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Tag: Artificial Intelligence

  • AI takes on return fraud as holiday returns surge

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    Data from Happy Returns, a UPS-owned reverse logistics company, shows that nearly one in every 10 retail returns in the United States involves fraud. Retailers now lose an estimated $76.5 billion a year to the problem. 

    To slow those losses, Happy Returns, which specializes in boxless in-store returns for online purchases, is testing a new artificial intelligence tool that flags fraudulent returns before refunds go out.

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    NEW IPHONE SCAM TRICKS OWNERS INTO GIVING PHONES AWAY

    Return fraud is costing U.S. retailers billions, with nearly 1 in 10 returns flagged as suspicious, according to data from Happy Returns. (Photo by Tim Boyle/Getty Images)

    How return fraud works in the real world

    Return fraud often looks harmless on the surface. A shopper requests a refund for a legitimate item. Instead of sending back the real product, they ship something cheaper, damaged or completely different. Retailers often issue refunds before anyone inspects the item. That speed allows fraud to slip through and drives up costs.

    Industry data from Happy Returns and the National Retail Federation shows retailers will handle nearly $850 billion in returned goods in 2025, representing almost 16% of total retail sales. According to the same research, an estimated 9% of those returns are fraudulent. The report also finds that many shoppers admit to some form of return policy abuse. Importantly, because Happy Returns conducts in-person item verification and uses AI-powered automated flagging plus audit processes to catch mismatches, the rate of confirmed fraud in its network is much lower than the industry-wide estimate. 

    Why boxless returns changed the equation

    Happy Returns operates nearly 8,000 in-person return drop-off locations inside stores such as Ulta Beauty and Staples, as well as at UPS locations. Shoppers can return eligible items without a box or shipping label, and refunds are often issued quickly after verification. Like any returns channel, fraud attempts can happen, but in-person drop-off, item verification, ongoing flagging and audits help keep confirmed fraud far lower than broader industry averages.

    Happy Returns says its boxless, in-person model already blocks many common fraud tactics, including empty boxes, partial returns and fake tracking numbers. “If you never touch the product, you can’t actually know what’s being returned matches what was sold,” the company says. Everlane says that physical handling alone acts as a deterrent. “Just the fact of knowing an individual will physically handle and verify the product at the Return Bar deters fraudsters from even attempting to commit fraud,” said Jim Green, director of logistics and fulfillment at Everlane. 

    Still, Happy Returns acknowledges that fraud tactics continue to evolve. Lookalike products and knockoffs can closely resemble the real thing, making subtle differences hard to spot without close inspection.

    THE FAKE REFUND SCAM: WHY SCAMMERS LOVE HOLIDAY SHOPPERS

    Woman shopping at a store.

    Happy Returns is testing a new artificial intelligence system designed to flag fraudulent retail returns before refunds are issued. (Photo By Helen H. Richardson/The Denver Post via Getty Images)

    How Return Vision uses AI to detect fraudulent returns

    This holiday season, Happy Returns is piloting its new AI system with select retailers, including Everlane, Revolve and Under Armour, as return volumes spike.

    The new AI tool is called Return Vision. It starts working the moment a shopper initiates a return online. The system looks for unusual patterns across return timing, frequency and location. A single return may appear normal on its own. When those signals overlap in suspicious ways, the return is flagged for review before a refund is issued.

    At drop-off points, workers can scan item barcodes and see photos of what the item should look like. They can reject obvious mismatches on the spot. Once returns reach Happy Returns hubs in California, Pennsylvania and Mississippi, flagged packages are sent to human auditors. The items are opened and photographed, including images of the front, back and identifying labels.

    Those photos are fed back into the AI system, which compares them against official product images and past transaction data. Human teams review the AI assessment and make the final decision. The goal is not automation alone. It is adding multiple layers of review where fraud is harder to hide.

    Early results show how effective AI is at catching return fraud

    While still in pilot, Happy Returns says Return Vision is showing early results. Less than 1% of returns flowing through its network are flagged as high risk. Of those flagged returns, about 10% are ultimately confirmed as fraud. The average prevented loss per confirmed case is just over $200. 

    Happy Returns says the system focuses on high-confidence cases, allowing most shoppers to move through returns without delay. The company notes that the tool does not address every form of abuse, such as wardrobing, when customers return worn items.

    WHY YOUR HOLIDAY SHOPPING DATA NEEDS A CLEANUP NOW

    Shoppers walking with their purchases.

    Boxless, in-person returns are helping retailers cut down on common fraud tactics like empty boxes and fake tracking numbers. (Photographer: David Paul Morris/Bloomberg via Getty Images)

    Why retailers are turning to AI to stop return fraud

    Happy Returns is not alone in turning to AI to stop return fraud. Amazon and FedEx both offer boxless returns and use automated systems to flag risky behavior. The U.S. Postal Service is rolling out similar services. Across retail, 85% of surveyed merchants say they use AI or machine learning to combat fraud. Many say the results have been mixed. Happy Returns says combining behavioral signals with physical product verification helps close gaps that data-only systems often miss.

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    Kurt’s key takeaways

    Retail returns have changed, and so has the fraud that comes with them. Easy drop-offs and instant refunds made life better for shoppers, but they also created new vulnerabilities. Happy Returns is betting that AI, combined with hands-on inspection, can tip the balance back toward retailers. Early results suggest it can help, even if it is not a cure-all. As fraudsters adapt, retailers are learning they have to adapt faster.

    Should retailers slow down instant refunds if it helps stop return fraud, or should convenience always come first? Let us know by writing to us at Cyberguy.com

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  • 5 Best apps to use on ChatGPT right now

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    ChatGPT has quietly changed how it works. It is no longer limited to answering questions or writing text. With built-in apps, ChatGPT can now connect to real services you already use and help you get things done faster. Instead of bouncing between tabs and apps, you can stay in one conversation while ChatGPT builds playlists, designs graphics, plans trips or helps you make everyday decisions. It feels less like searching and more like having a digital assistant that understands what you want.

    That convenience comes with responsibility. When you connect apps, take a moment to review permissions and disconnect access you no longer need. Used the right way, ChatGPT apps save time without giving up control. Here are the five best ChatGPT apps and how to start using them today.

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    THIRD-PARTY BREACH EXPOSES CHATGPT ACCOUNT DETAILS

    ChatGPT apps now let users connect everyday services like music, travel and design tools directly inside one conversation, changing how people get things done. (Philip Dulian/picture alliance via Getty Images)

    How to start using apps inside ChatGPT

    If you have not used ChatGPT apps before, getting started is simple. You do not need any technical setup or extra downloads. Apps appear as tools you can enable inside a conversation.

    App availability and placement may vary by device, model and region.

    iPhone and Android

    • Open the ChatGPT app and sign in
    • Start a new chat
    • Tap the plus (+) or tools icon near the message box
    • Review the available tools or apps shown
    • Select the app you want to use
    • Follow the on-screen prompt to connect your account if needed
    • Start asking ChatGPT to use the app naturally

    Mac and PC

    • Open ChatGPT in your browser or desktop app and sign in
    • Start a new chat
    • Look for available tools or apps in the chat interface
    • Select the app you want to use
    • Follow the on-screen prompt to connect your account if required
    • Start asking ChatGPT to use the app

    Once an app is connected, you can speak naturally. For example, you can ask ChatGPT to create a playlist, design a graphic or help plan a trip.

    1. Apple Music

    Apple Music is now available as an app inside ChatGPT, and it changes how people discover and organize music. Instead of scrolling through endless playlists, you can ask ChatGPT to create one using natural language. For example, you can request a holiday mix without overplayed songs or ask it to find a track you only half remember. ChatGPT searches Apple Music and builds the playlist for you. This integration does not stream full songs inside ChatGPT. It helps Apple Music subscribers find music, create playlists and discover artists faster, then links back to Apple Music for listening. ChatGPT can also activate Apple Music automatically based on your request, so you do not always need to select the app first.

    Note: Apple Music requires an active subscription.

    Why it stands out
    It turns music discovery into a simple conversation instead of a search.

    2. Canva

    Canva’s ChatGPT app helps you turn ideas into visuals fast. You can describe what you want in plain language, and ChatGPT helps generate layouts, captions and design ideas that open directly in Canva. This works well for featured images, social posts and simple marketing graphics.

    Why it stands out: You move from idea to design without starting from scratch.

    3. Expedia

    The Expedia app inside ChatGPT simplifies travel planning. You can ask for flight options, hotel ideas and destination tips in one conversation. ChatGPT also explains tradeoffs so you understand why one option may be better than another.

    Why it stands out: It turns scattered travel research into a clear plan.

    4. TripAdvisor

    TripAdvisor inside ChatGPT helps you plan trips with real traveler insight, not just search results. You can ask for hotel recommendations, top attractions and things to do based on your travel style. ChatGPT pulls in reviews and rankings, then helps narrow choices so you are not overwhelmed. It works especially well when you want honest opinions before booking or planning a full itinerary.

    Why it stands out: It combines real reviews with conversational guidance to make travel decisions easier.

    5. OpenTable

    OpenTable inside ChatGPT removes the guesswork from dining decisions. You can ask for restaurant recommendations by location, cuisine and vibe. From there, ChatGPT helps narrow choices and links you directly to reservations through OpenTable.

    Why it stands out: It saves time when choosing where to eat, especially on busy nights.

