Derek Lam has more than 31,000 followers on TikTok and nearly 40,000 on X as of this writing. He is shirtless a lot, he dances a lot, and he is shirtless dancing a lot, which may explain how he got so many fans. His comments are filled with compliments (“beautiful”) in different languages (“hombre bello y sensual”) and superlatives (“this might be the finest man on the internet”) accompanied by different emoji (red hearts, crying laughing, lips). Their responses make it seem like Derek Lam is the first and only beautiful man they’ve ever seen, which may explain why he is also selling “exclusive,” seemingly adult, content.
Tech
Is that thirst trap influencer AI? Inside the world of very convincing deepfakes
He is also, possibly unbeknownst to his many admirers, AI-generated.
To be fair, there were some signs that this man was not real: Despite the multiple videos, Derek never speaks. His videos are also rather brief, just seconds long. A real hot person probably would have parlayed a following of this size into brand deals or “get ready with me” videos. And the selfies on his X account show a completely different man just three years ago.
Still, the followers of Derek I talked to didn’t even notice he was AI because he seemed to blend in so seamlessly with the other hot men on the internet.
Derek isn’t the only AI thirst trap showing off defined abs for likes and money. He’s one of an increasing number of completely fake, AI-generated figures sinking their fangs into the real models, influencers, and porn stars who populate our feeds, sucking up their beautiful faces and bodies, and using them to profit, without a penny going to the real humans they fed from.
When it comes to the damage AI could wreak on society, an army of Dereks tricking horny people into giving him likes — or, worst case, money and Amazon gift cards — doesn’t exactly sound like the singularity doomsday scenario that we’ve been warned about. It’s clearly unfortunate for the adult entertainers competing with deepfakes and a fraud risk for their fans, but one might believe if they don’t fall into one of these two groups, they’re relatively safe and unaffected.
But there’s something more going on here. History shows that porn and sex drive innovation in the tech industry. The way tech platforms treat sex workers is typically a glimpse into the future, and a warning about how tech platforms will eventually treat all of us. If human desire demands the capability to steal, loot, and turn anyone and everyone into something for sale — possibly into hot Dereks — is anyone safe?
The Dereks of the internet are a bleak look at what’s happening in the real world: nothing belongs to us anymore — not our looks, our beauty, our sex, and our art. Our most human desires are slowly being synthesized, with or without our consent. And AI is making it all possible.
Deepfake technology has gotten alarmingly good in recent years
Artificial hots like Derek are considered “deepfakes,” an umbrella term for AI-generated media (audio, video, or both) that resembles a real-life person.
When deepfakes first started appearing in late 2017, they were fairly low-quality, making it easy to tell when someone had used a rudimentary app to paste a celebrity or politician’s head onto a different body. Still, it wasn’t very long until people started wielding this technology to be nasty.
“The first set of deepfakes were actually used to create pornographic videos. They replaced the subjects in those videos with the faces of celebrities,” Siwei Lyu, a professor at the University at Buffalo who studies digital forensics, told me.
Because the quality of those videos was bad and the content was often absurd or unrealistic, it was easy to tell they weren’t real. Those clunky apps needed a lot of data — videos, images, etc. — of real people to produce crappy videos; Lyu explained that this is why you mostly only saw deepfakes of politicians and celebrities at the time.
As the technology got better, it became less reliant on having a huge amount of data. Instead of needing a whole archive, the new versions of these apps can pretty much run on nothing. “They do not need that much data to train a model anymore. Some of the most recent algorithms just need a single picture — just a single picture of someone,” Lyu said. And the quality is better too. Lyu said that there are AI programs that can now change a person’s appearance and voice in real time, like in Facetimes and Zooms or on live broadcasts.
Given how many of us are constantly posting photos and videos online, it is now extremely easy to create a convincing social media presence for a person who is not real, and to use it to catfish unwitting people on the internet.
“This is the problem. It’s becoming more and more challenging to visually tell deepfakes apart,” Lyu said. “Seven years ago, when I started working in this area, checking them was not this difficult,” he added.
Lyu is an expert in digital media forensics and machine learning, and he went through one of Derek’s videos frame by frame and pointed out some obvious AI tells. There was a distorted watchface with weird swirls instead of numbers and a moment in the video where all of Derek’s fingers on one hand were the same length. Lyu also pointed out that Derek’s chest hair fluctuates, appearing dense in one frame and then dissipating in another.
Through social media, I attempted to contact the owner of Derek Lam’s account with evidence from Lyu that these videos are artificial; I did not hear back.
During my deep dive into Derek Lam’s social media presence, I looked at the accounts he was following. I noticed that of those accounts, someone who goes by the name Vance Ford also had tens of thousands of followers and had nearly identical videos to Derek. The flexing, dances, movements, and music they were set to were all the same, but with what appeared to be a different man performing them.
I attempted to contact Vance through DMs on social media and did not get a response. I also e-mailed two models who appear to be the actual people that the Derek and Vance AI personas were trained on, but they didn’t respond.
I sent two of Vance’s videos to Lyu, who analyzed them manually and with AI-detection software. He confirmed that “their movements are nearly identical — consistent with generation from a shared motion source,” and noted that the Vance videos had moments of distortion, unintelligible text, and facial warping.
“Young Magnum PI…Tom Selleck,” commented one admirer.
What happens when real people follow fake hots
“Wow I’m a boomer,” said Patrick, one of Derek’s followers on X, after I told him that he might be following an AI-generated thirst account. (Vox agreed to let Patrick, and Derek’s other followers, use a pseudonym so they could speak frankly about being thirsty for a fake guy.) Prior to our chat, Patrick had no idea Derek was likely a deepfake, and maintains that he didn’t even know he was following the account. Patrick is 33 years old, roughly 30 years younger than the youngest boomer, but being fooled by a hot AI man has made him feel old and vulnerable, susceptible to scams and perhaps light financial crime.
