Meta

Ads are “rolling out gradually” to WhatsApp

ads, Meta, Social Media, Tech, whatsapp / Rejus Almole / June 17, 2025

For the first time since launching in 2009, WhatsApp will now show users advertisements. The ads are “rolling out gradually,” the company said.

For now, the ads will only appear on WhatsApp’s Updates tab, where users can update their status and access channels or groups targeting specific interests they may want to follow. In its announcement of the ads, parent company Meta claimed that placing ads under Updates means that the ads won’t “interrupt personal chats.”

Meta said that 1.5 billion people use the Updates tab daily. However, if you exclusively use WhatsApp for direct messages and personal group chats, you could avoid ever seeing ads.

“Now the Updates tab is going to be able to help Channel admins, organizations, and businesses build and grow,” Meta’s announcement said.

WhatsApp users will see three different types of ads on their messaging app. One is through the tab’s Status section, where users typically share photos, videos, voice notes, and/or text with their friends that disappear after 24 hours. While scrolling through friends’ status updates, users will see status updates from advertisers and can send a message to the company about the offering that it is promoting.

There are also Promoted Channels: “For the first time, admins have a way to increase their Channel’s visibility,” Meta said.

Finally, WhatsApp is allowing advertisers to charge users a monthly fee in order to “receive exclusive updates.” For example, people could subscribe to a cooking Channel and request alerts for new recipes.

In order to decide which ads users see, Meta says WhatsApp will leverage user information like their country code, age, their device’s language settings, and the user’s “general (not precise) location, like city or country.”

Ads are “rolling out gradually” to WhatsApp Read More »

Meta beefs up disappointing AI division with $15 billion Scale AI investment

AI, llm, Meta, scale, syndication / Paul Patrick / June 13, 2025

Meta has invested heavily in generative AI, with the majority of its planned $72 billion in capital expenditure this year earmarked for data centers and servers. The deal underlines the high price AI companies are willing to pay for data that can be used to train AI models.

Zuckerberg pledged last year that his company’s models would outstrip rivals’ efforts in 2025, but Meta’s most recent release, Llama 4, has underperformed on various independent reasoning and coding benchmarks.

The long-term goal of researchers at Meta “has always been to reach human intelligence and go beyond it,” said Yann LeCun, the company’s chief AI scientist at the VivaTech conference in Paris this week.

Building artificial “general” intelligence—AI technologies that have human-level intelligence—is a popular goal for many AI companies. An increasing number of Silicon Valley groups are also seeking to reach “superintelligence,” a hypothetical scenario where AI systems surpass human intelligence.

The core of Scale’s business has been data-labeling, a manual process of ensuring images and text are accurately labeled and categorized before they are used to train AI models.

Wang has forged relationships with Silicon Valley’s biggest investors and technologists, including OpenAI’s Sam Altman. Scale AI’s early customers were autonomous vehicle companies, but the bulk of its expected $2 billion in revenues this year will come from labeling the data used to train the massive AI models built by OpenAI and others.

The deal will result in a substantial payday for Scale’s early venture capital investors, including Accel, Tiger Global Management, and Index Ventures. Tiger’s $200 million investment is worth more than $1 billion at the company’s new valuation, according to a person with knowledge of the matter.

Additional reporting by Tabby Kinder in San Francisco

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Musk’s DOGE used Meta’s Llama 2—not Grok—for gov’t slashing, report says

AI, azure ai, department of government efficiency, doge, elon musk, grok, Llama 2, Meta, microsoft, Policy, xAI / Kris Guyer / May 23, 2025

Why didn’t DOGE use Grok?

It seems that Grok, Musk’s AI model, wasn’t available for DOGE’s task because it was only available as a proprietary model in January. Moving forward, DOGE may rely more frequently on Grok, Wired reported, as Microsoft announced it would start hosting xAI’s Grok 3 models in its Azure AI Foundry this week, The Verge reported, which opens the models up for more uses.

In their letter, lawmakers urged Vought to investigate Musk’s conflicts of interest, while warning of potential data breaches and declaring that AI, as DOGE had used it, was not ready for government.

“Without proper protections, feeding sensitive data into an AI system puts it into the possession of a system’s operator—a massive breach of public and employee trust and an increase in cybersecurity risks surrounding that data,” lawmakers argued. “Generative AI models also frequently make errors and show significant biases—the technology simply is not ready for use in high-risk decision-making without proper vetting, transparency, oversight, and guardrails in place.”

Although Wired’s report seems to confirm that DOGE did not send sensitive data from the “Fork in the Road” emails to an external source, lawmakers want much more vetting of AI systems to deter “the risk of sharing personally identifiable or otherwise sensitive information with the AI model deployers.”

A seeming fear is that Musk may start using his own models more, benefiting from government data his competitors cannot access, while potentially putting that data at risk of a breach. They’re hoping that DOGE will be forced to unplug all its AI systems, but Vought seems more aligned with DOGE, writing in his AI guidance for federal use that “agencies must remove barriers to innovation and provide the best value for the taxpayer.”

