The US Department of Health and Human Services is developing a generative artificial intelligence tool to find patterns across data reported to a national vaccine monitoring database and to generate hypotheses on the negative effects of vaccines, according to an inventory released last week of all use cases the agency had for AI in 2025.

The tool has not yet been deployed, according to the HHS document, and an AI inventory report from the previous year shows that it has been in development since late 2023. But experts worry that the predictions it generates could be used by Health and Human Services secretary Robert F. Kennedy Jr. to further his anti-vaccine agenda.

A long-standing vaccine critic, Kenedy has upended the childhood vaccination schedule in his year in office, removing several shots from a list of recommended immunizations for all children, including those for Covid-19, influenza, hepatitis A and B, meningococcal disease, rotavirus, and respiratory syncytial virus, or RSV.

Kennedy has also called for overhauling the current safety monitoring system for vaccine injury data collection, known as Vaccine Adverse Event Reporting System, or VAERS, claiming that it suppresses information about the true rate of vaccine side effects. He has also proposed changes to the federal Vaccine Injury Compensation Program that could make it easier for people to sue for adverse events that haven’t been proven to be associated with vaccines.

Jointly managed by the Centers for Disease Control and Prevention and the Food and Drug Administration, VAERS was established in 1990 as a way to detect potential safety issues with vaccines after their approval. Anyone, including health care providers and members of the public, can submit an adverse reaction report to the database. Because these claims are not verified, VAERS data alone can’t be used to determine if a vaccine caused an adverse event.

“VAERS, at best, was always a hypothesis-generating mechanism,” says Paul Offit, a pediatrician and director of the Vaccine Education Center at Children’s Hospital of Philadelphia who was previously a member of the CDC’s Advisory Council on Immunization Practices. “It’s a noisy system. Anybody can report, and there’s no control group.”

Offit says the system only shows adverse events that happened at some point following immunization; it doesn’t prove that a vaccine caused those reactions. CDC’s own website says that a report to VAERS does not mean that a vaccine caused an adverse event. Despite this, anti-vaccine activists have misused VAERS data over the years to argue that vaccines are not safe.

Leslie Lenert, previously the founding director of the CDC’s National Center for Public Health Informatics, says government scientists have been using traditional natural language processing AI models to look for patterns in VAERS data for several years, so it’s not surprising that HHS would move toward the adoption of more advanced large language models.

One major limitation of VAERS is that it doesn’t include data on how many people received a vaccine, which can make events logged in the database seem more common than they actually are. For that reason, Lenert says it’s important to pair information from VAERS with other data sources to determine the true risk of an event.

LLMs are also famously good at producing convincing hallucinations, underscoring the need for humans to follow up on any hypotheses generated by an LLM.

“VAERS is supposed to be very exploratory. Some people in the FDA are now treating it as more than exploratory,” says Lenert, who is currently the director of the Center for Biomedical Informatics and Health Artificial Intelligence at Rutgers University.

SEGA’s Dreamcast may have met an early demise, but the console’s legacy lives on among fans. Now, a small crew has ported Super Mario 64 to the console. That’s right, programmer jnmartin84 finished what mrneo240 started in 2020, resulting in a game based on the original and burned onto a CD-R for crisper visuals as well as richer sound.

This was accomplished using a process known as decompilation, in which a team of volunteers spent years going over the original Nintendo 64 code line by line. This clean source code enables the existence of ports like this one. jnmartin84 improved the Dreamcast version by fixing the weird audio glitch, graphics issues, and adding the option to save to the VMU.

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To begin, get the source from GitHub and extract the textures and models from their own US version of Super Mario 64, as no resources are included in the source code to ensure that everything is totally legal. Next, a Dreamcast toolchain compiles everything into a binary that can be burned to a disk and loaded into the Dreamcast console, and voilà! Mario appears in his full 480p magnificence. Of course, emulators are supported as well, but let’s be honest: playing on real hardware is a whole different experience.

The transition from the N64’s muddy 240p to a gorgeous and sharp 480p is an improvement in itself. Not only that, but the textures, while identical to the original, appear slightly crisper due to the increased output. Not only does Mario’s world feel larger than ever before, but the framerate remains at a steady 30fps, just as it did in 1996.

One of the hardest tasks was sound, as the N64 has a dedicated chip for mixing sound, while the Dreamcast lacks one and has to use the SH4 CPU for everything. Early tests were putting a lot of stress on the CPU, so John Brooks, a veteran coder, came in and helped out with some vector math and floating-point code to get everything running smoothly.