“This was probably some smut account I followed before I moved all that over to an alt,” Patrick said, noting that in daily life, he’s only ever used AI to help organize and write emails. Wielding AI to create fake videos and photos does not thrill him, nor does the potential of seeing more of Derek.
How to spot a deepfake, especially when they’re hot
If you’re following someone extremely attractive online and found yourself wondering if they’re perfectly hot or simply an AI generated to be perfectly hot, deepfake experts and adult entertainers say there are a few things to check to see if your crush is an actual human:
- Look at logos or objects with text, like clocks and posters. As good as AI is getting, some apps still struggle with rendering text, numbers, and patterns. Instead of distinct text or numerals (e.g., the 12 digits on a watch face), it’ll look like a distorted jumble.
- Is the background consistent? If the background of a video or photo has an unusual blur to it, that could be a sign that a program was having difficulty creating the video.
- Is this person on OnlyFans? OnlyFans, as adult entertainers told me, has a set of rules regarding AI, along with an ID verification process — essentially, OnlyFans is where real creators are (at least for now). Smaller, less mainstream creator sites may not have the same kind of rules and guardrails.
- Is this person asking you for gift cards? “I don’t need an Amazon gift card,” one exasperated adult entertainer told me, pointing out that anyone asking for one-off, off-platform payments should raise suspicion. Other red flags also include asking for private information (like your bank account information or passwords).
- Are they too good to be true? Sometimes a fake hot can be “too perfect,” a digital forensic scientist told me. It’s worth asking yourself why that very handsome person is essentially shirtless on a plane in economy class, asking if you want to be his airplane crush, and thinking about how little sense taking this photo makes in the real world.
“A person being real, someone you could run into at a bar, is half the fun,” Patrick told me, explaining some of the accounts he follows. “AI porn is not of interest, to me, anyway.”
Not being able to tell the difference between the real beautiful men on the internet and the AI-generated beautiful men on the internet not only makes Patrick feel old, but also a bit “hollow.” The fact that the people we are attracted to are so unrealistically hot, so perfect, that machines can step in for them and go relatively undetected is a reflection of the current state of unattainable desire, which is just as scary as how good these programs have gotten at mimicry.
“Black mirror shit,” Patrick said.
The guys I DMed about Derek felt ashamed once they found out the truth.
“It’s embarrassing and he’s not my type,” said Chris, 33. “I’ve come across several AI accounts, and this one is really good, I have to say. But you can see there’s like no life in his eyes.”
Chris made clear to me that the humiliating thing isn’t that he follows attractive men on the internet. That isn’t a big deal.
What irks him that he got duped. Chris works in digital marketing and has seen AI used professionally to tabulate calculations for campaigns, and has used it privately for silly things like memes. “AI can do a lot of things, things we probably should not want it to do,” he told me. “I think what’s also scary…is that everybody has access to it. And yes I already unfollowed this person.”
Chris believes there’s something more nefarious afoot. He thinks that whoever is running Derek may have hijacked the username (i.e., the original person Chris was following) and then populated it with AI to drive up follower counts — a scam he’s seen online before.
“This is super concerning and super scary because you eventually could be texting with this person,” he said, describing a hypothetical situation where unknowing users could be lured into subscribing to fake content and, ultimately, giving the account their personal information, whether that’s photos or perhaps even passwords.
“This person could be selling your nudes,” he said, explaining one extreme end point of a possible scam. “But you were like jacking off to AI content and that’s embarrassing.”
AI deepfakes are bad for real thirst traps too
While flirting with or masturbating to a fake person is awkward but ultimately manageable and private, Cherie DeVille has an even more complicated problem with AI manipulation. If DeVille is scrolling social media, there’s usually a chance that she’s running into an AI version of herself saying things she’s never said and doing things she’s never done.
DeVille, an adult star who calls herself “The Internet’s Stepmom,” has roughly 4.5 million followers on Instagram. But her account is often down, which she says is the work of fraudsters that are determined to send traffic to DeVille’s AI imposters and get her actual account removed.
“It’s almost always the fake accounts of me reporting me,” DeVille said. “They want to be the biggest me. They want to be the biggest scammer. They want to use my altered AI images to scam fans without my real account getting in the way.”
DeVille and others I spoke to explained to me that deepfakes have been an annoying reality in the adult entertainment industry for years. The way the scam goes is that someone would fake photos or videos of DeVille (or any star), create an impostor profile, and then trick DeVille’s fans (e.g., through social media DMs) into following that copycat. Later they’d squeeze them for money, payments through Paypal, or Amazon gift cards, perhaps by offering unique content.
“If you made a fake me and I don’t do double anal, but my AI can, they could have all kinds of ‘exclusive’ stuff,” DeVille said, explaining that double anal is grueling work.
The lack of protections becomes even clearer when you consider that not every deepfake is a carbon copy. Some personas may borrow a face from one actress, a torso from another, or a pair of legs from a different star. This can make fakes tougher to track down and prove, and more difficult to fight from a legal aspect.
“Who owns your face once it’s scraped into AI systems? Who profits from your digital clone? How do performers protect themselves from unauthorized replicas or manipulated content?” Rachel Steele, an adult star and the CEO of Red MILF Productions, said to me in an email. “Those questions are still very unanswered.”