    How to disconnect apps from ChatGPT

    If you no longer use an app connected to ChatGPT, you can disconnect it at any time. Removing access helps limit data sharing and keeps your account more secure.

    iPhone and Android

    • Open the ChatGPT app and sign in
    • Tap the menu icon
    • Click your profile icon
    • Scroll down and tap Apps (It might say Connected appsTools or Integrations)
    • Select the app you want to remove
    • Tap Disconnect or Remove access
    • Confirm your choice if asked to

    Mac and PC

    • Open ChatGPT in your browser or desktop app and sign in
    • Click your profile icon
    • Select Settings
    • Open Apps (It might say Connected appsTools or Integrations)
    • Choose the app you want to disconnect from
    • Click Disconnect or Remove access
    • Confirm the change if asked to

    Once disconnected, ChatGPT will no longer access that app. You can reconnect later if you decide to use it again.

    MALICIOUS BROWSER EXTENSIONS HIT 4.3M USERS

    ChatGPT and Canva logos.

    Built-in apps turn ChatGPT from a chatbot into a digital assistant that can plan trips, build playlists and help make decisions faster. (Nikolas Kokovlis/NurPhoto via Getty Images)

    A quick privacy checklist for ChatGPT users

    Using apps inside ChatGPT is convenient, but it is smart to review your settings from time to time. This checklist helps you reduce risk while still enjoying the features. 

    1) Review connected apps regularly and remove ones you no longer use

    Connected apps can access limited account data while active. If you stop using an app, disconnect it. Fewer connections reduce your overall exposure and make account reviews easier.

    2) Only connect apps you trust and recognize

    Stick to well-known apps from established companies. If an app name looks unfamiliar or feels rushed, skip it. When in doubt, research the app before connecting it to your ChatGPT account. 

    3) Check account permissions after major app updates

    Apps can change how they work after updates. Take a moment to review permissions if an app adds new features or requests additional access. This habit helps you spot changes early.

    4) Avoid sharing sensitive personal or financial details in chats

    Even trusted tools do not need your Social Security number, bank details or passwords. Keep chats focused on tasks and ideas. Treat ChatGPT like a public workspace, not a private vault. 

    5) Use a strong, unique password for your ChatGPT account

    Your ChatGPT password should not match any other account. A password manager can help generate and store strong credentials. This step alone blocks many common attacks. Consider using a password manager, which securely stores and generates complex passwords, reducing the risk of password reuse.

    Next, see if your email has been exposed in past breaches. Our #1 password manager (see Cyberguy.com) pick includes a built-in breach scanner that checks whether your email address or passwords have appeared in known leaks. If you discover a match, immediately change any reused passwords and secure those accounts with new, unique credentials.

    Check out the best expert-reviewed password managers of 2025 at Cyberguy.com.

    6) Turn on two-factor verification if available

    Two-factor verification (2FA) adds a second layer of protection. Even if someone gets your password, they still cannot access your account without the extra code. Enable it whenever possible.

    REAL APPLE SUPPORT EMAILS USED IN NEW PHISHING SCAM 

    ChatGPT logo in front of "AI."

    Connecting apps inside ChatGPT saves time, but users should regularly review permissions and disconnect tools they no longer need. (Jakub Porzycki/NurPhoto via Getty Images)

    7) Use strong antivirus software on all your devices

    Antivirus software protects against malicious links, fake downloads and harmful browser extensions. Keep it updated and allow real-time protection to run in the background. Strong antivirus software helps protect against fake ChatGPT links, lookalike apps and malicious extensions designed to steal login details. Choose a trusted provider and keep automatic updates turned on.

    The best way to safeguard yourself from malicious links that install malware, potentially accessing your private information, is to have strong antivirus software installed on all your devices. This protection can also alert you to phishing emails and ransomware scams, keeping your personal information and digital assets safe.

    Get my picks for the best 2025 antivirus protection winners for your Windows, Mac, Android & iOS devices at Cyberguy.com

    8) Watch for fake ChatGPT links and scam downloads

    Scammers often create fake ChatGPT downloads and lookalike offers. Always access ChatGPT through its official app or website. Never enter your login details through links sent by email or text.

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    Kurt’s key takeaways

    ChatGPT is becoming a central hub for everyday tasks. With apps like Apple Music, Canva, Expedia, TripAdvisor and OpenTable, you can plan, create and decide without jumping between multiple platforms. That shift saves time and cuts down on friction. It also makes technology feel more helpful and less overwhelming. The best ChatGPT apps solve real problems, from discovering music to planning trips and choosing where to eat. As more apps roll out, ChatGPT will feel less like a chatbot and more like a true digital assistant. Just remember to stay smart, review connected apps and watch for scams.

    If ChatGPT could replace three apps you use every day, which ones would you choose and why? Let us know by writing to us at Cyberguy.com

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  • Draft Chinese AI Rules Outline ‘Core Socialist Values’ for AI Human Personality Simulators

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    As first reported by Bloomberg, China’s Central Cyberspace Affairs Commission issued a document Saturday that outlines proposed rules for anthropomorphic AI systems. The proposal includes a solicitation of comments from the public by January 25, 2026.

    The rules are written in general terms, not legalese. They’re clearly meant to encompass chatbots, though that’s not a term the document uses, and the document also seems more expansive in its scope than just rules for chatbots. It covers behaviors and overall values for AI products that engage with people emotionally using simulations of human personalities delivered via “text, image, audio, or video.”

    The products in question should be aligned with “core socialist values,” the document says.

    Gizmodo translated the document to English with Google Gemini. Gemini and Bloomberg both translated the phrase “社会主义核心价值观” as “core socialist values.”

    Under these rules, such systems would have to clearly identify themselves as AI, and users must be able to delete their history. People’s data would not be used to train models without consent.

    The document proposes prohibiting AI personalities from:

    • Endangering national security, spreading rumors, and inciting what it calls “illegal religious activities.”
    • Spreading obscenity, violence, or crime
    • Producing libel and insults
    • False promises or material that damages relationships
    • Encouraging self harm and suicide
    • Emotional manipulation that convinces people to make bad decisions
    • And Soliciting sensitive information

    Providers would not be allowed to make intentionally addictive chatbots, or systems intended to replace human relationships. Elsewhere, the proposed rules say there must be a pop-up at the two hour mark reminding users to take a break in the event of marathon usage.

    These products also have to be designed to pick up on intense emotional states and hand the conversation over to a human if the user threatens self-harm or suicide.

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  • DoorDash launches Zesty, an AI app for finding local food

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    DoorDash wants to help you decide where to eat, not just how your food arrives. The company has launched Zesty, a new artificial intelligence-powered social app built to make finding local restaurants faster and easier. 

    Zesty is now in public testing in the San Francisco Bay Area and New York. Instead of scrolling through endless reviews, menus and social videos, the app lets you ask an AI chatbot for recommendations in plain language.

    Think of it as a digital concierge for food discovery.

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    How Zesty works

    Once you open Zesty and sign in with your DoorDash account, the experience feels familiar and simple. You see nearby restaurants and a chat box where you can type exactly what you want. DoorDash says users can ask prompts like:

    The app blends AI search with social discovery, showing photos, comments, and saved spots shared by other diners.    (Kurt “CyberGuy” Knutsson)

    HOW RESTAURANT RESERVATION PLATFORM OPENTABLE TRACKS CUSTOMER DINING HABITS

    • A low-key dinner in Williamsburg that’s good for introverts
    • Brunch spots good for groups
    • Romantic dinner with a vintage feel

    The AI then curates recommendations by pulling information from DoorDash data, Google Maps, TikTok, Reddit and other sources. According to DoorDash co-founder Andy Fang, the goal is to surface the best suggestions from across the web in one place. Each recommendation includes context such as ratings, social buzz and where the suggestion came from. DoorDash says the results do not imply sponsorships or paid placements.

    A social network built around food

    Zesty also adds a social layer. Users can post photos, leave comments, follow other diners and share saved spots with friends. If you find a restaurant that looks promising, you can bookmark it for later or send it to someone planning dinner with you. This makes Zesty feel less like a search engine and more like a food-focused social network. It is designed for people who enjoy discovering places through other people’s experiences, not just star ratings. For DoorDash, this is a clear shift toward community-driven discovery.

    Why DoorDash built Zesty

    DoorDash wants to remove friction from the decision process. Instead of bouncing between Google, TikTok, Yelp and delivery apps, Zesty aims to bring everything together in a single guided experience. That approach also aligns with a broader trend. More people already use AI tools like ChatGPT and Gemini to plan meals and trips. Zesty aims to offer that same convenience with a strong local and social focus.

    DoorDash sign

    Zesty lets users ask for restaurant recommendations in natural language instead of scrolling through endless reviews and menus. (Smith Collection/Gado/Getty Images)

    “At DoorDash, we’re always looking for new ways to help people connect with the best of their communities,” a company spokesperson told CyberGuy. “We’re piloting an app called Zesty to make it easier to discover great nearby restaurants, coffee shops, bars, and more through personalized search and social sharing. Zesty is now in public beta in San Francisco and New York, and we’re excited to learn from early testers as we keep shaping what local discovery can look like.”

    Of course, Zesty faces an uphill climb. Many users already rely on Google Maps or existing social apps to find restaurants. Some may not want to download another standalone app, even if it promises better recommendations. Still, Zesty could appeal to users who enjoy food discovery as a social activity. For them, a dedicated network built around local dining may feel more useful than generic search results. DoorDash appears willing to test that idea and see how users respond. For now, the company is focused on getting people to use the app, learning what works, and fine-tuning its matching engine. Once that experience feels right, Zesty will expand to more cities.

    WOULD YOU EAT AT A RESTAURANT RUN BY AI?

