome of the record labels’ new suit could have deep implications for the future development of generative AI in creative fields, including requiring companies to license all musical training data used in creating music-synthesis models.

Compulsory licenses for AI training data could make AI model development economically impractical for small startups like Udio and Suno—and judging by the aforementioned open letter, many musical artists may applaud that potential outcome. But such a development would not preclude major labels from eventually developing their own AI music generators themselves, allowing only large corporations with deep pockets to control generative music tools for the foreseeable future.

Music industry giants allege mass copyright violation by AI firms Read More »

anthropic-introduces-claude-3.5-sonnet,-matching-gpt-4o-on-benchmarks

Anthropic introduces Claude 3.5 Sonnet, matching GPT-4o on benchmarks

AI, Anthropic, Biz & IT, Claude, Claude 3, Claude 3.5, Claude 3.5 Sonnet, Claude Sonnet, Google Gemini, GPT-4, GPT-4o, large language models, LLMs, machine learning, Meta, Mistral, openai, text synthesis / /
The Anthropic Claude 3 logo, jazzed up by Benj Edwards.

Anthropic / Benj Edwards

On Thursday, Anthropic announced Claude 3.5 Sonnet, its latest AI language model and the first in a new series of “3.5” models that build upon Claude 3, launched in March. Claude 3.5 can compose text, analyze data, and write code. It features a 200,000 token context window and is available now on the Claude website and through an API. Anthropic also introduced Artifacts, a new feature in the Claude interface that shows related work documents in a dedicated window.

So far, people outside of Anthropic seem impressed. “This model is really, really good,” wrote independent AI researcher Simon Willison on X. “I think this is the new best overall model (and both faster and half the price of Opus, similar to the GPT-4 Turbo to GPT-4o jump).”

As we’ve written before, benchmarks for large language models (LLMs) are troublesome because they can be cherry-picked and often do not capture the feel and nuance of using a machine to generate outputs on almost any conceivable topic. But according to Anthropic, Claude 3.5 Sonnet matches or outperforms competitor models like GPT-4o and Gemini 1.5 Pro on certain benchmarks like MMLU (undergraduate level knowledge), GSM8K (grade school math), and HumanEval (coding).

Claude 3.5 Sonnet benchmarks provided by Anthropic.

Enlarge / Claude 3.5 Sonnet benchmarks provided by Anthropic.

If all that makes your eyes glaze over, that’s OK; it’s meaningful to researchers but mostly marketing to everyone else. A more useful performance metric comes from what we might call “vibemarks” (coined here first!) which are subjective, non-rigorous aggregate feelings measured by competitive usage on sites like LMSYS’s Chatbot Arena. The Claude 3.5 Sonnet model is currently under evaluation there, and it’s too soon to say how well it will fare.

Claude 3.5 Sonnet also outperforms Anthropic’s previous-best model (Claude 3 Opus) on benchmarks measuring “reasoning,” math skills, general knowledge, and coding abilities. For example, the model demonstrated strong performance in an internal coding evaluation, solving 64 percent of problems compared to 38 percent for Claude 3 Opus.

Claude 3.5 Sonnet is also a multimodal AI model that accepts visual input in the form of images, and the new model is reportedly excellent at a battery of visual comprehension tests.

Claude 3.5 Sonnet benchmarks provided by Anthropic.

Enlarge / Claude 3.5 Sonnet benchmarks provided by Anthropic.

Roughly speaking, the visual benchmarks mean that 3.5 Sonnet is better at pulling information from images than previous models. For example, you can show it a picture of a rabbit wearing a football helmet, and the model knows it’s a rabbit wearing a football helmet and can talk about it. That’s fun for tech demos, but the tech is still not accurate enough for applications of the tech where reliability is mission critical.

Anthropic introduces Claude 3.5 Sonnet, matching GPT-4o on benchmarks Read More »

single-point-of-software-failure-could-hamstring-15k-car-dealerships-for-days

Single point of software failure could hamstring 15K car dealerships for days

Biz & IT, car dealers, car dealerships, Cars, cdk global, crm, ransomware, SaaS, Security, venture capital, VPN / /

Virtual Private Failure —

“Cyber incident” affecting 15K dealers could mean outages “for several days.”

– Updated

Ford Mustang Mach E electric vehicles are offered for sale at a dealership on June 5, 2024, in Chicago, Illinois.

Enlarge / Ford Mustang Mach E electric vehicles are offered for sale at a dealership on June 5, 2024, in Chicago, Illinois.

Scott Olson / Getty Images

CDK Global touts itself as an all-in-one software-as-a-service solution that is “trusted by nearly 15,000 dealer locations.” One connection, over an always-on VPN to CDK’s data centers, gives a dealership customer relationship management (CRM) software, financing, inventory, and more back-office tools.