Like DeVille, Steele worries about how many of the people using AI to create and consume content don’t seem to consider the artists, models, writers, performers, etc. that these engines have been trained on. It’s bad enough to watch AI slurp up and regurgitate your written work or your digital art. Some people also have to contend with LLMs that have been trained on their own faces and bodies.
“Real creators are competing against characters that can be flawless in every image, never age, never have bad lighting, never get tired, and can appear available 24/7,” Raissa Bellini, an OnlyFans creator who touts gymnastics and firebreathing among her unique skills, told me of the impossibility of keeping up with a machine. She explained to me that she’s seen people create AI-generated personas with the looks of popular models or influencers, only tweaking small details like hair color or eye color.
A spokesperson for OnlyFans told Vox via email that the company’s terms of service prohibit deceptive or inappropriate content, and said that all content posted on OnlyFans must belong to a verified 18+ OnlyFans content creator: “This means that you can only share content which has been generated, altered or enhanced by AI if it clearly features the verified OnlyFans creator and the user can tell that the content has been generated, altered or enhanced by AI.”
Bellini explained to me that while OnlyFans has measures to protect its creators, some smaller subscription and adult-content platforms do not have the same kind of guardrails. She also noted that most social media sites do not have strict rules or enforcement when it comes to AI, and that she’s seen the algorithm appear to favor AI over human creators.
“AI raises questions not only about competition, but also about likeness rights, authenticity, audience expectations, and what happens when fans can no longer easily tell the difference between a real person and a generated character,” Bellini added.
What’s stopping a stranger from creating an AI thirst trap of you? Nothing, really.
For Deville, Steele, Bellini, their cohort, and even you and I, there are minimal protections stopping someone creating an AI us and making money off of these fake variants.
According to Jason Schultz, a law professor and director of NYU’s Technology Law & Policy Clinic, humans have, for the last couple of centuries, generally been protected by copyright and right of publicity laws.
AI obviously didn’t exist when these laws were written, and courts now have to interpret the laws in the context of all of this new technology, in combination with other existing rights (like free speech). Schultz told me that there are more than 100 current cases pending about training AI with copyrighted material.
He also explained the difficulty of determining whether or not an AI-generated persona constitutes a violation of someone’s right of publicity. It’s more clear-cut when the human involved is a celebrity, because their public persona and appearance is so distinct. It gets murkier when the humans aren’t well known, and the AI creates a persona that’s more of an amalgam than a one-to-one copy.
“It would raise this question of whether these avatars are based on a particular entertainer, or are they more of an aggregate?” Schultz explained to me. But even if courts side with the humans whose likenesses are being used to create fake personas, Schultz cautions that the technology will always accelerate faster than court decisions are handed down. “I think that the thing that worries me a little is we’re going to get these sets of decisions in two years, but we’ll be dealing with the next three generations of technologies,” he said.
DeVille, who has been working in the industry for nearly two decades, told me that without better legal protection, she isn’t hopeful for the future of porn or, more broadly, any type of art.
“If my income started tanking and their theft was at the point where I couldn’t compete with literally myself, there might be no choice but to retire,” DeVille said.
But she also wants to make it extremely clear that she isn’t against AI; she would just like to be in control of it. That means being able to own her likeness, her voice, her image, and the ability to choose whatever she wanted to do with it — or at least get some compensation or have some legal protection if someone’s using Cherie DeVille without her permission.
“It would be a beautiful way to extend my career beyond what my knees can take,” DeVille told me. But, she added, “if someone’s making an AI of me doing double anal, I should be making the money.”
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With this funding, European researchers can test how their scientific work could impact society.
Four Irish-based researchers have won Proof of Concept grants from the European Research Council (ERC).
Funding for the first funding round this year is worth more than €27m, and is divided between 182 researchers with ideas that show potential for commercial or societal impact. Each individual grant is worth €150,000.
Some of the chosen ideas include developing 3D-printed ‘bio-inspired’ electronics, a tool to help doctors protect vital parts of the brain during surgery, and an advanced ready-made breast cancer vaccine.
University College Dublin (UCD) researcher Prof Niamh Nowlan received ERC funding to further her work around new treatments for a broad range of paediatric growth disorders.
Nowlan is a professor of biomedical engineering at the UCD School of Mechanical and Materials Engineering and a fellow of the UCD Conway Institute.
Her project, called ‘Grow-Reg’, will attempt to identify specific cell surface markers that aid in the growth of children’s bones, to help develop treatments designed to speed up or slow down growth of one or more bones without systemic drugs or surgeries.
“Advancing basic research closer to patients (especially babies and children) is hugely rewarding and we are excited to get started,” said Nowlan. Grow-Reg builds on a previous ERC-funded project led by Nowlan.
“By creating the foundation for a targeted delivery platform capable of modulating growth plate activity with high anatomical precision, we hope to ultimately enable new treatments for a broad range of paediatric growth disorders, reduce reliance on invasive surgery, and improve the safety and specificity of existing biologic therapies,” she said.
Meanwhile, two University of Galway research projects also succeeded in receiving Proof of Concept grants. Led by systems biomedicine professor Ines Thiele, ‘iChatRD’ aims to develop a user-centred clinical decision support system to diagnose rare and inherited metabolic diseases.
“When exploring avenues for translating our fundamental research on digital metabolic twins into patient-focused applications, we kept encountering a major challenge. The richest clinical information exists as free text – the language of a human, not of a computer,” Thiele said.
“iChatRD bridges this gap by enabling metabolic modelling and natural language work together to suggest candidate diagnoses for inherited metabolic diseases.
“The ERC Proof of Concept grant now helps us take iChatRD into the real world by working directly with clinicians to help shorten the diagnostic odyssey that may burden rare disease patients for years.”
