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Category: Science & Tech

  • Remember When Bosses Were Forcing Their Workers to Use AI? They’re Now Realizing They Made a Huge Mistake

    Remember When Bosses Were Forcing Their Workers to Use AI? They’re Now Realizing They Made a Huge Mistake

    For years, many bosses have been adamant that employees use AI at all costs — despite research suggesting there’s little to gain from it in terms of productivity, evidence that flies in the face of the tech industry’s repeated promises of a workplace revolution brought on by the tech.

    But now that execs are drowning in meaningless “workslop,” they’re starting to sing a very different tune. As Business Insider reports, one CEO of a tech recruiting company suddenly found herself being inundated with Slack messages from employees that they’d clearly generated using AI, leading her to implement a new policy that strictly forbids the practice for internal communications.

    She’s not the first. One anonymous CEO got so fed up, they threatened to “fire the next person” who blasted them with unedited ChatGPT slop, as Inc reported earlier this year. Instead of fundamentally reshaping white collar industries for the better, it’s finally dawning on bosses that the extensive and often counterproductive use of AI tools could be doing far more harm than good.

    Case in point, in a new study published in the journal The Leadership Quarterly, a team of researchers led by Hebrew University of Jerusalem PhD student Samuel Meyers found that employees who doubled down on using tools like ChatGPT are being trusted less by their employers, actively hurting their chances of promotion.

    That’s even at workplaces where the use of AI tools are still actively being encouraged, suggesting there’s a paradoxical price workers who embrace the tech are paying.

    In a series of experiments, the team asked supervisors to decide whether to trust an employee’s report, while knowing whether they had used AI or not — but not basing their judgment on the quality of the work itself. Employees who didn’t use AI had a 68 percent chance of earning their trust. When they used AI, that number shrank down to just 24 percent.

    “AI is changing not only how we work, but also how we judge the people we work with,” said coauthor and Hebrew University of Jerusalem senior lecturer Yochanan Bigman in a statement. “An employee may use AI to produce better work more efficiently yet still lose their manager’s trust simply because AI was involved.”

    As a result, “organizations need to recognize that adopting AI is not just a technological challenge — it is also a psychological and managerial one,” Bigman added.

    Beyond eroding trust, executives have also found that the use of AI agents and coding tools in particular have sent costs soaring, seriously hurting their companies’ bottom lines and often forcing them to reverse course and cut spending.

    Meanwhile, researchers have yet to detect a meaningful windfall from using AI at work, making it an expensive distraction. Polls have shown that the vast majority of CEOs haven’t seen any productivity gains.

    It’s a particularly unfortunate reality as the job market continues to deteriorate, with or without any AI-related productivity boost.

    Employees are now stuck between a rock in a hard place: either follow their supervisors’ instructions and use AI, or earn their trust by ignoring those calls. Meyers and his colleagues worry this growing tension could give rise to “shadow AI” — undisclosed use of the tech at work, that could further hurt their career prospects.

    More on work and AI: There Are Now Growing Signs That AI Is Hurting Employment in the Job Market

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  • Casio releases new G-Shock watches with unusual dials in more countries

    Casio releases new G-Shock watches with unusual dials in more countries

    Casio is now selling its new G-Shock GAC2500 analog watches in countries across North America and Europe. These octagonal resin watches appeared earlier in 2026, more recently launching alongside the metal bezel GMC2500 watches.

    In the US, two of these Casio G-Shocks, the white GAC2500-7A and the bright orange GAC2500-9A, are available for $145 each. However, the black GAC2500-1A and the dark green GAC2500-3A, also retailing for $145, are out of stock. Users can sign up to receive an email notification when more stock arrives using the ‘notify me’ button on the product page.

    All four of these Casio G-Shock GAC-2500 watches are available to purchase in European countries like the Netherlands, France and Spain. Each model is priced at €129. It is worth noting that the orange GAC-2500-9A is for Casio ID members only. However, you can sign up for a free Casio ID member account relatively easily on the brand’s website.

