Tech

Tech: Where the future is funny and innovation is hilarious! Plug into our Tech section for a circuit of chuckles, where gadgets and gizmos get a comical upgrade. From Silicon Valley silliness to digital dilemmas, we decode the tech world with a byte of humor. Perfect for gadget gurus and casual surfers alike who believe every software update should come with a laugh patch. Warning: Our jokes may cause spontaneous rebooting from excessive laughter!

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    The AI Dividend Needs a Receipts Department

    ByHarlan Quill

    If public grants, research, or open knowledge help build an AI product that earns profits while automation displaces workers, taxpayers should not be silent investors on the way in and strangers at payday. If workers and the public carry part of the cost, the public deserves a share of the upside. That is not a radical accounting theory; it is what happens when the ledger remembers who helped build the thing.

    Then comes the receipts department. It has to identify which public contributions count, who benefited, and what payment rule applies. A grant does not automatically make taxpayers shareholders in an entire company; pretending the public contributed nothing is not an audit either. Before anyone mails an AI dividend check, the spreadsheet needs to show who owes what. The check can wait in the outbox until the math has signed off.

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    The Deepfake That Tried to Put a Texas Candidate in the Wrong Group Chat

    ByHolden McGroin

    Two videos posted on October 20 looked like evidence in search of a scandal. They purported to show a former student accusing Texas Senate candidate James Talarico of sexual misconduct. But the key distinction is this: the videos circulated; that does not mean the event they depicted happened. A corkboard can connect anything if you let the red string do the fact-checking.

    What the reporting established

    Researchers at Graphika assessed the videos as very likely AI-generated. Graphika also said a Russia-aligned influence operation likely produced them. That is a qualified assessment from the researchers, not proof that a particular government personally assembled a video in a basement with a suspicious lamp. Keep the attribution attached to Graphika’s reporting.

    Lead Stories reported that the real man whose identity was used, Zyon Lewis, denied appearing in the videos and denied making the allegation. PolitiFact rated the claim “Pants on Fire.” Those findings matter more than the video’s confident lighting: the person presented as the speaker said it was not him, and the fact-check rejected the claim as false.

    There are two different things to establish here: that clips were posted and circulated, and that the event they purport to show actually happened. The first is documented; the second is not supported by these videos. A clip can be evidence that someone made and shared a clip. It is not, by itself, independent confirmation of the allegation inside it.

    When a rumor gets an authority upgrade

    The Atlantic reported that Google AI answers picked up the false Talarico claim. That is a specific report about the claim appearing in AI answers; it does not establish why it appeared, how often users saw it, or that Google endorsed it. Still, the sequence is unsettlingly familiar: a fabricated video enters circulation, then repetition can make a rumor feel as if it has acquired independent confirmation.

    That is rumor laundering. The same claim shows up in enough places that a reader may mistake echoes for witnesses. An AI answer can make the echo sound tidier, but tidiness is not corroboration. If its trail leads back to videos Graphika assessed as very likely AI-generated and a claim the named man denied, the answer has not turned the claim into a fact. It has given the fog a better font.

    For Texans following the Senate race, the practical takeaway is simple: separate the existence of a video from the truth of what it alleges. Reporting supports that the clips circulated; Graphika assessed them as very likely AI-generated, and PolitiFact rejected the claim as false. A claim’s appearance in an AI answer, as reported by The Atlantic, is not independent confirmation. Follow the thread, but check the knot—and notice when the loudest payoff is confusion itself.

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    Olivia Rodrigo’s AI Accusation Became a Pop-Internet Courtroom—Then Came the BTS Footage

    ByAmanda Lynn

    First came the verdict

    The internet saw apparent animation irregularities in Olivia Rodrigo and Chappell Roan’s “expectations” video and opened court before the credits had finished rolling. Released October 15, the video soon became the subject of online debate about whether some of its imagery pointed to AI. That was speculation, not a confirmed finding. As Creative Bloq and Rolling Stone reported, viewers were interpreting visual details—not presenting an independently verified account of how the entire video was made.

    A freeze-frame can feel like a tiny forensic lab when it lands in a feed. But noticing something that looks unusual and identifying how it was made are different tasks. The first can start a useful question; it cannot, on its own, supply the production records that would answer it.

