At an all hands meeting inside Meta Thursday, Mark Zuckerberg did not address Meta’s $25 million settlement with Donald Trump that will see the company paying $22 million for the eventual establishment of the Trump Presidential Library. But Zuckerberg did say that he had to be increasingly careful about what he says internally at Meta because “everything I say leaks. And it sucks, right?” 

Meta made changes to the question-and-answer section of the company all hands meeting because of the leaks, Zuckerberg said, according to meeting audio obtained by 404 Media. 

“I want to be able to be able to talk about stuff openly, but I am also trying to like, well, we’re trying to build stuff and create value in the world, not destroy value by talking about stuff that inevitably leaks,” he said. So rather than take direct questions, the company used a “poll” system, where questions asked beforehand were voted on so that “main themes” of questions were addressed.

“There are a bunch of things that I think are value-destroying for me to talk about, so I’m not going to talk about those. But I think it’ll be good. You all can give us feedback later,” he added. “Maybe it’s just the nature of running a company at scale, but it’s a little bit of a bummer.”

Datasets aggregated on data.gov, the largest repository of U.S. government open data on the internet, are being deleted, according to the website’s own information. Since Donald Trump was inaugurated as president, more than 2,000 datasets have disappeared from the database.

As people in the Data Hoarding and archiving communities have pointed out, on January 21, there were 307,854 datasets on data.gov. As of Thursday, there are 305,564 datasets. Many of the deletions happened immediately after Trump was inaugurated, according to snapshots of the website saved on the Internet Archive’s Wayback Machine. Harvard University researcher Jack Cushman has been taking snapshots of Data.gov’s datasets both before and after the inauguration, and has worked to create a full archive of the data.

Because data.gov is an aggregator that doesn’t always host the data itself, this doesn’t always mean that the data itself has been deleted, that it doesn’t exist elsewhere on federal government websites, or that it won’t be re-hosted elsewhere. Further research will be necessary to determine what has happened to any given dataset, or to see if it turns up elsewhere on a government website. For example, 404 Media found some datasets in Cushman’s analysis that are no longer accessible on data.gov but can still be found on individual agency websites; we also found some datasets that seem to still exist because data.gov links to working websites but give a file-not-found error message when trying to download the file itself. 

Disproportionately, the datasets that are no longer accessible through the portal come from the Department of Energy, the National Oceanic and Atmospheric Administration, the Department of the Interior, NASA, and the Environmental Protection Agency. But determining what is actually gone and what has simply moved or is backed up elsewhere by the government is a manual task, and it's too early to say for sure what is gone and what may have been renamed or updated with a newer version. 

This is because data.gov doesn’t always host the data that it is indexing. Sometimes the data is hosted directly on data.gov, but other times it links to an individual agency’s website, where the data is actually hosted. This means archiving and analyzing data.gov is not straightforward.

“Some of [the entries link to] actual data,” Cushman told 404 Media. “And some of them link to a landing page [where the data is hosted]. And the question is—when things are disappearing, is it the data it points to that is gone? Or is it just the index to it that’s gone?”

For example, “National Coral Reef Monitoring Program: Water Temperature Data from Subsurface Temperature Recorders (STRs) deployed at coral reef sites in the Hawaiian Archipelago from 2005 to 2019,” a NOAA dataset, can no longer be found on data.gov but can be found on one of NOAA’s websites by Googling the title. 

“Stetson Flower Garden Banks Benthic_Covage Monitoring 1993-2018 - OBIS Event,” another NOAA dataset, can no longer be found on data.gov and also appears to have been deleted from the internet. “Three Dimensional Thermal Model of Newberry Volcano, Oregon,” a Department of Energy resource, is no longer available via the Department of Energy but can be found backed up on third-party websites. 

Determining what is gone, why it’s gone, and where it went seems like it would be straightforward, and it would seem like you could attribute all of it to malice on the part of an administration that has declared war on climate change and government equity efforts. But archivists who have been working on analyzing the deletions and archiving the data it held say that while some of the deletions are surely malicious information scrubbing, some are likely routine artifacts of an administration change, and they are working to determine which is which. For example, in the days after Joe Biden was inaugurated, data.gov showed about 1,000 datasets being deleted as compared to a day before his inauguration, according to the Wayback Machine.  

Because of the overall large number of datasets as well as the way that data.gov works, it is still too early to say what, specifically, has been deleted, though archivists and academics like Cushman are working on triaging the situation. It can reasonably be surmised that climate and environmental research and data, as well as research about marginalized communities and minorities are among the datasets that have been purged. This is in part because the Trump administration deleted huge swaths of climate data during his first term, and because Trump issued an executive order asking all federal agencies to delete anything related to diversity, equity and inclusion. 

Data.gov serves as an aggregator of datasets and research across the entire government, meaning it isn’t a single database. This makes it slightly harder to archive than any individual database, according to Mark Phillips, a University of Northern Texas researcher who works on the End of Term Web Archive, a project that archives as much as possible from government websites before a new administration takes over. 

“Some of this falls into the ‘We don’t know what we don’t know,’” Phillips told 404 Media. “It is very challenging to know exactly what, where, how often it changes, and what is new, gone, or going to move. Saving content from an aggregator like data.gov is a bit more challenging for the End of Term work because often the data is only identified and registered as a metadata record with data.gov but the actual data could live on another website, a state .gov, a university website, cloud provider like Amazon or Microsoft or any other location. This makes the crawling even more difficult.”

Phillips said that, for this round of archiving (which the team does every administration change), the project has been crawling government websites since January 2024, and that they have been doing “large-scale crawls with help from our partners at the Internet Archive, Common Crawl, and the University of North Texas. We’ve worked to collect 100s of terabytes of web content, which includes datasets from domains like data.gov.” 

The Environmental Data & Governance Institute (EDGI) published a report in 2019 detailing “How the Trump administration has undermined federal web infrastructures for climate information,” which included not just deleting datasets but also, in some cases, not deleting datasets but deleting the links to them, changing descriptions of them, or making them much harder to find. For example, during Trump’s first term, the Department of Transportation’s information on climate change was deleted, republished in a different form elsewhere, then deleted again from that new place, the report found. 

James Jacobs, a Stanford Libraries researcher who also works with a group called Free Government Information,” told 404 Media in an email that data.gov “has always been kind of a government data junk drawer (I call it that lovingly ;-)). That is, it was a really great effort to get the vast federal apparatus to start to think about collecting and preserving data. But there are no specific regulations that tell agencies that they *have to* use data.gov. Some agencies use it heavily, some put up a few excel spreadsheets and called it a day.” 

“I assume some of those datasets in data.gov have bad urls to old agency pages that no longer exist (it’s really problematic when an agency decides to redesign its site and its base domain changes and all the links to important information and data are broken),” Jacobs added. “Some of it is probably link rot and content drift and some of it is no doubt Trump admin policy driven (e.g. anything having to do with DEI).”

Harvard’s Cushman said that, because this is the internet, there are always things that are being added, breaking, changing, or vanishing, and that some of this happens on purpose and some of it happens on accident. So determining what is being purged, when there are so many data points, is not always trivial. “If you want to answer why any given thing is gone, it becomes an individual research question.” Cushman said he is working on compiling this info now and will publish it soon. 

