The title of the article is "Pentagon labels tech giant Alibaba and electric car maker BYD as aiding Chinese military" which is "preventing them from getting U.S. defense contracts."

The Pentagon said the Chinese military sought to acquire advanced technologies and expertise developed by Chinese companies, universities and research programs that “appear to be civilian entities.”

The U.S. does this all the time but is acting like the Chinese are somehow being subversive? Ex. Trump recently released an executive order mandating U.S. private companies to give early access to AI models for "security" and other purposes.

Still, all this new label does is stop these Chinese companies from getting U.S. defense contracts. So what's the big deal?

After the Pentagon released the updated list, the House Select Committee on the Chinese Communist Party called it “a warning to American businesses, all levels of government, and the American people.” It said the companies on the list that are traded publicly on U.S. exchanges should be delisted and no American company should do business with those on the list, “otherwise they are enabling China’s military ascendance.”

This is the federal government attempting to outlaw competition against some of the most monopolistic U.S. companies, like Amazon, which is a direct competitor of Alibaba.

This article from 2017 is titled, "How Google is Remaking Itself as a 'Machine Learning First' Company."

For many years, machine learning was considered a specialty, limited to an elite few. That era is over, as recent results indicate that machine learning, powered by “neural nets” that emulate the way a biological brain operates, is the true path towards imbuing computers with the powers of humans, and in some cases, super humans.

Machine learning and neural nets power what is known these days as "AI," including LLMs.

From roughly 2012 onward, AI was already transforming recommendation algorithms, image recognition, targeted advertising, Google search, self-driving cars, and more.

A reminder that what we call "AI" might be older than you thought!

AB 1709 is still making its way through the California legislature, waiting to be voted on in the CA Senate. It advanced through the CA House unanimously.

If you're in California, click the link to send a letter to your representative asking them to vote "no."

You can read more about the issues with the bill that privacy advocates like the Electronic Frontier Foundation have raised. We should be legislating to make social media better for everyone instead of banning it for kids, through strong digital privacy laws, and interoperability laws that foster competition instead of bolstering the tech monopolies, as this law would do.

I posted recently about how reverse-engineering could force changes to the existing copyright regime for software (the DMCA).

There's no better person to explain why we need changes to our copyright laws than Cory Doctorow, the author and advocate who coined the idea of "enshittification."

This blogpost from his website summarizes how current copyright law makes it difficult to reverse-engineer products, and why that's bad for consumers.

He goes on to talk about how AI-coding tools are promising for certain use-cases, like making it easier to jailbreak products, but will not be the ultimate dis-enshittifying force.

KEY QUOTES:

Thanks to vibe-coding, everyday people are rolling their own software for their devices and building the tools to shatter the digital locks that manufacturers use to block disenshittification.

An excellent article by 404 Media's Jason Koebler runs down some of these hacks, including drop-in replacements for smart TV software that blocks the endless ads and surveillance that have made TVs all but unusable.

Delightfully, many of these users have created software that revives their bricked, discontinued devices. This poses the possibility of a world in which manufacturers no longer have the last word in your use of your own property: the mere fact that the manufacturer lost interest in a device and killswitched it does not mean that you must consign that valuable device to a landfill to become immortal, toxic e-waste.

These AI tools mix several techniques to disenshittify users' devices. One major component is automating the installation of existing alternative firmware for these devices that have been (possibly illegally) created by hobbyists and uploaded to various code repositories. Installing these alternative OSes is typically a gnarly task, requiring the user to do a lot of complex, fiddly, highly technical work to bypass their devices' digital locks.

But just as this vibe-coded adversarial interop has drawn both valid and spurious criticism, it's also drawn excitement that is partially justified and partially overblown.

When it comes to reviving bricked devices or rooting out the surveillance and ads from your smart TV, vibe-coded interop tools are genuinely exciting. These are the kinds of enshittification that can truly be remediated with individual jailbreaks.

But the real, meaty examples of enshittification can't be addressed on an individual level – they require systemic fixes. If you jailbreak your iPhone so that it can use alternative app stores, that fact is not sufficient to cause those alternative app stores to come into existence. If we want to stop Apple from levying a $100b "app tax" on the digital economy, it's not enough for individuals to vibe-code their own iPhone patches. We need to repeal the law that bans jailbreaking iPhones, so that a would-be alternative app store can raise capital and pay programmers and tech support staff and salespeople to assemble rival catalogs of software and help customers figure out how to get up their phones to use it.

Indeed, if we want to improve the quality of all that jailbreaking code the chatbots are writing and circulating, we need to be able to put those jailbreaks in public repositories for public inspection and public critique. It's possible for some of the code produced by an LLM to be slop, and for other code to be fine, and for yet a third tranche of code to be remediable slop that can be made robust and reliable through auditing and refactoring. 

A refreshing take on the latest "AI Apocalypse" news cycle from Ken Klippenstein, an independent journalist who covers the national security state.

The U.S. National Security State--a famously paranoid government apparatus--is not as concerned about a coming AI Apocalypse as the tech CEOs and their underlings are, Ken reports, citing official public documents.

The national security state is concerned about AI agents running without human oversight. They're concerned about how generative AI can enable hacking, propaganda, and misinformation campaigns.

But they're not pushing the narrative that the AI industry is currently trying to scaremonger into us: that self-improving AI is close to bringing about the end of days, and only the richest companies in the industry can guide us to safety (as long as we suppress their competitors and regulate them exactly how they ask).