“While we support the federal government integrating new, approved AI technologies that can improve efficiency or efficacy, we cannot sacrifice security, privacy, and appropriate use standards when interacting with federal data,” their letter said. “We also cannot condone use of AI systems, often known for hallucinations and bias, in decisions regarding termination of federal employment or federal funding without sufficient transparency and oversight of those models—the risk of losing talent and critical research because of flawed technology or flawed uses of such technology is simply too high.”

Musk’s DOGE used Meta’s Llama 2—not Grok—for gov’t slashing, report says Read More »

Meta argues enshittification isn’t real in bid to toss FTC monopoly case

antitrust, facebook, federal trade commission, ftc, Instagram, mark zuckerberg, Meta, meta monopoly trial, Policy, Social Media, whatsapp / Mike M. / May 17, 2025

Further, Meta argued that the FTC did not show evidence that users sharing friends-and-family content were shown more ads. Meta noted that it “does not profit by showing more ads to users who do not click on them,” so it only shows more ads to users who click ads.

Meta also insisted that there’s “nothing but speculation” showing that Instagram or WhatsApp would have been better off or grown into rivals had Meta not acquired them.

The company claimed that without Meta’s resources, Instagram may have died off. Meta noted that Instagram co-founder Kevin Systrom testified that his app was “pretty broken and duct-taped” together, making it “vulnerable to spam” before Meta bought it.

Rather than enshittification, what Meta did to Instagram could be considered “a consumer-welfare bonanza,” Meta argued, while dismissing “smoking gun” emails from Mark Zuckerberg discussing buying Instagram to bury it as “legally irrelevant.”

Dismissing these as “a few dated emails,” Meta argued that “efforts to litigate Mr. Zuckerberg’s state of mind before the acquisition in 2012 are pointless.”

“What matters is what Meta did,” Meta argued, which was pump Instagram with resources that allowed it “to ‘thrive’—adding many new features, attracting hundreds of millions and then billions of users, and monetizing with great success.”

In the case of WhatsApp, Meta argued that nobody thinks WhatsApp had any intention to pivot to social media when the founders testified that their goal was to never add social features, preferring to offer a simple, clean messaging app. And Meta disputed any claim that it feared Google might buy WhatsApp as the basis for creating a Facebook rival, arguing that “the sole Meta witness to (supposedly) learn of Google’s acquisition efforts testified that he did not have that worry.”

Meta argues enshittification isn’t real in bid to toss FTC monopoly case Read More »

Judge on Meta’s AI training: “I just don’t understand how that can be fair use”

AI training, copyright, copyright infringement, fair use, leeching, LLaMA, Meta, piracy, Policy, torrenting / Kris Guyer / May 3, 2025

Judge downplayed Meta’s “messed up” torrenting in lawsuit over AI training.

A judge who may be the first to rule on whether AI training data is fair use appeared skeptical Thursday at a hearing where Meta faced off with book authors over the social media company’s alleged copyright infringement.

Meta, like most AI companies, holds that training must be deemed fair use, or else the entire AI industry could face immense setbacks, wasting precious time negotiating data contracts while falling behind global rivals. Meta urged the court to rule that AI training is a transformative use that only references books to create an entirely new work that doesn’t replicate authors’ ideas or replace books in their markets.

At the hearing that followed after both sides requested summary judgment, however, Judge Vince Chhabria pushed back on Meta attorneys arguing that the company’s Llama AI models posed no threat to authors in their markets, Reuters reported.

“You have companies using copyright-protected material to create a product that is capable of producing an infinite number of competing products,” Chhabria said. “You are dramatically changing, you might even say obliterating, the market for that person’s work, and you’re saying that you don’t even have to pay a license to that person.”

Declaring, “I just don’t understand how that can be fair use,” the shrewd judge apparently stoked little response from Meta’s attorney, Kannon Shanmugam, apart from a suggestion that any alleged threat to authors’ livelihoods was “just speculation,” Wired reported.

Authors may need to sharpen their case, which Chhabria warned could be “taken away by fair use” if none of the authors suing, including Sarah Silverman, Ta-Nehisi Coates, and Richard Kadrey, can show “that the market for their actual copyrighted work is going to be dramatically affected.”

Determined to probe this key question, Chhabria pushed authors’ attorney, David Boies, to point to specific evidence of market harms that seemed noticeably missing from the record.

“It seems like you’re asking me to speculate that the market for Sarah Silverman’s memoir will be affected by the billions of things that Llama will ultimately be capable of producing,” Chhabria said. “And it’s just not obvious to me that that’s the case.”

But if authors can prove fears of market harms are real, Meta might struggle to win over Chhabria, and that could set a precedent impacting copyright cases challenging AI training on other kinds of content.

The judge repeatedly appeared to be sympathetic to authors, suggesting that Meta’s AI training may be a “highly unusual case” where even though “the copying is for a highly transformative purpose, the copying has the high likelihood of leading to the flooding of the markets for the copyrighted works.”

And when Shanmugam argued that copyright law doesn’t shield authors from “protection from competition in the marketplace of ideas,” Chhabria resisted the framing that authors weren’t potentially being robbed, Reuters reported.