    Part of DoorDash’s bigger expansion plan

    Zesty is not an isolated experiment. It fits into DoorDash’s broader push beyond food delivery. Earlier this year, DoorDash rolled out features for in-person dining reservations and in-store rewards. The company also continues to invest heavily in automation and AI-driven logistics

    We reported a few months ago on another major innovation from DoorDash: Dot, its fast new autonomous delivery robot. Dot is designed for short local trips and runs on an AI-powered delivery platform that decides whether an order should be handled by a Dasher, a robot or another method. Together, Zesty and Dot show how DoorDash is trying to own more of the local commerce experience, from discovery to delivery.

    What this means to you

    If you enjoy trying new restaurants, Zesty could save you time and decision fatigue. Instead of reading dozens of reviews, you can ask for exactly what you want and get curated suggestions instantly. For casual diners, the app may feel unnecessary if Google already works fine. For food lovers who like sharing finds and following others with similar tastes, Zesty could become a useful daily tool. It also signals where local discovery may be heading. AI-driven recommendations paired with social proof could soon replace traditional review hunting.

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    Food delivery apps seen on a screen, including DoorDash, GrubHub, Uber Eats, Caviar, Postmates and Seamless.

    Zesty is now in beta in San Francisco and New York as DoorDash tests and refines its personalized matching experience. (iStock)

    Kurt’s key takeaways

    Zesty shows DoorDash experimenting with how people choose where to eat, not just how food gets delivered. By combining AI search with social sharing, the company is testing a more conversational and community-driven approach to local discovery. Whether Zesty becomes essential or stays niche will depend on how well it delivers meaningful recommendations. Still, it highlights DoorDash’s growing ambition to shape more parts of our everyday local life.

    Would you trust an AI-powered social app to pick your next favorite restaurant, or do you still prefer finding places the old-fashioned way? Let us know by writing to us at Cyberguy.com.

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  • Nvidia Deal With Groq Called ‘Strategic’ Amid Rise Of Custom AI Chips

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    Nvidia’s (NVDA) technology licensing deal with Groq and hiring of the AI start-up’s key personnel is a strategic move as the focus of artificial intelligence moves from training to inference, Wall Street analysts say. Nvidia stock rose on Friday. Groq announced late Wednesday that it had entered into a nonexclusive inference technology licensing agreement with Nvidia. As part of the…

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  • Fox News AI Newsletter: How we can live with AI without losing our humanity

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    Welcome to Fox News’ Artificial Intelligence newsletter with the latest AI technology advancements.

    IN TODAY’S NEWSLETTER:

    – Here’s how we can live and work with artificial intelligence without losing our humanity
    – Amazon adds controversial AI facial recognition to Ring
    – New US military GenAI tool ‘critical first step’ in future of warfare, says expert

    OPINION: The Vatican’s recent document on artificial intelligence, Antiqua et Nova — “The Old and the New” — is not a technical treatise, but a philosophical reminder: The advance of AI provokes in new ways fundamental questions about the nature of intelligence and the kind of people we must become to wield powerful tools responsibly.

    AI messaging

    The Vatican’s document on artificial intelligence and comments from Pope Leo XIV frame AI as a powerful human achievement while warning that easy access to information can undermine genuine understanding, especially among the young. (iStock)

    ‘FAMILIAR FACES’: Amazon’s Ring video doorbells are getting a major artificial intelligence (AI) upgrade, and it is already stirring controversy. The company has started rolling out a new feature called Familiar Faces to Ring owners across the United States. Once enabled, the feature uses AI-powered facial recognition to identify people who regularly appear at your door. Instead of a generic alert saying a person is at your door, you might see something far more personal, like “Mom at Front Door.” On the surface, that sounds convenient.

    ‘FORGE AHEAD’: The recently launched “GenAI” tool for U.S. service members and Department of War workers is a “critical first step” in the future of warfare, according to a military expert. This month, the Pentagon announced the launch of GenAI.mil, a military-focused AI platform powered by Google Gemini. Secretary of War Pete Hegseth said the platform is designed to give U.S. military personnel direct access to AI tools to help “revolutioniz[e] the way we win.”

    Secretary of War Pete Hegseth speaks at a Pentagon press conference

    Secretary of War Pete Hegseth addressed reporters during a Pentagon news conference in Arlington, Virginia, on June 26, 2025. (Andrew Harnik/Getty Images)

    POWER SHIFT: China is racing ahead of the U.S. in artificial intelligence (AI), bypassing regulatory roadblocks that O’Leary Ventures Chairman Kevin O’Leary warns are leaving America dangerously behind.

    THE NEXT FRONTIER: Google executive Royal Hansen responded to some lawmakers’ calls to slow the development of artificial intelligence (AI) in the U.S., emphasizing the need to develop and use the technology responsibly rather than fall behind other countries.

    FEED FREEDOM NOW: Instagram is rolling out a new tool called Your Algorithm that gives you direct control over the videos that fill your Reels tab. Your interests shift as time moves on. Now your feed can shift with you in real time.

    ‘AHEAD OF THE GAME’: FBI Director Kash Patel said Saturday the agency is ramping up its use of artificial intelligence (AI) tools to counter domestic and international threats. In a post on X, Patel said the FBI has been advancing its technology, calling AI a “key component” of its strategy to respond to threats and stay “ahead of the game.”

    Patel addresses White House press briefing about China visit

    FBI Director Kash Patel speaks during a press briefing at the White House in Washington, D.C., on Nov. 12, 2025. (AP Photo/Evan Vucci)

    WHO’S IN CHARGE?: A week after Time Magazine named the “Architects of AI” as Person of the Year, the latest Fox News national survey of registered voters finds broad support for careful development of artificial intelligence — yet little agreement on who should regulate it. The poll, released Thursday, finds 8 in 10 voters favor a careful approach to developing AI to manage potential risks to the U.S., while 2 in 10 prefer rapid advancement to stay ahead of countries like China.

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    Stay up to date on the latest AI technology advancements and learn about the challenges and opportunities AI presents now and for the future with Fox News here.

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  • The Main Street AI Playbook

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    Recently, I fed a legal contract into ChatGPT and asked it to spot issues and rewrite a paragraph with my feedback. Minutes later, it completed the task about as well as most lawyers I’ve worked with.

    I still sent it to my attorney for review. His usual five-hour bill? Cut down to one hour. That’s an 80 percent cost reduction.

    OpenAI recently announced they’ll be working with investment banks to create AI agents that can do an investment banker’s job. The speculation is that AI companies are going to do this to every job vertical. Doctors. Lawyers. Accountants. Other white-collar work.

    There’s a possibility for massive disruption, so how can you prepare? With these three strategies: ownership, dispersion, and a tech-first approach.

    Here’s a paradox that creates opportunity: While everyone’s running to catch the AI bullet train in Silicon Valley, there’s real money in wiring yesterday’s businesses with tomorrow’s technology.

    The dispersion gap

    Silicon Valley moves at light speed. Main Street? It’s walking at a leisurely pace.

    The contrast is staggering. ChatGPT hit one million users in five days—the fastest adoption in history. Yet as of 2022, 27 percent of American small businesses did not have a website. Even among those that do, most are running on decade-old technology.

    Main Street adoption happens slowly. The first ecommerce transaction dates back to 1994, but it took until 2015 for ecommerce to make up 10 percent of retail purchases. By 2024, that climbed to 16.1 percent.

    This gap between invention and integration is an AI arbitrage opportunity.

    However, the last person to get fired in any business is the owner. They also accrue the profit from productivity gains.

    The thesis is simple: Buy, run, or operate low-tech Main Street businesses. Integrate AI. Dominate your local market while competitors are still working on setting up a Facebook page.

    Why yesterday’s businesses win

    While public technology companies trade at 44.4 times earnings, I’ve repeatedly found profitable Main Street businesses that sell for 32 percent returns at 3-4 times earnings. Someone who invests in Main Street buys actual revenue, real customers, cash flowing assets—not a pitch deck and a prayer.

    HVAC companies. Plumbing services. Main Street business services. They’re printing cash while startups burn through Series B funding, and the stock market sits on Everest with NVIDIA matching the total asset value of small countries.

    And those same Main Street businesses all have problems AI solves. Customer scheduling? Automate it. Billing headaches? Gone. Phone calls eating up staff time? Let AI handle it.

    I’ve acquired eight businesses, turning them into passive money machines, and lately I’ve been integrating AI into every one of them.

    Add the tech layer, and you’re suddenly the most efficient operator in a sleepy market. Your margins expand while your competitors’ tech stack is stuck in 2015.

    The 3-step playbook

    The owner should be tired. Ready to exit. Undervaluing what they’ve built because they can’t see past the daily grind.

    Step 2: Rewire a company for AI

    First, document all processes. While doing this, figure out how much time each process takes and what can be handed off to AI agents and automated workflows.

    AI agents can do incredible things. Bookkeeping? Financial auditing? Appointment setting? Automate it.

    The result? I’ve seen 20-40 percent efficiency gains. Your cost structure drops while service quality improves. Customers get faster responses. Staff focuses on high-value work. I’ll re-invest the time savings into growth to supercharge the business.

    Step 3: Build your moat

    Now you’re the tech-first operator in a sleepy, local market. Your competitors can’t keep up—they lack the knowledge and urgency.

    Your margins expand while theirs compress. You can outbid them for talent, outspend them on marketing, and generate superior returns.

    Best part? You’ve built a repeatable, scalable playbook, and the sky’s the limit.