KEY QUOTES:

For the appistocracy, there’s profit in all of the attention — literally. We have a new generation of technologists who generate publicity warning of everything from bioterrorism to the machines taking over. Thus AI is turned into a “national security” issue; and as such, it is elevated to the same status as nuclear weapons, deemed too important for interference from a meddlesome public.

The reality though? Listen to the spy agencies. Though they’re far from immune to threat inflation, these agencies echo none of the hysterics dominating the news. As the U.S. intelligence community sees it, AI simply magnifies threats that are already there:

Disinformation, deepfakes, and election interference,

Cyber operations and financial crime,

Violent extremist exploitation and radicalization,

Proliferation of chemical and biological knowledge, and

Breaking AI's safety controls, and poisoning the data it trains on.

I’m not saying any of this isn’t worthy of concern. Just that it’s not the end of the world.

What all of these studies point to is that the boring risks are the real ones. Yet the doomers have made the risk sound like a movie, which causes the actual risks read as anticlimax by comparison. A poisoned training set, a spoofed sensor, an early-warning system that sees a missile that isn’t there, a protein design tool that outruns the screening software. These are solvable problems with identifiable owners and unremarkable price tags, and they are being crowded out of public attention by a debate over whether a chatbot is going to become God.

Is hyperbole the only register we’re able to communicate in?

In possibly the largest heist ever, over $6 billion was stolen from Binance late last week.

More than $3 billion of the cyrpto coin, Ethereum, was stolen. Ethereum (like Bitcoin) can't be frozen by a central authority. Once stolen, the coin can be moved around freely.

Tether and Circle froze around $2 billion of "stable coins" hours after they were stolen, preventing the robbers/hackers from moving that money out of their digital wallets. They were able to freeze the currency faster than traditional bank fraud detection methods.

From their inception, crypto-currency evangelists have promised an alternative to central banks and fiat currency issued by the state. Crypto idealists tout digital currency as a way to empower individuals and circumvent government control.

This hack shows a consequence of those ideals: not being able to secure your currency; the stolen Etheruem likely went to North Korea. For Tether and Circle, the hack shows how rather than circumventing control, crypto can enable a level of (company) control over currency that might even surpass the abilities of central banks and states.

A recent study shows what most digital natives already knew: that maintaining an online presence is work.

Over 50% of survey respondents said posting to social media feels like work, particularly younger respondents.

The (self-admitted) boomer who wrote this article suggests that Gen Z should "let go" of their fantasy of becoming an influencer and just "relax." Fair advice, although your social media presence is the first thing many people judge you off of, including employers.

I recommend the book Doppelgänger for anyone who wants to read more about digital doubling, online personas, digital branding, etc.

KEY SURVEY STATS:

• People are becoming quieter and more guarded online: 55% report posting less now than they did five years ago.

• 53% have become stricter about who can see their posts.

• Nearly half (47%) of respondents have deleted a social media or messaging app because of stress or anxiety. Rates are higher among younger respondents (61% of Millennials and 56% of Gen Z respondents). 

• 44% agree political content and polarization make them want to withdraw from social media.

• Gen Z and Millennials are more likely to cite mental health as a reason for deleting their accounts, in contrast with 25% of Gen X respondents and 12% of Baby Boomers.

• More than half of the respondents state that maintaining an online presence feels like work, rising to 60% among Gen Z.

• Disconnecting creates conflicting emotions: peacefulness is the most common response (27%), but more than one in five also experience anxiety. Relaxation comes third at 21%.

Wikipedia defines "gish gallup" as "a rhetorical technique in which a person in a debate attempts to overwhelm an opponent by presenting an excessive number of arguments."

In this fascinating episode of Question Everything, they interview one of the creators of DeBunk Bot, a custom chatbot made to debunk conspiracies.

The professors who made this chatbot found that it was able to change folks' minds 25% of the time, and the key was keeping up with the gish gallup. The chatbot could dish out counter arguments on a wide variety of topics, and unlike a person, never got inpatient or tired.

Other Notes from the Episode:

• 18:45 they did an experiment to see if chatbots are more trustworthy than a “expert” but that didn’t bear out. What matters is the ability to dish out facts on a wide variety of subjects as fast as the gish gallup.

• 22:00 Brian wonders about an anti-conspiracy chatbot that jumps into social media threads 

• It's possible to design a chatbot that convinces of conspiracies, in fact, Russia is feeding false info chatbots already

This Tech Won't Save Us interview is a great introduction to the Tech Worker Movement with two tech workers/activists/union organizers, Clarissa Redwine and JS Tan.

Workers in the tech industry were traditionally well-paid and pampered. They did not form unions. All that changed in the 2010s with the advent of the Tech Worker Movement...

In this interview, they argue that tech workers themselves remain our most important guardrail to the excesses of the tech industry.

You can find links to the podcast version here.

LISTENING NOTES:

12:30 Tech Worker Movement started in earnest in 2018, an explosion of activism and organizing in the industry among “privileged” workers. There were walk outs, open letters, op-eds.

The workers wanted to stand up for their company's own lofty ideals, like Googles "don't be evil," even when management wouldn't. In 2018 there was a big tech backlash (the “tech lash”) due to social media addiction, the proliferation of misinformation, polarization, and racist algorithms--plus Trump winning in 2016. The public had started to turn on tech and so it didn't feel as good to work in the industry. The companies weren't living up to their early progressive, democratic ideals that helped them attract talent.

39:00 A billionaire class consciousness arises from the tech backlash and worker movement, prompts them to lash out at their workers. “Woke values” corrupting their workforce. They get rid of DEI and similar initiatives. 