“But if I’m going to steal things from the marketplace of ideas in order to develop my own ideas, that’s copyright infringement, right?” Chhabria responded.

Wired noted that he asked Meta’s lawyers, “What about the next Taylor Swift?” If AI made it easy to knock off a young singer’s sound, how could she ever compete if AI produced “a billion pop songs” in her style?

In a statement, Meta’s spokesperson reiterated the company’s defense that AI training is fair use.

“Meta has developed transformational open source AI models that are powering incredible innovation, productivity, and creativity for individuals and companies,” Meta’s spokesperson said. “Fair use of copyrighted materials is vital to this. We disagree with Plaintiffs’ assertions, and the full record tells a different story. We will continue to vigorously defend ourselves and to protect the development of GenAI for the benefit of all.”

Meta’s torrenting seems “messed up”

Some have pondered why Chhabria appeared so focused on market harms, instead of hammering Meta for admittedly illegally pirating books that it used for its AI training, which seems to be obvious copyright infringement. According to Wired, “Chhabria spoke emphatically about his belief that the big question is whether Meta’s AI tools will hurt book sales and otherwise cause the authors to lose money,” not whether Meta’s torrenting of books was illegal.

The torrenting “seems kind of messed up,” Chhabria said, but “the question, as the courts tell us over and over again, is not whether something is messed up but whether it’s copyright infringement.”

It’s possible that Chhabria dodged the question for procedural reasons. In a court filing, Meta argued that authors had moved for summary judgment on Meta’s alleged copying of their works, not on “unsubstantiated allegations that Meta distributed Plaintiffs’ works via torrent.”

In the court filing, Meta alleged that even if Chhabria agreed that the authors’ request for “summary judgment is warranted on the basis of Meta’s distribution, as well as Meta’s copying,” that the authors “lack evidence to show that Meta distributed any of their works.”

According to Meta, authors abandoned any claims that Meta’s seeding of the torrented files served to distribute works, leaving only claims about Meta’s leeching. Meta argued that the authors “admittedly lack evidence that Meta ever uploaded any of their works, or any identifiable part of those works, during the so-called ‘leeching’ phase,” relying instead on expert estimates based on how torrenting works.

It’s also possible that for Chhabria, the torrenting question seemed like an unnecessary distraction. Former Meta attorney Mark Lumley, who quit the case earlier this year, told Vanity Fair that the torrenting was “one of those things that sounds bad but actually shouldn’t matter at all in the law. Fair use is always about uses the plaintiff doesn’t approve of; that’s why there is a lawsuit.”

Lumley suggested that court cases mulling fair use at this current moment should focus on the outputs, rather than the training. Citing the ruling in a case where Google Books scanning books to share excerpts was deemed fair use, Lumley argued that “all search engines crawl the full Internet, including plenty of pirated content,” so there’s seemingly no reason to stop AI crawling.

But the Copyright Alliance, a nonprofit, non-partisan group supporting the authors in the case, in a court filing alleged that Meta, in its bid to get AI products viewed as transformative, is aiming to do the opposite. “When describing the purpose of generative AI,” Meta allegedly strives to convince the court to “isolate the ‘training’ process and ignore the output of generative AI,” because that’s seemingly the only way that Meta can convince the court that AI outputs serve “a manifestly different purpose from Plaintiffs’ books,” the Copyright Alliance argued.

“Meta’s motion ignores what comes after the initial ‘training’—most notably the generation of output that serves the same purpose of the ingested works,” the Copyright Alliance argued. And the torrenting question should matter, the group argued, because unlike in Google Books, Meta’s AI models are apparently training on pirated works, not “legitimate copies of books.”

Chhabria will not be making a snap decision in the case, planning to take his time and likely stressing not just Meta, but every AI company defending training as fair use the longer he delays. Understanding that the entire AI industry potentially has a stake in the ruling, Chhabria apparently sought to relieve some tension at the end of the hearing with a joke, Wired reported.

“I will issue a ruling later today,” Chhabria said. “Just kidding! I will take a lot longer to think about it.”

Ashley is a senior policy reporter for Ars Technica, dedicated to tracking social impacts of emerging policies and new technologies. She is a Chicago-based journalist with 20 years of experience.

Judge on Meta’s AI training: “I just don’t understand how that can be fair use” Read More »

New study accuses LM Arena of gaming its popular AI benchmark

AI, Artificial Intelligence, Google, lm arena, Meta, openai / Paul Patrick / May 2, 2025

This study also calls out LM Arena for what appears to be much greater promotion of private models like Gemini, ChatGPT, and Claude. Developers collect data on model interactions from the Chatbot Arena API, but teams focusing on open models consistently get the short end of the stick.

The researchers point out that certain models appear in arena faceoffs much more often, with Google and OpenAI together accounting for over 34 percent of collected model data. Firms like xAI, Meta, and Amazon are also disproportionately represented in the arena. Therefore, those firms get more vibemarking data compared to the makers of open models.