The second Galway project, called ‘GelEV’, will focus on developing technology that could improve regenerative medicine delivery to injured tissue sites. Led by Meadhbh Brennan, the project is engineering a hyaluronic acid hydrogel for better delivery to extracellular vesicles.
University of Limerick also bagged a grant win with a project called ‘Eve Heals’ that hopes to heal diseases affecting the skin using in-vitro engineered living substitutes. The project is led by Dimitrios Zevgolis, who also works across institutes at UCD.
“Many of today’s innovations begin with a researcher asking a fundamental question. These 182 projects show that curiosity-driven science and real-world impact go hand-in-hand,” said Ekaterina Zaharieva, the European commissioner for start-ups, research and innovation.
“With Proof of Concept funding, ERC researchers can test how their discoveries could become new treatments, technologies, services or solutions that benefit people across Europe.”
2026’s first Proof of Concept round invited 15pc more proposals than a year ago, the ERC said. Applications for the second round are open, with a September deadline.
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Business Email Compromise (BEC) is often described in the media as merely an email scam, but in reality, it’s part of an organized broad operation. The email itself is only one part of the attack chain. In order to support a successful monetization of email fraud, attackers need to be patient and learn about the procurement process in the organization, and to build or rent an entire infrastructure and operation.
A single BEC often includes gaining access to their targeted business, gathering raw data, analyzing the mailbox context, building reliable communication channel, accessing t reliable payment infrastructure, orchestrating everything in the right timing, and finding a way to move money after it’s stolen.
Flare researchers sampled and analyzed underground posts related to BEC from the past year; Highlights of the findings include:
- AI-powered BEC is getting popular, reducing the learning time and increasing the scam “quality”.
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Actors are interested mainly in SaaS accounts (such as O365). Corporate leadership and financial employees are the most desired targets.
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There are special call centers designed to apply pressure on a targeted business to finalize the fraudulent payment.
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Cash-out is the biggest bottleneck of BEC, hackers need to find relevant business bank accounts or cash-out partners which is relatively considered a difficult task.
BEC Exceeds the Boundaries of Email
BEC begins with access to an organizational mailbox or a business SaaS account. Once in, the threat actors often analyze the account, then study and map the organization, mainly by understanding organizational structure and specifically financial privileges, procurement process, internal conversations, communication with vendors, and invoices.
After everything is collected, the threat actors can attempt to make a fraudulent request.
This is what makes BEC difficult to detect. A suspicious email from an unknown sender is one thing. But a message sent from a compromised mailbox, inside an existing conversation, using real names, real invoice references, and familiar wording is much harder for employees to question.
Unsurprisingly, Flare data shows that threat actors highly value email accounts of employees from the finance department, as they are tools to understand the financial operations.
Inside these accounts, the threat actors are looking for referenced accounts receivable, accounts payable, payrolls, invoices, overdue payments, and customer payment relationships.
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Case Study: Hacker Discussions on BEC
A thread named “Business Email Compromise (BEC) – Experiences & Discussion” created by a threat actor named Bigjack, in January 2026, clearly illustrates how this operation works.
Bigjack described how he is using remote access malware to gain initial access, then compromising company mailboxes and using them to send invoices. The actor’s questions focused less on the technical intrusion and more on the practical fraud aspects based on experience:
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When to send the invoice
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How to create urgency
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How to ask for a large amount without raising suspicion
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What mailbox information should be reused
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What kind of proof can be provided if questioned
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Which mistakes can ruin the operation
The replies showed how other threat actors view BEC and therel experiences. One threat actor highlighted the significance of intercepting an invoice payment process. Another said that identifying who validates the payment requests and defrauding him is the most important aspect. Other threat actors’ emphasize the significance of cash-out, saying that reliable collaboration and support is the most critical aspect.
This single correspondence clearly depicts the mindset of threat actors regarding BEC. Threat actors learn from experience that they need to fully understand the procurement process (the right timing, the right pressure, the right financial context, and the right receiving account) before they can start sending effective fraudulent invoices.
From compromised finance accounts to cash-out networks and call center recruitment, threat actors plan BEC operations openly on criminal forums.
Flare monitors these discussions, so you can see the attack coming before the invoice does.
The Cash-Out Part Is a Bottleneck
Monetization of BEC is nearly impossible without a reliable proper receiving account, so. threat actors connect to mule networks and use cash-out services. This is a hard task because the threat actors need to find a reliable, operational, “clean”, relevant bank account to finalize the fraud.
A threat actor named neoresu emphasizes that it’s not just the destination bank account, but also the person who validates the payment needs special care. He offered his services and also talked about using a call center to increase the success rate.
Another threat actor named “Capita” claimed to have operated BEC activity for six years in Europe (mainly in Germany, Finland, and Austria) and described using peer-to-peer money movement, and a call center to pressure companies into faster payments.
There are also posts that are looking to recruit money mules for a BEC scheme. Specifically involving business bank accounts, and fast money transfer.
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Support Call Centers to Apply Pressure
Several posts also referenced calls as part of the BEC process. In the Bigjack thread, the actor asked when to call after sending the invoice, while another participant claimed to operate a call center used to pressure companies into faster payments.
This matters because BEC is not always email-only fraud. A follow-up call can make the request feel more legitimate and urgent. For defenders, a second channel should not be treated as proof of authenticity if the requester introduced or controlled that channel.
AI-Powered BEC Attacks
Underground discussions indicate that AI is increasingly being adopted to improve the effectiveness and scalability of BEC campaigns.
In the post below by blackhatpakistan, the threat actors describe using AI to generate realistic business correspondence, mimic executive and employee writing styles, and produce context-aware payment requests or invoice fraud emails that blend into legitimate communication.