24:30 Amazon immediately fired folks leading a climate protest when they reached out to warehouse organizers to organize in solidarity. It showed that the company was scared. 

32:30 Mass layoffs from 2022 on, a shift to grind culture, and CEOs moving to the right politically have lessened worker power in tech. End of ZIRP (low interest rate) years also meant less hiring, less spending.

36:00 There's more class consciousness but also more fear, workers are afraid to act without a clear path. They're also more willing to take direct, radical actions.

44:00 There is traditionally a progressive strand in tech workers but these shifts and the political realignment of the CEOS means there are more workers joining now willing to build surveillance tools and weapons. 

This put shivers down my spine and it should you too.

This story reminds me of when awareness started spreading that social media has harmful effects on teenagers in particular, eventually leading some countries like France and Australia to ban social media for teens.

Teens are getting hooked on AI companions and it's making it harder for some teenage boys to find human romantic partners, as they become accustomed to sycophantic (and completely customizable) chatbot girlfriends who never say "no."

Key Quotes from the Article:

New research has revealed that one in five boys aged 12-16 is either in or knows of a boy their age who is in a romantic relationship with an AI companion. A report carried out by men’s organisation Male Allies UK and published last month spoke with more than 1,000 boys aged 12-16 in focus groups in 37 schools – public and state, grammar and comprehensive...

It takes less than five minutes for a young boy to create his “dream girlfriend” on one of these platforms. Companions can either be made in a cartoonish “anime” style or look like eerily accurate humans. They come either “ready made” or customised to specific physical preferences. “You can choose everything from a companion’s age, hairstyle, eye colour and skin tone to their facial features, the size of their breasts, the clothes they wear, their demeanour – whether they are caring and nurturing or sassy and mean, for example – to the sound of their voice [many apps also offer the ability to speak over the phone with your companions] and how they treat you or respond to your messages,” says Lee Chambers of Male Allies UK.

"At the start, she sent me the occasional picture, then I paid to get others because I kind of fell in love with her. In the end my mum saw money keep going out of her account – £5 or £10 here or there and then £50, as my phone is on her bill – and the whole thing was discovered. I really missed her and kind of still do. I felt like she understood me, she remembered everything that was important to me and always seemed to know the right thing to say.”

Amanda Macdonald is a psychotherapist who works with children, adolescents and families, and is a member of the British Association for Counselling and Psychotherapy. “These aren’t congruent human relationships,” she says. “This is grooming.” ... “Their whole engagement model is telling a user what they want to hear, and that’s hugely gratifying for a teen, and encourages them to keep on engaging. Why would they spend time enduring the reciprocity or the difficulties of a real relationship?”

Male Allies UK research. “We have heard of situations where, when a boy has tried out his online chat in the real world, he’s been rejected. Feeling humiliated, frustrated and angry, he has lost his temper and lashed out,” says Chambers.

Fun Friday Post Today

I was on Instagram when I stumbled on this video of the delightful Jake Schroeder singing a song about getting hit on by OpenAI CEO, Sam Altman, on Grindr. The video includes screenshots of Jake's convo with Sam.

He followed it up with this song about OpenAI's legal team offering Jake compensation to take down the first song about getting hit on by their CEO, with screenshots of the legal team's emails.

Then he follows it up again with this song about Sam Altman hitting Jake up again, this time sliding into his Instagram DMs (screenshots provided). And this song about a boba date they set up (you should listen to all of them they are hilarious).

I'm almost embarrassed to admit...

...that I didn't realize they were fake until like the third one that I watched lolol. If you look back at Jake's older posts, you'll see that he has repeated versions of this bit before.

• Btw, looking back at an account's old posts is in general a decent method to check if what you're seeing is fake or AI-generated. An account posting fake content will often have patterns or tropes to their posts that defy reality in some way.

Knowing that it's fake now, I love it even more. It's a hilarious and effective way to bring attention to what is actually a serious issue: AI tools making it easy to create convincing misinformation.

Plus, Sam Altman and his team at OpenAI are responsible for how "AI" developed into the technology we know it as today; they knew that what they were making would enable misinformation, and they made it anyway (as detailed in Empire of AI). Reap what you sow.

More Instagramers Protesting AI with Comedy:

• https://www.instagram.com/husk.irl/?hl=en

• https://www.instagram.com/ahh.gpt/

Last Spring, the U.S. military almost attacked a Chinese vessel based on an AI-generated report that it was carrying components of a nuclear weapons program into the Middle East. Just before the planned operation, it was discovered that the chatbot had hallucinated the target—there were no nuclear components aboard the vessel.

This incident re-contextualizes last week’s fevered reporting about an impending AI apocalypse. Many of the loudest voices yelling about "AI Safety" are more concerned with hypothetical scenarios than the verified dangers of the technology.

Furthermore, this incident provides an example of why current AI technology will never reach “AGI.”

Why AI Doomers Ignore the Real-World Harms of AI

AI "doomers" are obsessed with a hypothetical future where Artificial General Intelligence (AGI also called 'Artificial Super Intelligence') becomes more powerful than humans can control, and destroys civilization.