    You have maybe 36 months before this becomes common practice. My lawyer’s bill got cut by 80 percent. In three years, every Main Street business will face the same pressure.

    The question isn’t whether AI will transform local markets. It’s whether you will be the one who profits from the transformation.

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  • Supercharge Your Retail and CPG AI Strategy in 2026

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    As a C-suite advisor working closely with retail and consumer packaged goods (CPG) brands, I am seeing a consistent pattern across the industry. Leaders recognize that AI has the power to transform how they forecast demand, manage supply chains, engage consumers, and operate stores and plants. Yet despite high ambition and extensive experimentation, most organizations are not capturing enterprise level value. Many have multiple pilots running, but few have built the operating systems required to scale AI responsibly and profitably. At the same time, AI capabilities are advancing at a pace that outstrips traditional planning and deployment cycles. To win in 2026, retail and CPG companies must shift from fragmented activity to an integrated, disciplined approach that makes AI a core driver of growth, speed, and resilience.

    This shift starts with process intelligence. Real value emerges only when AI is anchored in an accurate understanding of how work happens across manufacturing, distribution, stores, digital platforms, and consumer interactions. Combined with targeted prioritization, workflow redesign, and continuous iteration, process intelligence becomes the backbone of an AI strategy that consistently delivers measurable outcomes. The following four box framework reflects the highest performing organizations’ practices and provides a clear roadmap for retail and CPG leaders ready to accelerate impact.

    Box one: Map operational truth with process intelligence

    Across retail and CPG operations, work rarely flows as designed. Stores follow multiple replenishment patterns depending on staffing. Plants exhibit microvariations in setup and changeover that suppress throughput. Digital channels contain subtle breaks that increase abandonment and returns. Supply chains absorb friction in ways that leaders cannot easily see. Process intelligence reveals these realities by reconstructing actual workflows, highlighting variation, bottlenecks, and inefficiencies.

    This visibility is essential because the companies capturing the greatest AI returns are those that redesign workflows during deployment. They cannot redesign without understanding the truth. Process intelligence shows precisely where AI should intervene and what must change for AI to succeed. Examples include identifying that most out-of-stocks originate from backroom accuracy issues rather than forecasting, discovering that promotional execution varies significantly by retail partner, or uncovering that production delays stem from a pattern of short stoppages overlooked in manual reporting.

    With this fact base, leaders can move beyond assumptions and direct AI investment toward the highest leverage points.

    Box two: Prioritize AI where margin, growth, and friction collide

    The most common mistake retail and CPG leaders make is spreading AI efforts too thin. High performers take the opposite approach. They identify where AI can most meaningfully shape margins, growth, and consumer experience, then channel resources into those opportunities. A structured intake and evaluation model ensures that the best ideas rise to the top based on economic potential and feasibility, rather than enthusiasm alone.

    For retailers, high value opportunities often include demand forecasting, allocation, replenishment, labor optimization, personalization, and service automation. For CPG companies, predictive maintenance, inventory planning, trade optimization, supply chain synchronization, and accelerated insights generation offer the strongest returns.

    A disciplined prioritization framework evaluates impact. It also evaluates feasibility and data readiness, in addition to reuse potential. This prevents wasted energy and ensures AI is deployed where it can reshape performance. Examples include targeting AI toward rework loops in retail contact centers, applying machine learning to optimize trade spend effectiveness, or using predictive models to reduce factory downtime. This focus ensures that AI investments meaningfully influence financial and competitive outcomes.

    Box three: Redesign workflows to embed AI, not sit alongside it

    AI only creates lasting value when it is woven into the flow of work. Retail and CPG companies must redesign processes so AI informs or automates key decisions and employees know how to collaborate with these systems. Workflow redesign transforms AI from a tool into a capability.

    In retail, this might include closed loop replenishment systems that link shelf scanning, automated ordering, and dynamic labor scheduling. In customer experience, AI might be embedded directly into omnichannel journeys to improve guidance. It could be used to reduce returns and accelerate resolution. In CPG operations, predictive quality and yield models may be integrated into line operations, while agent-based systems support procurement, logistics, and planning teams.

    Workflow redesign also requires data consistency, clear decision rights, and ongoing human oversight. Employees must understand how to supervise AI and refine its outputs. When workflows are redesigned, AI drives speed, accuracy, and consistency while unlocking new capacity for higher value work.

    Box four: Build continuous governance, measurement, and iteration

    Retail and CPG operate in highly dynamic environments shaped by promotions, seasonality, supply volatility, and shifting consumer sentiment. AI systems must be equally dynamic. Continuous evaluation and strong governance are needed, while rapidly iterating to ensure that AI remains accurate and effective.

    Leaders must establish governance structures that clarify decision rights, protect data, and accelerate approvals. They must define clear performance indicators such as grounding accuracy, reliability, response time, cost efficiency, and business impact. AI systems should be monitored continuously to detect drift and unexpected behavior. They also monitor performance degradation.

    Iteration closes the loop. Retailers may retrain demand models weekly to capture new patterns, refine pricing recommendations when overrides reveal model gaps, or adjust customer service workflows based on real world usage. CPG brands may refine predictive maintenance models based on emerging line performance or recalibrate trade algorithms based on retailer specific dynamics.

    2026 and beyond

    In my role, I see unmistakable momentum paired with equally significant risk. AI is poised to redefine the future of both sectors, yet only the organizations that establish the operating systems required for scale will capture its full value. Process intelligence provides the clarity needed to understand how work truly happens. Rigorous prioritization ensures that investment flows to the opportunities with the greatest strategic return. Workflow redesign creates the structural conditions for AI to operate effectively in that workflow. Continuous iteration enables systems and teams to adapt as markets and operations evolve. Together, these capabilities form a disciplined, enterprise ready AI strategy capable of delivering durable competitive advantage.

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  • ChatGPT’s GPT-5.2 is here, and it feels rushed

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    OpenAI, the company behind ChatGPT, has moved at an unusually fast pace in 2025. According to the company, it launched GPT-5 in August, followed by GPT-5.1 in November. Now, just weeks later, GPT-5.2 has launched with familiar claims of being the smartest and most capable ChatGPT yet.

    At first glance, the rapid rollout might seem surprising. But there’s context behind it. OpenAI CEO Sam Altman has reportedly called a “code red” inside the company, urging teams to move faster on improving ChatGPT. That push comes as competition heats up. Google recently released Gemini 3, which reportedly outperformed ChatGPT on several artificial intelligence benchmarks and delivered stronger image generation. At the same time, Anthropic’s Claude continues to advance quickly.

    Against that backdrop, GPT-5.2 feels less like a routine upgrade and more like a strategic response. So what actually changed in GPT-5.2, and why does OpenAI say it matters?

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    AMAZON ADDS CONTROVERSIAL AI FACIAL RECOGNITION TO RING

    OpenAI CEO Sam Altman looks on as he takes a lunch break, during the Federal Reserve’s Integrated Review of the Capital Framework for Large Banks Conference in Washington, D.C., July 22, 2025. (REUTERS/Ken Cedeno)

    What exactly is GPT-5.2

    GPT-5.2 is the newest version in OpenAI’s flagship 5-series of large language models. Like its predecessor, it includes two default variants. GPT-5.2 Instant is designed for everyday chatting and web searches. GPT-5.2 Thinking is meant for more complex tasks like long reasoning chains and multi-step problem solving. These two models are now the default for all ChatGPT users, including free users. They replace GPT-5.1 Instant and Thinking entirely. If you are using ChatGPT today, you are already using GPT-5.2, whether you realize it or not.

    What OpenAI says GPT-5 brings to ChatGPT

    At the same time, OpenAI continues to position GPT-5 as “expert intelligence for everyone.” The company says GPT-5 delivers stronger performance across math, science, finance, law and other complex subjects. In OpenAI’s view, ChatGPT now acts more like a team of on-demand experts than a basic chatbot. To support that claim, OpenAI points to practical examples. These include better coding help, more expressive writing support, clearer health-related explanations and improved safety and accuracy. The company showcases use cases such as generating app code, writing speeches, explaining medications and correcting mistakes in user-submitted images. In theory, GPT-5.2 builds on that same foundation. However, while OpenAI emphasizes deeper thinking and more reliable answers, those gains remain subtle for many everyday users.

    What new features does GPT-5.2 add?

    Here’s the short answer. None. GPT-5.2 does not introduce new tools, interfaces, or headline features. Instead, OpenAI describes a series of behind-the-scenes improvements that supposedly make ChatGPT faster, smarter and more capable. According to OpenAI, GPT-5.2 performs better at:

    • Building presentations
    • Completing complex projects
    • Creating spreadsheets
    • Understanding long context windows
    • Interpreting images
    • Using tools more effectively
    ChatGPT app

    Kurt Knutsson reviews the new features in ChatGPT-5.2. (Kurt “CyberGuy” Knutsson)

    OpenAI also released new benchmarks showing GPT-5.2 outperforming GPT-5.1 and competing models by small margins. However, big numbers on charts do not always translate into noticeable improvements for real users.

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    Why testing chatbot improvements is tricky

    Evaluating chatbot upgrades is harder than it sounds. Responses can vary widely even when prompts stay the same. A model might excel at one task and struggle with a nearly identical one just moments later. On top of that, OpenAI’s 5-series models already perform at or near the top of the field. When performance starts that high, meaningful gains become harder to detect. With that in mind, we tested GPT-5.2, and in most tests, it behaved almost identically to GPT-5.1.