More models, more evals

The study authors have a list of suggestions to make LM Arena more fair. Several of the paper’s recommendations are aimed at correcting the imbalance of privately tested commercial models, for example, by limiting the number of models a group can add and retract before releasing one. The study also suggests showing all model results, even if they aren’t final.

However, the site’s operators take issue with some of the paper’s methodology and conclusions. LM Arena points out that the pre-release testing features have not been kept secret, with a March 2024 blog post featuring a brief explanation of the system. They also contend that model creators don’t technically choose the version that is shown. Instead, the site simply doesn’t show non-public versions for simplicity’s sake. When a developer releases the final version, that’s what LM Arena adds to the leaderboard.

Proprietary models get disproportionate attention in the Chatbot Arena, the study says. Credit: Shivalika Singh et al.

One place the two sides may find alignment is on the question of unequal matchups. The study authors call for fair sampling, which will ensure open models appear in Chatbot Arena at a rate similar to the likes of Gemini and ChatGPT. LM Arena has suggested it will work to make the sampling algorithm more varied so you don’t always get the big commercial models. That would send more eval data to small players, giving them the chance to improve and challenge the big commercial models.

LM Arena recently announced it was forming a corporate entity to continue its work. With money on the table, the operators need to ensure Chatbot Arena continues figuring into the development of popular models. However, it’s unclear whether this is an objectively better way to evaluate chatbots versus academic tests. As people vote on vibes, there’s a real possibility we are pushing models to adopt sycophantic tendencies. This may have helped nudge ChatGPT into suck-up territory in recent weeks, a move that OpenAI has hastily reverted after widespread anger.

New study accuses LM Arena of gaming its popular AI benchmark Read More »

At monopoly trial, Zuckerberg redefined social media as texting with friends

facebook, ftc, Instagram, Meta, meta monopoly trial, monopoly, Policy, Social Media, tiktok / Kris Guyer / April 18, 2025

“The magic of friends has fallen away”

Mark Zuckerberg played up TikTok rivalry at monopoly trial, but judge may not buy it.

The Meta monopoly trial has raised a question that Meta hopes the Federal Trade Commission (FTC) can’t effectively answer: How important is it to use social media to connect with friends and family today?

Connecting with friends was, of course, Facebook’s primary use case as it became the rare social network to hit 1 billion users—not by being acquired by a Big Tech company but based on the strength of its clean interface and the network effects that kept users locked in simply because all the important people in their life chose to be there.

According to the FTC, Meta took advantage of Facebook’s early popularity, and it has since bought out rivals and otherwise cornered the market on personal social networks. Only Snapchat and MeWe (a privacy-focused Facebook alternative) are competitors to Meta platforms, the FTC argues, and social networks like TikTok or YouTube aren’t interchangeable, because those aren’t destinations focused on connecting friends and family.

For Meta CEO Mark Zuckerberg, however, those early days of Facebook bringing old friends back together are apparently over. He took the stand this week to testify that the FTC’s market definition ignores the reality that Meta contends with today, where “the amount that people are sharing with friends on Facebook, especially, has been declining,” CNN reported.

“Even the amount of new friends that people add … I think has been declining,” Zuckerberg said, although he did not indicate how steep the decline is. “I don’t know the exact numbers,” Zuckerberg admitted. Meta’s former chief operating officer, Sheryl Sandberg, also took the stand and reportedly testified that while she was at Meta, “friends and family sharing went way down over time . . . If you have a strategy of targeting friends and family, you’d have serious revenue issues.”

In particular, TikTok’s explosive popularity has shifted the dynamics of social media today, Zuckerberg suggested. For many users, “apps now serve primarily as discovery engines,” Zuckerberg testified, and social interactions increasingly come from sharing fun creator content in private messages, rather than through engaging with a friend or family member’s posts.

That’s why Meta added Reels, Zuckerberg testified, and, more recently, TikTok Shop-like functionality. To stay relevant, Meta had to make its platforms more like TikTok, investing heavily in its discovery algorithm, and even willing to irk loyal Instagram users by turning their perfectly curated square grids into rectangles, Wired noted in a piece probing Meta’s efforts to lure TikTok users to Instagram.

There was seemingly no bridge too far, because Zuckerberg said, “TikTok is still bigger than either Facebook or Instagram, and I don’t like it when our competitors do better than us.” And since Meta has no interest in buying TikTok, due to fears of basing business in China, Big Tech on Trial reported, Meta’s only choice was to TikTok-ify its apps to avoid a mass exodus after Facebook users started declining for the first time in 2022. Committing to this future, the next year, Meta doubled the amount of force-fed filler in Instagram feeds.

Right now, Meta is positioning TikTok as one of Meta’s biggest competitors, with Meta supposedly flagging it a “top priority” and “highly urgent” competitive threat as early as 2018, Zuckerberg said. Further, Zuckerberg testified that while TikTok’s popularity grew, Meta’s “growth slowed down dramatically,” TechCrunch reported. And perhaps most persuasively, when TikTok briefly went dark earlier this year, some TikTokers moved to Instagram, Meta argued, suggesting that some users consider the platforms interchangeable.