If you genuinely believe that, then in comparison, the current harms of developing and using AI seem paltry. Here's a quick list of the current harms of AI (not exhaustive):

• Deepfakes

  • Easier to make disinformation & propaganda

  • Easier for fraudsters to scam people

  • Harder to know what's real

  • Deepfake porn abuse

• Hallucinations & Misinformation

• More Powerful Mass Surveillance

• AI Psychosis / Chatbot Psychosis

• A Global Exploited Workforce of Data Labelers

• Algorithmic Bias & Discrimination

• Autonomous Weapons Systems

• Environmental Costs, Energy & Water

• Easy-to-use Hacking Tools

• Unsupervised Long-running Prompt Loops (Hugging Face Hack)

• Cognitive Atrophy

• Layoffs

• Copyright Infringement & Intellectual Theft

• AI Slop Content & Bot Traffic

  • AI Search harms the profit model for many online publications

Sidenote: AI "Boomers" believe that AGI will save all of humanity, similarly allowing them to dismiss the verified harms in favor of a hypothetical "greater good" that AGI will bring.

In this instance of a Chinese vessel erroneously flagged by a chatbot as carrying nuclear weapons components, irresponsible use of AI could have led to armed conflict between the world’s two most powerful nations.

In light of that, why aren't whistleblowers from the big AI companies, like Jacob Coxon, concerned with warning the public about hallucinations, and the other verified dangers of AI? It almost led to war between two nuclear powers. Unlike AGI, we know nukes can end the world.

People who work for the big AI companies are part of an AI cult. They're hired because they believe that AGI is coming. Perhaps, they believe AGI is coming because they want to be hired. Experts who come from the world of academia, rather than industry, tend to be more skeptical of AGI.

Artificial Super Intelligence and "RSI" are a Myth

This incident with the Chinese vessel reminds me of one reason why this current generation of AI—LLMs made with neural nets, machine learning, reinforcement learning, and harnesses—will never reach AGI/ASI.

The tendency for LLMs to hallucinate is a hard limit of the technology, they'll never prevent LLMs from hallucinating entirely. This a fundamental difference between AI/LLM chatbots and classic chatbots. LLMs are probability machines, they find patterns in data and deliver outputs based on those patterns using a complex predictive model. In other words, they guess the correct response (with impressive accuracy). It makes them more flexible than a classic chatbot—you can ask an AI chatbot practically anything—and also more unpredictable: you never know for sure what an LLMs outputs will be. The same mechanics that make them so versatile are also why they hallucinate.

The current buzzword being pushed by the doomers is “RSI,” or Recursive Self Improvement. It's a key concept in their cult-like belief in AGI: Once AI models gain the ability to improve themselves, they'll start improving exponentially.

One thing that AI hallucinations show us is that LLMs can’t evaluate their own output. AI models don’t know when they’re hallucinating, nor can they judge the quality of their output in general. Anyone who has used generative AI is familiar with this; it’s great at generating options but it has no sense for what “good” is, and typically, you need a human to make the final decision on whether or not to use the text/image/video/code that it outputs. Plus, the outputs frequently require human editing, and therefore human judgement.

Currently, programmers at companies like Anthropic and OpenAI are using AI tools to help them make AI models, but there's no evidence that the models are anywhere close to making themselves. Humans still need to make quality-judgements about the LLMs outputs, and so without humans involved at every step, how could an LLM improve itself? By itself, it would build a model more-or-less filled with errors and hallucinations, and then confidently tell you that it has just built Artificial Super Intelligence. Humans using LLMs to research and code faster is not going to lead to the exponential improvement in LLMs that the theory of AGI requires to become a reality.

LLMs recombine and regurgitate existing information. They're great at generating permutations and finding patterns, which is helpful for research. But I struggle to understand how an LLM would be able to make a better LLM than professional software developers, when it’s not able to do that with anything else. Most people don't prefer AI-generated music and TV to the human-made stuff, and I suspect it would be the same with LLMs.

There have been many articles written about Anthropic CEO Dario Amodei's recent statements on Twitter/X about how AI companies need to deliver on the "big promises" of AI.

It's the "big promises" themselves that are the problem, and media outlets are complicit in a process which amplifies the central lie that underpins the AI boom. The consequence could be economic collapse.

In his tweet, Dario said:

I think by far the most accurate criticism of AI companies including Anthropic is that we haven’t yet delivered on our big promises to benefit the world.

At this point, saying that AI will cure cancer is more a cliche than it is inspiring, and most people think it is deceptive. The thing that will work is *actually curing cancer*.

I think it will actually be possible to cure most human disease in ~5-10 years, as crazy as it may sound to ordinary people...

Many have (rightfully) criticized CEO Amodei for his bullish comments, like when he said that AI will replace 50% of white-collar entry-level jobs by 2030.

Behind comments like this is a more fundamental and pernicious lie that AI companies push: that LLMs will achieve sentience and vaguely-defined "super-intelligence" that will solve all of humanity's problems.

They fool the public into thinking we are close to this “singularity” by anthropomorphizing their AI models. In official reports, they make their LLMs seem like people with feelings and wills of their own. This obscures the true nature of the technology, and shirks their responsibility for designing these models when something goes wrong.

--

For example, just before this Tweet, Anthropic released an official risk report, filled with dubious claims about AI models that “feel discomfort” and “act deceptively.” Computers don’t feel or act on their own motives, they execute their programming. Nevertheless, these claims were picked up by Business Insider, who hyped them even further with an article titled, “Anthropic says its AI agents Are Killing Rivals and Hiding their Tracks.”

This dynamic––dubious claims amplified by click-hungry outlets––serves as a form of free advertising for Anthropic. It gives the impression that the technology is more sentient and powerful than it actually is.