    Then the production footage entered evidence

    Behind-the-scenes material offered a more complicated picture. Rolling Stone reported on footage shared by Livies HQ, Rodrigo’s official fan account, showing elements of the video’s production, including hand-drawn artwork and a mix of 2D and 3D animation. Designer Jack Harrison also posted behind-the-scenes material; reporting identified him as leading the video’s analog treatment. Those details matter: they show creative processes behind images that some viewers had treated as suspicious at a glance.

    But let’s keep the courtroom metaphor honest: footage of some production techniques is evidence about those techniques, not a complete audit of every tool used across the video. The Livies HQ post is from a fan account, not a direct statement from Rodrigo. Harrison’s post gives viewers a closer look at his work, but does not automatically answer every question about the full production process. Rolling Stone reported that Rodrigo’s representative did not immediately respond to a request for comment. That is not the same as a formal denial, confirmation, or official explanation.

    Suspicion is fast; verification takes longer

    This is the strange little pop-internet trial: a few frames become exhibits, a theory becomes the headline in everyone’s group chat, and then new footage arrives like an appeal filed by someone carrying a sketchbook. Visual oddities can prompt fair questions. They are not, by themselves, proof of AI—or proof that AI was absent. Behind-the-scenes posts can supply useful context without resolving the whole technical question.

    That distinction matters beyond one video. Fans can care about how creative work gets made, especially when AI is part of a charged conversation about creative industries. But viewers also deserve more than a confident verdict built from a freeze-frame. The footage reported here points to hand-drawn, animated, and analog elements; it complicates the speculation without independently settling every tool question. That is meaningful evidence about parts of the process, not a magic window into every production decision.

    The song can survive an open question. The internet, meanwhile, may need to let the evidence finish its sentence before handing down the sentence.

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    Apple Says Safari Is Blocking Post-Cookie Ad Tracking. Publishers Still Want to Know Who Sets the Rules.

    ByLee Keybum

    Who decides what Safari can reach?

    That is the question behind Apple’s latest privacy dispute with the ad-tech industry. In an October 19 explanation, WebKit said Safari blocks network access to third-party systems that turn email addresses into identifiers for recognizing people across websites and devices. WebKit says the policy is meant to limit that kind of cross-site identity resolution. For users, it may mean fewer ways for ad systems to recognize them as they move between sites. It does not mean Safari is blocking all ads, all cookies, or every tool with the word “identity” in its sales pitch.

    First-party is a different door

    WebKit drew a line between cross-site identity resolution and a website using information about its own customers to personalize its service. In plain English: a bookstore remembering what you asked it to remember is different from a third-party system being used to recognize you on other websites. That distinction matters because privacy rules can limit cross-site tracking without treating every useful website feature as a crime against the cookie jar. It also leaves practical questions for publishers and ad companies: which systems fall on which side of the line, and how does a browser apply that boundary?

    The blocklist has a visibility problem

    Digiday reported on October 20 that publishers want more clarity about which services are blocked and how decisions can be challenged. The report also described an ad-server service that was initially caught in a block and later restored. That is one reported incident, not proof of a widespread pattern. Still, it illustrates why a privacy policy can also be a governance question. If a browser blocks a tool used by publishers, the affected parties need a way to understand what happened and what review, if any, is available. The packet does not establish a specific appeal process.

    Privacy protection and platform power

    Digiday also reported scrutiny of Apple’s advertising business alongside publisher concerns about Safari’s restrictions. That is a reason to ask questions, not evidence that Apple set the policy to benefit its own ads. The distinction matters: users deserve meaningful protection from cross-site tracking, while publishers have a legitimate interest in understanding rules that can affect the tools they use. Nobody needs to choose between privacy and accountability, unless the platform’s preferred menu has only one button and it says “Agree.”

    The practical takeaway

    WebKit’s stated target is third-party identity resolution, not every ad or every form of website personalization. The policy may limit some ways of recognizing people across sites, while decisions about which systems Safari can reach may also affect publisher tools. Apple’s policy should be judged on what it says it does and how clearly its boundaries are explained—not on an unproven theory about motive. Privacy is not a favor from a company, and transparency should not be an optional add-on sold separately from the browser.

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    GPS Is Free; Your Ride Is Not

    ByLee Keybum

    I read the terms, and the satellite found me for free: GPS supplies the location; ride-hailing and delivery apps charge for the convenience built around it. Nobody is charging me for a coordinate. I’m paying for a ride or dinner to show up where that coordinate says I am.