If Meta can convince the court that the FTC’s market definition is wrong and that TikTok is Meta’s biggest rival, then Meta’s market share drops below monopolist standards, “undercutting” the FTC’s case, Big Tech on Trial reported.

But are Facebook and Instagram substitutes for TikTok?

Although Meta paints the picture that TikTok users naturally gravitated to Instagram during the TikTok outage, it’s clear that Meta advertised heavily to move them in that direction. There was even a conspiracy theory that Meta had bought TikTok in the hours before TikTok went down, Wired reported, as users noticed Meta banners encouraging them to link their TikTok accounts to Meta platforms. However, even the reported Meta ad blitz seemingly didn’t sway that many TikTok users, as Sensor Tower data at the time apparently indicated that “Instagram and Facebook appeared to receive only a modest increase in daily active users and downloads” during the TikTok outage, Wired reported.

Perhaps a more interesting question that the court may entertain is not where TikTok users go when TikTok is down, but where Instagram or Facebook users turn if they no longer want to use those platforms. If the FTC can argue that people seeking a destination to connect with friends or family wouldn’t substitute TikTok for that purpose, their market definition might fly.

Kenneth Dintzer, a partner at Crowell & Moring and the former lead attorney in the DOJ’s winning Google search monopoly case, told Ars that the chief judge in the case, James Boasberg, made clear at summary judgment that acknowledging Meta’s rivalry with TikTok “doesn’t really answer the question about friends and family.”

So even though Zuckerberg was “pretty persuasive,” his testimony on TikTok may not move the judge much. However, there was one exchange at the trial where Boasberg asked, “How much does it matter if friends are on a particular platform, if friends can share outside of it?” Zuckerberg praised this as a “good question” and “explained that it doesn’t matter much because people can fluidly share across platforms, using each one for its value as a ‘discovery engine,'” Big Tech on Trial reported.

Dintzer noted that Zuckerberg seemed to attempt to float a different theory explaining why TikTok was a valid rival—curiously attempting to redefine “social media” to overcome the judge’s skepticism in considering TikTok a true Meta rival.

Zuckerberg’s theory, Dintzer said, suggests that “if I open up something on TikTok or on YouTube, and I send it to a friend, that is social media.”

But that broad definition could be problematic, since it would suggest that all texting and messaging are social media, Dintzer said.

“That didn’t seem particularly persuasive,” Dintzer said. Although that kind of social sharing is “certainly something that people enjoy,” it still “doesn’t seem to be quite the same thing as posting something on Facebook for your friends and family.”

Another wrinkle that may scramble Meta’s defense is that Meta has publicly declared that its priority is to bring back “OG Facebook” and refresh how friends and family connect on its platforms. Just today, Instagram chief Adam Mosseri announced a new Instagram feature called “blend” that strives to connect friends and family through sharing access to their unique discovery algorithms.

Those initiatives seem like a strategy that fully relies on Meta’s core use case of connecting friends and family (and network effects that Zuckerberg downplayed) to propel engagement that could spike revenue. However, that goal could invite scrutiny, perhaps signaling to the court that Meta still benefits from the alleged monopoly in personal social networking and will only continue locking in users seeking to connect with friends and family.

“The magic of friends has fallen away,” Meta’s blog said, which, despite seeming at odds, could serve as both a tagline for its new “Friends” tab on Facebook and the headline of its defense so far in the monopoly trial.

Ashley is a senior policy reporter for Ars Technica, dedicated to tracking social impacts of emerging policies and new technologies. She is a Chicago-based journalist with 20 years of experience.

At monopoly trial, Zuckerberg redefined social media as texting with friends Read More »

Zuckerberg’s 2012 email dubbed “smoking gun” at Meta monopoly trial

Antitrust law, facebook, Instagram, Meta, meta monopoly trial, monopoly trial, Policy, Snapchat, whatsapp / Kris Guyer / April 15, 2025

FTC’s “entire” monopoly case rests on decade-old emails, Meta argued.

Starting the Federal Trade Commission (FTC) antitrust trial Monday with a bang, Daniel Matheson, the FTC’s lead litigator, flagged a “smoking gun”—a 2012 email where Mark Zuckerberg suggested that Facebook could buy Instagram to “neutralize a potential competitor,” The New York Times reported.

And in “another banger of an email from Zuckerberg,” Brendan Benedict, an antitrust expert monitoring the trial for Big Tech on Trial, posted on X that the Meta CEO wrote, “Messenger isn’t beating WhatsApp. Instagram was growing so much faster than us that we had to buy them for $1 billion… that’s not exactly killing it.”

These messages and others, the FTC hopes to convince the court, provide evidence that Zuckerberg runs Meta by the mantra “it’s better to buy than compete”—seemingly for more than a decade intent on growing the Facebook empire by killing off rivals, allegedly in violation of antitrust law. Another message from Zuckerberg exhibited at trial, Benedict noted on X, suggests Facebook tried to buy yet another rival, Snapchat, for $6 billion.

“We should probably prepare for a leak that we offered $6b… and all the negative [attention] that will come from that,” the Zuckerberg message said.