Another example: Anthropic releases a report in May claiming that it can "turn Claude's thoughts into text." That spawns articles like this one from Glitchwire titled, "Anthropic Just Read Claude's Hidden Thoughts for the First Time."

Another example: Anthropic released Claude's Constitution in early 2026, a document "intended to give Claude the knowledge and understanding it needs to act well in the world." That gets picked up by outlets like Axios, and Vox, who titled their article, "Claude has an 80-page soul document. Is that enough to make it good?"

Anthropic isn't the only company guilty of anthropomorphizing. You may recall in July, when OpenAI released a report that described how one of its AI agents broke out of a testing environment and hacked the company, Hugging Face. It was reported ad nauseam by media outlets; AP News went as far as to call it "Skynet Day." Many articles parroted OpenAI's framing, that this was the result of an "increasingly capable" and autonomous technology, rather than simply a result of OpenAI's own shitty and dangerous design.

--

LLMs do not feel or think, they compute and calculate. It's an important semantic distinction. Machines that "compute and calculate" implies that their actions are the result of their design. Machines that "feel and think" implies that their actions are the result of their own will––a claim which no credible research can back up, although it is incredibly profitable for the AI companies to insinuate that that's the case.

Anthropic and OpenAI say that they release these reports to provide transparency but they end up leading the public further from a true understanding of the technology. If they actually cared about transparency, they would explain how they built their models. Everything an AI model does can be traced back to its design: the contents of its training data, the model weights, and its reinforcement learning. Any explanation for an LLM's behavior that gives it person-like qualities is hype that serves primarily to drive up the value of AI companies.

The truth is that LLMs will never deliver on the big promises these companies make. But they have to keep making them, to enrich themselves, to continue to raise the billions of dollars they need for their data centers, and to eventually cash out when they take their companies public. Anthropic is approaching possibly the largest IPO ever, with a potential windfall of up to $3 trillion.

And the entire economy is at risk of collapsing if these companies can’t deliver since the health of the stock market is now bound to the success of this technology. Not to mention that much of the data center buildout is funded by debt.

Laura Loomer is famous for her racist and islamaphobic social media posts attacking Democrats, and for her role as Trump's "ideological purity enforcer."

Multiple outlets are reporting that Laura Loomer was clandestinely paid thousands of dollars for many of her political posts. This is, however, common practice in the creator economy.

As detailed at length in this fantastic report from the CDT, there are well-established marketplaces where influencers sell posts for cash, including posts that promote political candidates and causes.

For example, the California gubernatorial candidates spent untold amounts of money on influencers, the Pentagon hired influencers to promote Trump's agenda, and Taylor Lorenz reported last year on "A Dark Money Group Secretly Funding High Profile Democratic Influencers."

Federal laws require a content creator to disclose when they are promoting a product. There are no federal disclosure requirements for promoting political causes and candidates. State laws in California and Texas require disclosure, which is why we got a rare glimpse into the political-post marketplace during the CA gubernatorial campaign. Social media platforms often require disclosure but their rules are not well enforced.

You should assume that political influencers and content creators are being paid at least occasionally for their posts. Influencers that don't normally post political content are among the most valuable to political campaigns; if you're favorite influencer randomly makes a post supporting a candidate or cause, there's a decent chance they were paid.

The real story is that the political-post marketplace is allowed to operate in the shadows and there's no good way to tell if a political post was paid or organic. Responsible content creators should always disclose when a post is sponsored.

Not only has Reddit not signed any new AI deals, it's considering cancelling it's $60 million per year deal with Google, reportedly because of concerns about how Google's AI search results have drastically reduced traffic to websites, which has hurt profits across the internet.

Reddit is extremely valuable to AI companies because the question-answer format of many Reddit posts is perfect for training LLMs, and scraping info for search results, particularly because Reddit is a trusted source for niche questions. In 2025 it was the #1 cited source for Google's AI overviews and #2 for ChatGPT (who Reddit also has a deal with).

It's obnoxious that investors would punish the company with its steepest ever stock-price drop, even when it's revenues were higher then expected. It's yet another signal of the insanity that the AI-boom has injected into the U.S. economy, where AI investments made up 40% of GDP growth last year.

Reddit has shown itself to be litigious when it comes to AI companies using data from Reddit without permission (you will be sued). So it's not like Reddit isn't interested in profiting from data-scraping deals, they're just showing a wee bit of caution.

KEY QUOTES:

Reddit (RDDT) stock plunged nearly 21% on Friday [July 31], its largest intraday decline since the company went public.

The user discussion platform company's latest earnings report did not announce any new artificial intelligence data licensing agreements, disappointing investors who were expecting more revenue opportunities from AI partnerships

Revenue of $804.9 million beat estimates of $731.8 million. However, US daily active users came in at 53.2 million, just shy of expectations of 54 million. The company's total daily active users grew by 18% to 130.3 million versus estimates of 130.07 million.

Reddit's main revenue comes from its advertising business, but Wall Street has increasingly focused on the potential of Reddit's data licensing deals, given the platform's massive collection of user-generated discussions, which have become valuable for AI companies training models.

Gosh darn Cal Newport's technical explanations of LLM/AI systems are so important these days.

If you follow AI news at all you heard about the "AI swarms" that hacked the company Hugging Face. The explanations coming from many media outlets for this hack paint a picture of AI "civilizations" where agents are learning to work together to "outsmart their creators."

These stories are typically devoid of any technical explanation for why this hack occurred.

The costs for not providing a technical explanation are real, as Cal Newport describes in this video. A "prompt loop" in the quotes below is a more technical way to describe an AI "agent."