That all-in-one nature explains why people trying to buy cars, and especially those trying to sell them, have had a rough couple of days. CDK’s services have been down, due to what the firm describes as a “cyber incident.” CDK shut down most of its systems Wednesday, June 19, then told dealerships that evening that it restored some services. CDK told dealers today, June 20, that it had “experienced an additional cyber incident late in the evening on June 19,” and shut down systems again.

“At this time, we do not have an estimated time frame for resolution and therefore our dealers’ systems will not be available at a minimum on Thursday, June 20th,” CDK told customers.

As of 2 pm Eastern on June 20, an automated message on CDK’s updates hotline said that, “At this time, we do not have an estimated time frame for resolution and therefore our dealers’ systems will not be available likely for several days.” The message added that support lines would remain down due to security precautions. Getting retail dealership services back up was “our highest priority,” the message said.

On Reddit, car dealership owners and workers have met the news with some combination of anger and “What’s wrong with paper and Excel?” Some dealerships report not being able to do more than oil changes or write down customer names and numbers, while others have sought to make do with documenting orders they plan to enter in once their systems come back online.

“We lost 4 deals at my store because of this,” wrote one user Thursday morning on r/askcarsales. “Our whole auto group uses CDK for just about everything and we are completely dead. 30+ stores in our auto group.”

“We were on our own server until a month ago because CDK forced us to go to the cloud so we could implement [Electronic Repair Orders, EROs],” wrote one worker on r/serviceadvisors. “Since the change, CDK freezes multiple times a day… But now being completely down for 2 days. CDK I want a divorce.”

CDK benefits from “a rise in consolidation”

CDK started as the car dealership arm of payroll-processing giant ADP after ADP acquired two inventory and sales systems companies in 1973. CDK was spun off from ADP in 2014. In mid-2022, it was acquired by venture capital firm Brookfield Business Partners and went private, following pressure from activist public investors to trim costs.

Brookfield said at the time that it expected CDK “to benefit from a rise in consolidation across the dealership industry,” an industry estimated to be worth $30 billion by 2026. Analysts generally consider CDK to be the dominant player in the dealership management market, with an additional 15,000 customers in the trucking industry.

Under CEO Brian McDonald, who returned to the firm after its private equity buyout, the company pushed most of its enterprise IT unit to global outsourcing firm Genpact in March 2023.

CDK released a report on cybersecurity for dealerships in 2023. It noted that dealerships suffered an average of 3.4 weeks of downtime from ransomware attacks, or potentially an average payout of $740,144 (or even both). Insurer Zurich North America noted in a 2023 report that dealerships are a particularly rich target for attackers because “dealerships store large amounts of confidential, personal data, including financing and credit applications, customer financial information and home addresses.”

“In addition,” the report stated, “dealership systems are often interconnected to external interfaces and portals, such as external service providers.”

Ars contacted CDK for comment and will update this post if we receive a response. As of Thursday morning, the firm has not clarified if the “cyber incident” is due to ransomware or another kind of attack.

This post was updated at 2 pm to note a message indicating that CDK’s outage could last several days.

Listing image by Scott Olson / Getty Images

Single point of software failure could hamstring 15K car dealerships for days Read More »

ex-openai-star-sutskever-shoots-for-superintelligent-ai-with-new-company

Ex-OpenAI star Sutskever shoots for superintelligent AI with new company

AI, Biz & IT, Illya Sutskever, machine learning, sam altman, SSI / /

Not Strategic Simulations —

Safe Superintelligence, Inc. seeks to safely build AI far beyond human capability.

–

Illya Sutskever physically gestures as OpenAI CEO Sam Altman looks on at Tel Aviv University on June 5, 2023.

Enlarge / Ilya Sutskever physically gestures as OpenAI CEO Sam Altman looks on at Tel Aviv University on June 5, 2023.

On Wednesday, former OpenAI Chief Scientist Ilya Sutskever announced he is forming a new company called Safe Superintelligence, Inc. (SSI) with the goal of safely building “superintelligence,” which is a hypothetical form of artificial intelligence that surpasses human intelligence, possibly in the extreme.

“We will pursue safe superintelligence in a straight shot, with one focus, one goal, and one product,” wrote Sutskever on X. “We will do it through revolutionary breakthroughs produced by a small cracked team.“

Sutskever was a founding member of OpenAI and formerly served as the company’s chief scientist. Two others are joining Sutskever at SSI initially: Daniel Levy, who formerly headed the Optimization Team at OpenAI, and Daniel Gross, an AI investor who worked on machine learning projects at Apple between 2013 and 2017. The trio posted a statement on the company’s new website.

A screen capture of Safe Superintelligence's initial formation announcement captured on June 20, 2024.