    The Casio G-Shock GAC-2500 has two analog hands set on the rounded octagonal face, with an unusual “two-eye” design. A seconds indicator in the 9 o’clock position is used for the model’s stopwatch function. The second indicator, in the 3 o’clock position, shows the day of the month. Other features include an LED backlight, a hands shift function and 200 m water resistance.

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  • Questyle to Launch ¥33,000 Dongle DAC ‘MEX’ in December, High SNR Without a Battery — BigGo Finance

    Questyle to Launch ¥33,000 Dongle DAC ‘MEX’ in December, High SNR Without a Battery — BigGo Finance

    Shenzhen, China-based audio equipment maker Questyle will release the MEX, a dongle-type portable DAC/headphone amplifier, in mid-December. The expected price is around ¥33,000 (approximately $210). The company announced the product at a launch event held in Tokyo on November 7. Pre-orders have been open since the same day on the crowdfunding site Mimigoto, with plans starting at ¥26,400 (approximately $170), a discount of up to 20%. Orders will be accepted through November 29.

    The MEX carries two ESS DAC chips, the ES9219Q, and four “SiP current-mode amplifier modules” — Questyle’s patented current-mode amplification circuit packaged as a system-in-package (SiP). It supports native playback of PCM up to 384kHz/32bit and DSD up to 256. The housing is bus-powered, connecting directly to a smartphone or PC, and contains no built-in battery.

    The output terminals consist of one 4.4mm balanced and one 3.5mm single-ended connection. Maximum output is 4V for balanced and 2V for single-ended (both at 300Ω). Gain can be set to three levels — high, medium, and low — and volume adjusts across 64 steps. The 3.5mm jack also supports earphones with a microphone, and the unit itself has a built-in microphone.

    Its biggest feature is two modes that let users switch how sound is shaped. A slide switch on the unit toggles between “PURE mode,” which minimizes signal processing to amplify the original sound, and “TUNE mode,” which allows fine-tuning of sound quality from a smartphone app. The app supports both iOS and Android and has obtained Apple’s “MFi certification.” When connected to an iPhone, the app launches automatically.

    TUNE mode offers a 10-band parametric EQ (PEQ). Frequency, gain, and Q value can be set for each band, and the filter type can be selected from five options: low shelf, peaking, high shelf, low-pass, and high-pass. Adjustments can be made while visually checking the results on a graph, and created settings can be saved and recalled at any time. It also features “DRE (Dynamic Range Enhancement),” which picks up minute sonic details to expand the usable dynamic range, plus two types of DAC digital filters; these work in both PURE and TUNE modes.

    Founder and CEO Wang Fengshuo traveled to Japan to speak at the launch event. According to Wang, the idea for current-mode amplification dates back to 2004, when he was a student at China’s Yangzhou University and accidentally assembled a circuit during a communications circuit experiment that showed excellent characteristics for audio use. After graduating, he first joined a U.S. IC design company, worked on solving issues for mass production, and then founded Questyle in Shenzhen in 2012.

    Whereas ordinary amplifiers amplify music signals in voltage form, current-mode amplification first converts the signal to current, amplifies it, and finally converts it back to voltage. The advantages are said to be that distortion is unlikely even with large signals, and current consumption can be kept low while maintaining a wide bandwidth. Initially, the effort required to match transistor characteristics was a barrier to mass production, but after repeated improvements the circuit has now been miniaturized to a 3mm-square IC chip size.

    Asked why the device adopts a skeleton structure that exposes the board circuitry on the back, Wang said, “Our stance is to show what’s inside for things we’re confident about.” He also indicated plans to build out “Q-Code,” a mechanism allowing users to share sound-quality settings with one another, and to spread the company’s “easy Hi-Fi” concept of letting people enjoy Hi-Fi regardless of whether they have specialized knowledge.