    Why benchmarks don’t tell the full story

    OpenAI’s benchmarks show modest gains for GPT-5.2. That matters for researchers and developers working at scale. Still, even advanced users may struggle to see practical benefits. Other companies have delivered clearer upgrades. Google’s Gemini Nano Banana Pro model shows obvious gains in AI image generation and editing. Those improvements are easy for anyone to test and verify. By contrast, GPT-5.2’s changes feel abstract. They exist mostly on paper rather than in daily use.    

    What this means to you

    If you pay for ChatGPT, there’s little downside to using GPT-5.2. It replaces GPT-5.1 in the model lineup and generally performs at least as well in everyday use. Free users don’t have much choice either, as model access is handled automatically. For most people, the experience feels familiar and stable.

    The picture shifts slightly for programmers and those who use it for business. Early pricing details suggest GPT-5.2 may cost roughly 40 percent more per million tokens than GPT-5.1, depending on usage tier and access method. That makes testing important before committing at scale.

    Woman on smartphone in Italy

    ChatGPT-5.2 works fine but may not feel exciting, Kurt Knutsson writes. (Michael Nguyen/NurPhoto via Getty Images)

    In short, GPT-5.2 works fine. It simply may not feel exciting.

    KEVIN O’LEARY WARNS CHINA ‘KICKING OUR HEINIES’ IN AI RACE AS REGULATORY ROADBLOCKS STALL US

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    Kurt’s key takeaways

    GPT-5.2 feels like a model released under pressure rather than inspiration. It performs well, stays reliable, and moves forward in measurable ways. Still, it doesn’t deliver the kind of clear progress many people expect from a new version number. OpenAI remains a leader in AI, but competition is closing in fast. As rivals roll out more noticeable improvements, small updates may no longer be enough to stand out. For now, GPT-5.2 feels less like a breakthrough and more like OpenAI holding its ground.

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    Should AI companies slow down releases until improvements feel more meaningful? Let us know by writing to us at Cyberguy.com.

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  • Amazon adds controversial AI facial recognition to Ring

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    Amazon’s Ring video doorbells are getting a major artificial intelligence (AI) upgrade, and it is already stirring controversy.

    The company has started rolling out a new feature called Familiar Faces to Ring owners across the United States. Once enabled, the feature uses AI-powered facial recognition to identify people who regularly appear at your door. Instead of a generic alert saying a person is at your door, you might see something far more personal, like “Mom at Front Door.” On the surface, that sounds convenient.

    Privacy advocates, however, say this shift comes with real risks.

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    Ring’s new Familiar Faces feature uses AI facial recognition to identify people who regularly appear at your door and personalize alerts. (Chip Somodevilla/Getty Images)

    How Ring’s Familiar Faces feature works

    Ring says Familiar Faces helps you manage alerts by recognizing people you know. Here is how it works in practice. You can create a catalog of up to 50 faces. These may include family members, friends, neighbors, delivery drivers, household staff or other frequent visitors. After labeling a face in the Ring app, the camera will recognize that person as they approach. Anyone who regularly passes in front of your Ring camera can be labeled by the device owner if they choose to do so, even if that person is unaware they are being identified.

    From there, Ring sends personalized notifications tied to that face. You can also fine-tune alerts on a per-face basis, which means fewer pings for your own comings and goings. Importantly, the feature is not enabled by default. You must turn it on manually in the Ring app settings. Faces can be named directly from Event History or from the Familiar Faces library. You can edit names, merge duplicates or delete faces at any time.

    Amazon says unnamed faces are automatically removed after 30 days. Once a face is labeled, however, that data remains stored until the user deletes it.

    Why privacy groups are pushing back

    Despite Amazon’s assurances, consumer protection groups and lawmakers are raising alarms. Ring has a long history of working with law enforcement. In the past, police and fire departments were able to request footage through the Ring Neighbors app. More recently, Amazon partnered with Flock, a company that makes AI-powered surveillance cameras widely used by police and federal agencies. Ring has also struggled with internal security. In 2023, the FTC fined Ring $5.8 million after finding that employees and contractors had unrestricted access to customer videos for years. The Neighbors app previously exposed precise home locations, and Ring account credentials have repeatedly surfaced online. Because of these issues, critics argue that adding facial recognition expands the risk rather than reducing it.

    Electronic Frontier Foundation (EFF) staff attorney Mario Trujillo tells CyberGuy, “When you step in front of one of these cameras, your faceprint is taken and stored on Amazon’s servers, whether you consent or not. Today’s feature to recognize your friend at your front door can easily be repurposed tomorrow for mass surveillance. It is important for state regulators to investigate.” The Electronic Frontier Foundation is a well-known nonprofit organization that focuses on digital privacy, civil liberties and consumer rights in the tech space. 

    WASHINGTON COURT SAYS FLOCK CAMERA IMAGES ARE PUBLIC RECORDS

    Photo of a mounted ring camera.

    Once a face is labeled by the device owner, Ring can replace generic notifications with named alerts tied to that individual. (CyberGuy.com)

    Where the feature is blocked and why that matters

    Legal pressure is already limiting where Familiar Faces can launch. According to the EFF, privacy laws are preventing Amazon from offering the feature in Illinois, Texas and Portland, Oregon. These jurisdictions have stricter biometric privacy protections, which suggests regulators see facial recognition in the home as a higher-risk technology. U.S. Senator Ed Markey has also called on Amazon to abandon the feature altogether, citing concerns about surveillance creep and biometric data misuse.

    Amazon says biometric data is processed in the cloud and not used to train AI models. The company also claims it cannot identify all locations where a face appears, even if law enforcement asks. Still, critics point out the similarity to Ring’s Search Party feature, which already scans neighborhoods to locate lost pets.

    We reached out to Amazon for comment but did not receive a response before our deadline.

    Ring’s other AI feature feels very different

    Not all of Ring’s AI updates raise the same level of concern. Ring recently introduced Video Descriptions, a generative AI feature that summarizes motion activity in plain text. Instead of guessing what triggered an alert, you might see messages like “A person is walking up the steps with a black dog” or “Two people are peering into a white car in the driveway.”

    HOW RESTAURANT RESERVATION PLATFORM OPENTABLE TRACKS CUSTOMER DINING HABITS

    A Ring doorbell alert with two people getting out of a car

    Ring’s Video Descriptions feature takes a different approach by summarizing activity without identifying people by name. (Amazon)

    How Video Descriptions decides what matters

    This AI focuses on actions rather than identities. It helps you quickly decide whether an alert is urgent or routine. Over time, Ring says the system can recognize activity patterns around a home and only notify you when something unusual happens. However, as with any AI system, accuracy can vary depending on lighting, camera angle, distance and environmental conditions. Video Descriptions is currently rolling out in beta to Ring Home Premium subscribers in the U.S. and Canada. Unlike facial recognition, this feature improves clarity without naming or tracking specific people. That contrast matters.

    Ring doorbell notifications on an iPhone screen

    Video Descriptions turns motion alerts into short summaries, helping you understand what is happening without identifying who is involved. (Amazon)

    Should you turn Familiar Faces on?

    If you own a Ring doorbell, caution is wise. While Familiar Faces may reduce notification fatigue, labeling people by name creates a detailed record of who comes to your home and when. Given Ring’s past security lapses and close ties with law enforcement, many privacy experts recommend keeping the feature disabled. If you do use it, avoid full names and remove faces you no longer need. In many cases, simply checking the live video feed is safer than relying on AI labels. Not every smart home feature needs to know who someone is.

    How to turn Familiar Faces on or off in the Ring app

    If you want to review or change this setting, you can do so at any time in the Ring mobile app.

    To enable Familiar Faces:

    • Open the Ring app
    • Tap the menu icon
    • Select Control Center
    • Tap Video and Snapshot Capture
    • Select Familiar Faces
    • Toggle the feature on and follow the on-screen prompts

    To turn Familiar Faces off:

    • Open the Ring app
    • Go to Control Center
    • Tap Video and Snapshot Capture
    • Select Familiar Faces
    • Toggle the feature off

    Turning the feature off stops facial recognition and prevents new faces from being identified. Any labeled faces can also be deleted manually from the Familiar Faces library if you want to remove stored data.

    Alexa is now answering your door for you

    Amazon is also rolling out a very different kind of AI feature for Ring doorbells, and it lives inside Alexa+. Called Greetings, this update gives Ring doorbells a conversational AI voice that can interact with people at your door when you are busy or not home. Instead of identifying who someone is, Greetings focuses on what they appear to be doing. Using Ring’s video descriptions, the system looks at apparel, actions, and objects to decide how to respond. 

    For example, if someone in a delivery uniform drops off a package, Alexa can tell them exactly where to leave it based on your instructions. You can even set preferences to guide delivery drivers toward a specific spot, or let them know water or snacks are available. If a delivery requires a signature, Alexa can ask the driver when they plan to return and pass that message along to you. The feature can also handle sales representatives or service vendors. You might set a rule such as politely declining sales pitches without ever coming to the door yourself.

    Greetings can also work for friends and family. If someone stops by while you are away, Alexa can greet them and ask them to leave a message for you. That interaction is saved so you can review it later. That said, the system is not perfect. Because it relies on visual context rather than identity, mistakes can happen. A friend who works in logistics could show up wearing a delivery uniform and be treated like a courier instead of being invited to leave a message. Amazon acknowledges that accuracy can vary. Importantly, Amazon says Greetings does not identify who a person is. It uses Ring’s video descriptions to determine the main subject in front of the camera and generate responses, without naming or recognizing individuals. That makes it fundamentally different from the Familiar Faces feature, even though both rely on AI.