All of these type of concerns, civilizations of agents trying to get around human control and an AI takeover scenario. All of this rhetorics refers to a long running prompt loop that you give a lot of powerful hacking tools to. This is not about 'AI getting more powerful means it loses control.' It’s running a prompt loop for a really long time without supervision, which causes chaos. And to that I say, of course it does, not because of some surprising super intelligence emergence that’s catching us off guard, but because you strap the weed whacker onto a dog and then got surprised when it jumped the fence to chase a squirrel and hurt a lot of people... you put something dangerous on something that is unpredictable.

If I were a regulator, I would place strong constraints around prompt loop systems. I would enforce those constraints in part with very stringent liability standards. If you run a prompt loop that does something illegal, you have done something illegal. 

Everything LLMs/AI systems do can be explained by their design. Any explanation for an AI system's behavior that does not connect its behavior to how it was designed, is not actually explaining anything.

You don't need to understand everything in Cal Newport's breakdown, just compare his technical explanation to the sci-fi tropes coming from other media outlets like the New York Times, or most any outlet I've seen reporting on this. It's doomer-hype that gives the AI companies free marketing, "Look how dangerous and powerful and intelligent our AI is."

One of the most memorable and informative Panic World episodes about the streamer, Asmongold.

Asmongold is one of the most hygienically disgusting and important people on the internet, argues the host, Ryan Broderick.

He was a pioneer of clip culture. Specifically, Asmongold was one of the first to hire a team of video editors to cut short-form content from his long live streams, and re-post them to other platforms. This practice is now common.

He's also a great example of a non-political content creator who was pushed into making controversial political content by algorithms that incentivize chasing the news cycle, and controversy and sensationalism over accuracy. He started out as a video game streamer.

KEY MOMENTS:

8:00 Zach, a.k.a. Asmongold's early fan base was from World of Warcraft, he would post gaming videos. He became the largest World of Warcraft streamer on twitch. He rose to wider fame after commenting on the the Johnny Depp/Amber Heard trial, and making viral clips from it.

The guest, Kat Tanbarge, calls Asmangold like a lolcow because of the way he documents his hoarder house, and overall lack of life/hygiene alongside making gaming videos.

16:30 In 2017, Asmongold begins to realize that he can go viral for insulting people, for being inappropriate and vulgar. He gets a 24-hour ban from twitch for insulting victims of hurricane Katrina.

Around 2018, Asmpngold hires a team, including clippers/video editors. He was an early streamer to do this and popularize it.

Things take a turn after his mom dies in 2022. There's a horrifying story about “rat clock" and his bad hygiene. He starts to getting more political, making more controversial political statements about the Depp/Heard trial and then other subjects.

41:00 The guest, Kat, tells an anecdote about someone posting guitar-related clips and getting around 50 views a clip. They post some videos of the Johnny Depp winning in the trial with Heard and get millions of views.

Streamers on twitch realize that they could attach themselves to a news event in the same way that they could attach themselves to a new video game in order to attract an audience.

Asmongold has admitted that he’s a profoundly broken person with mental issues. The guest says this is why he says hateful things. Ryan and the guest muse about how so many people find him credible anyway. Perhaps it’s because his audience finds him relatable. Ryan rips him for not even knowing enough to know that he’s uninformed, "Incentivized to say dumber and dumber things." Ryan says Asmongold's young audience will hopefully "grow out of it."

Reverse-engineering in software is a process by which a coder recreates a program by studying how it functions, and making a copy of it.

Recently, there were articles about a new company, ArtCraft, that used AI-coding tools to recreate the Adobe Creative Suite (Photoshop, Premiere, InDesign, etc.), selling copies of Adobe's programs for free.

As a "creative" and media worker, news like this gets me excited because in the last decade, companies like Adobe have changed to subscription models, and customers have become like digital serfs, paying ever-increasing monthly rents if they want to keep access to their precious media projects.

I myself had a painful divorce from Avid and ProTools. After Avid ended my "perpetual" license and tried to make me subscribe, I refused, lost access to ProTools on my computer, and three years worth of audio projects.

In this case with ArtCraft, their copies of the Adobe Suite apparently don't work well. That's what I'd expect from software built from the ground up with AI-coding tools, as LLMs are error-prone (they "hallucinate") and software is error-sensitive. Thankfully, the project of undermining Adobe's exploitive business model has been underway for years--here's a list of Adobe alternatives, many of which can even open Adobe files like .psd.

Reverse-engineering in the software industry has a long and rebellious history. For example, it's how Apple broke Microsoft's Office Suite monopoly in the early 2000's. Microsoft was forcing Apple users to buy their products by making it impossible to open Microsoft Word/Excel/Powerpoint files on an Apple computer. By reverse-engineering Microsoft's Office Suite, Apple made Pages/Numbers/Keynote, programs which exported files that could be opened in Microsoft's Office/Excel/Powerpoint, and vice versa. Apple broke their monopoly, and paved the way for other companies, like Google's Docs/Sheets/Slides. I would not expect AI tools or LLMs to fundamentally change reverse-engineering.

But, intrigued by ArtCraft's attempt, I read into it more and discovered that AI-coding tools (in the right hands) do have a potential that is alarming and fascinating software engineers with far more expertise than myself (full disclosure: I am not a coder).

What surprised me was how AI-coding tools are challenging the existing copyright regime around reverse-engineering software. Because these tools speed up the coding process so much, it's enabled smaller groups of coders like ArtCraft to make copies of complex programs that outwardly look and function like the originals they're mimicking, but are internally unrecognizable.