Enlarge / A screen capture of Safe Superintelligence’s initial formation announcement captured on June 20, 2024.

Sutskever and several of his co-workers resigned from OpenAI in May, six months after Sutskever played a key role in ousting OpenAI CEO Sam Altman, who later returned. While Sutskever did not publicly complain about OpenAI after his departure—and OpenAI executives such as Altman wished him well on his new adventures—another resigning member of OpenAI’s Superalignment team, Jan Leike, publicly complained that “over the past years, safety culture and processes [had] taken a backseat to shiny products” at OpenAI. Leike joined OpenAI competitor Anthropic later in May.

A nebulous concept

OpenAI is currently seeking to create AGI, or artificial general intelligence, which would hypothetically match human intelligence at performing a wide variety of tasks without specific training. Sutskever hopes to jump beyond that in a straight moonshot attempt, with no distractions along the way.

“This company is special in that its first product will be the safe superintelligence, and it will not do anything else up until then,” said Sutskever in an interview with Bloomberg. “It will be fully insulated from the outside pressures of having to deal with a large and complicated product and having to be stuck in a competitive rat race.”

During his former job at OpenAI, Sutskever was part of the “Superalignment” team studying how to “align” (shape the behavior of) this hypothetical form of AI, sometimes called “ASI” for “artificial super intelligence,” to be beneficial to humanity.

As you can imagine, it’s difficult to align something that does not exist, so Sutskever’s quest has met skepticism at times. On X, University of Washington computer science professor (and frequent OpenAI critic) Pedro Domingos wrote, “Ilya Sutskever’s new company is guaranteed to succeed, because superintelligence that is never achieved is guaranteed to be safe.“

Much like AGI, superintelligence is a nebulous term. Since the mechanics of human intelligence are still poorly understood—and since human intelligence is difficult to quantify or define because there is no one set type of human intelligence—identifying superintelligence when it arrives may be tricky.

Already, computers far surpass humans in many forms of information processing (such as basic math), but are they superintelligent? Many proponents of superintelligence imagine a sci-fi scenario of an “alien intelligence” with a form of sentience that operates independently of humans, and that is more or less what Sutskever hopes to achieve and control safely.

“You’re talking about a giant super data center that’s autonomously developing technology,” he told Bloomberg. “That’s crazy, right? It’s the safety of that that we want to contribute to.”

Ex-OpenAI star Sutskever shoots for superintelligent AI with new company Read More »

runway’s-latest-ai-video-generator-brings-giant-cotton-candy-monsters-to-life

Runway’s latest AI video generator brings giant cotton candy monsters to life

AI, AI-generated video, Biz & IT, Deepfakes, filmmaking, films, Gen-2, Gen-3, Gen-3 Alpha, giant cotton-candy monster, Google, machine learning, Meta, openai, Runway, Sora, Special Effects, video synthesis / /
Screen capture of a Runway Gen-3 Alpha video generated with the prompt

Enlarge / Screen capture of a Runway Gen-3 Alpha video generated with the prompt “A giant humanoid, made of fluffy blue cotton candy, stomping on the ground, and roaring to the sky, clear blue sky behind them.”

On Sunday, Runway announced a new AI video synthesis model called Gen-3 Alpha that’s still under development, but it appears to create video of similar quality to OpenAI’s Sora, which debuted earlier this year (and has also not yet been released). It can generate novel, high-definition video from text prompts that range from realistic humans to surrealistic monsters stomping the countryside.

Unlike Runway’s previous best model from June 2023, which could only create two-second-long clips, Gen-3 Alpha can reportedly create 10-second-long video segments of people, places, and things that have a consistency and coherency that easily surpasses Gen-2. If 10 seconds sounds short compared to Sora’s full minute of video, consider that the company is working with a shoestring budget of compute compared to more lavishly funded OpenAI—and actually has a history of shipping video generation capability to commercial users.

Gen-3 Alpha does not generate audio to accompany the video clips, and it’s highly likely that temporally coherent generations (those that keep a character consistent over time) are dependent on similar high-quality training material. But Runway’s improvement in visual fidelity over the past year is difficult to ignore.

AI video heats up

It’s been a busy couple of weeks for AI video synthesis in the AI research community, including the launch of the Chinese model Kling, created by Beijing-based Kuaishou Technology (sometimes called “Kwai”). Kling can generate two minutes of 1080p HD video at 30 frames per second with a level of detail and coherency that reportedly matches Sora.

Gen-3 Alpha prompt: “Subtle reflections of a woman on the window of a train moving at hyper-speed in a Japanese city.”

Not long after Kling debuted, people on social media began creating surreal AI videos using Luma AI’s Luma Dream Machine. These videos were novel and weird but generally lacked coherency; we tested out Dream Machine and were not impressed by anything we saw.