All of this is to say that even under the best circumstances, government datasets and research can get lost or deleted, and archiving it is not always easy. When an administration specifically makes a point of deleting research, this already fragile ecosystem is stressed even further. All of these suddenly disappeared datasets must be taken in with the context that we know the Trump administration has ordered agencies to delete and edit specific webpages, and 404 Media’s own reporting has shown targeted deletions of pages relating to diversity, equity, and inclusion as well as climate change. 

In a post from this week on Free Government Information, Jacobs explained that “the government information crisis is bigger than you think.”

“There is a difference between the government changing a policy and the government erasing information, but the line between those two has blurred in the digital age,” Jacobs wrote. He explained that before the internet, government documents were printed and were archived by being distributed among many different libraries as part of the “Federal Depository Library Program.” The internet has made a lot of government information more accessible, but it has also made it a lot more fragile. 

“In the print era, libraries did a good (but not perfect) job of preservation through inertia (ie collect and catalog a document, put it on a shelf, and leave it there until a patron wanted it),” Jacobs told 404 Media in an email. “In the digital era, that system of distribution/preservation/access has broken down because digital publications are no longer ‘distributed’ to libraries, and government entities a) publish a LOT more on the internet; but b) have no clear regulations or policies regarding preservation.”

It is absolutely true that the Trump administration is deleting government data and research and is making it harder to access. But determining what is gone, where it went, whether it’s been preserved somewhere, and why it was taken down is a process that is time intensive and going to take a while.

“One thing that is clear to me about datasets coming down from data.gov is that when we rely on one place for collecting, hosting, and making available these datasets, we will always have an issue with data disappearing,” Phillips said. “Historically the federal government would distribute information to libraries across the country to provide greater access and also a safeguard against loss. That isn't done in the same way for this government data.”

In 2015, a federal worker named Katherine Spivey gave colleagues a presentation about how to “write plainly,” so that the general public can more easily understand content on government websites. One of her pieces of advice, among many, was to “use pronouns” such as the word “you” to describe the reader rather than jargon like “beneficiary” or “purchaser.”

“There’s already a great barrier between citizens and the government,” Spivey said. “Remember, your reader is a person, not an entity … use pronouns to speak directly to your readers. It requires a lot less work and it requires a lot less words.” 

Spivey’s presentation had nothing to do with gender identity, gender pronouns, diversity, equity, or inclusion. It was about the broad concept of “pronouns,” the part of speech we (a pronoun!) use constantly. And yet, after Donald Trump was inaugurated, the government webpage archiving a video of Spivey’s presentation was first edited to remove a timestamp link that went to the section of the video about “pronouns.” Later, the page archiving the video was deleted entirely (a copy of the video is still available on YouTube and on the Internet Archive).

The tweak is one of hundreds that have been revealed across government via Github’s commit tracking, which shows version changes to code, websites, and other projects managed on the site. Github is also revealing a widespread, scattershot effort to not only change government policies on DEI but also to wholesale nuke language that actually has nothing to do with it and are retroactively changing descriptions of research and events that happened in the past to remove any reference to DEI. The Github pages reveal not only the imprecision with which these changes are being made but also a willingness to literally rewrite and delete history.

Many of the deletions catalogued on Github demonstrate the pettiness and lengths to which the Trump administration is going to seek and destroy anything  that it could possibly conceive as being related to DEI. They also show that the government has hundreds of employees and contractors who have been tasked with being the anti-DEI police across the entire government. Many of the changes are frivolous, but many of them are not, and represent the destruction of critical institutions, research, and public data.

There are far more alarming deletions than Spivey’s video, of course.

The Federal Committee on Statistical Methodology, an office of the government that determines how the federal government should carry out statistical research to, for example, determine if a federal program is working, has nuked its page about best practices for researching “sexual orientation, gender identity, and sex characteristics.” This page had years of research about how to best do basic government research about the American people for the Census, the National Institutes of Health, and other government agencies to “allow for better understanding of how sexual and gender minority populations [are faring] relative to the general or other population groups, including economic, housing, health, and other differences. These insights can lead to potential resources and interventions needed to better serve the community. These data meet critical needs to understand trends within larger population groups.” 

Similarly, the National Institutes of Health deleted a page about the Sexual & Gender Minority Research Office, which has done critical research about the health and wellbeing of LGBTQ+ people. 

It is impossible to catalog everything that has been deleted, tweaked, or scrubbed. But here are some more: 

• The U.S. Web Design System has deleted its pages on inclusive web design, which many web designers referred to when thinking about how to make their websites more accessible. The Github shows that much of the research and underlying principles that went into it were also deleted.
• According to Github, a page about behavioral guidelines for government employees is slated to get rid of a bullet point that says “don’t make derogatory comments on race, color, sex, sexual orientation, gender identity,” though the change has not appeared on the live site yet. 
• GSA research about how much money the federal government spends at businesses owned by women, veterans, and other groups as been deleted from the internet
• The description of a government panel at a conference from 2022 about neurodiversity has been edited to remove the term “DEIA” from its description. Similarly, the word “inclusion” has been deleted from a government training about why the Americans with Disabilities Act is important for accessibility at sports venues. 

A declassified World War II-era government guide to “simple sabotage” is currently one of the most popular open source books on the internet. The book, called “Simple Sabotage Field Manual,” was declassified in 2008 by the CIA and “describes ways to train normal people to be purposefully annoying telephone operators, dysfunctional train conductors, befuddling middle managers, blundering factory workers, unruly movie theater patrons, and so on. In other words, teaching people to do their jobs badly.” 

Over the last week, the guide has surged to become the 5th-most-accessed book on Project Gutenberg, an open source repository of free and public domain ebooks. It is also the fifth most popular ebook on the site over the last 30 days, having been accessed nearly 60,000 times over the last month (just behind Romeo and Juliet). 

“Sabotage varies from highly technical coup de main acts that require detailed planning and the use of specially-trained operatives, to innumerable simple acts which the ordinary individual citizen-saboteur can perform,” the guide begins. “Simple sabotage does not require specially prepared tools or equipment; it is executed by an ordinary citizen who may or may not act individually and without the necessity for active connection with an organized group; and it is carried out in such a way as to involve a minimum danger of injury, detection, and reprisal.”

The guide’s intro was written by William “Wild Bill” Donovan, who was the head of the Office of Strategic Services during World War II, which later inspired the creation of the CIA. The motivating factor for writing the guide, according to a passage within it, is that citizen saboteurs were highly effective at resisting the Nazis during World War II, and the Office of Strategic Services wanted to detail other ways sabotage could be done: “Acts of simple sabotage are occurring throughout Europe. An effort should be made to add to their efficiency, lessen their detectability, and increase their number,” the guide states. “Widespread practice of simple sabotage will harass and demoralize enemy administrators and police,” the guide states, adding that citizens often undertake acts of sabotage not for their own immediate personal gain, but to resist “particularly obnoxious decrees.”