Rather than relying on a single template, AI enables the creation of thousands of unique email variations, making campaigns more difficult for traditional content-based detection systems to identify.
Dedicated underground tools are also promoted for generating entire email conversation chains, allowing attackers to hijack existing business discussions and inject fraudulent payment requests with a higher degree of authenticity.
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Practical Advices for Defenders
Underground discussions clearly show that we must increase BEC defenses.. The security posture should begin way long before the first fraudulent invoice arrives. What we’ve learned from attackers:
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Attackers target specific personnel in the organization. Defenders must identify the potential targets and apply additional training to leadership, the financial department and whoever takes part in the procurement process.
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Attackers are now using AI-powered artifacts such as emails, invoices, documents, and messages. Defenders need to identify AI-generated content and deep-fake items.
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Attackers leverage dedicated call centers to pressure financial decision-makers and payment approvers into authorizing fraudulent transactions. Defenders should gather intelligence and learn what techniques these centers use to better educate their relevant employees.
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Attackers highlight the significance of specific points in time, waiting for approvers to be on vacation, as well as other tips to improve the success rate of their fraudulent activity. Defenders should learn about these special markers and apply further defense mechanisms during specific periods, such as employee vacations.
Flare helps by giving security teams visibility into these underground markets and by monitoring exposed employee credentials, corporate domains, login portals, SaaS applications, and related indicators across deep and dark web sources.
This allows organizations to detect when their access points appear in credential collections or search-service advertisements, prioritize the most relevant exposures, and respond faster with password resets, session revocation, MFA enforcement, and investigation of possible account misuse.
Learn more by signing up for our free trial.
Sponsored and written by Flare.
X is making it easier for AI assistants like Claude, Cursor, Grok Build, and other MCP-compatible apps to connect directly to the platform through a new hosted MCP server.
On Monday, the Elon Musk-owned social network unveiled a hosted Model Context Protocol (MCP) server that lets AI tools communicate with the X API using a user’s own account permissions.
MCP, for context, is an open standard that defines a common way for AI models to connect to external tools and services. Previously, if developers wanted an AI assistant like Claude or Cursor to access X, they would have to build their own MCP server, host it, connect to the X API, and handle the authentication. Now, X hosts the MCP, and users authenticate with their own X account’s permissions.
This allows developers to save the time spent on integration work to focus on whatever it is they’re actually building.
Developers have long been able to search X, read posts, look up users, analyze conversations and trends, and do more using the platform’s API. The hosted MCP doesn’t add new capabilities on that front; it just makes them easier to expose to AI applications. By doing so, X can position itself as an information network filled with real-time data to retrieve and analyze, rather than just a social hangout.
The move sees X joining a growing number of companies that now offer their own official MCP servers or endpoints, like GitHub, Slack, Notion, Stripe and Salesforce.
Of course, there’s always concern that by removing an infrastructure hurdle, X is opening itself up to more automated posting or spam.
It’s worth noting that the hosted MCP isn’t bypassing X’s API rules, which continue to restrict its use if the company detects spammy behavior.
X also updated its API v2 earlier this year to address the issue of AI-generated spam, particularly programmatic replies to conversations. Plus, it recently updated its API pricing, increasing the cost for publishing posts to $0.015, and posting links to $0.20. The price increases were designed to “curb vectors of misuse,” X said at the time — meaning it’s at least getting more expensive to spam X.
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Verdict
Perfectly balanced, powerful, and incredibly quiet, the Stihl FSA 50 Cordless Grass Trimmer is a must for any serious home gardener. It’s an expensive piece of kit, but it’s worth the money for its performance and handling.
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Converts to an edging tool in seconds
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Excellent balance and minimal vibrations
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Quiet operation
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Some might struggle with the safety trigger
Key Features
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Review Price:
£159
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28cm cutting width
Ideal for clearing growth quickly.
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Adjustable length
Change the shaft length to suit your height.
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Battery powered
Runs on Stihl’s AK battery system.
Introduction
If you’re in the habit of gardening early in the morning or late at night, this ultra-quiet grass trimmer will keep you in your neighbour’s good books. Powerful, comfortable, and highly versatile, I think the Stihl FSA 50 Cordless Grass Trimmer is one of the best cordless grass trimmers available right now.
Find out why in my in-depth review.
Design and Features
- Adjustable shaft length
- Adjustable cutting head angle
- Converts to an edge trimmer
First off, this is an incredibly well-made grass trimmer. The steel shaft trigger, blade guard and handle feel premium, and there’s no wobble or rattling during use.
Weighing just over 4kg when combined with the AK20 battery, I thought this cordless grass trimmer would feel heavy. Thanks to Stihl’s excellent ergonomics and balance, it doesn’t feel weighty at all. The shaft length can be adjusted by about 20cm to suit gardeners of different heights, and the front loop handle can be adjusted to a comfortable position and locked in place.
A collar halfway along the shaft lets you rotate the cutting head, converting the trimmer to a powerful edging tool in seconds. The cutting head uses bump feed, too, paying out fresh line whenever you tap it on the lawn. In my opinion, bump feed beats auto feed because it’s more economical and has fewer moving parts that can go wrong.
Down at the business end of the grass trimmer, there’s plenty of adjustment available too. The cutting head angles to stay running flat on the lawn, regardless of your height. Flick the switch round to the “E” setting and the head drops straight down for edging the lawn instead. And another clever bit of thinking from Stihl, you can adjust it with your foot and not have to bend over. Notably, a cordless grass trimmer like this offers more convenience for different lawn jobs.