    Greetings is compatible with Ring Wired Doorbell Pro (3rd Gen) and Ring Wired Doorbell Plus (2nd Gen). It is available to Ring Premium Plan subscribers who have video descriptions enabled and is currently rolling out to Alexa+ Early Access users in the United States and Canada.

    Thinking about a Ring doorbell?

    If you are already in the Ring ecosystem or considering a video doorbell, Ring’s lineup includes models with motion alerts, HD video, night vision, and optional AI-powered features such as Video Descriptions. While Familiar Faces remains controversial and can be turned off, many homeowners still use Ring doorbells for basic security awareness and package monitoring. 

    If you decide Ring is right for your home, you can check out the latest Ring Video Doorbell models or compare features and pricing with other options by visiting Cyberguy.com and searching “Top Video Doorbells.”

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    Kurt’s key takeaways

    Amazon Ring’s AI facial recognition feature shows how quickly convenience can collide with privacy. Familiar Faces may offer smarter alerts, but it also expands surveillance into deeply personal spaces. Meanwhile, features like Video Descriptions prove that AI can be useful without identifying people. As smart home tech evolves, the real question is not what AI can do but what it should do.

    Would you trade fewer notifications for a system that recognizes and names everyone who comes to your door? Let us know by writing to us at Cyberguy.com.

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  • Prominent Canadian Musician Says Gig Was Cancelled After Google AI Overview Wrongly Branded Him Sex Pest

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    Prominent Canadian fiddler Ashley MacIsaac says he was wrongly branded a convicted sex offender by Google’s AI Overview feature, leading concert organizers to cancel a gig last week. 

    Before we continue, I’ll need you to watch the music video for “Sleepy Maggie” by Ashley MacIsaac (with Scottish Gaelic vocals by Mary Jane Lamond). Not being from Canada where this song was a hit in 1995, I had never been treated to this sumptuous feast of 90s imagery and sounds before today, but that oversight has been corrected thanks to this news event. For best results, light up a clove cigarette before pushing play:

     

    Anyway, according to an article in The Globe and Mail on Tuesday, the guy in that video with the fiddle, Ashley MacIsaac, was preparing to perform at the Sipekne’katik First Nation community in central Nova Scotia when organizers suddenly backed out, apparently having read that MacIsaac had ghastly sounding convictions on his record for sexual assault and “internet luring.”

    It later emerged, MacIsaac says, that these organizers had seen a Google AI Overview result that had mixed up MacIsaac’s biography with some other, much more horrible, MacIsaac, also from eastern Canada. 

    You probably remember the controversy over the Google AI Overviews feature from back in 2024, when it debuted, and quickly became a joke after telling people to put glue on pizza and such. For my part, I gave the feature six months to improve before reviewing it, and found a number of bizarre error types it was still prone to making in what I believed were plausible simulations of real world use cases. Google told me at the time it still had “work to do on the quality side of things.”

    If MacIsaac’s characterization is right, it still does, and it really needs to not make mistakes like the one alleged here. There’s a choice quote in the Globe and Mail from Clifton van der Linden, an assistant professor at McMaster University who has researched AI misinformation. “We’re seeing a transition in search engines from information navigators to narrators,” he told the newspaper.

    AI Overviews are original snippets of text, sort of like chatbot answers made fresh to order when a term gets Searched on Google, and they’re derived from whatever Google can find online that seems to relate to the subject you’re searching. You never know how someone might phrase a search about you, because the possibilities are endless, and thus, you never know how the AI Overview might go wrong.

    MacIsaac wonders in the Globe and Mail piece if other people had Googled him, and seen similar results without telling him. He views this as a potential cause for concern, because he thinks he may have lost work, or gained an enemy who believed what they read and decided to cause him harm.

    For what it’s worth, Google spokesperson Wendy Manton told the Globe and Mail the following: “Search, including AI Overviews is dynamic and frequently changing to show the most helpful information. When issues arise – like if our features misinterpret web content or miss some context – we use those examples to improve our systems, and may take action under our policies.” That newspaper also says Google “amended search results for the musician.” 

    Also, a representative from the Sipekne’katik First Nation community told MacIsaac they “We deeply regret the harm this error caused to your reputation, your livelihood, and your sense of personal safety,” and told him he was welcome to perform there in the future, he says. The Globe and Mail didn’t hear back from Sipekne’katik First Nation when they requested a comment.

    This all sounds like a lot of trouble for a lot of people to go through over an apparent AI hallucination. But hey, at least I learned about “Sleepy Maggie.” 

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    Mike Pearl

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  • The year data centers went from backend to center stage | TechCrunch

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    There was a time when most Americans had little to no knowledge about their local data center. Long the invisible but critical backbone of the internet, server farms have rarely been a point of interest for folks outside of the tech industry, let alone an issue of particularly captivating political resonance.

    Well, as of 2025, it would appear those days are officially over.

    Over the past 12 months, data centers have inspired protests in dozens of states, as regional activists have sought to combat America’s ever-increasing compute buildup. Data Center Watch, an organization tracking anti-data center activism, writes that there are currently 142 different activist groups across 24 states that are organizing against data center developments.

    Activists have a variety of concerns: the environmental and potential health impacts of these projects, the controversial ways in which AI is being used, and, most importantly, the fact that so many new additions to America’s power grid may be driving up local electricity bills.

    Such a sudden populist uprising appears to be a natural response to an industry that has grown so quickly that it’s now showing up in people’s backyards. Indeed, as the AI industry has swelled to dizzying heights, so, too, has the cloud computing business. Recent U.S. Census Bureau data shows that, since 2021, construction spending on data centers has skyrocketed a stunning 331%. Spending on these projects totals in the hundreds of billions of dollars. So many new data centers have been proposed in recent months that many experts believe that a majority of them will not — and, indeed, could not possibly — be built.

    This buildout shows no signs of slowing down in the meantime. Major tech giants — including Google, Meta, Microsoft, and Amazon — have all announced significant capital expenditure projections for the new year, a majority of which will likely go toward such projects.

    New AI infrastructure isn’t just being pushed by Silicon Valley but by Washington, D.C., where the Trump administration has made artificial intelligence a central plank of its agenda. The Stargate Project, announced in January, set the stage for 2025’s massive AI infrastructure buildout by heralding a supposed “re-industrialization of the United States.”

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    In the process of scaling itself exponentially, an industry that once had little public exposure has suddenly been thrust into the limelight — and is now suffering backlash. Danny Cendejas, an activist with the nonprofit MediaJustice, has been personally involved in a number of actions against data centers, including a protest that took place in Memphis, Tennessee, earlier this year, where locals came out to decry the expansion of Colossus, a project from Elon Musk’s startup, xAI.

    Cendejas told TechCrunch that he meets new people every week who express interest in organizing against a data center in their community. “I don’t think this is going to stop anytime soon,” he said. “I think it’s going to keep building, and we’re going to see more wins — more projects are going to be stopped.”

    Evidence in support of Cendejas’ assessment is everywhere you look. Across the country, communities have reacted to newly announced server farms in much the same way the average person might react to the presence of a highly contagious plague. In Michigan, for instance, where developers are currently eyeing 16 different locations for potential data center construction, protesters recently descended upon the state’s capitol, saying things like: “Michiganders do not want data centers in our yards, in our communities.” Meanwhile, in Wisconsin — another development hot spot — angry locals appear to have recently dissuaded Microsoft from using their town as a headquarters for a new 244-acre data center. In Southern California, the tiny city of Imperial Valley recently filed a lawsuit to overturn its county’s approval of a data center project, expressing environmental concerns as the rationale.

    The discontent surrounding these projects has gotten so intense that politicians believe it could make or break particular candidates at the ballot box. In November, it was reported that rising electricity costs — which many believe are being driven by the AI boom — could become a critical issue that determines the 2026 midterm elections.

    “The whole connection to everybody’s energy bills going up — I think that’s what’s really made this an issue that is so stark for people,” Cendejas told TechCrunch. “So many of us are struggling month to month. Meanwhile, there’s this huge expansion of data centers…[People are wondering] Where is all that money coming from? How are our local governments giving away subsidies and public funds to incentivize these projects, when there’s so much need in our communities?”

    In some cases, protests appear to be working and even halting (if only temporarily) planned developments. Data Center Watch claims that some $64 billion worth of developments have been blocked or delayed as the result of grassroots opposition. Cendejas is certainly a believer in the idea that organized action can halt companies in their tracks. “All this public pressure is working,” he said, noting that he could sense a “very palpable anger” around the issue.

    Unsurprisingly, the tech industry is fighting back. Earlier this month, Politico reported that a relatively new trade group, the National Artificial Intelligence Association (NAIA), has been “distributing talking points to members of Congress and organizing local data center field trips to better pitch voters on their value.” Tech companies, including Meta, have been taking out ad campaigns to sell voters on the economic benefits of data centers, the outlet wrote. In short: The tech industry’s AI hopes are pegged to a compute buildout of epic proportions, so for now it’s safe to say that in 2026 the server surge will continue, as will the backlash and polarization that surround it.

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    Lucas Ropek

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  • From Fear to Curiosity: How Great Leaders Reframe Innovation

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    My “aha” moment with AI didn’t start in the boardroom. It started in my music room.

    While I’ve been experimenting with generative AI tools for a few years, when I started exploring how they could help my musical progress, it all clicked for me. Project one was creating visuals to go with music for my brother. I don’t have a coding background, but with AI and a friend’s help, we created a program that could visualize sound for his performance. Next, I created a virtual tutor that helped me accelerate my music production and mastering skills, which I had only recently started exploring.

