When a Department of Homeland Security official sent out an alert to stop Samuel Tunick, a Stop Cop City activist, at an airport in January 2025, they said the reason was because he was suspected of “terrorist activities,” according to new filed court records which include a screenshot of the alert and photos of Tunick’s interrogation.

Tunick ultimately provided Customs and Border Protection (CBP) officials with a code that, when entered, wiped his security- and privacy-focused GrapheneOS phone. Tunick is now being criminally charged for that alleged act, in one of the most high profile technology civil rights cases in recent memory.

The court records also showed that CBP officials lied to Tunick during his interrogation. Instead of saying he was being targeted for suspected terrorism — although this search happened just at the start of the second Trump administration, it has dramatically broadened what organizations or people may be considered such — they said they needed his phone to look for “kiddie porn.”

Over the weekend, it became fashionable to use AI to replace the operating systems on smart TVs with vibe coded or AI reverse-engineered ones to make them less bloated. People have taken proprietary internet-of-things devices that were bricked and abandoned by their creators and used AI to hack them and install new software on them, giving functionality the original developers took away.  

In the last few days I have seen people hack smart picture frames to become AI-powered smart calendars, baby monitors to remove all ads, and bricked Lululemon mirrors to bring them back to life with new software. And dozens and dozens of TVs to install AI-written software that removes bloatware, ads, and simplifies the user interface. 

What we’re seeing is vibe coding, but instead of making something from scratch, people are using AI to take an existing piece of software and replicate its features, its functionality, or cloning it wholesale. In some cases, people are using AI to take a proprietary piece of hardware and install some version of open source software on it. All of this is some mix of “decompiling,” “reverse-engineering,” “hacking,” vibe coding, AI slop, and stealing. It is the plagiarism machine being used for plagiarism, but also it is random people using AI to take control back over devices whose proprietary software was used to arbitrarily lock away basic functionality, to add advertisements, surveillance, and bloat to devices that probably shouldn’t have them, or whose functionality was bricked altogether. 

“All I am hearing from software engineers is that software-as-a-service is dying as a business model,” Mike Nolan, who studies the politics of open source software, told 404 Media about the recent spate of AI-driven clones. “It’s becoming so easy to recreate the functionality that you want [with AI.]”

“The barrier for recreating this stuff is lower, so a lot of people are doing it for fun,” he added. “But there’s a lot of work associated with maintaining software so there may be a lot of instances where the software may not be reliable enough to use—I don’t know how many companies are going to be adopting these clones.”

In one example, a user named Gathin wrote in a post on X: “Vibe coded my parents’ TV this afternoon! It was showing a sponsored ad before you could even get to Netflix. Gave Claude Code the model number, it found the TV on wifi, removed 25 Xiaomi packages and wrote a new launcher.” That post has allegedly been viewed more than 6 million times. “Looks like an Apple TV now lol.”

It has been possible to do a lot of this for a long time using open source, human-coded repositories. There are many communities of people who have spent hundreds of hours bringing bricked internet-of-things hardware from the dead or finding vulnerabilities that allow one to modify or repair devices that have proprietary software on them. 

But over the weekend, a project called “Reverse Engineer Anything” became one of the most viral GitHub repositories in recent memory, with more than 342,000 stars as of the time I’m writing this. The project uses AI to deconstruct features in other pieces of software, and allows the user to replicate them: “See a feature in an app that you want in your own product? Ask your agent to investigate it with REA. It can inspect the app without its source code, explain how the feature works, show the evidence, and build a version for your project.”

What this promises is a way to easily clone and modify other people’s products; it is the same general principle that has in recent weeks allowed for the viral, AI-driven clones of Adobe’s Creative Cloud software, Microsoft Office and the “decompilation” of hundreds of different video games. This tactic is being used not just on software you run on your computer, but also to reverse-engineer and modify the embedded software on physical devices. 

A person who claims to make guitar pedals, for example, claimed on Hacker News that he used AI to clone the effects algorithms of three of his competitors using AI: “In the past 72 hours I have ONE-SHOT decompiled 3 of my main competitors products. Like, I could in theory just stick them in a box and resell them […] Basically, anyone with a Claude subscription can now rip off [sic] any best-in-class algorithm from any competitor.”

It is not necessarily the case that everyone will be writing and running their own software or that Adobe or Microsoft are screwed. But I’ve seen enough to say that the “decompiling” or “reverse-engineer anything” craze is going to have an actual real-world impact on software companies, coding communities, and open-source projects. 

One of the criticisms I heard last week after writing about video game “decompiling” communities being overrun with AI-powered decompilations, ports, and clones is that a lot of the AI decompilations are not actually “decompiling” anything — that the resulting source code usually isn’t the same as the original, and that the resulting software has weird bugs, is of low quality, or doesn’t fully work. 

But that’s one of the main problems here: AI-powered, cloned software often has bugs that the person using the AI doesn’t understand or know how to fix, and people are doing it anyway, using the software anyway, and unleashing it on the world and on these communities at a speed with which it cannot be vetted or moderated. Part of the reason that this will have an impact is specifically because, at least in the short term, a lot of this software will suck: The ability to cheaply and quickly clone software and modify features is going to have some sort of sloppifying impact on society whether you vibecode software or not. Unlike some of Silicon Valley’s wildest sickos, I do not expect most people to vibe code their own software or to hack their baby monitors, but like AI slop on social media or on menus, flyers, and billboards, you do not need to actually use AI or think that it’s good in order to be affected by this. 