Running on the powerful AK system, the battery slots into the back of the trimmer and helps to keep things balanced and comfortable. And the 28cm cut width is wide enough for clearing decent swathes through long grass.
It all adds up to a supremely comfortable grass trimmer. The only place that might cause issues is when you want to stow it away. Although the shaft length is adjustable, it doesn’t fold or break down into two pieces. So, if you have limited storage a smaller grass trimmer would be a better option.
Performance
- Minimal vibration even at top speed
- Extremely quiet
- Effective variable speed trigger
Assembling the FSA 50 for its first use took me about five minutes. The loop handle bolts on and tightens in place by hand, but you’ll need a cross head screwdriver to attach the blade guard. The flower guard snaps into place without much fuss, but I had to be careful to avoid scratching the plastic.
It’s great to see that Stihl includes a pair of safety glasses in the box, and they’re big enough to go on over top of most glasses as well. Safety is always a priority when using a grass trimmer, so it’s a welcome addition to the FSA 50.
The lack of noise that this trimmer makes is impressive. If you really want to avoid annoying the neighbours, trimming on the lowest speed is almost silent. And controlling the speed is easy too, thanks to the sensitive trigger. I found it easy to keep it at a low enough speed to conserve battery life but kick it up to full speed when necessary. Additionally, the cordless grass trimmer design helps keep noise levels down for quiet operation.
The two stage safety trigger might not be to everyone’s tastes, however. To turn on the trimmer, you need to engage the rear and side safety switches before the variable speed trigger works. It’s an effective safety feature but a little fiddly to get used to.
The lack of vibration is another welcome feature. Even at full speed, the FSA 50 didn’t push much vibration into my hands. It’s definitely an easy trimmer to use, even for long periods.
I used an AK20 battery in the trimmer, which is rated to power the trimmer for up to 50 minutes. The smaller AK10 will give you 25 minutes of trimming, and the big AK30 battery provides an hour of use.
While the trimmer comes with a line trimmer head and 1.6 mm round line, you can swap it out for the Polycut 3-2 mowing head with plastic blades to double your working time. That’s good to know if you have lots of brush to clear.
However, if you have a bigger garden to look after you might want to take a look at the FSA 50’s big brother, the mighty Stihl FSA 70R instead.
Should you buy it?
You want power and flexibility
Ergonomically brilliant, this trimmer is comfortable and easy to use, working as well as an edge trimmer as in regular use.
You want something smaller and lighter
If you’ve got a smaller garden, a smaller, easier-to-store trimmer might make more sense.
Final Thoughts
I’m struggling to find the downsides of this grass trimmer. It works just as well as an edging tool, it’s quiet, comfortable, and easy to use for extended periods of time. So, although it’s expensive even without batteries, this is the ultimate multi-purpose trimmer. If you need something smaller (or larger), read the guide to the best grass trimmers.
How We Test
We test every grass trimmer we review thoroughly over an extended period of time. We use standard tests to compare features properly. We’ll always tell you what we find. We never, ever, accept money to review a product.
Find out more about how we test in our ethics policy.
- Used as our main trimmer for the review period
- Used on a variety of grass lengths and weeds to see how well the mower cuts
- Tested to see how easy the trimmer is to carry, use and store
FAQs
What type of battery does the Stihl FSA 50 use?
This trimmer uses Stihl’s AK series of batteries, which are compatible with a wide range of garden tools.
Full Specs
| Stihl FSA 50 Cordless Grass Trimmer Review | |
|---|---|
| Manufacturer | – |
| Size (Dimensions) | 148 CM |
| Weight | 2.9 KG |
| Release Date | 2026 |
| First Reviewed Date | 30/06/2026 |
| Model Number | Stihl FSA 50 |
| Cutting width | 28 cm |
| Strimmer type | Cordless |
| Adjustable length | – |
| Cutting tool | 1.6mm line, optional Polycut head |
| Rotating head | Yes |
Slashdot reader joshuark summarizes this walk down memory lane from the tech site MakeUseOf:
Facing real competition from Digital Research’s DR DOS, Microsoft secretly embedded a sabotaging mechanism known as “AARD code” into beta versions of Windows 3.1 to prevent it from running on Digital Research’s competing DR DOS operating system.
This code triggered fake, alarming error messages to convince developers that DR DOS was unstable… Although Microsoft disabled the feature in the final retail release, the California-based firm Caldera, Inc., which had acquired DR DOS assets, sued Microsoft for anti-competitive practices.
Microsoft settled the lawsuit out of court in 2000 for $280 million, a figure that remained sealed until it was unsealed in 2009.
When you’re driving your car, you’re probably regularly looking at the speedometer to make sure you comply with the local speed limits. The method by which it works is simple enough: the rotation of the wheels is sent mechanically via a cable to a dial on the dash, or an electronic sensor counts the rotations of the drivetrain and an electronically-controlled needle or display shows the speed.
But what about if you were in an aircraft, and the wheels had nothing to do with how fast you were going? How would you even begin to measure speed? There are two ways: there’s a convenient solution to this problem rooted in simple fluid mechanics, and a far-more-complex modern solution. Today, we’ll explore how planes and helicopters are able to figure out how fast they’re going, by the old ways and the new.
Classical Methods
A key thing most aviators want to know is how fast their aircraft is going. Specifically, it’s nice to know how fast it’s moving relative to the airstream around it, which is referred to as airspeed. This is important, because it’s the aircraft’s velocity relative to the flow, such as wind, that determines the performance of the airfoils, how much lift is generated, and whether or not the aircraft is approaching a stall condition where it might fall out of the sky.