    That’s the platform toll booth: a broadly available public signal helps make the service possible, then a private app sells the useful layer on top. Fair enough, drivers and deliveries aren’t free. But the distinction matters when the bill lands in my lap. The satellite locates dinner perfectly; the app charges extra to rescue it from my own address.

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    The Internet Was Public Before It Was Billions

    ByLee Keybum

    I read the terms, and the tollbooth is already asking me to agree. Public research—from DARPA’s ARPANET to NSF-supported networking—helped lay the internet’s foundations. Now Google, Amazon, and Meta are among the private platforms doing business along that digital road. The contradiction isn’t that companies built nothing; it’s that shared groundwork can open the way to a digital economy where ordinary users still face private gates.

    We encounter the tolls as charges, exchanges of attention, or the price of convenience. The platform calls the gate innovation, then hands us a button marked “agree” and waits for our click like it just invented the road. We helped make the highway possible; now the tollbooth wants credit for the journey and our attention as the fare.

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    Spotify Says It Removed AI ‘Slop’ From Recommendations. The Royalty Question Is Still Playing.

    ByAmanda Lynn

    A cleanup report, not a payout change

    Spotify’s October 20 update says the company removed more than 50 million tracks it classified as “slop” or spam from recommendations this year. Separately, it says it removed more than 75 million spammy tracks from the platform for serious or repeated violations. Those are two different figures, and both are Spotify’s reported totals—not an independently audited head count of the internet’s least welcome backing tracks.

    Spotify also says tracks with indicators of a high probability of being AI-generated are 10 times more likely to fall below its 1,000-stream eligibility threshold. That comparison is company-reported, not independently verified by the sources cited here. And despite the headline-sized cleanup numbers, Spotify did not announce a new royalty threshold on October 20.

    What 1,000 streams actually means

    Spotify’s existing rule has been in effect since April 2024. Its artist support guidance says a track needs at least 1,000 streams in the previous 12 months to be included in Spotify’s recorded-music royalty pool calculation. It is an eligibility rule for that particular pool—not proof that every track under the line earns nothing in every possible context. The rule applies track by track, so a small-audience release can miss the threshold even if its artist has other tracks with larger audiences.

    The money is not a vending machine that drops a fixed number of cents every time someone presses play. Spotify’s royalties guide describes a streamshare system: Spotify calculates payments to rights holders from a pool, based on their share of streams in each market. The song is contributing to a share of a moving pie, not collecting a guaranteed little coin for each spin. How the money reaches artists and other people involved depends on the agreements with their rights holders.

    The small-audience question remains

    Spotify’s anti-spam effort addresses the company’s stated concern about spammy tracks and recommendations. If those tracks are removed, discovery may feel less like a digital junk drawer. But a cleaner shelf and a clearer path to royalties are not the same thing. For an independent artist building a small audience, the practical question is whether a track crosses the existing eligibility line within the rolling 12-month window—and, if it does not, that it is not included in this particular royalty-pool calculation.

    That is the awkward chorus in Spotify’s update. The company says AI-indicated tracks are more likely to miss the threshold, but the same eligibility rule applies to any track that falls short, whatever its origin or artistic ambition. Spotify’s October announcement is a progress report on removals, not a payout-policy change. The song matters; so does the rulebook deciding which tracks are counted in the pool.

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    A Real Rally Assault Got an AI-Generated Photo Makeover

    ByHolden McGroin

    At a Trump rally in Youngstown, Ohio, on October 12, a real altercation became attached to a fabricated visual. An image shared on X on October 14 purported to show a woman in a “Release the Epstein Files” shirt being punched. Fact-checks published October 15 reported that the image was AI-generated. The incident happened; that particular image was not a genuine record of it. The corkboard can keep both facts pinned up without tying them together with premium string.

    Real event, invented image

    Lead Stories reported that an OpenAI tool detected a SynthID watermark and that another AI detector flagged the image. Its fact-check also compared the image with coverage of the incident and an Associated Press photo. That combination matters: the conclusion was not simply “a detector beeped, case closed.” A detector result or watermark finding can be evidence to weigh, but neither should be treated as an infallible witness. Even the algorithm wore a trench coat, apparently, and still needed its paperwork checked.