    These personal experiments really changed how I thought about creativity. AI didn’t make me less creative; if anything, it made me a better creator. It didn’t replace my ideas; it amplified them. The speed of learning had me wanting more, rather than getting stuck in place. And that realization sparked something bigger: If AI could unlock that kind of curiosity in me personally, what could it do for my team professionally?

    Curiosity starts at home
    When I got back to work, I began encouraging everyone at Agiloft to explore AI in their own lives. Not as a corporate initiative, but as an invitation: Try it out, play with it, see what it can do for you.

    I am a firm believer that transformation doesn’t start with technology. It starts with curiosity. You can’t force people to innovate, and you certainly can’t easily train away their fear of new tools. But if they see firsthand how technology can make them more creative—whether that’s in music, writing, or problem solving—they start to approach it with excitement instead of anxiety.

    That shift, from fear to curiosity, is what drives real change. AI is ultimately a human story. It doesn’t replace people; it expands what people are capable of. But in order to get there, leaders have to create a culture where experimentation feels safe and curiosity is rewarded.

    Building a culture of experimentation
    When we started operationalizing AI at Agiloft, we didn’t launch a massive top-down program. We began with what we called an AI Council—a handful of naturally curious employees from across the company who were already tinkering with AI tools. Their goal wasn’t to set policy; it was to learn, share, and inspire.

    As interest grew, that council evolved into an AI Opsteam—a dedicated group that helps scale the best ideas across departments. But even as the structure matured, the spirit always stayed the same: Start small, learn fast, and keep the human at the center.

    That’s something every leader can take to heart. People don’t usually fear technology itself; they fear being left behind by it. Our job as leaders isn’t just to provide new tools, it’s to help our teams reimagine their work and their potential in an AI-powered world.

    To take advantage of that, employees have to start thinking less about their title and more about their rolein the workflow.

    Here’s an example straight from a customer. In their contracting process, multiple teams review every contract, including security. Traditionally, that security step slowed things down by a week (at least) or the contract requestor avoided it. So, they used Agiloft’s prompt lab to build an AI agent that reviews contracts to determine if they even need full security review. And if they do, it pre-redlines them automatically.

    The result? Faster turnaround, 100 percent compliance, and happier humans on both sides of the process. When we focus on goals and outcomes versus rigid ownership, AI becomes an ally that helps everyone do their best work.

    The human transformation behind the tech
    Every CEO today is under pressure to “become AI native.” But the real and persistent challenge isn’t technological—it’s human.

    We’re asking people to reimagine how they work, learn new skills, and see their roles differently. That’s much more than a software rollout; it’s a mindset shift. Leaders have to make space for learning, mistakes, and discovery. Because the companies that thrive won’t just be AI-powered—they’ll be human-powered, first and foremost.

    In my experience as a leader, I’ve learned that curiosity scales best when it’s supported. Phase one is experimentation; phase two is building systems to make those experiments repeatable. Along the way, we invest in necessary upskilling so that no one feels like AI is happening to them—it’s happening with them.

    That’s the balance every leader needs to strike. You can’t lose your humans. The best agents, the smartest models, the fastest tools—they all rely on people who are curious enough to ask the right questions and bold enough to explore the answers.

    The same curiosity that helped me become a better musician has made me a better leader. When people are free to explore—whether that’s through sound, code, or business strategy—they uncover possibilities they never knew existed.

    That’s how fear turns into curiosity. And that’s how curiosity becomes innovation.

     

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    Eric Laughlin

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  • Insight-How a Silicon Valley Dealmaker Charmed Trump and Gave Intel a Lifeline

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    By Max A. Cherney and Jeffrey Dastin

    SAN FRANCISCO, Dec 24 (Reuters) – It was a Thursday before dawn in Silicon Valley when Intel CEO Lip-Bu Tan found himself under attack by the president of the United States.

    “The CEO of INTEL is highly CONFLICTED and must resign, immediately,” U.S. ‌President Donald Trump ​wrote on his Truth Social platform at 4:39 AM Pacific Time on August 7. Before he was Intel CEO, Tan had been a prolific investor ‌in companies in China.

    Trump and Tan had not met. While technology leaders from Nvidia, AMD, OpenAI, Amazon, Google and Palantir had all recently traveled to see Trump, the head of America’s most storied chipmaker had not spent time with the president since joining Intel in March.

    Politics was not Tan’s top priority. It had been more than 20 years since Tan, 66, had ​donated to a presidential election campaign. Though he spoke with a handful of U.S. government leaders, including Commerce Secretary Howard Lutnick in April, the Intel CEO did not fill the company’s top policy job in Washington for months after its prior holder, a Democrat, resigned.

    Almost immediately after Trump’s attack, Intel scrambled to lock down time with the president, two people with knowledge of the situation said. That culminated in the most pivotal, roughly 40-minute meeting of Tan’s decades-long career.

    Previously unreported details about Tan and Intel show how a man Trump had accused of supporting China’s interests came away from the meeting with a ‍commitment from the U.S. government to invest billions of dollars for a nearly 10% stake in the company.

    The deal gave Intel a ​too-strategic-to-fail aura and opened doors to potential partners who might want to win the president’s favor. It also may pave the way for the government to take more equity stakes in businesses the administration deems strategic, in what some investors previously described to Reuters as ushering in a new era of U.S. industrial policy.

    Intel’s share price has risen around 80% since Tan’s appointment, outpacing the percentage gains of the S&P 500 and Nvidia in that time.

    Reuters spoke with around 20 people who are current and former Intel employees, government advisers, and Tan’s industry contacts. Some of them questioned whether Tan has the ​technical acumen to restore Intel’s lead in chip manufacturing and find a ⁠winning artificial intelligence strategy, even as his skills as a dealmaker served him well in the Oval Office and elsewhere. 

    Though Intel’s chips powered some of the first mass-produced PCs, years of dysfunction had allowed foreign competitors such as TSMC to eclipse Intel in high-end chip production. 

    In statements, an Intel spokesperson said Tan needed no persuading to engage with the Trump administration. Early on, he elevated government affairs, among other functions, to report to him. Intel announced in December that a Trump economic adviser would helm the unit.

    “Lip-Bu Tan has a long, and well-established history of engagement in Washington, both before and after joining Intel,” the spokesperson said. Intel declined to make Tan available for an interview. 

    A White House spokesperson said President Trump was using his executive power to get “the best bargain for the American taxpayer” and safeguard U.S. security.

    “The Administration’s historic deal with Intel is one of many initiatives to reshore semiconductor and other critical manufacturing back to the United States,” the White House spokesperson said.

    40 MINUTES IN THE OVAL OFFICE

    Before heading into the White House, Tan called on his own allies who had forged relationships with the president, including Microsoft CEO Satya Nadella and Nvidia CEO Jensen Huang, to vouch for him, said two people familiar with the discussions.

    Tan “spoke, as he does often, with confidantes who would have relevant insight and perspective ahead of his meeting with President Trump,” the Intel spokesperson said. Nvidia and Microsoft did not comment for this story.

    Prior to the meeting, Tan strategized with his advisors on how to convince Trump he was an American patriot ‌by discussing his personal story and his commitment to the United States, the two people said. He also prepared to discuss his China holdings, the people said.

    Tan has made some 600 investments in China, some linked to the country’s military, according to Reuters reporting. Those connections to China are what ultimately landed him in the crosshairs of the president. Two of Tan’s investment firms — Walden International and Walden Catalyst — did not answer requests for comment. A third, Celesta Capital, ​said ‌it had made one China investment that it exited in 2020.

    His dealmaking acumen, Celesta Capital said, ‍is a key reason Tan “is so well suited to lead Intel’s current moment.”

    Just two cabinet members joined the meeting between Trump and Tan ⁠in the Oval Office: Lutnick and Treasury Secretary Scott Bessent, one of the people said. Trump questioned the Intel CEO about how he planned to turn the company around, the person said.

    Tan had already told Lutnick in a prior meeting that he did not want billions in handouts that the U.S. owed Intel as part of the CHIPS Act, the Commerce Secretary said in a video on X in August. Neither Lutnick nor Tan said why. The grant money had been offered to companies under the 2022 CHIPS Act in exchange for reviving domestic manufacturing so the U.S. could reduce its reliance on foreign semiconductor production. 

    The administration of former President Joe Biden had announced dozens of these awards to various chip-related companies. 

    So when Trump proposed that the U.S. receive equity in exchange for giving Intel more CHIPS Act money – an idea that two sources said Lutnick had talked about for weeks with government staff – Tan struck a deal. Intel declined to comment on the specifics of the private conversation, but Lutnick later said in the video that equity made the exchange “fair.”

    The deal gave Intel a $5.7 billion cash infusion and set up the U.S. government to be its largest shareholder. After the initial meeting, Tan pledged to “make Intel great again” in the video that Lutnick posted on social media, with the caption, “The Art of the Deal: Intel.”

    Within weeks of his White House coup, Tan finalized a partnership with Nvidia, securing $5 billion from its CEO Huang who called Tan his “long-time friend.” Unlike Intel, known for manufacturing chips called central processing units, Nvidia designs the world’s top chips for AI.

    Trump celebrated the deal on social media, posting an AI-generated image of himself staring at a chart of Intel’s stock and showing how the value of the U.S. stake had risen by 50% after Nvidia’s investment.

    INTEL’S VENTURE CAPITALIST CEO

    Born in Malaysia to a Chinese-language journalist and a teacher, Tan started out in the hard sciences and had plans to become a nuclear engineer, but he ultimately went to business school and in or around 1983 got his first job in venture capital in California. 