Measuring airspeed is most commonly achieved with the use of a device called a Pitot tube. The pitot tube is a tube with a hole in one end that points directly into the airflow in the direction of travel of the aircraft.
As air flows in, it reaches a dead end and the flow slows to a stop, or stagnates, since it has nowhere to go. This allows a pressure sensor or a manometer or other device to measure the stagnation pressure at this point. The stagnation pressure measurement is related to the flowspeed of the incoming air since the kinetic energy of the flow is converted to pressure as the flow comes to a halt.
A secondary tube, pointing perpendicular to the airflow, is then used to measure the static pressure of the surrounding air, without the ram effect of the air being forced in by the aircraft’s forward motion. Then, it’s possible to calculate the velocity of the aircraft relative to the airstream by plugging the stagnation pressure and static pressure into a rearranged Bernoulli’s equation. If the pitot tube and static tube are hooked up to electronic sensors, the airspeed can be calculated electronically, and fed to a display or digital gauge.
Alternatively, it’s possible to effectively do this “calculation” mechanically. In earlier days, static and stagnation pressure captured by each tube would be fed to a gauge. Inside, the stagnation pressure would be fed to a diaphragm which moved due to the difference relative to the static pressure which is fed into the gauge body, and the movement of the diaphragm would, via a simple mechanism, shift the needle on the gauge.
A small General Aviation aircraft might mount a single pitot tube on the aircraft, feeding the air speed instrument in the cockpit. Commercial aircraft might mount two or more for safety’s sake, in case one becomes inoperable, while large airliners may have four or even more to provide a high level of redundancy and error checking. Heaters are commonly included on pitot tubes to ensure they can be kept free of ice, which can otherwise completely block a tube and make it impossible to obtain an airspeed reading.
For pilots, not knowing how fast (or slow) the aircraft is going can be highly dangerous, as it can lead to entering unstable flight regimes such as stall. Thus, it’s imperative that the pitot tubes remain unobstructed and functional for safe flight. Many aircraft accidents have occurred because of blocked or malfunctioning pitot tubes or airspeed instruments.
The New Way
Of course, you could fuss about with pitot tubes and pressure sensors and deicing measures, but that’s all very fiddly and old hat. There is an entirely different way to figure out a plane’s speed, though it’s only been available for the last few decades. It’s as simple as throwing a GNSS receiver on the aircraft.
Yes, whether your particular poison is GPS, Baidou, GLONASS, or Galileo, any major satellite navigation system will be able to tell you the speed of your receiver. Simply measuring the change in the receiver’s position over time is enough to calculate out the speed, and any off-the-shelf receiver will present this information as standard. It’s generally not used as a primary indicator in aircraft, because it reports ground speed, not airspeed, the latter being more relevant for aviation purposes. Still, it can prove to be a useful sense check when traditional airspeed indicators are non-operative or reporting confusing data, and GNSS devices are widely used on many aircraft today.
Flying High
If you’ve ever wondered how an aircraft measures its speed as it floats through the amorphous gas cloud we call an atmosphere, now you know. Even to this day, where electronics and computer wizardry control our fanciest aircraft, airspeed measurements are still done with the same simple physics, just with some fancier sensors for help. The fundamentals haven’t changed at all. Now you know, you can always dig deeper into the many other rich applications of Bernoulli’s equation and fluid mechanics in general. Happy learning.
Meta wants its own AI coding tools. To get there, it is telling its engineers to be careful with the rival tools they lean on today.
Meta has placed strict limits on how engineers in its applied AI division use Anthropic’s Claude Code and OpenAI’s Codex, The Information reported. The worry is inadvertent distillation. One internal memo even told some teams to pause tasks that used the outside tools. It warned that the rivals’ output could seep into Meta’s training data and trigger “serious escalations with partner companies”.
What distillation means here
Distillation is when one model learns from another model’s outputs. A company feeds a strong model’s answers into its own system, and the smaller model picks up the bigger one’s skills. The method is cheap, fast, and legally fraught.
That is the heart of Meta’s problem. The company is building its own coding tool, called MetaCode, to replace Claude Code and Codex. If its engineers rely on those rival tools while shaping the replacement, Meta could end up training on a competitor’s model by accident. That could breach the rivals’ terms of service and hand them a lawsuit.
The bind Meta is in
The situation is awkward. Meta still needs the best coding tools to move fast. For now, the best ones belong to Anthropic and OpenAI. So Meta is asking staff to keep using the very products it wants to leave behind, only with more caution. The rules sit inside its new applied AI engineering division, the unit Meta built to catch up in the model race.
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Cost is the other half of the story. Meta is trying to wean itself off expensive outside coding tools. It is not alone. Amazon is weighing cheaper alternatives after Anthropic raised its prices. The pressure to cut the AI bill is everywhere.
Anthropic keeps gaining leverage
This is the latest sign of Anthropic’s growing clout. Its Claude models have become a default for coders, which gives the company room to push. It recently struck a half-price deal to put Claude across California’s state agencies. It is also winning paying customers at pace.
The flip side is friction with the very firms that depend on it. Anthropic has already accused Alibaba of distilling Claude into a rival model. Meta clearly does not want to be next in line.
Squeezed on every side
Meta’s pinch is not only about Anthropic and OpenAI. Google has capped how much Meta can use its Gemini models for coding and chatbots, Engadget reported, citing a lack of capacity. So Meta faces limits from three rivals at once. It must build its own tools, and fast.
That is a strange place for a company of Meta’s size. It spends billions on AI talent and chips. Yet on coding tools, it still depends on the labs it is racing against. The new rules try to close that gap without tripping a legal wire.
Why it matters
The episode shows how the AI business is maturing. The model makers are no longer just selling access. They are guarding their outputs as prized training data, and they are watching who learns from them.