The controls on this version snap neatly into place, as the Dreamcast’s stick steers Mario around with precision, while the button for jumps, the B button for braking, and the D-pad for switching cameras all function as expected. Because the VMU can save your game in the middle of a run, you can continue where you left off without having to restart from the beginning, no uncomfortable remapping required.

Rackspace’s new pricing for its email hosting services is “devastating,” according to a partner that has been using Rackspace as its email provider since 1999.

In recent weeks, Rackspace updated its email hosting pricing. Its standard plan is now $10 per mailbox per month. Businesses can also pay for the Rackspace Email Plus add-on for an extra $2/mailbox/month (for “file storage, mobile sync, Office-compatible apps, and messaging”), and the Archiving add-on for an extra $6/mailbox/month (for unlimited storage).

As recently as November 2025, Rackspace charged $3/mailbox/month for its Standard plan, and an extra $1/mailbox/month for the Email Plus add-on, and an additional $3/mailbox/month for the Archival add-on, according to the Internet Archive’s Wayback Machine.

Rackspace’s reseller partners have been especially vocal about the impacts of the new pricing.

In a blog post on Thursday, web hosting service provider and Rackspace reseller Laughing Squid said Rackspace is “increasing our email pricing by an astronomical 706 percent, with only a month-and-a half’s notice.”

Laughing Squid founder Scott Beale told Ars Technica that he received the “devastating” news via email on Wednesday. The last time Rackspace increased Laughing Squid’s email prices was by 55 percent in 2019, he said.

“The price increase has a major impact on the ability to make money due to the fact that email is now our largest expense, and we were only given a month-and-a-half notice,” Beale told Ars.

Online, there are reports of Rackspace partners being quoted email pricing increases of 110 percent to nearly 500 percent. The reports say that the new, higher-per-mailbox quotes don’t include volume pricing discounts. Beale noted that Laughing Squid’s quote doesn’t include discounts that the company previously received.

If you’ve ever used a 3D printer, you may recall the wondrous feeling when you first printed something you could have never sculpted or built yourself. Download a model file, load some plastic filament, push a button, and almost like magic, a three-dimensional object appears. But the result isn’t polished and ready for mass production, and creating a novel shape requires more skills than just pushing a button. Interestingly, today’s AI coding agents feel much the same way.

Since November, I have used Claude Code and Claude Opus 4.5 through a personal Claude Max account to extensively experiment with AI-assisted software development (I have also used OpenAI’s Codex in a similar way, though not as frequently). Fifty projects later, I’ll be frank: I have not had this much fun with a computer since I learned BASIC on my Apple II Plus when I was 9 years old. This opinion comes not as an endorsement but as personal experience: I voluntarily undertook this project, and I paid out of pocket for both OpenAI and Anthropic’s premium AI plans.

Throughout my life, I have dabbled in programming as a utilitarian coder, writing small tools or scripts when needed. In my web development career, I wrote some small tools from scratch, but I primarily modified other people’s code for my needs. Since 1990, I’ve programmed in BASIC, C, Visual Basic, PHP, ASP, Perl, Python, Ruby, MUSHcode, and some others. I am not an expert in any of these languages—I learned just enough to get the job done. I have developed my own hobby games over the years using BASIC, Torque Game Engine, and Godot, so I have some idea of what makes a good architecture for a modular program that can be expanded over time.

In December, I used Claude Code to create a multiplayer online clone of Katamari Damacy called “Christmas Roll-Up.”

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Claude Code, Codex, and Google’s Gemini CLI, can seemingly perform software miracles on a small scale. They can spit out flashy prototypes of simple applications, user interfaces, and even games, but only as long as they borrow patterns from their training data. Much like a 3D printer, doing production-level work takes far more effort. Creating durable production code, managing a complex project, or crafting something truly novel still requires experience, patience, and skill beyond what today’s AI agents can provide on their own.

The world generates tons of electronic waste every year, leaving a profound impact on the environment. For tech enthusiasts, unused or broken electronics might be piling up in your garage or storage, but there’s hope. 

Transforming old electronic projects into green solutions is good for the planet and offers an opportunity for you to get creative and make the most out of the technology you love. Here are some clever ways to reduce your e-waste and put those old devices to use. 

1. Donate Working Electronics 

These professionals also understand more niche topics like the packaging requirements for battery disposal and its importance. Many of these centers ensure proper disposal of harmful components, such as lithium-ion batteries or toxic chemicals. 