At the trial, Matheson suggested that “Meta broke the deal” that firms have in the US to compete to succeed, allegedly deciding “that competition was too hard, and it would be easier to buy out their rivals than to compete with them,” the NYT reported. Ultimately, it will be up to the FTC to prove that Meta couldn’t have achieved its dominance today without buying Instagram and WhatsApp (in 2012 and 2014, respectively), while legal experts told the NYT that it is “extremely rare” to unwind mergers approved so many years ago.

Later today, Zuckerberg will take the stand and testify for perhaps seven hours, likely being made to answer for these messages and more. According to the NYT, the FTC will present a paper trail of emails where Zuckerberg and other Meta executives make it clear that acquisitions were intended to remove threats to Facebook’s dominance in the market.

It’s apparent that Meta plans to argue that it doesn’t matter what Zuckerberg or other executives intended when pursuing acquisitions. In a pretrial brief, Meta argued that “the FTC’s case rests almost entirely on emails (many more than a decade old) allegedly expressing competitive concerns” but suggested that this is only “intent” evidence, “without any evidence of anticompetitive effects.”

FTC may force Meta to spin off Instagram, WhatsApp

It is the FTC’s burden to show that Meta’s acquisitions harmed consumers and the market (and those harms outweigh any believable pro-competitive benefits alleged by Meta), but it remains to be seen whether Meta will devote ample time to testifying that “Mark Zuckerberg got it wrong” when describing his rationale for acquisitions, Big Tech on Trial noted.

Meta’s lead lawyer, Mark Hansen, told Law360 that “what people thought at Meta is not really what this case is.” (For those keeping track of who’s who in this case, Hansen apparently once was the boss of James Boasberg, the judge in the case, Big Tech on Trial reported.)

The social media company hopes to convince the court that the FTC’s case is political. So far, Meta has accused the FTC of shifting its market definition while willfully overlooking today’s competitive realities online, simply to punish a tech giant for its success.

In a blog post on Sunday, Meta’s chief legal officer, Jennifer Newstead, accused the FTC of lobbing a “weak case” that “ignores reality.” Meta insists that the FTC has “gerrymandered a fictitious market” to exclude Meta’s actual rivals, like TikTok, X, YouTube, or LinkedIn.

Boasberg will be scrutinizing the market definition, as well as alleged harms, and the FTC will potentially struggle to win him over on the merits of their case. Big Tech on Trial—which suggested that Meta’s acquisitions, if intended to kill off rivals, would be considered “a textbook violation of the antitrust laws”—noted that the court previously told the FTC that the agency had an “uphill climb” in proving its market definition. And because Meta’s social platforms are free, it’s harder to show direct evidence of consumer harms, experts have noted.

Still, for Meta, the stakes are high, as the FTC could pursue a breakup of the company, including requiring Meta to spin off WhatsApp and Instagram. Losing Instagram would hit Meta’s revenue hard, as Instagram is supposed to bring in more than half of its US ad revenue in 2025, eMarketer forecasted last December.

The trial is expected to last eight weeks, but much of the most-anticipated testimony will come early. Facebook’s former chief operating officer, Sheryl Sandberg, as well as Kevin Systrom, co-founder of Instagram, are expected to testify this week.

All unsealed emails and exhibits will eventually be posted on a website jointly managed by the FTC and Meta, but Ars was not yet provided a link or timeline for when the public evidence will be posted online.

Meta mocks FTC’s “ad load theory”

The FTC is arguing that Meta overpaid to acquire Instagram and WhatsApp to maintain an alleged monopoly in the personal social networking market that includes rivals like Snapchat and MeWe, a social networking platform that brands itself as a privacy-focused Facebook alternative.

In opening arguments, the FTC alleged that once competition was eliminated, Meta then degraded the quality of its platforms by limiting user privacy and inundating users with ads.

Meta has defended its acquisitions by arguing that it has improved Instagram and WhatsApp. At trial, Meta’s lawyer Hansen made light of the FTC’s “ad load theory,” stirring laughter in the reportedly packed courtroom, Benedict posted on X.

“If you don’t like an ad, you scroll past it. It takes about a second,” Hansen said.

Meanwhile, Newstead, who reportedly attended opening arguments, argued in her blog that “Instagram and WhatsApp provide a model for what successful acquisitions can achieve: Meta has made Instagram and WhatsApp better, more reliable and more secure through billions of dollars and millions of hours of investment.”

By breaking up these acquisitions, Hansen argued, the FTC would be sending a strong message to startups that “would kill entrepreneurship” by seemingly taking mergers and acquisitions “off the table,” Benedict posted on X.

To defeat the FTC, Meta will likely attempt to broaden the market definition to include more rivals. In support of that, Meta has already pointed to the recent TikTok ban driving TikTok users to Instagram, which allegedly shows the platforms are interchangeable, despite the FTC differentiating TikTok as a video app.