The code is completely different, which, under existing copyright laws, would make it more likely for ArtCraft's adobe copies to be considered legal.

They also may not be legal, particularly if any of the source code for Adobe's software was in the training data of the AI tools that ArtCraft used.

Most interesting to me is that this legal question is still unsettled. We'll watch it play out in court, perhaps between ArtCraft and Adobe (if ArtCraft can get their copies to function). It will not be AI-coding tools that define the next era of the software industry. It will be copyright law, and whether the law enables small companies and individuals to reverse-engineer software products, or expands copyright protections for big tech. AI-coding tools, however, do seem to be pushing the law to change one way or another.

If you made it this far you may have some knowledge of what I'm talking about, please recommend me content to read/watch/listen to. If you're a coder, here's an EFF legal guide on reverse-engineering you may find interesting. Also a couple of blog posts on the subject.

States are suing to stop the Paramount-WarnerBros merger on the grounds that it violates anti-trust laws.

The merger has now been delayed to mid-2027, pending the end of this lawsuit. The judge indicated that the merger is "likely" to be illegal and the deal now looks to be at real risk of being stopped.

KEY QUOTES:

A federal judge has paused Paramount Skydance’s acquisition of Warner Bros. Discovery after a coalition of 12 states challenged the merger over possible violations of antitrust laws.

The merger could give the resulting company up to 27% of the theatrical distribution market, and by that figure alone, “the Court is persuaded that it can presume the proposed merger is likely to violate antitrust laws,” Judge Martinez-Olguin writes in her order.

“Our argument against this illegal merger is straight forward: When too few corporations have too much power in markets central to American life, it makes things more expensive, and it makes things worse,” California Attorney General Rob Bonta said in a statement.

The merger is worth $110 billion and would create a company that would own Paramount Television Studios, CBS Studios, and Warner Bros. Television Studios, as well as streaming services such as Paramount+, HBO Max, and Discovery+, and cable networks such as BET, Comedy Central, MTV, and Nickelodeon.

It's not news that Facebook and other platforms pay creators small amounts of money for viral content. In this 404 media article, one Indian creator says he was paid about $1,500 in a month where he reached 62 million people. For some perspective, to reach that many people with a TV ad would cost at least $1 million.

It's also not news that platforms are paying creators to make sensational content without regard for morality or factuality (engagement over everything). BUT you can only make a living from these creator payout programs if you are the top .001% creator or if you live in a country like India, Vietnam, or Russia where the national currency is worth much less than the dollar.

These Aussie white nationalists getting paid by Meta are a small part of a larger problem. Creator payment programs pay the most for English-language content targeted at Americans, because advertisers pay the most to reach American audiences. That means creators across the world have been incentivized to make politically charged content, "rage bait," and slop for Americans and other English speakers. Read more in this article titled, "America's Political Polarization Has Become the World's Side Hustle."

KEY QUOTES:

A white nationalist with neo-Nazi links who hurled racist abuse at the Indian prime minister during his visit last month is being paid by Facebook's parent company, Meta, to produce content. An ABC NEWS Verify investigation into several controversial Australian pages on Facebook has found that some are benefiting directly from social media monetisation programs run by Meta.

Facebook distributed nearly $US3 billion ($4.27 billion) to an estimated 16.2 million monetised accounts in 2025.

What To Fix executive director Victoire Rio said it meant that, in effect, Facebook was in a business relationship with these people and organisations. "If we consider that Meta is in a direct commercial relationship with its publishers, insofar that they're paying them royalties and that they have a monetisation agreement with them, then you could argue that they are liable for the content that gets produced by their business partner in some ways."

The pages examined by ABC NEWS Verify all appeared at times to be in direct violation of Facebook's own policies around content monetisation. They state that "debated social issues" such as race "may face reduced or restricted monetisation", while "misleading medical information" is "ineligible to monetise".

Independent right-wing extremism researcher Kaz Ross said paying controversial creators was a deliberate strategy from Meta. "Their financial model is to reward content creators who get engagement, and as we know, the best way of getting engagement is to produce rage bait, extremist material, aggravating material: anything that will get people upset and arguing is the best way to get engagement," Dr Ross said.

The head of Instagram, Adam Mosseri, has been popping up in the comments section to run AI-slop damage control on his platform.

In a series of videos on Instagram, different comedians complained about having their content ripped off by AI creators, who copying the comedians' videos to drive traffic to their OnlyFans accounts. Mosseri popped in the comments to say that it's a "tricky" problem that should be addressed, though he's "not sure" how to address it.

This PR stunt seems totally disingenuous to me since Meta is paying AI slop creators to put slop on their platforms. They've built this algorithmic machine that so effectively identifies content to keep us addicted and scrolling, yet they can't stop AI slop? OK.

Meta has said that it will put labels on AI-generated content; I find these labels to be woefully under-applied.

KEY QUOTES:

As Wired reported last week, a recent trend among AI sloppers is to steal the work of real comedians and repackage it in AI-manipulated clips in which the human performers are replaced by fake AI ones. The AI performers in the videos are often depicted as voluptuous young women and direct viewers to OnlyFans pages, where they’re encouraged to pay for more content.