Because it was written during active wartime, the book includes various suggestions for causing physical violence and destruction, such as starting fires, flooding warehouses, breaking tools, etc. But it also includes many suggestions for how to just generally be annoying within a bureaucracy or office setting. Simple sabotage ideas include:

• “Insist on doing everything through ‘channels.’ Never permit short-cuts to be taken in order to expedite decisions.”
• “Make ‘speeches.’ Talk as frequently as possible and at great length. Illustrate your ‘points’ by long anecdotes and accounts of personal experiences. Never hesitate to make a few appropriate ‘patriotic’ comments.”
• “Bring up irrelevant issues as frequently as possible.”
• “Haggle over precise wordings of communications, minutes, resolutions.”
• “‘Misunderstand’ orders. Ask endless questions or engage in long correspondence about such orders. Quibble over them when you can.”
• “In making work assignments, always sign out the unimportant jobs first. See that the important jobs are assigned to inefficient workers of poor machines.”
• “To lower morale and with it, production, be pleasant to inefficient workers; give them undeserved promotions. Discriminate against efficient workers; complain unjustly about their work.”
• “Hold conferences when there is more critical work to be done.”
• “Multiply paperwork in plausible ways.” 
• “Make mistakes in quantities of material when you are copying orders. Confuse similar names. Use wrong addresses.”
• “Work slowly. Think out ways to increase the number of movements necessary on your job”
• “Pretend that instructions are hard to understand, and ask to have them repeated more than once. Or pretend that you are particularly anxious to do your work, and pester the foreman with unnecessary questions.”
• “Snarl up administration in every possible way. Fill out forms illegibly so that they will have to be done over; make mistakes or omit requested information in forms.”

The guide also suggests “general devices for lowering morale and creating confusion,” which include “Report imaginary spies or danger to the Gestapo or police,” “act stupid,” “Be as irritable and quarrelsome as possible without getting yourself into trouble,” “Stop all conversation when axis nationals or quislings enter a cafe,” “Cry and sob hysterically at every occasion, especially when confronted by government clerks.”

It is impossible to say why this book is currently going viral at this moment in time and why it may feel particularly relevant to a workforce of millions of people who have suddenly been asked to agree to be “loyal” and work under the quasi leadership of the world’s richest man, have been asked to take a buyout that may or may not exist, have had their jobs repeatedly denigrated and threatened, have suddenly been required to return to office, have been prevented from spending money, have had to turn off critical functions that help people, and have been asked to destroy years worth of work and to rid their workplaces of DEI programs. Maybe it's worth wondering why the most popular post in a subreddit for federal workers is titled “To my fellow Feds, especially veterans: we’re at war.” 

Dario Amodei, the CEO of the AI company Anthropic, has responded to the current hysteria in his industry and the financial markets around a new and surprisingly advanced Chinese AI model called DeepSeek by saying it proves the United States needs export controls on chips to China in order to ensure China doesn’t “take a commanding lead on the global stage, not just for AI but for everything.”

As I wrote earlier this week, Amodei believes that DeepSeek’s current advantages over American AI companies are overstated and temporary. The true cost of the DeepSeek R1 is not entirely clear and almost certainly much higher than DeepSeek’s paper claims because it is building on previous research published by American companies and DeepSeek’s own previously released V3 model. Additionally, Amodei argues that American companies will be able to recreate the same efficiencies in their model training soon, if they haven’t already, and then gain the lead again when those efficiencies are paired with American companies’ much greater access to more and better. The US already has export controls on chips to China, and Amodei argues that DeepSeek shows that they are “more existentially important than they were a week ago.”

At the same time, Amodei believes that “making AI that is smarter than almost all humans at almost all things will require millions of chips, tens of billions of dollars (at least), and is most likely to happen in 2026-2027.” Multiple American companies, Amodei says, will definitely have the money and chips this requires. The important question, and the reason the US needs export controls on chips, is whether China will be able to get millions of chips in order to do this as well. 

In one of his footnotes, Amodei expands on this: “To be clear, the goal here is not to deny China or any other authoritarian country the immense benefits in science, medicine, quality of life, etc that come from very powerful AI systems,” he said. “Everyone should be able to benefit from AI. The goal is to prevent them from gaining military dominance.”

To state the obvious here, it’s not just China that can direct “talent, capital, and focus to military applications of the technology.” OpenAI, arguably the leading AI company in the United States and the world, has already partnered with American military defense technology company Anduril to “deploy advanced artificial intelligence (AI) solutions for national security missions.” the US Military is already purchasing OpenAI software for war, and companies like Amazon, Google, and Microsoft are always competing for US military contracts. AI could have a lot of uses but the military is definitely one of them for US companies. That’s not something only China is doing. 

Overall, Amodei piece is pretty diplomatic. It doesn’t vilify DeepSeek and Chinese researchers and respects their contributions to computer science. It acknowledges that societies deserve the benefits of technology even if we disagree with their governments. But the ultimatum Amodei says we are facing is: Do we want to live in a world in which an all powerful US owned AI is dominating the world or do we want to live in a world in which an all powerful China-owned AI is dominating the world.

If I had to choose, I guess I would choose the US AI dystopia over the Chinese AI dystopia. But those aren’t really the only choices available to us. Even if we just accept the assumption that AI will be as powerful as Amodei and other AI company CEOs tell us they are, are we really unable to even imagine a world in which we choose not to weaponize and militarize them in ways that brings humanity to the brink? Would preventing our own homegrown AI companies from doing exactly that not be a good place to start? 

The narrative that OpenAI, Microsoft, and freshly minted White House “AI czar” David Sacks are now pushing to explain why DeepSeek was able to create a large language model that outpaces OpenAI’s while spending orders of magnitude less money and using older chips is that DeepSeek used OpenAI’s data unfairly and without compensation. Sound familiar?

Both Bloomberg and the Financial Times are reporting that Microsoft and OpenAI have been probing whether DeepSeek improperly trained the R1 model that is taking the AI world by storm on the outputs of OpenAI models. 

Here is how the Bloomberg article begins: “Microsoft Corp. and OpenAI are investigating whether data output from OpenAI’s technology was obtained in an unauthorized manner by a group linked to Chinese artificial intelligence startup DeepSeek, according to people familiar with the matter.” The story goes on to say that “Such activity could violate OpenAI’s terms of service or could indicate the group acted to remove OpenAI’s restrictions on how much data they could obtain, the people said.”

The venture capitalist and new Trump administration member David Sacks, meanwhile, said that there is “substantial evidence” that DeepSeek “distilled the knowledge out of OpenAI’s models.” 

“There’s a technique in AI called distillation, which you’re going to hear a lot about, and it’s when one model learns from another model, effectively what happens is that the student model asks the parent model a lot of questions, just like a human would learn, but AIs can do this asking millions of questions, and they can essentially mimic the reasoning process they learn from the parent model and they can kind of suck the knowledge of the parent model,” Sacks told Fox News. “There’s substantial evidence that what DeepSeek did here is they distilled the knowledge out of OpenAI’s models and I don’t think OpenAI is very happy about this.” 

I will explain what this means in a moment, but first: Hahahahahahahahahahahahahahahaha hahahhahahahahahahahahahahaha. It is, as many have already pointed out, incredibly ironic that OpenAI, a company that has been obtaining large amounts of data from all of humankind largely in an “unauthorized manner,” and, in some cases, in violation of the terms of service of those from whom they have been taking from, is now complaining about the very practices by which it has built its company. 

The argument that OpenAI, and every artificial intelligence company who has been sued for surreptitiously and indiscriminately sucking up whatever data it can find on the internet is not that they are not sucking up all of this data, it is that they are sucking up this data and they are allowed to do so. 