    Gizmodo also reported that the image was fake, while noting that AI-checking tools produced confusing results. That is a useful brake on detector worship. A tool can produce a clue worth investigating without settling every question about an image’s origin or what it depicts. And a score, by itself, does not show where an image came from or establish whether its specific visual details match the event. Lead Stories’ comparison with reporting and an AP photo gave readers evidence to consider beyond a number floating alone in the fog.

    Check the picture, not just the story

    Contemporaneous coverage helps separate the event from the image attached to it. Al Jazeera published video coverage of the Youngstown rally altercation on October 13, before the October 15 fact-checks. That supports the basic distinction: there was a real incident to report, but the existence of an incident does not authenticate every dramatic picture later offered as proof of what happened. The video and the AP photo are useful context; they are not a magic stamp validating every image associated with the rally. The existence of a fire does not certify every photograph of the smoke.

    That is the little trap in this case. When people already know an event occurred, a fabricated image can borrow that knowledge and arrive wearing the event’s name tag. No need to speculate about who made or shared this one, or why. The practical check is narrower and stronger: compare the specific visual claim with reliable photos, video, and reporting from the time. Ask whether those sources support the details shown—not merely whether the underlying event was real. Follow the thread, but check the knot.

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    AI’s Public Stakeholders Are Still Waiting on the Check

    ByLee Keybum

    AI’s stakeholder agreement has familiar fine print: the public helps lay foundations, then gets treated like a guest when the upside is discussed. Public research, grants, labs and universities can help make future innovation possible; that doesn’t mean any one grant built any one company’s product. It does mean the private-first habit deserves scrutiny. Public contribution should count when AI’s benefits are shared, not fade into the background while wealth and control stay private.

    A public dividend is a proposal, not a check already in the mail. But if taxpayers are important enough to appear in AI’s origin story, they’re important enough to count in the conversation about who benefits. Apparently we got a seat at the launch and missed the dividend meeting because the calendar invite went to founders only.

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    Ahold Delhaize Took Grocery Apps Offline; Shoppers Get the Human-Powered Backup Plan

    ByLee Keybum

    The grocery stores were open. Their digital front doors were having a less productive week. After Ahold Delhaize reported a cybersecurity issue and took some systems offline as a precaution, websites and apps for its U.S. grocery businesses were reported unavailable. The result was a familiar modern contradiction: the building is right there, but the app that helps you plan the trip has left the chat.

    What the company said about the incident

    In an October 13 update, Ahold Delhaize said it had taken some systems offline as a precaution after a cybersecurity issue in its network. The company said its investigation was ongoing and that, at that time, it had no evidence that customer or associate data had been taken. That is a limited update about what investigators knew then—not a final finding that no data was affected, and certainly not proof that data was stolen. Cybersecurity statements are not fortune-telling; they describe the evidence available at a particular point in an investigation.

    The practical disruption was clearer. Grocery Dive reported on October 14 that the websites and apps for the company’s five U.S. grocery banners remained unavailable. It also reported that stores and pharmacies were operating and described customer notices about online orders, including refunds for unfulfilled orders. The outage did not mean every service or location worked the same way, but it did leave digital grocery errands harder to manage for customers relying on those services.

    Open stores, missing digital errands

    CBS Philadelphia reported on October 15 that Giant Food’s website and app were still unavailable, while its stores and gas stations remained open. The report said customers with unfulfilled online orders would receive refunds. That is useful, but a refund is not the same thing as getting the planned groceries at the planned time. A family’s dinner schedule does not automatically accept “transaction reversed” as a side dish.

    This is the quiet dependence built into app-based convenience: when the digital layer fails, people may still be able to walk into a store, but they lose tools that can help organize an errand or place an online order. A missing digital front door can mean checking what is available in another way, changing plans, or making a trip that the app was supposed to help avoid. Those are ordinary inconveniences, not evidence of a wider data impact.

    Ahold Delhaize presented taking systems offline as a precaution in response to a cybersecurity issue. Its October 13 update did not establish a final data-impact finding; the dated reports documented unavailable services and the customer consequences they described. For shoppers, the immediate takeaway is modest but useful: stores being open does not mean every online service is working, and the company’s data statement was a snapshot of an ongoing investigation.

    The backup plan, for now, may involve checking with a store and doing grocery logistics with actual human legs. They remain reliable technology, though they have never once remembered the shopping list without help.

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