Some tech companies, like Apple or Best Buy, run recycling programs that collect used electronics at no charge to make the process easier. Always check that the battery compartment is empty before recycling and look for separate battery drop-off locations nearby. 

4. Sell Usable Parts 

Old tech often holds more value than you think, especially when you break it down into parts. Sell components like graphics cards, memory sticks, and processors individually via online marketplaces to other people who are working on repairs or upgrades. 

Selling these usable pieces allows other tech enthusiasts to extend the lifespan of their devices with affordable options. Before listing anything for sale, test component functionality and provide detailed descriptions for potential buyers. 

5. Upcycle Into Art 

Turn outdated circuit boards, wires, and other electronic components into unique art pieces that add character to your home or office. Circuit boards, with their intricate designs, look great as the foundation for creative sculptures. You might also fashion jewelry, such as earrings or pendants, from compact mechanical parts. 

Upcycling is an excellent way to showcase your love for technology while turning old electronics into greener solutions. Online platforms like Pinterest or Etsy have a wealth of inspiration for creating tech-inspired art.

6. Refurbish and Reuse 

Refurbishing old devices gives them a second life and keeps them out of landfills. Whether it’s a forgotten smartphone or a dusty tablet, replacing damaged screens, upgrading components, or repairing ports makes them useful again. Many online repair guides and tools are available to help you get started. You can also consult local repair services if you’re not confident handling electronics yourself. 

7. Compost Bio-Plastics 

Certain biodegradable electronics are now available on the market,  and if you’ve been a part of such innovative projects, consider composting them correctly. Bio-plastics offer an environmentally-friendly alternative to traditional, toxic materials used in items like device casings. 

After removing and recycling the electronic components, check the manufacturer’s guidance on how to safely compost the biodegradable parts. Composting allows these materials to break down naturally, which reduces their impact on the environment and enriches the soil. 

8. Convert to Smart Devices 

When you’re not ready to let go of your older tech, repurpose and upgrade it to serve modern smart functions. For example, an old Android phone can become a home security camera using apps specialized for that purpose. Similarly, you could repurpose a tablet as a digital cookbook or an extra monitor for your workstation. 

Many tutorials are available online to guide you through these transformations, which require minimal hassle and tools. This approach creates value without needing to purchase an entirely new device. 

9. Create Educational Displays 

Old electronic devices teach others about technology, especially young learners who are curious about how things work. Carefully dismantling items like computers or gaming consoles provides the components to create displays showcasing their inner workings. 

Label each part to explain its role in the device to provide a hands-on learning experience. Through education, older electronics continue to serve a vital purpose. Set up these displays in classrooms, community libraries, or science fairs to spark curiosity and inspire creativity in future tech enthusiasts. 

10. Transform Into Furniture 

For larger pieces of electronics, such as CRT TVs or bulky desktop computers, consider turning them into one-of-a-kind furniture. Hollow out an old TV and convert it into a fish tank or shelf. Similarly, a CPU tower might make a great base for a table or storage unit. 

These projects require minimal additional materials but do call for a touch of creativity and craftsmanship. By upcycling into tech furniture, you keep larger items from becoming waste while adding quirky, functional pieces to your space. 

Technology evolves quickly, and it’s easy for electronic projects to fall by the wayside. By thinking creatively and sustainably, old devices find new life, reduce waste, and even educate or inspire other learners and enthusiasts. Begin giving a second life to your retired projects today and make a meaningful difference. 

To work around those rules, the Humanizer skill tells Claude to replace inflated language with plain facts and offers this example transformation:

Before: “The Statistical Institute of Catalonia was officially established in 1989, marking a pivotal moment in the evolution of regional statistics in Spain.”

After: “The Statistical Institute of Catalonia was established in 1989 to collect and publish regional statistics.”

Claude will read that and do its best as a pattern-matching machine to create an output that matches the context of the conversation or task at hand.

An example of why AI writing detection fails

Even with such a confident set of rules crafted by Wikipedia editors, we’ve previously written about why AI writing detectors don’t work reliably: There is nothing inherently unique about human writing that reliably differentiates it from LLM writing.

One reason is that even though most AI language models tend toward certain types of language, they can also be prompted to avoid them, as with the Humanizer skill. (Although sometimes it’s very difficult, as OpenAI found in its yearslong struggle against the em dash.)