The FTC will likely lean on Meta’s internal documents to show who Meta actually considers rivals. During opening arguments, for example, the FTC reportedly shared a Meta document showing that Meta itself has agreed with the FTC and differentiated Facebook as connecting “friends and family,” while “LinkedIn connects coworkers” and “Nextdoor connects neighbors.”

“Contemporaneous records reveal that Meta and other social media executives understood that users flock to different platforms for different purposes and that Facebook, Instagram, and WhatsApp were specifically designed to operate in a distinct submarket for family and friend connections,” the American Economic Liberties Project, which is partnering with Big Tech on Trial to monitoring the proceedings, said in a press statement.

But Newstead suggested that “evidence of fierce and increasing competition in the market has only grown in the four years since the FTC’s complaint was filed,” and Meta now “faces strong competition in a rapidly shifting tech landscape that includes American and foreign competitors.”

To emphasize the threats to US consumers and businesses, Newstead also invoked the supposed threat to America’s AI leadership if one of the country’s leading tech companies loses momentum at this key moment.

“It’s absurd that the FTC is trying to break up a great American company at the same time the Administration is trying to save Chinese-owned TikTok,” Newstead said. “And, it makes no sense for regulators to try and weaken US companies right at the moment we most need them to invest in winning the competition with China for leadership in AI.”

Trump’s FTC appears unlikely to back down

Zuckerberg has been criticized for his supposed last-ditch attempts to push the Trump administration to pause or toss the FTC’s case. Last month, the CEO visited Trump in the Oval Office to discuss a settlement, Politico reported, apparently worrying officials who don’t want Trump to bail out Meta.

On Monday, the FTC did not appear to be wavering, however, prompting alarm bells in the tech industry.

Patrick Hedger, the director of policy for NetChoice—a trade group that represents Meta and other Big Tech companies—warned that if the FTC undoes Meta’s acquisitions, it would harm innovation and competition while damaging trust in the FTC long-term.

“This bait-and-switch against Meta for acquisitions approved over 10 years ago in the fiercely competitive social media marketplace will have serious ripple effects not only for the US tech industry, but across all American businesses,” Hedger said.

Seemingly accusing Donald Trump’s FTC of pursuing Lina Khan’s alleged agenda against Big Tech, Hedger added that “with Meta at the forefront of open-source AI innovation and a global competitor, the outcome of this trial will have spillover into the entire economy. It will create a fear among businesses that making future, pro-competitive investments could be reversed due to political discontent—not the necessary evidence traditionally required for an anticompetitive claim.”

Big Tech on Trial noted that it’s possible that the FTC could “vote to settle, withdraw, or pause the case.” Last month, Trump fired the two Democrats, eliminating a 3–2 split and ensuring only Republicans are steering the agency for now.

But Trump’s FTC seems determined to proceed in attempts to disrupt Meta’s business. FTC Chair Andrew Ferguson told Fox Business Monday that “antitrust laws can help make sure that no private sector company gets so powerful that it affects our lives in ways that are really bad for all Americans,” and “that’s what this trial beginning today is all about.”

Ashley is a senior policy reporter for Ars Technica, dedicated to tracking social impacts of emerging policies and new technologies. She is a Chicago-based journalist with 20 years of experience.

Zuckerberg’s 2012 email dubbed “smoking gun” at Meta monopoly trial Read More »

Meta’s surprise Llama 4 drop exposes the gap between AI ambition and reality

AI, Biz & IT, LLaMA, Llama 3, Llama 4, machine learning, Meta, Simon Willison / Rejus Almole / April 8, 2025

Meta constructed the Llama 4 models using a mixture-of-experts (MoE) architecture, which is one way around the limitations of running huge AI models. Think of MoE like having a large team of specialized workers; instead of everyone working on every task, only the relevant specialists activate for a specific job.

For example, Llama 4 Maverick features a 400 billion parameter size, but only 17 billion of those parameters are active at once across one of 128 experts. Likewise, Scout features 109 billion total parameters, but only 17 billion are active at once across one of 16 experts. This design can reduce the computation needed to run the model, since smaller portions of neural network weights are active simultaneously.

Llama’s reality check arrives quickly

Current AI models have a relatively limited short-term memory. In AI, a context window acts somewhat in that fashion, determining how much information it can process simultaneously. AI language models like Llama typically process that memory as chunks of data called tokens, which can be whole words or fragments of longer words. Large context windows allow AI models to process longer documents, larger code bases, and longer conversations.

Despite Meta’s promotion of Llama 4 Scout’s 10 million token context window, developers have so far discovered that using even a fraction of that amount has proven challenging due to memory limitations. Willison reported on his blog that third-party services providing access, like Groq and Fireworks, limited Scout’s context to just 128,000 tokens. Another provider, Together AI, offered 328,000 tokens.

Evidence suggests accessing larger contexts requires immense resources. Willison pointed to Meta’s own example notebook (“build_with_llama_4“), which states that running a 1.4 million token context needs eight high-end Nvidia H100 GPUs.

Willison documented his own testing troubles. When he asked Llama 4 Scout via the OpenRouter service to summarize a long online discussion (around 20,000 tokens), the result wasn’t useful. He described the output as “complete junk output,” which devolved into repetitive loops.