    At the event, audio critic Kenji Nomura and audio/DTM writer Ken Fujimoto explained how to use the sound-tuning features. Nomura noted that conventional dongle-type DACs draw power from the smartphone, making it hard to raise the signal-to-noise ratio, and said the MEX achieves effective noise reduction despite having no battery, and that with its low distortion, PURE mode earns high marks. Fujimoto recommended using the PEQ not to dramatically change the sound but to pinpoint-adjust frequency bands of concern.

    Key specifications are as follows.

    Item Specification
    DAC chip ESS “ES9219Q” ×2
    Amplifier SiP current-mode amplifier module ×4
    Supported formats PCM 384kHz/32bit, DSD256
    Output terminals 4.4mm balanced / 3.5mm single-ended
    Maximum output 4V (balanced), 2V (single-ended, at 300Ω)
    Gain 3 levels (H/M/L)
    Volume adjustment 64 steps
    Power Bus-powered (no built-in battery)
    Expected price Around ¥33,000 (approximately $210)
    Pre-order From ¥26,400 (approximately $170) (through November 29)

    Note: Prices include tax. Pre-orders are being accepted on the crowdfunding site Mimigoto.

    The portable DAC market into which the MEX is being launched has expanded mainly among people who enjoy high-quality earphones with their smartphones. However, prices range widely from a few thousand yen to tens of thousands of yen, and major smartphone makers and Chinese players are entering one after another. Questyle positions its in-house-developed amplifier circuit and rich adjustment features as its differentiation axes. The ¥30,000-plus price places it in the mid-range for dongle types, aiming to capture not only users accustomed to sound tuning but also those who want to correct the quirks of their earphones.

    For the company, the MEX is a product that extends the current-mode technology cultivated in desktop and portable players into a more accessible price range. Along with expanding brand recognition, how firmly it can establish the ongoing touchpoint of sharing settings via the app will likely shape future sales.

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  • OpenAI Hears Voters’ Overwhelming Rebuke To Data Centers, Vows to Build More of Them

    OpenAI Hears Voters’ Overwhelming Rebuke To Data Centers, Vows to Build More of Them

    The “blue tsunami” that swept over the midterm elections made it clear that voters are sick of tech billionaires meddling in politics, opposed to data center construction, and deeply suspicious of the AI industry.

    But OpenAI chief financial officer Sarah Friar apparently didn’t get that memo. In an interview with CNBC on Friday, she vowed that OpenAI would keep pouring money into data center construction so it can please its corporate customers — voters be damned.

    “When I think about the midterms, I need to keep thinking about how do we keep investing to meet that customer demand,” Friar told CNBC’s Sara Eisen in the interview. “It starts early with having built relationships with all of the hyperscalers, and it will continue to mean that we raise capital.”

    While Eisen is focused on “customer demand,” she should probably start paying attention to what voters are asking for. Across 41 local ballot measures on restricting AI data centers, voters supported all but one, Ballotpedia data showed. 56 percent of Americans considered AI and data centers a crucial or major factor in how they voted, according to NBC News exit polls.

    Meanwhile, Democratic challengers flipped seats in multiple states while campaigning against the data center buildout. Texas governor-elect Gina Hinojosa will become the first Democrat to lead the state in over three decades after promising voters to impose a moratorium on new data centers.

    But all that is moot to OpenAI’s Friar — since, in her eyes, people want AI.

    “The demand for AI is real,” Friar said in the interview. “I don’t think anyone’s arguing with that, or if they are, I think it’s a losing argument.”

    In all, she doesn’t believe that the election drastically changes anything for the company. To her, it seems, the backlash to AI is more or less a messaging problem.

    “If the midterm means more focus on data centers and communities, we’re going to keep doing the work to get into those communities and to build trust with them,” Friar said. 

    She put it in more transactional terms elsewhere in the interview: “We are going to keep building out those relationships with communities so we can get the compute we need.”