Also, humans can write in chatbot-like ways. For example, this article likely contains some “AI-written traits” that trigger AI detectors even though it was written by a professional writer—especially if we use even a single em dash—because most LLMs picked up writing techniques from examples of professional writing scraped from the web.

Along those lines, the Wikipedia guide has a caveat worth noting: While the list points out some obvious tells of, say, unaltered ChatGPT usage, it’s still composed of observations, not ironclad rules. A 2025 preprint cited on the page found that heavy users of large language models correctly spot AI-generated articles about 90 percent of the time. That sounds great until you realize that 10 percent are false positives, which is enough to potentially throw out some quality writing in pursuit of detecting AI slop.

Taking a step back, that probably means AI detection work might need to go deeper than flagging particular phrasing and delve (see what I did there?) more into the substantive factual content of the work itself.

from the kashing-in dept

Kash Patel, FBI Director, is not very good at his job. There are plenty of examples to demonstrate that notion, from him apparently completely misunderstanding the purpose and protections of the 2nd Amendment and Minnesota gun laws (whatever your thoughts on gun rights might generally be), to his gathering of barely trained castoffs to serve in the FBI, to the absolute wild waste of resources he spent last summer trying to root out independent thought within his agency. None of this is justice. None of it is good policing. All of it is the result of putting a podcast host shitposter in charge of America’s federal police force. Ol’ Crazy-Eyes just might not be the right person for the role.

And if you’re going to be the leader of a federal police force, one of the skills you probably want to have is the capability of shutting the fuck up. Kash can’t do this. Rather than simply not answering, it appears Patel may have lied to Congress about the Epstein files (remember those?). In the immediate aftermath of the Charlie Kirk assassination, Patel blabbed about suspects all over social media and elsewhere, leading to wasted time and attention on completely innocent parties.

And, now, in the wake of an operation by the FBI that would appear to violate Mexican law, Patel decided to gush about the whole thing on the internet. What other option did he have, I wonder?

Ryan Wedding is a former Olympian who, by all accounts, turned himself into a violent cocaine drug kingpin working with a Mexican cartel. He was charged in Canada in 2015 for cocaine trafficking and in America in 2025 for that and for murder. Recently, Wedding found himself in American custody to face those charges. How that happened wasn’t initially disclosed in coverage of the arrest. But then Kash Patel got out his phone and decided to gush about the whole thing on internet.

On Friday, however, FBI Director Kash Patel announced the joint operation publicly on X. “Our FBI HRT teams executed with precision, discipline, and total professionalism alongside our Mexican partners to bring Ryan James Wedding back to face justice,” he wrote, sending shock waves through Mexico.

Except there’s a problem with that statement. A pretty big one, actually. Mexican law is very clear that foreign LEOs are not to operate on Mexican soil. That would make the FBI’s participation as outlined by Patel illegal. And that might create problems for his eventual prosecution and a really big headache for the Mexican government.

Mexican President Claudia Sheinbaum scrambled to perform damage control, as foreign intervention in Mexico is politically toxic. She said that there was no U.S. involvement in the operation and that U.S. agents in Mexico are limited by law.

“I’m not going to get into a debate with the FBI director, nor do I want there to be a conflict,” Sheinbaum said at a press conference Tuesday. “What they, the U.S. authorities, told the Mexican authorities is that it was a voluntary surrender.” She pointed to a picture Wedding posted to his Instagram account at the U.S. Embassy in Mexico announcing that he was turning himself in.

Wedding’s lawyer disputes that account, because of course he did. Whether Wedding actually surrendered or not is unknown to me, of course, but I’ve been well-trained the past 13 months not to believe a single thing my government says, so who the fuck knows. Wedding’s lawyer claims he was handcuffed and transported to California and that this runs contrary to any claim any of this was voluntary. And because of all of this, the Mexican government now has both an internal problem and has to deal with an unreliable shitposting partner in the American government.

Patel’s rash decision to post about Wedding’s arrest online doesn’t help the situation right now. It opens Sheinbaum up to political attacks in Mexico and makes the U.S.-Mexico relationship even shakier. Under Trump, though, American law enforcement is playing fast and loose with not just the law but diplomatic relations.

I’m not exactly advocating that the American government carryout these illegal extraditions violating our allies’ own laws and then hiding it through silence. That would be crazy.

Instead, the point is that this administration’s goons, such as Kash Patel, are so shitty that they can’t even carry out such nefarious actions in silence because they can’t shut the fuck up about them.

Filed Under: claudia sheinbaum, doj, international incident, kash patel, mexico, ryan wedding, social media