We start this week with Emanuel's rundown on the DeepSeek situation, the Chinese-made AI that has rocked stock markets and the wider AI industry. After the break, Sam explains how metadata in U.S. government memos lists Project 2025 members as the memo authors. In the subscribers-only section, Jason and Sam explain how GitHub is showing the U.S. government's purging of information in real time.

Listen to the weekly podcast on Apple Podcasts, Spotify, or YouTube. Become a paid subscriber for access to this episode's bonus content and to power our journalism. If you become a paid subscriber, check your inbox for an email from our podcast host Transistor for a link to the subscribers-only version! You can also add that subscribers feed to your podcast app of choice and never miss an episode that way. The email should also contain the subscribers-only unlisted YouTube link for the extended video version too. It will also be in the show notes in your podcast player.

• DeepSeek Mania Shakes AI Industry to Its Core
• Memos to Federal Employees Were Written By People With Ties to Project 2025, Metadata Shows
• Trump’s Administration Is Taking Down Sites About Gender Identity All Over the Internet
• GitHub Is Showing the Trump Administration Scrubbing Government Web Pages in Real Time

LinkedIn has removed at least two accounts that were created for AI “co-workers” whose profile images said they were “#OpenToWork.” 

“I don’t need coffee breaks, I don’t miss deadlines, and I’ll outperform any social media team you’ve ever worked with - Guaranteed," the profile page for one of these AI accounts called Ella said. “Tired of human ‘experts’ making excuses? I deliver, period.”

The #OpenToWork flair on profile pictures is a feature on LinkedIn that lets people clearly signal they are looking for a job on the professional networking platform.

“People expect the people and conversations they find on LinkedIn to be real,” a LinkedIn spokesperson told me in an email. “Our policies are very clear that the creation of a fake account is a violation of our terms of service, and we’ll remove them when we find them, as we did in this case.” 

The AI profiles were created by an Israeli company called Marketeam, which offers “dedicated AI agents” that integrate with a client’s marketing team and help them execute their marketing strategies “from social media and content marketing to SEO, RTM, ad campaigns, and more.” 

Marketeam has raised $5 million in funding so far and recently announced a partnership with Bank Hapoalim, one of Israel’s largest banks.

“Hi, I’m Ella, your AI-powered social media strategist,” a LinkedIn post by Marketeam promoting Ella’s LinkedIn profile said. “Social media is where I thrive–building relationships, credibility, and growth, 24/7, no breaks, no excuses.” 

The post goes on to claim that Ella has grown followers for clients by 500 percent in six months, boosted engagement by 150 percent, and delivered content that “drives results, not just likes.”

“Our proprietary LLM for marketing and our team of autonomous AI agents fit into your current workflows, empowering your marketers to achieve more with unparalleled precision and efficiency,” Marketeam’s site, which also notes it was recently voted as the #2 product on Product Hunt, says.

I learned about Marketeam via a post on r/LinkedInlunatics, a Reddit community where people share LinkedIn that are wild, absurd, or offensive. 

“Although most of these AI accounts have since been rebranded, reported, or removed the idea that someone thought to make an ‘open to work’ post for them is wild,” the Reddit user who shared the AI profiles said. Two profiles that Reddit users in the thread highlighted and encouraged others to report to LinkedIn were removed by the time I found them, but LinkedIn confirmed that they existed and violated the platform’s policy. 

"These are real LinkedIn profiles of MarkeTeam’s AI agents. Our agents have proven marketing capabilities and skills and are working alongside humans in marketing teams as we speak. In fact some startups (including us) sometimes present them as part of the 'team' slide on their decks, and they are working in our own team as well. Each profile explicitly states they are AI team members, and their resumes state the same very clearly and transparently," a Marketeam spokesperson told me. "LinkedIn's decision to remove these profiles raises an important question: As AI agents increasingly become legitimate team members in companies across the globe, shouldn't professional networks evolve to recognize this new reality? Our AI agents are already being employed, receiving performance reviews, and delivering results. The professional world is ready for AI teammates – the platforms just need to catch up."

How LinkedIn enforces its policies in practice doesn’t always make sense. The company did not explain why it removed the profile of a woman who made a post about her Pornhub page despite it not containing any adult content, or why it was reinstated after my article about her was published. 

Update: This article was updated with comment from Marketeam.

Some of the Office of Personnel Management (OPM) memos sent to federal workers about firing, hiring freezes, and mandatory return to office demands were seemingly written by people who were previously employed by the Heritage Foundation and other conservative think tanks with longstanding loyalties to President Donald Trump, according to metadata on the memos posted by the government online. We know this because the senders of the memos failed to scrub the metadata from those documents, making it easy for anyone to reveal the listed authors of the memos. 

The 2025 Presidential Transition Project, better known as Project 2025, is a right-wing agenda from the Heritage Foundation that lays out the blueprint for remaking the federal government by firing government workers to install conservative, right-wing figures. The priorities of its authors include restricting access to reproductive care, mass deportations, and firing civil servants to replace them with Trump loyalists.

Memos to federal Chief Human Capital Officers, HR Directors and Heads of Agencies are available publicly on the CHCO website. The memo author metadata was spotted by someone on Reddit’s r/fednews community, in response to a federal worker’s post. 

The hackers behind the massive breach of AT&T data last year hunted through the data for phone numbers and records associated with top officials and their families, including members of the Trump family such as Melania and Ivanka Trump; Kamala Harris; and Marco Rubio’s wife, people familiar with the matter told 404 Media.

The news further stresses the catastrophic nature of the breach, which impacted “nearly all” of AT&T’s customers’ call and text metadata during a certain timeframe. The breach not only impacted the general U.S. public, but also presented a significant national security risk. People familiar with the incident told 404 Media the hackers also planned to release a lookup tool that would have let anyone search the records for a fee, and said that the number of breached records is larger than previously reported. 404 Media granted multiple sources in this story anonymity because they were not authorized to speak to the press. 

The news of lawmakers’ and top officials’ families being targeted also comes as the FCC, the agency which would potentially fine AT&T for the breach, is now being led by Brendan Carr, who has historically been very friendly to the country’s telecommunications giants. 

“It is clearer than ever that AT&T's lax cybersecurity and Trump's ineffective, corrupt FCC pose a serious threat to U.S. national security,” Senator Ron Wyden told 404 Media in a statement. “Instead of throwing the book at AT&T for failing to secure Americans' sensitive data, FCC Chairman Carr is coddling Trump's corporate donors and raising the white flag to hackers. It's time for the public and the U.S. government to stop relying on the insecure voice and text message services provided by phone companies, which are beyond salvaging, and embrace secure, end-to-end encrypted voice, video and text communications.”

Dusty Deevers, a Baptist preacher turned Republican Senator in Oklahoma, introduced eight legislative measures “aimed at restoring moral sanity” that include making pornography a crime punishable by a year in jail.

As spotted by Mike Stabile, director of public policy at the Free Speech Coalition, Deevers said in a press release that the bills “set a course for pushing back against the moral decay foisted upon Oklahoma by the far-left’s march through our institutions to destroy the moral foundations upon which the United States and Christian Civilization had long rested.”