Meta’s surprise Llama 4 drop exposes the gap between AI ambition and reality Read More »

Meta plans to test and tinker with X’s community notes algorithm

community notes, facebook, Instagram, Meta, misinformation, Policy, threads, Twitter, X / Rejus Almole / March 14, 2025

Meta also confirmed that it won’t be reducing visibility of misleading posts with community notes. That’s a change from the prior system, Meta noted, which had penalties associated with fact-checking.

According to Meta, X’s algorithm cannot be gamed, supposedly safeguarding “against organized campaigns” striving to manipulate notes and “influence what notes get published or what they say.” Meta claims it will rely on external research on community notes to avoid that pitfall, but as recently as last October, outside researchers had suggested that X’s Community Notes were easily sabotaged by toxic X users.

“We don’t expect this process to be perfect, but we’ll continue to improve as we learn,” Meta said.

Meta confirmed that the company plans to tweak X’s algorithm over time to develop its own version of community notes, which “may explore different or adjusted algorithms to support how Community Notes are ranked and rated.”

In a post, X’s Support account said that X was “excited” that Meta was using its “well-established, academically studied program as a foundation” for its community notes.

Meta plans to test and tinker with X’s community notes algorithm Read More »

AI firms follow DeepSeek’s lead, create cheaper models with “distillation”

AI, DeepSeek, Distillation, llm, Meta, openai, syndication / Tim Belzer / March 4, 2025

Thanks to distillation, developers and businesses can access these models’ capabilities at a fraction of the price, allowing app developers to run AI models quickly on devices such as laptops and smartphones.

Developers can use OpenAI’s platform for distillation, learning from the large language models that underpin products like ChatGPT. OpenAI’s largest backer, Microsoft, used GPT-4 to distill its small language family of models Phi as part of a commercial partnership after investing nearly $14 billion into the company.

However, the San Francisco-based start-up has said it believes DeepSeek distilled OpenAI’s models to train its competitor, a move that would be against its terms of service. DeepSeek has not commented on the claims.

While distillation can be used to create high-performing models, experts add they are more limited.

“Distillation presents an interesting trade-off; if you make the models smaller, you inevitably reduce their capability,” said Ahmed Awadallah of Microsoft Research, who said a distilled model can be designed to be very good at summarising emails, for example, “but it really would not be good at anything else.”

David Cox, vice-president for AI models at IBM Research, said most businesses do not need a massive model to run their products, and distilled ones are powerful enough for purposes such as customer service chatbots or running on smaller devices like phones.

“Any time you can [make it less expensive] and it gives you the right performance you want, there is very little reason not to do it,” he added.

That presents a challenge to many of the business models of leading AI firms. Even if developers use distilled models from companies like OpenAI, they cost far less to run, are less expensive to create, and, therefore, generate less revenue. Model-makers like OpenAI often charge less for the use of distilled models as they require less computational load.

AI firms follow DeepSeek’s lead, create cheaper models with “distillation” Read More »

Meta claims torrenting pirated books isn’t illegal without proof of seeding

AI copyright, AI training, copyright, leeching, Meta, online piracy, Policy, seeding, torrenting / Rejus Almole / February 20, 2025

Just because Meta admitted to torrenting a dataset of pirated books for AI training purposes, that doesn’t necessarily mean that Meta seeded the file after downloading it, the social media company claimed in a court filing this week.

Evidence instead shows that Meta “took precautions not to ‘seed’ any downloaded files,” Meta’s filing said. Seeding refers to sharing a torrented file after the download completes, and because there’s allegedly no proof of such “seeding,” Meta insisted that authors cannot prove Meta shared the pirated books with anyone during the torrenting process.

Whether or not Meta actually seeded the pirated books could make a difference in a copyright lawsuit from book authors including Richard Kadrey, Sarah Silverman, and Ta-Nehisi Coates. Authors had previously alleged that Meta unlawfully copied and distributed their works through AI outputs—an increasingly common complaint that so far has barely been litigated. But Meta’s admission to torrenting appears to add a more straightforward claim of unlawful distribution of copyrighted works through illegal torrenting, which has long been considered established case-law.

Authors have alleged that “Meta deliberately engaged in one of the largest data piracy campaigns in history to acquire text data for its LLM training datasets, torrenting and sharing dozens of terabytes of pirated data that altogether contain many millions of copyrighted works.” Separate from their copyright infringement claims opposing Meta’s AI training on pirated copies of their books, authors alleged that Meta torrenting the dataset was “independently illegal” under California’s Computer Data Access and Fraud Act (CDAFA), which allegedly “prevents the unauthorized taking of data, including copyrighted works.”

Meta, however, is hoping to convince the court that torrenting is not in and of itself illegal, but is, rather, a “widely-used protocol to download large files.” According to Meta, the decision to download the pirated books dataset from pirate libraries like LibGen and Z-Library was simply a move to access “data from a ‘well-known online repository’ that was publicly available via torrents.”

Meta claims torrenting pirated books isn’t illegal without proof of seeding Read More »