    If Friar’s intentions are to portray the company as unphased, it’s coming a little too late. In the wake of the elections, OpenAI moved swiftly to announce “new commitments to the communities” where it’s building data centers, which included a promise to no longer use non-disclosure agreements while discussing data center construction with government officials. 

    CEO Sam Altman, meanwhile, showed his poker face still needed improvement by immediately tweeting that “people should always be in control of the future.”

    More on AI: Voters Supported Every Single Anti-Data Center Proposal in America, Except One

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  • Security Researcher Max Justicz Finds Remote Android Takeover With AI in One Afternoon — BigGo Finance

    Security Researcher Max Justicz Finds Remote Android Takeover With AI in One Afternoon — BigGo Finance

    Max Justicz bought a brand-new, fully patched Android phone, pointed the same AI models he’d used on server software at it, and within hours found a way to take it over remotely — sending a malicious message over the cell network to seize control of the device. That finding, and a separate remote root code-execution bug in the package manager behind every Debian and Ubuntu machine, are the strongest evidence yet that the hardest part of security research — finding the flaw — has been radically democratized, according to Justicz, speaking on the MTS podcast.

    “The worst of the worst finding where I could send a malicious message just over cell networks to an Android phone and take it over,” he said, describing the Android result. He is not a full-time security researcher; he has a day job and does bug bounties on the side. That’s precisely his point: what took him “dicking around one afternoon” would, until recently, have demanded expertise built over years.

    The package manager is the most dangerous place to find a bug

    The APT bug came first. Justicz had audited package-manager code by hand years earlier, which gave him the intuition to aim GPT-5.6 at it. After a couple of hours, the model returned a flaw that, by his account, affects all Ubuntu and Debian machines: a man-in-the-middle on the network can force those machines to install arbitrary software as root. “If you compromise the package manager, you compromise everything,” he said.

    He reported the bug in September 2026. The fix and its rollout took five or six weeks — a delay he attributes to people, not engineering, since maintainers were partly on vacation during the window. In his view, a patch could have been written and shipped the same day.

    The more telling signal, he argues, is what the speed of the find says about coverage. “The fact that I was able to find this app bug as quickly as I was kind of indicates to me that no one’s even bothered to aim an AI model at this code,” he said. That gap extends well beyond Linux: he points to radio firmware on an aircraft that decodes signals from other planes as an example of software where the first person to point a model at the code will find whatever is there.

    A patch is not a fix when it takes six weeks

    The episode’s practical through-line is a widening gap between how fast AI can find flaws and how fast humans can fix them. Discovery now runs in hours; patching still runs on human schedules, vacations included.

    Bug Reported Patch status Time to patch
    APT (Debian/Ubuntu package manager) September 2026 Rolled out 5-6 weeks
    Android remote takeover over cellular During the interview period Still rolling out Ongoing at interview time

    For ordinary users, Justicz has little comfort to offer. “I think ordinary users are in a pretty bad spot right now,” he said, and the main lever is using fewer services. His pre-AI advice still holds: stick with major smartphone brands likely to be patched quickly, use major operating systems, and keep everything up to date. He called the current situation “a little bit feudal.”

    His skill advantage is a leading indicator, not a moat

    Justicz refuses to cast himself as an elite. He says he is not one of the world’s best hackers but has had some bug-bounty success, and he has seen a massive uplift from the models. His only edge is taste — knowing which targets are worth aiming a model at — and he expects that edge to evaporate fast.

    “I’ve seen just a massive uplift in what I can do because of these models. And I think that marginal difference due to my skills is just going to quickly diminish to the point where if you’re completely unskilled, you’ll be able to do the same thing,” he said. “I have a little bit of taste in being able to aim the models at things that I think are worth looking at, but what kind of moat is that? I don’t think that’s going to last very long.”

    He describes himself as a canary in the coal mine. A couple of months before the interview, the most skilled hackers were the ones getting extra results from AI; at the time of the interview it was people like him; soon it will be ordinary computer users. He is “pretty confident” of that progression.