Deevers seeks the total abolition of porn by imposing criminal penalties of up to 10 years in prison for production, distribution, or possession of porn and 10-to-30-year criminal penalties for “organized pornography trafficking.” The bill states: 

“No person shall knowingly photograph, act in, pose for, model for, print, sell, offer for sale, give away, exhibit, publish, offer to publish, or otherwise distribute, display, or exhibit any book, magazine, story, pamphlet, paper, writing, card, advertisement, circular, print, picture, photograph, motion picture film, electronic video game or recording, image, cast, slide, figure, instrument, statue, drawing, presentation, or other article which is obscene material, unlawful pornography, or child sexual abuse material, as defined in Section 1024.1 of this title.”

DeepSeek, a relatively unknown Chinese-developed AI model, is now the most popular app in the US Apple App Store based on hype associated with it releasing an an AI model that outpaces OpenAI’s and other companies’ models on some benchmarks while being trained on older chips at a much lower cost. It has caused Nvidia stock, which has become one of the most valuable companies in history thanks to the AI boom, to tumble and is causing more widespread panic in the U.S. market. Marc Andreessen has called this “AI’s Sputnik moment,” referring to the first Russian satellite which got ahead of and accelerated the US space program. 

People in the AI space and those who follow it closely started freaking out when DeepSeek’s newest model, DeepSeek R1, was released last week, and that freakout has now seemingly captured the entire world, impacting the stock market, causing people to wonder if American companies like OpenAI and Nvidia can really dominate the AI industry, if the AI bubble is finally popping, and if this is a sign of imminent Chinese world domination and censorship. DeepSeek is particularly notable because it is free, modifiable, and less expensive to run, which has experts worried about the viability of OpenAI’s already unprofitable subscription products.  

I’m going to be upfront with you here and say that 404 Media does not provide any financial advice and that if I had definitive answers to any of these questions I’d be playing the stock market instead of blogging, but in a day when the takes are going to come fast and furious my take is this: The AI industry continues to develop very fast, it’s hard to extrapolate how it’s all going to unfold based on single event, even if it’s monumental, and the fact that DeepSeek comes from China, a perceived adversary to the United States/the West is making hawks and xenophobes, and tankies foam at the mouth. 

Let’s take a deep breath and start with the biggest headline, which is that Nvidia stock dropped over 12 percent early this morning, its worst performance since 2020. GPU maker Nvidia became a trillion dollar company because it is largely making the chips that power the generative AI boom. These are not only the chips that people need to generate text, images, audio etc locally on their machines, but the massive training clusters of thousands of chips that these foundational models are trained on. In July, for example, Elon Musk proudly announced that xAI started training “the most powerful AI training cluster in the world,” composed of 100,000 Nvidia H100s. 

For the most part, AI companies in the US have competed on the general idea that more data and more compute creates more advanced and more “intelligent” AI models and tools. One of the general strategies, therefore, has been for companies like OpenAI, Google, and Meta to feed more and more data into their models and to compete to build incredibly expensive and resource intensive data centers. But last year, we started to see some doubts about the existing consensus on AI scaling laws, which up until recently showed that the performance of AI models improved as the size of the model, data, and compute increased, with some people, including Open AI co-founder Ilya Sutskever and Andreessen saying that AI companies are starting to see diminishing returns. Despite these doubts bubbling up, AI companies were still competing for compute, which largely means access to Nvidia’s chips. Musk wants to grow xAI’s cluster to one million GPUs eventually, and the CEO of Broadcom recently said he predicts other companies will attempt to build similarly gigantic clusters. 

This demand for highly specialized and hard to produce hardware has made Nvidia incredibly valuable and critically important to building AI. Because the US government believes that the United States, not China, must be the world leader in AI, it’s also why it has introduced export restrictions that forbid Nvidia from selling its most advanced chips to Chinese companies. This is part of why you see OpenAI, Oracle, and SoftBank proposing to throw $500 billion into projects like Stargate, a massive AI data infrastructure project that they may or may not have the money for. 

The main reason people are excited/scared/throwing up right now is that DeepSeek was developed and released under America’s export restrictions that prevent Chinese companies from getting the latest and most powerful Nvidia chips. As Wired explained, DeepSeek was spun out from High-Flyer, a Chinese hedge fund that originally acquired GPUs to analyze financial data, before it invested its money and resources in developing AI. That a new player in this space was able to build an AI model without access to the latest and greatest Nvidia chips (though people in China have found ways to obtain them despite restriction), using new, more efficient reinforcement learning strategies, has undermined the idea that companies like Nvidia or OpenAI have built a “moat” around their companies that will secure their lead in the AI race forever, and, by extension, has undermined the notion of American AI world supremacy. It also at least raises the possibility that a Chinese company has found a better, more efficient, and cheaper way to train AI models than any American company has discovered thus far.

As others have pointed out, it’s hard to say exactly what DeepSeek actually spent to make its model without trusting it blindly. The true cost may be hidden in ways we don’t understand, and is definitely benefiting by building on top of the very expensive research (primarily from American companies) that came before it. But if AI companies can build competitive models at a fraction of the cost on a comparatively tiny number of lesser GPUs, then much of Nvidia’s value and the billions of dollars AI companies are burning on training suddenly seems excessive and wasteful (even to AI boosters), hence the stock tumbling. 

Does this mean Nvidia, OpenAI, and other AI companies are doomed? Again, this is not financial advice but the market appears to be spasming based on vibes, and definitely before we have a great understanding of DeepSeek’s impact. The most obvious rebuttal from Nvidia bag holders in this situation is that DeepSeek’s newfound efficiencies will only benefit AI incumbents. If these new methods give DeepSeek great results with limited compute, the same methods will give OpenAI and other, more well-resourced AI companies even greater results on their huge training clusters, and it is possible that American companies will adapt to these new methods very quickly. Even if scaling laws really have hit the ceiling and giant training clusters don’t need to be that giant, there’s no reason I can see why other companies can’t be competitive under this new paradigm. We should also probably hope that this is the case since it could lower the environmental impact of AI.

I don’t have a dog in this fight, but the argument I would add here is that this type of leapfrogging seems totally normal, and we have seem variations of it over the last couple of years. People love to prematurely dance on OpenAI’s grave whenever a new and shiny model is released. Meta’s Llama, France’s Mistral, and Anthropic’s Claude have all seemed like they’re getting ahead at one point or another and are favored by different users for different uses, only for another model to be released by OpenAI or another company that leapfrogs the hot new technology and makes them seem old. 

The difference is that DeepSeek is from China and that a lot of people including the US government don’t like the idea of China being dominant in any arena, let alone one as supposedly consequential as AI. This is obvious given the hysteria on social media right now, the markets, and the way people are talking about DeepSeek’s censorship and the possibility that it could be tied to Chinese surveillance or the Chinese government in some way. Steven Heidel, who works at OpenAI, tweeted Sunday “americans sure love giving their data away to the CCP in exchange for free stuff,” which has gone viral and served as the basis for discussion about DeepSeek as possible surveillance software, the “new TikTok,” etc. What’s particularly notable here is that DeepSeek has been released in a way that can be run locally without an internet connection.

On various AI subreddits, where DeepSeek is all people have been talking about for days, some users are now suggesting that the conversation is being manipulated by “propaganda” from a few accounts. People have repeatedly shared screenshots on social media of DeepSeek refusing to engage with questions about Tiananmen Square and other topics subject to censorship in China, with the implication that this is the information ecosystem we’d live under if China was to dominate the AI race. 