For Meta, the lesson is sharp. Owning the frontier means more than raw compute and big hires. It means controlling the tools your own engineers use every day. Until Meta’s in-house coding system is ready, it has to borrow from rivals while trying not to copy them. That is a tightrope, and the memos show Meta knows it.
Don’t get hit with the Apple tax.
Apple’s App Store is quietly a major source of the company’s revenue. Every time an iPhone user subscribes to a service through Apple’s billing platform, the Cupertino giant skims up to 30 percent off the top of each recurring charge. The practice has been so brazen that a court ruled Apple must allow third-party billing to be offered, then, last year, the same court found the company in contempt for violating that ruling when it charged developers a comparable fee to implement their own billing tools.
But app developers had already adjusted to Apple’s fee skimming long before the court case was decided. Rather than eat a 15-30 percent loss on subscription revenues, many developers simply offset those costs by charging customers more when they subscribe through the App Store. A service that might be $10 when you subscribe on the company’s website becomes $13 when you subscribe on the App Store. It’s a phenomenon that’s become known as the “Apple tax.”
YouTube Premium is a prime example. We’ve noted that some users can swap existing music subscriptions for YouTube Premium, but it’s a different story when subscribing through the App Store. Indeed, when we look at pricing for YouTube Premium, we can see Google charging an Apple Tax. When subscribed to through the YouTube website, the monthly subscription cost for an individual is $16. However, head to the App Store, and the price tag increases to $21 a month. That’s $5 leaving your wallet each month for no reason other than helping Google to cover Apple’s tolls, making it much harder to get your money’s worth from YouTube Premium.
Apple’s App Store is convenient for managing subscriptions, but it’s not worth paying extra for YouTube Premium
Some people prefer to bill their subscriptions through Apple’s App Store because of how predatory first-party billing can be. Once you give some companies your credit card information, it can be nearly impossible to get them out of your pocket. After digging around in settings menus to find the “cancel subscription” button, which appears deliberately hidden like Waldo, you’re made to go through three confirmation screens, presented with a special, one-time-only discount offer, and then made to fill out a survey explaining why you want to cancel. And that’s if you’re lucky. Some subscriptions from smaller outfits will make you send an email, or you might resort to replacing your credit card in order to stop the subscription from being charged.
There may be situations where paying an Apple tax on your subscriptions is worth a few extra dollars for the peace of mind that comes with the ability to cancel them in just a few taps on your smartphone. Apple would love to keep collecting its fees from your subscription, but the company also wants you to enjoy using your iPhone and is therefore not as straightforwardly incentivized to act like a gremlin with your credit card.
Even so, it’s worth saving money where you can. Thankfully, YouTube Premium makes it reasonably easy to cut off a subscription on its own billing platform. Canceling is a relatively straightforward process, and Google won’t give you much guff about your decision to stop giving it money. If you’re currently overpaying for YouTube Premium through the App Store, or if you’ve been considering signing up for the service, you’re better off doing so away from the tax collector at Apple’s walled garden gates.
Conducted jointly with China Telecom and optical equipment maker Dekoli, the test ran on the world’s longest cross-border commercial HCF cable. The result sets a new world record achieved without the signal boosters that long-haul fiber links typically depend on.
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I love cordless vacuums, and I don’t just say that because I’m one of CNET’s primary testers of the category. I say it because switching from corded vacuums to cordless vacuums was a big quality-of-life upgrade, thanks to the ease of use and maneuverability around my apartment. The downside is that cordless vacuums don’t usually match the suction power and cleaning capabilities of upright or canister models.
Shark’s PowerDetect Transformer 3-in-1 is the company’s attempt to address this trade-off without forcing you to buy multiple vacuums.
“The upright vacuum has looked and worked the same way for decades,” said Petra Oman, vice president of marketing at SharkNinja, in a press statement. “We saw an opportunity to rethink the category by eliminating the bulky hose and creating a system that adapts to the way people actually clean. Transformer delivers the deep-cleaning performance consumers expect from an upright, with the flexibility and reach needed to clean everything from floors and carpets to stairs, furniture, ceilings and the car.”
The main upright dustbin is detachable when you want to use it as a slimmer cordless vac.
As the name suggests, the PowerDetect Transformer is three vacuums in one. It’s a full-size upright vacuum that’s intended for deep cleaning carpets and hardwood floors with the strongest suction. Shark says you can remove the main canister with one click, and it’ll turn into a slim stick vacuum for regular, lightweight cleaning, getting under furniture and into other tight spots. One more click turns it into a handheld vacuum, making it easier to clean stairs, upholstery, corners and cars.
In terms of specs, the Transformer will have key features from Shark’s most popular models, including LED lighting to help you find debris and automatic detection of dirt levels, flooring types, edges and movement to automatically adjust suction and cleaning performance. It features anti-tangle brushrolls, odor-neutralizing tech like the Shark Stratos and HEPA filtration. It’ll also come with an auto-emptying system that empties the debris into the main dustbin when the handheld clicks back into place.
I haven’t had a chance to go hands-on with this vacuum yet, and I’m not entirely sure how the system breaks down. I’ll be testing it both at home and at CNET’s Louisville lab. The most interesting question will be whether the PowerDetect Transformer can truly deliver the cleaning performance of an upright vacuum without compromising elsewhere.
The Transformer has all the key features we’ve liked from the most popular Shark models.
Price and availability
The Shark PowerDetect Transformer 3-in-1 will be available on SharkNinja and TikTok Shop for $529. It’ll also come to Amazon, Walmart, Best Buy, Target, Costco and Sam’s Club.
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