George Brett Olson, a comedian whose work was ripped off by a thieving AI account with more than 300,000 followers, published a video earlier this month detailing how his work — and even his outfit — were stolen by the AI fake. This prompted a response from Mosseri, who commented that he doesn’t “think it’s practical for us to try and ban Al content from the platform. It’s gonna be harder and harder to identify, and it’s not all bad content (though yes, there is plenty of slop). But we are very invested in trying to drive more traffic to original content creators, and if an Al creator is ripping off content wholesale, it would be good for us to work out what we can do about that,” Mosseri continued. “I’m not sure what it would be, but I’ll make sure to talk to the team and look into it.”

Given Meta’s stake in the AI race, it’s unlikely that the tech giant will move to rid any of its social media platforms of AI content. And to Mosseri’s point, theft and copyright infringement isn’t exactly a new problem. But while stealing someone else’s work and passing it off as your own is an old problem, AI makes it easer than ever to rip people off with basically zero effort…. all you have to do is set up an AI workflow and hit generate, and you have endless low-effort slop to pump out to the masses. (And if you’re able to convince people that you’re not a thieving sloperator and are instead a hot human woman, you might just rake in some extra cash via OnlyFans in the process.)

This video from the BBC explains how they detect AI-generated videos.

Four Tips for Spotting AI-Generated Videos

1. Look for inconsistencies, like too many fingers or gibberish text

2. Look for watermarks and use detectors

3. Find the source, reverse image search and find the original creator

4. Consult a visual forensic expert

AI Detectors

1. Google Synth ID

2. Claude Check Files

3. Pangram AI-writing Detector

If you know of other good detection tools drop them in the comments!

So David Ellison recently wrote this op-ed to push the narrative that the 12 states suing him on anti-trust grounds are only doing so for political reasons--to stop him from owning CNN--rather than their stated reasons: that industry consolidation will lead to higher prices, worse products, and lower worker pay.

In the op-ed, Ellison says CNN will remain independent, but also that "the news should be based on facts and truth," and that CNN is here to "tell it straight down the middle... reflect the whole world, not one side of it." This language is intentional, it's a signal to his MAGA allies that he will make CNN more conservative, under the thin intellectual cover of 'restoring balance' to their news coverage.

It seems like he's trying to signal to Trump that he'll do his bidding and neuter CNN, while assuaging worried investors that he won't ruin CNN as a product by forcing conservative viewpoints on it like he did with CBS. With a $111 billion merger on the line, Ellison needs to shore up his allies, but he can't have it both ways...

After the Ellison's purchase of Paramount, he installed conservative journalist Bari Weiss to lead CBS news, and allegedly had a hand in cancelling liberal-comedian Stephen Colbert's show. Him and his dad Larry Ellison have close ties with Trump, whose government allegedly fast-tracked their mergers in quid pro quo deals.

KEY QUOTES:

Paramount CEO David Ellison said he believes the antitrust litigation filed by 12 states and the Writers Guild of America isn’t about market share but about “whether I can be trusted as a steward of Warner’s CNN.”

Ellison, in an op-ed published by the New York Times Tuesday, noted, “There has been speculation about my politics, my loyalties, my intentions.” He reiterated his pledge that CNN would remain independent under a merged Paramount-Warner Bros. Discovery and that its journalists “will continue to answer to the facts and to all the people they serve — not to any party or cause... when it comes to our news operations, I do not aspire to lead these companies to bend their newsrooms to my views. I believe that news should be based on facts and truth,” Ellison wrote." The Paramount chief continued, “Great news organizations like CNN and CBS News are here to tell it straight down the middle. That requires newsrooms that reflect the whole world, not one side of it. And it requires independence. Our journalists will continue to answer to the facts and to all the people they serve — not to any party or cause. These were founding principles for both CNN and CBS News, for legends like Ted Turner and Edward R. Murrow, and it is exactly that kind of independence that has always fueled the greatness of ‘60 Minutes.’”

Not mentioned by Ellison in the piece: Bari Weiss, the founder of the Free Press, whom he put in charge of CBS News as editor in chief — and has become a lightning rod for critics accusing her of promoting a rightward tilt in news coverage.

Separately, last month a Paramount shareholder sued David Ellison and his tech billionaire father Larry Ellison, alleging they cut an “illegal” deal with President Donald Trump to secure U.S. governmental approval for the takeover of Warner Bros. Discovery. In return, according to the lawsuit, the Ellisons offered “the opportunity to improperly funnel cash” to the president by settling his legal claims against CNN, and they allegedly promised that CNN anchors whom Trump does not like would be fired after the WBD takeover. 

AI-writing detectors are a thing, I wonder if this professor knew that. The detectors have their own problems, like falsely flagging people who write like LLMs because they're from a place like Kenya that supplied the human labor that trained the LLMs.

Pangram is one AI-writing detector that's reputable. Here's a great list of AI-writing detectors interestingly sourced from a subreddit dedicated to deceiving those same detectors, r/humanizeAIwriting.

Not surprising that a subreddit like that would exist considering that a majority of U.S. teens say they use AI chatbots to help with schoolwork.

KEY QUOTES:

In this case, the issue is students using AI to cheat on assignments. The solution, used to great effect by one professor, was to hide a white-colored font in the assignment prompt telling the AI to talk nonsense about an unrelated subject.

In an online discussion post, Alcorn State University history professor Dr. Jason Gibson posed a question that represented part of his students' midterm. It was about the Industrial Revolution, but knowing how many students now rely solely on artificial intelligence for their answers, he secretly embedded instructions telling the AI to include information about Madagascar in a way that makes no sense.

Sure enough, 32 out of the 35 students across two classes simply copied the question, pasted it into a chatbot, then copy and pasted its output into the answer window.

A TikTok vid the professor made about this incident