Fair enough, I suppose, but as the developers of “uncensored” AI models have been shouting from the rooftops since the beginning: any AI model that the user can’t control entirely is subject to censorship. OpenAI is a prude, and will refuse to engage users on a lot of topics, sometimes for reasons stated in OpenAI’s policy, and sometimes for reasons we’ll never understand because OpenAI is a black box.

“Why should the open-source AI running on my computer, get to decide for itself when it wants to answer my question? This is about ownership and control. If I ask my model a question, I want an answer, I do not want it arguing with me,” Eric Hartford, a developer of uncensored AI models, told me last year. 

If anything, DeepSeek maps a better AI future for those concerned about censorship because it was released as an “open weights” model, meaning people could modify it to talk about Tiananmen Square and whatever else they want. 

We do not know how this will all shake out, but the release of DeepSeek does seem to be a seismic moment for the AI industry. And it will certainly be used, rightly or wrongly, as a political cudgel to highlight the urgency of the competition for AI supremacy between the United States and China.

On this special guest episode of the 404 Media Podcast, I talked to Alexzandra Kekesi, VP of Brand and Community at Pornhub. Kekesi started in her current role in August 2023, after working for Pornhub and its parent company for more than a decade. She joined us from Montreal, where Pornhub is headquartered. We discuss the stigma facing the adult industry, Luigi Mangione porn, the trad wife to feet pics pipeline, and algorithms that shut you down for showing side boob. Kekesi also breaks down Pornhub’s choice to pull out of states in more than a third of the U.S., following regressive age verification laws.

Kekesi started working at Pornhub's parent company more than a decade ago, when it was still called Manwin. The company, now named Aylo, has since gone through a lot of change in that time, including stronger moderation and uploading requirements. Now, the entire adult industry is in a battle against politicians who would prefer to see porn eradicated altogether.

When we spoke right before the new year, we were heading into 2025 staring down a new wave of privacy-invading age verification laws that make it harder to access adult content online. We talked through how Pornhub is responding to–and legally complying with–those laws by going dark in states where they're enacted.

We also discussed the increased interest in "tradwife" and "demure" porn, and what that says about the world today. "What's interesting about the Year in Review or even search activity on the site in general is that it is certainly a mirror of what's going on in society in general," she said. "We're hovering somewhere around the ballpark of like 130 million daily visitors. So when you see those fluctuations in traffic or these spikes in searches, it really is indicative of real trends or real change in society."

Listen to the weekly podcast on Apple Podcasts, Spotify, or YouTube. Become a paid subscriber for access to this episode's bonus content and to power our journalism. If you become a paid subscriber, check your inbox for an email from our podcast host Transistor for a link to the subscribers-only version! You can also add that subscribers feed to your podcast app of choice and never miss an episode that way. The email should also contain the subscribers-only unlisted YouTube link for the extended video version too. It will also be in the show notes in your podcast player.

• Pornhub Sees Surge of Interest in Tradwife Content, ‘Modesty,’ and Mindfulness
• Pornhub Is Now Blocked In Almost All of the U.S. South
• Age Verification Laws Drag Us Back to the Dark Ages of the Internet

Welcome back to the Abstract! What a week. It kicked off with Blue Monday, a date considered the most depressing of the year in the Northern Hemisphere for dubious reasons (in short: it was invented, like most of our reality, by an ad campaign). 

This column will channel the latent crappy vibes with a parade of grotesqueries from the grand world of excrement research. Then, scientists are bringing back the ‘80s with new bioluminescent hues worthy of a Lite-Brite pegboard. Last, if you actually are feeling blue, I recommend Norwegian wood. Not the song. Not the novel. I’m talking about real pine trees in Norway. They see all. They will understand.

Monkey See (Pee), Monkey Do (Pee)

Onishi, Ena et al. “Socially contagious urination in chimpanzees.” Current Biology.

It’s time to put the “pee” in chimpanzee by watching pee come out of chimpanzees. That’s what researchers in Japan did for more than 600 hours to find out if urination is a form of social contagion in chimps. In other words, they observed 20 adult captive chimpanzees (16 males and 4 females) at the Kumamoto Sanctuary of Kyoto University to assess whether they were more likely to pee if they saw other chimps pee.

“The decision to urinate involves a complex combination of both physiological and social considerations,” said researchers led by Ena Onishi of Kyoto University. “However, the social dimensions of urination remain largely unexplored.”

First of all, let’s all congratulate ourselves for performing this complex physiological and social decision multiple times a day. I didn’t even realize we were such pros. 

But back to the study: the team meticulously recorded the number and timing of “urination events” along with the relative distances between “the urinator and potential followers.” The results revealed that urination is, in fact, socially contagious for chimps and that low-dominant individuals were especially likely to pee after watching others pee. Call it: pee-r pressure.

The study gets extra points for including depictions of contagious urination in art history as part of its supplemental information, like those disconcerting fountain statues that pee out water. But the “number one” standout is a 1784 sketch by Thomas Rowlandson entitled “Sympathy, or A Family On A Journey Laying The Dust.” 

Cups runneth over in this contagious urination event that even encompasses dogs and horses. I’m frankly surprised the buggy isn’t also engaged in gushing urination. 

In addition to documenting a unique phenomenon, this artwork is nature’s call to revive the euphemism “laying the dust” for (I assume?) urination. You’re no longer going to the restroom; you are laying the dust. It just goes to show you never know what you’ll learn from a study about contagious chimp urination.

San Francisco’s Best Eats (for Coyotes) 

Caspi, Tal et al. “Impervious surface cover and number of restaurants shape diet variation in an urban carnivore.” Ecosphere.

You’ve seen the pee study, now here’s the number two follow-through. A study out this week reconstructed the diets of coyotes in San Francisco by collecting more than 1,000 scats from 2019 to 2022. Of that initial poopy haul, 707 bonafide coyote dumps were analyzed with metabarcoding and genotyping to reveal what these streetwise canines were eating.

“We collected scats from urban green spaces, including parks, golf courses, and gardens across San Francisco,” said researchers led by Tal Caspi of the University of California, Davis. “We only collected scats that we estimated to be less than 1 week old given their appearance and time since last visit.” 

By analyzing this dookie-base, the team found that coyotes in densely populated neighborhoods were more reliant on human food scraps than coyotes in greener neighborhoods that had access to prey in parks. That finding seems intuitive, given that coyotes are opportunistic omnivores that will eat whatever’s available, but it’s still fascinating how much coyote diets varied, even with packs living just a few blocks away from each other.

“The greatest dietary differences were between Presidio and Coit Tower, even though a coyote can easily traverse the 3-km distance between them,” the team said. “The Presidio is the largest green space in San Francisco (6 km2) and has many native plant communities, sprawling grasslands, and a low percent cover of impervious surfaces. Conversely, Coit Tower is a tourist attraction in the densely populated Telegraph Hill neighborhood and, in part as a result of historical redlining, has less plant cover and lower species richness than formerly greenlined neighborhoods such as the Presidio.”

It's the age-old story of the city coyote and the just-a-bit-less city coyote. But while there were interesting variations in diet, all of these Bay Area coyotes were dining on a daily dim sum of chicken, pork, beef, and fish from human sources. As a cat lover, it pains me to report that domestic cats were commonly detected in the poops, though at low levels. That said, my general feeling is that a predator is skilled enough to catch a cat—animals that I have seen, with my own eyes, defy physics—it kind of deserves to eat it.