Inevitably, poorly coded, barely-functional, insecure software is going to be installed on critical hardware, which will lead to devices and networks being hacked; reverse-engineering communities and open source projects are going to be overrun with people Kool-Aid manning in with “their” AI projects and code. 

All of this has been enabled by the agentification of AI, improving models, and the removal of guardrails. It is now possible to tell an AI to go do something, and to generally have it do that thing. This is leading to more people making more things and more AI agents acting in annoying and perhaps antisocial ways on the internet—we are likely to see an onslaught of semi-functional software and hardware slop, which will have knock-on effects for us all.

We are going to see hastily-created hardware startups using poorly cloned software that barely works, we are going to go to restaurants and be asked to order through a touch screen using cloned software with bizarre bugs. We are going to see people installing and using random code that they know nothing about on internet-connected physical hardware; and we are likely to see hackers try to infiltrate this process to include malware on some of that code. We are going to see smaller software and hardware companies killed by competitors who used AI to steal their products and undercut them. But what people use this for is likely to be a bit of a mixed bag; we are also likely going to see decompiled software used to remove manufacturer guardrails on products that never should have existed in the first place.

Scientists have discovered that an exotic particle that existed at the birth of the universe might solve one of the biggest mysteries in cosmology and help explain reality as we know it, according to a new study in Physical Review Letters.

Our modern universe is dominated by matter, but it also contains fleeting amounts of antimatter, which is like a bizarro version of matter made of particles with the same mass, but opposite electrical charges. For instance, matter contains positively-charged protons and negatively-charged electrons, whereas antimatter is made up of the inverse: negatively-charged antiprotons and positively-charged positrons. 

As a result of these opposite features, matter and antimatter particles annihilate each other when they meet. This mutual destruction is the source of a major cosmic mystery, given that equal amounts of matter and antimatter are predicted to have formed in the split-seconds following the Big Bang. Yet somehow, matter emerged as the far more dominant substance in the cosmos, an asymmetry that has yet to be explained.

Now, a pair of scientists have pinpointed an overlooked particle, known as the heaviest decoupled right-handed neutrino (RHN), as a solution to this problem—plus, they predict that their hypothesis could be experimentally tested in the future. 

“No one talks about this decoupled right-handed neutrino,” Rishav Roshan, a research fellow at the University of Southampton and a co-author of the study, told 404 Media. “We realized that this decoupled right-handed neutrino could alter the expansion of the universe and affect the matter-antimatter asymmetry of the universe.”

“This thing was present in the literature for a very long time, and for some reason people did not pay that much attention to this particular point,” he added.

This particle is the heaviest of a trio of hypothetical decoupled RHNs that existed briefly after the Big Bang, and are key to the “minimal seesaw model” that explains the origin of modern neutrinos, which are extremely lightweight particles that are abundant in the universe today.  

“The heaviest decoupled right-handed neutrino is a particle that exists in the minimal seesaw model but interacts very weakly with regular matter, making it nearly invisible to current experiments,” Roshan told 404 Media. For this reason, he noted that this particle has been “overlooked because many researchers focus on the lighter neutrinos” and view “the heavy states as irrelevant due to their minimal influence on observable physics.”

Roshan and co-author Sudipta Show, a postdoctoral researcher at the Indian Institute of Technology Kanpur, had a hunch that this exotic heavy particle could have played a role in the domination of matter in the early universe. In their new study, they included the particles in models of the primordial universe, which suggested that the particle could have slowly decayed, creating an imbalance in particles known as “leptons”—a class that includes different “flavors” such as electrons, muons, and neutrinos—that was then amplified into the larger matter-antimatter imbalance. 

“In the early universe, when this heavy neutrino was produced, the temperature of the universe was extremely high, much greater than the mass energy of this neutrino, and it behaved as radiation,” Roshan explained over email. “As the universe began to expand, its temperature slowly decreased.” 

“Once the temperature fell below the mass energy of the heavy neutrino, the particle became non-relativistic and started to behave like matter due to its extremely weak interactions, influencing the dynamics of the universe's expansion and affecting the creation of matter versus antimatter,” he continued.

Scientists have already pinpointed the process of uneven lepton and antilepton formation—known as leptogenesis—as a leading explanation for how matter dominated the universe. Roshan and Show now demonstrate that the heaviest decoupled RHN is key to this hypothesis and should be included in future models.

Moreover, the team noted that a new generation of observatories could potentially detect this process hidden in gravitational waves, which are ripples in spacetime. Current detectors, such as the Laser Interferometer Gravitational-Wave Observatory (LIGO) can pick up gravitational waves made by cataclysmic events, such as mergers between black holes. But a spate of advanced detectors, due to come online in the 2030s and 2040s, are designed to tune into “primordial” waves from the split-seconds after the Big Bang, which may contain spectral signs of the heaviest decoupled RHN. 

“Future detectors like SKA, LISA, DECIGO, and ET could potentially observe these signatures. These instruments are being developed to detect gravitational waves, with some expected to come online within the next few years. If successful, they could pick up signals related to the heavy neutrino’s effects on the early universe,” Roshan wrote over email.

“Solving the matter-antimatter asymmetry question could transform our understanding of cosmic evolution and the fundamental laws of physics,” he added. “It may challenge or refine the Standard Model and influence theories of the universe's formation and structure. A new understanding of this asymmetry could also lead to insights about dark matter and the early moments of the universe, potentially reshaping our view of cosmic history.”