Meanwhile, one of the original text-to-video pioneers, New York City-based Runway—founded in 2018—recently found itself the butt of memes that showed its Gen-2 tech falling out of favor compared to newer video synthesis models. That may have spurred the announcement of Gen-3 Alpha.

Gen-3 Alpha prompt: “An astronaut running through an alley in Rio de Janeiro.”

Generating realistic humans has always been tricky for video synthesis models, so Runway specifically shows off Gen-3 Alpha’s ability to create what its developers call “expressive” human characters with a range of actions, gestures, and emotions. However, the company’s provided examples weren’t particularly expressive—mostly people just slowly staring and blinking—but they do look realistic.

Provided human examples include generated videos of a woman on a train, an astronaut running through a street, a man with his face lit by the glow of a TV set, a woman driving a car, and a woman running, among others.

Gen-3 Alpha prompt: “A close-up shot of a young woman driving a car, looking thoughtful, blurred green forest visible through the rainy car window.”

The generated demo videos also include more surreal video synthesis examples, including a giant creature walking in a rundown city, a man made of rocks walking in a forest, and the giant cotton candy monster seen below, which is probably the best video on the entire page.

Gen-3 Alpha prompt: “A giant humanoid, made of fluffy blue cotton candy, stomping on the ground, and roaring to the sky, clear blue sky behind them.”

Gen-3 will power various Runway AI editing tools (one of the company’s most notable claims to fame), including Multi Motion Brush, Advanced Camera Controls, and Director Mode. It can create videos from text or image prompts.

Runway says that Gen-3 Alpha is the first in a series of models trained on a new infrastructure designed for large-scale multimodal training, taking a step toward the development of what it calls “General World Models,” which are hypothetical AI systems that build internal representations of environments and use them to simulate future events within those environments.

Runway’s latest AI video generator brings giant cotton candy monsters to life Read More »

men-plead-guilty-to-aggravated-id-theft-after-pilfering-police-database

Men plead guilty to aggravated ID theft after pilfering police database

Biz & IT, doxxing, extortion, Identity theft, Security / /

GUILTY AS CHARGED —

Members of group called ViLE face a minimum of two years in prison.

–

Men plead guilty to aggravated ID theft after pilfering police database

Getty Images

Two men have pleaded guilty to charges of computer intrusion and aggravated identity theft tied to their theft of records from a law enforcement database for use in doxxing and extorting multiple individuals.

Sagar Steven Singh, 20, and Nicholas Ceraolo, 26, admitted to being members of ViLE, a group that specializes in obtaining personal information of individuals and using it to extort or harass them. Members use various methods to collect social security numbers, cell phone numbers, and other personal data and post it, or threaten to post it, to a website administered by the group. Victims had to pay to have their information removed or kept off the website. Singh pled guilty on Monday, June 17, and Ceraolo pled guilty on May 30.

Impersonating a police officer

The men gained access to the law enforcement portal by stealing the password of an officer’s account and using it to log in. The portal, maintained by an unnamed US federal law enforcement agency, was restricted to members of various law enforcement agencies to share intelligence from government databases with state and local officials. The site provided access to detailed nonpublic records involving narcotics and currency seizures and to law enforcement intelligence reports.

Investigators tied Singh to the unlawful access after he logged in with the same IP address he had recently used to connect to a social media site account registered to him, prosecutors said in charging papers filed in March 2023. Prosecutors said Singh also threatened to harm one victim’s family unless the victim, referred to as Victim-1 in court papers, turned over credentials for an Instagram account.

“In order to drive home the threat, Singh appended Victim-1’s social security number, driver’s license number, home address, and other personal details,” prosecutors wrote. “Singh told Victim-1 that he had ‘access to [] databases, which are federal, through [the] portal, I can request information on anyone in the US doesn’t matter who, nobody is safe.’” The defendant ultimately directed Victim-1 to sell Victim-1’s accounts and give the proceeds to Singh.

The criminal complaint went on to allege that Ceraolo used a compromised email account belonging to a Bangladeshi police official to email account to pose as a Bangladeshi police official to contact US-based social media companies and ask them for personal information belonging to certain users under the false pretense that the users were committing crimes or were in life-threatening danger. In one case, one of the social media companies complied. The pair then used the data belonging to victims to extort them in exchange for not publishing it.

On a different occasion, the pair used the compromised email account to request user information from a different social media company after claiming that the user had sent bomb threats, distributed child abuse images, and threatened officials of a foreign government. The social media company ultimately refused and later posted on X (formerly Twitter) that it had identified the fraudulent request.

Both defendants face a minimum sentence of two years in prison and a maximum of seven years. The date of sentencing isn’t immediately known.

Men plead guilty to aggravated ID theft after pilfering police database Read More »