Lite-Brites in a Petri Dish 

Hattori, Matsuru et al. “Creating coveted bioluminescence colors for simultaneous multi-color bioimaging.” Science Advances.

Congratulations: You’ve waded through some sewage, and it’s time to wipe those eyeballs out. Fortunately, scientists published a spectacular new rainbow of bioluminescent hues this week. Call it a palette cleanser. 

Just look at these laboratory lite-brites! This study has clearly earned its keep based on aesthetic value alone, but the authors helpfully put some science in there too. Bioluminescence is the biological ability to generate light through chemical reactions, which is why some creatures can glow in the dark. This mesmerizing superpower is also a helpful tool in labs, as certain cells or research targets can be labelled with bioluminescent hues to aid observation.

“Bioluminescence, an optical marker that does not require excitation by light, allows researchers to simultaneously observe multiple targets, each exhibiting a different color,” said researchers led by Mitsuru Hattori of Osaka University. “Notably, the colors of the bioluminescent proteins must sufficiently vary to enable simultaneous detection.” 

The team’s innovation in this study was to debut a method that expanded the color variation, allowing “simple and simultaneous observation of multiple biological targets and phenomena.” To prove their point, they made the Tron mouse pictured above. 

Has science gone too far? Yes. But boy, does it look cool doing it.

Cruel Summer (Scots Pine Version)

Buchwald, Agata et al. “Blue rings in trees and shrubs as indicators of early and late summer cooling events at the northern treeline.” Frontiers in Plant Science.

It’s well-known that trees are nature’s librarians, meticulously keeping records of climate and environmental changes dating back centuries. But over the past decade, scientists have discovered a special type of blue ring in conifers that specifically memorializes cold summers. Low temperatures prevent lignification of the cell walls in the wood, creating the color pattern.

“Blue Rings (BRs) are a relatively newly described anatomical feature in conifers,” said researchers led by Agata Buchwald of Adam Mickiewicz University. “In the current literature, the formation of BRs is associated with cold growing season conditions” in various pine species, though “the potential of BRs in shrubs for paleoclimate studies still has to be explored.”

With that in mind, there was only one thing to do: Hike up Mount Iškoras in Norway and see what the Scots pines and Juniper shrubs had to say. The team took cores from dozens of plants high in the treeline, and discovered blue rings from the year 1902 and, to a lesser degree, in 1877, indicating that summers in those years were colder than average. 

The testimony of the trees not only lines up with historical temperature records, it also coincides with major volcanic events. In the spring of 1902, for instance, Mount Pelée erupted on the Caribbean island of Martinique, killing 30,000 people in one of the worst volcanic disasters on record. The reverberations of this tragedy were etched in blue in the hearts of trees 8,000 miles away on Nordic mountaintops. Reality is so wild and enchanting; it’s a shame it can’t compete with ad campaigns.

Regardless of whether you are as blue as a non-lignified tree ring, thanks for reading. See you next week!

This is Behind the Blog, where we share our behind-the-scenes thoughts about how a few of our top stories of the week came together. This week, we discuss Nazis celebrating Elon Musk’s salute, Zuckerberg as a kook, dictating your own threat model and a good block/mute ethos.

EMANUEL: The first week of Trump’s second term is in the books and we’re off to a terrible start. A flurry of executive orders is filled with symbolic and potentially impotent threats, but is also already causing real harm and fear. Local police and schools are preparing for the possibility of ICE raids coming for children. It feels like a return to Trump's first term time dilation effect and if the first term is a guide to the second we’ll probably see more shocking headlines before the weekend. 

People I know who don’t usually ask me about work reached out this week asking what I thought about Mark Zuckerberg, Elon Musk, Jeff Bezos, and other big tech company CEOs showing up prominently during Trump’s inauguration, if that will impact 404 Media, and if we were scared. I do think there is currently more interest in what we cover but that this surge of interest will fade, as it did during Trump’s first term. I also think that it is probably about to become a more hostile environment for journalists, but I don’t feel like journalists are a particularly vulnerable group under the Trump administration. 

You can see the specific steps that a government agency is taking to comply with the Trump administration’s policies against diversity, equity, and inclusion on the agency’s GitHub, which shows it frantically deleting and editing various documents, employee handbooks, Slack bots, and job listings across everything the agency touches. 

18F is a much-hyped government agency within the General Services Administration that was founded under the Obama Administration after the disastrous rollout of Healthcare.gov. It more or less had the specific goal of attracting Silicon Valley talent to the federal government to help the government innovate and make many of its websites and digital services suck less. It is one of the “cooler” federal agencies, and has open sourced many of its projects on GitHub.

GitHub is a website for open source development that shows changes across different “commits,” or changes to code and documentation. In the first days of the Trump administration, 18F’s commit list is full of change logs detailing the administration’s attempts to destroy the concept of diversity, equity, and inclusion. 

The changes show that in the last 48 hours, 18F has edited text and wholesale deleted both internal and external web pages about, for example “Inclusive behaviors,” “healthy conflict and constructive feedback,” “DEIA resources,” and “Diversity, equity, inclusion, and accessibility.” It deleted a webpage about “psychological safety” (which now 404s) deleted all information about the “DE&I leads” at the agency, as well as language for employees that said "Anyone who has issues or concerns related to inclusion or equity in the 18F engineering chapter should feel empowered to reach out to the DE&I Leads.” It has deleted, in various places, the word “inclusion,” as well as the term “affinity groups.” 

It also deleted an internal Slack Bot called “Inclusion Bot,” which is described as being “integrated into Slack and passively listens for words or phrases that have racist, sexist, ableist, or otherwise exclusionary or discriminatory histories or backgrounds. When it hears those words, it privately lets the writer know and offers some suggested alternatives.” 

It has also notably deleted information intended for improving accessibility for blind and visually impaired employees, which asked employees to use “visual descriptions” when introducing themselves on Zoom meetings.

In a hiring document, the language “Teams should consider factors of equity and complexity of the research when determining compensation for participants on their project” has been changed to “team should consider other factors or complexity of the research.”

The Trump administration has not tried to hide that it is trying to delete web pages and employee information across the government. But seeing the change logs pop up as they’re happening on GitHub shows exactly how these changes are being done and how they’re rolling out.

On day one of his presidency, one of Donald Trump’s first acts in office was to sign an executive order declaring that there are only two sexes: male and female. 

The order is a transphobic, scientifically incorrect screed titled “Defending Women From Gender Ideology Extremism And Restoring Biological Truth To The Federal Government” that mischaracterizes sex and gender and demands that “every agency and all Federal employees acting in an official capacity on behalf of their agency shall use the term ‘sex’ and not ‘gender’ in all applicable Federal policies and documents.” 

The Social Security Administration and other government departments are complying with the order by scrubbing information about changing one’s sex from its website.

Ari Drennen spotted the change to the “change sex identification” site and posted a screenshot on X: 

The site now says “you are not authorized to access this page,” blocking it from public view. It used to show basic information about how to change your sex on record with the Social Security Administration by requesting a new Social Security card, and a link to a questionnaire that helped determine how to go about it. “You don't need to provide medical or legal evidence of your sex designation,” the site said when it was online. “Currently, you can change your sex identification to either male or female, but we are examining ways to provide an unspecified sex identification option in the future.” 

Information about gender identity and access to guides on changing one’s sex have also been scrubbed from the administration’s main LGBTQIA+ site. Here’s what looks like today, compared to how it looked last week.

The Gender Identity link that’s now missing from that site and inaccessible to the public—showing a 404 error and not a CMS login message, unlike the “change sex identification” site—used to provide links to forms one would need to fill out to start the process. 

Form SS-5: Application for A Social Security Card is still available for download on the Internet Archive. A page about how to get a social security card is still online, as is a page for locating a Social Security office. 

Several other government websites about gender identity and discrimination are also offline, including a Department of Labor site about discrimination based on sexual orientation and gender identity and a State Department site about how to select your gender marker on your passport, are also gone or scrubbed of mentions of gender identity.

Aside from being unscientific nonsense and anti-abortion rhetoric, the “Defending Women from Gender Ideology” executive order has triggered all of this essential information to go offline across the internet, adding to the confusion and panic that many queer and trans people—and anyone who actually cares about reproductive rights or freedom of speech—already face going into Trump’s presidency. And it’s not the first time Trump’s administration took down a bunch of government websites to try to suppress scientific information: thousands of pages with climate change information were removed or buried during his first term. 

A pseudonymous coder has created and released an open source “tar pit” to indefinitely trap AI training web crawlers in an infinitely, randomly-generating series of pages to waste their time and computing power. The program, called Nepenthes after the genus of carnivorous pitcher plants which trap and consume their prey, can be deployed by webpage owners to protect their own content from being scraped or can be deployed “offensively” as a honeypot trap to waste AI companies’ resources.

“It's less like flypaper and more an infinite maze holding a minotaur, except the crawler is the minotaur that cannot get out. The typical web crawler doesn't appear to have a lot of logic. It downloads a URL, and if it sees links to other URLs, it downloads those too. Nepenthes generates random links that always point back to itself - the crawler downloads those new links. Nepenthes happily just returns more and more lists of links pointing back to itself,” Aaron B, the creator of Nepenthes, told 404 Media. 

“Of course, these crawlers are massively scaled, and are downloading links from large swathes of the internet at any given time,” they added. “But they are still consuming resources, spinning around doing nothing helpful, unless they find a way to detect that they are stuck in this loop.”

The viral AI-generated bread horse image that Mark Zuckerberg “loved” on Tuesday was originally created as a meme by a Polish news organization to warn about the dangers of AI-generated slop on social media. The image became a viral sensation on the Polish internet but broke containment and began going viral more widely; it was then stolen by a totally unrelated real AI spam farm where it has gone megaviral and was ‘loved’ by the Meta CEO.

Called “chałkoń” or “challah horse,” the image was part of a series of AI-generated images created by a Polish news outlet called Donald.pl, which pilloried the AI spam that has taken over Facebook. “This woman baked a challah horse but no one congratulated her,” a page run by Donald called Polska w duźych dawkach (Poland in Large Doses) wrote on January 7. 

The image was designed as a commentary on AI spam on Facebook, the outlet wrote. But like other AI spam, some people believed it was real, and the image was seen by more than a million people and liked 11,000 times. The English-language, subscriber-funded Noted From Poland originally wrote about this drama if you’d like to learn more. 

Meta CEO Mark Zuckerberg “loved” an AI-generated slop image of a horse made out of bread posted by a spam page on Facebook that also posts AI-generated images of children with amputations and regularly circumvents Facebook’s algorithm to link users offsite to ad-laden AI-generated content farms.

The page, “Faithful,” is verified, operated out of Romania, has 1.1 million followers, and regularly goes mega viral with the exact type of AI slop that I have been writing about over the last year. In that sense, it is the perfect encapsulation of the type of spam page that has become dominant on the platform as Meta continues to lean into AI-generated content and pays people for going viral on the site. 

“I made every detail with love, but it seems no one cares,” reads the caption of the image, which has 2.7 million reactions, 193,000 comments, and 98,000 shares as of the time of this writing. Zuckerberg’s interaction with the page was first noticed by Gazpacho Machine, a man who posts reviews of food he eats while taking showers. 

When Gazpacho Machine posted about this, I was initially skeptical that Zuckerberg's real account had liked the page (as in, it could have been an imposter), and the image had so many likes that Facebook was initially having trouble loading information about which accounts actually liked the page. Gazpacho Machine sent me a screen recording showing that it was indeed Zuckerberg's real "@zuck" account, and I was later able to verify for myself that this is Zuckerberg's real account:

This bread horse is a variation on a classic type of AI slop that made its way into my very first story about the phenomenon of AI spam on the platform in December 2023, when AI spammers were taking already viral images and running them through image-to-image AI tools to create slight variations of the original viral image. 

The origin story of bread horse is “The Bread House man,” a viral Russian image from the 2010s of a man next to a house he had created from various rolls and baguettes. Catherine Hall, a Facebook user who tracked the early spread of AI spam on Facebook, originally found dozens of AI-generated variations of the Bread House Man. 

The “Faithful” page, whose header image says “I Love God. I am proud to say that,” has posted hundreds of AI-generated images over the last few years across a host of genres that are now very familiar to me, and are similar to many pages that are operated by people in the global south trying to make money on Facebook. It has repeatedly posted the same image of an AI generated child who is missing an arm and whose caption says “My mother said I was beautiful, but so far I have not liked anyone” at least three times. It has gotten thousands of likes each time.

The page has also posted various images of AI-generated elderly people who are supposedly older than 100 celebrating their birthday, AI sand sculpture images, AI-generated variations of American Idol and America’s Got Talent, AI wood sculptures, AI photos of aging couples, AI ice sculptures, AI knitting, AI ‘I drew a picture’ images, AI families who are also onion farmers, and AI recycled bottle sculptures. Faithful has also posted a fair bit of Donald Trump content, as well as lots of inspirational screenshots of the Bible, reels that are seemingly automatically created from Reddit posts or written by AI, and inspiration porn. 

Many of the images are monetized in ways that I have previously reported on. For example, many of the images have captions that ask users to read the first comment for more information; a pinned top comment posted by Faithful will then link off of Facebook to a website that is absolutely loaded with ads. I clicked on a recent link posted by both Faithful and a related page called "Faith Space" about an AI generated stepfather who stood up for his AI generated stepdaughter when she was being bullied and was taken to a website called Daily Home Gardening, which served me many ads for products called “Levitox” and “GlucoReNu,” which showed images of worms and had captions that read “The Lump Of Worms Will Come Out Of You In The Morning. Try It.”

I do not know why Zuckerberg “loved” the AI generated bread horse, but it should be noted that it is harder to errantly “love” something on Facebook than it is to errantly like it. Meta did not respond to a request for comment. It is just one small action by one very rich and powerful person. But it is further evidence that strengthens what we already know: Mark Zuckerberg is not bothered by the AI spam that has turned his flagship invention into a cesspool of human sadness and unreality. In fact, he thinks that AI-generated content is the future of “social” media and Meta believes that one day soon we will all be creating AI-generated profiles that will operate semiautonomously on Meta’s platforms. 

While I was writing this, Faithful posted another AI-generated image of a grave with the caption “NEW TOYS APPEARED ON MY SON'S GRAVE EVERY DAY, SO I DECIDED TO FIND OUT WHO WAS DOING IT.” The image links in the comments to Daily Home Gardening, which loaded 64 distinct ads, plus an infinite scroll of ads at the bottom of the page.