    During his career, Tan established himself as a man with a golden touch with startups that successfully were sold to other companies or went public. He amassed an estimated personal fortune well above $500 million.

    Tan’s dealmaking savvy is helping Intel only to a point, three people with knowledge of the company said. For ​instance, Tan’s bid to buy SambaNova was the subject of internal debate given how the startup makes application-specific AI chips while the market favored general-purpose ones.

    Additionally, these people said, chipmaking requires more engineering expertise than a typical tech business. Factories that make advanced chips rely on tools so precise they could pinpoint a U.S. quarter-dollar coin as far away as the moon. Some of its most successful executives, like Nvidia’s Huang, are electrical engineers by training.

    Still, some Wall Street analysts say Tan is an excellent choice for Intel CEO, with decades of chip-industry experience and a track record of delivering returns to shareholders. 

    “Lip-Bu is deeply involved in technical decisions, including product roadmaps,” the Intel spokesperson said. “These are technical, hands-on changes that highlight the depth of his technical leadership.”

    Tan was also “keenly aware” of Intel’s challenges when he took the CEO job, the Intel spokesperson said, because he had served on its board from 2022 until 2024.

    But once inside Intel – which had around 100,000 staff when he joined – the complexity of the chip manufacturer was unlike anything Tan had faced as a CEO before, said two of the sources, who worked at Intel.

    The company was bleeding cash to build factories for chip manufacturing, an effort begun under his predecessor Pat Gelsinger, and it needed an estimated $20 billion or more to have a shot at winning customers.

    Tan called on top executives in his network and asked how they did things, one of the sources said. He likewise called on big customers – cloud providers like Amazon and Google – and asked what they wanted, said two people familiar with the matter.

    Tan shook up Intel’s management team, similar to when he led the chip design company Cadence. There, he had worked with a deputy to draft a list of executives to fire, a person familiar with his Cadence days said. Cadence declined to comment.

    Tan is cutting deeper still: laying off around 15% of Intel employees per securities filings, many of them managers.

    He bypassed middle managers to have technical talent brief him directly, two of the people said. Tan named Intel engineering veteran Pushkar Ranade as his chief of staff and in December elevated him to interim chief technology officer.

    Despite the intensity of his task at Intel, Tan has split his time with his myriad other commitments, which include his investment firms. When evaluating potential deals for Intel’s venture arm, Tan would also ask his investment firms for their opinion, one of the former Intel employees said.

    An alleged conflict of interest with his venture portfolio prompted Intel’s board to push back on Tan over an acquisition this year, Reuters reported this month. 

    His Intel employment requires that he spend “such time as is necessary” to perform his duties as CEO, a change from the prior Intel chief’s contract that had required “full business efforts and time to Intel.”

    Celesta Capital said Tan’s time commitment to the firm is now minimal, and its team has received no request to review deals for Intel Capital. Walden International and Walden Catalyst did not answer requests for comment.

    Intel said Tan is working daily on transforming the company and “acted decisively” to flatten its structure, adding he is a “highly engaged CEO” who is “helping to restore speed, accountability, and create an engineering-centric, customer-focused culture.”

    A ‘LIFELINE’ FOR INTEL

    So far, the U.S. investment has been a catalyst for Intel. Its Corporate Vice President John Pitzer said in a ​September interview that President Trump had just hosted top technology CEOs for dinner to discuss AI, and that their companies were potential Intel customers.

    The deal was a “lifeline” for Intel, said technology lobbyist and Chamber of Progress CEO Adam Kovacevich. Without it, Intel could have been out a CEO if it had succumbed to Trump’s pressure, he said.

    The same week as the White House deal, Intel announced a $2 billion investment from Masayoshi Son’s SoftBank, where Tan once was a board member.

    Lutnick, who previously had no vested interest in phone calls to his office from business or government leaders about Intel’s manufacturing, now has an incentive to jump at them, said one of the sources, who is familiar with the administration. Lutnick has indicated that Americans have skin in the game for Intel to land a foundry deal that could bolster U.S. chip production, the person said.

    Foreign chip manufacturers operating in the U.S. are concerned that government officials will tip the scales for customers to manufacture with Intel instead of with them, according to two sources familiar with these worries.

    A Commerce Department official said the U.S. stake gives Intel a shot at success but not a leg up, and Intel is not “too strategic to fail.” The official said further that Secretary Lutnick talks to all parties rather than prioritizing calls for Intel’s sake.

    While Intel is picking up steam on the deals front, its manufacturing unit has struggled to produce quality in-house chips.

    Nvidia recently tested out ​whether it would manufacture its chips using Intel’s production process known as 18A but stopped moving forward, two people familiar with the matter said. Nvidia did not answer a request for comment.

    An Intel spokesperson said the company’s 18A manufacturing technologies that make advanced chips are “progressing well,” and it “continues to see strong interest” for its next-generation production process, called 14A, which is expected to produce chips that are more powerful and efficient.

    Nvidia made no commitment to manufacture with Intel in September when investing $5 billion in the chipmaker. “Right now we are focused on collaborations,” Tan told reporters while announcing the deal with Nvidia’s Huang.

    (Reporting by Max A. Cherney and Jeffrey Dastin in San Francisco)

    Copyright 2025 Thomson Reuters.

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    Reuters

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  • As Raleigh grows, the city uses AI to rethink traffic management

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    At a busy downtown intersection where cars, scooters, cyclists and pedestrians cross paths, Raleigh traffic engineers are testing a new approach to managing congestion as the city continues to grow.

    Using existing traffic cameras paired with artificial intelligence and mapping software, the city is analyzing how people and vehicles move through select intersections in near real time. City officials say the goal is not to eliminate traffic but to make signals operate more efficiently and safely, especially in areas with heavy pedestrian activity.

    “One of the core challenges of traffic engineering is moving vehicles efficiently,” said Jed Niffenegger, Raleigh’s city transportation manager. “We can’t change the fact that an intersection is busy. What we can do is make sure it’s operating as efficiently as possible.”

    The pilot program relies on computer vision technology that converts live video into data. Software tracks turning movements, traffic volumes and different modes of travel, replacing a manual process that once required staff to stand at intersections and count vehicles by hand.

    “The cameras allow us to make changes much more quickly,” Niffenegger said. “With analytics, the amount of work it takes has been reduced to a fraction of what it used to be.”

    Raleigh has roughly 250 closed-circuit traffic cameras citywide. For now, the AI system can analyze data from about 10 to 12 cameras at a time because of computing limits. Transportation staff rotate intersections into the program based on where signal timing studies or corridor reviews are underway, including along Glenwood Avenue and in parts of downtown.

    The technology allows engineers to fine-tune signal timing during peak hours, sometimes by only a few seconds, based on real-world conditions rather than assumptions.

    “We’ll look at the evening rush and see whether a signal is running too long or needs to start a little later,” Niffenegger said. “It’s about fine-tuning what we’re already doing.”

    City officials say that focus on intersections matters. While widening roads has long been used to relieve congestion, engineers say intersections are often the true bottlenecks.

    “If we can maximize efficiency at intersections, we can delay costly road-widening projects,” Niffenegger said. “That saves money and allows us to invest in other places where it can have a bigger impact.”

    James Alberque, Raleigh’s emerging technology manager, said the project is part of a broader effort to better understand how the city moves as its population grows. Raleigh surpassed 500,000 residents last year, putting new pressure on streets that were not designed for current traffic volumes.

    “Cameras record video, and we’re turning that video into data,” Alberque said. “That data helps traffic engineers understand what’s happening across the city, not just at one camera at one moment.”

    The data is visualized using a high-resolution, three-dimensional model of Raleigh, sometimes called a digital twin. City staff can compare traffic conditions before and after signal changes and evaluate whether adjustments are working as intended.

    The pilot initially focused on vehicle traffic. After validating those results, the city expanded the analysis to include pedestrians and bicycles, particularly in downtown areas with heavy foot traffic and scooter use.

    “We wanted to understand all modes of transportation,” Alberque said. “GIS allows us to integrate traffic data with other information and analyze it in one place.”

    City officials emphasized that privacy protections are built into the system. The city does not store video or collect personally identifiable information. The data is limited to anonymous counts, such as whether an object is a vehicle, pedestrian or bicycle, aggregated in 15-minute intervals.

    “There’s no identifying information at all,” Alberque said. “We’re not recording video.”

    The technology is not used to automatically change signal timing. Instead, the data is reviewed by engineers and used to inform decisions, with humans remaining in control throughout the process.

    During the pilot, the city has validated the AI results by running manual counts alongside the software. Alberque said more than a dozen test cases have been reviewed so far, helping staff build confidence in the accuracy of the data.

    Beyond traffic management, Raleigh’s camera network already supports other city departments. Police, 911 dispatchers and stormwater crews use the cameras during emergencies, including flooding events, to better understand conditions on the ground.

    Scaling the system beyond the pilot phase would require additional investment. Alberque said the city has so far relied on existing infrastructure and limited resources while testing the technology’s potential.

    “The technology is advancing very quickly,” he said. “We’re trying to be thoughtful about how we invest so we’re making good decisions as this evolves.”

    For now, city leaders say the pilot offers a way to improve safety and efficiency at busy intersections without expanding roadways, an approach they see as increasingly important as Raleigh continues to grow.

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  • Video: How Much Water Does the A.I. Industry Use?

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    new video loaded: How Much Water Does the A.I. Industry Use?

    Kevin Roose and Casey Newton, the hosts of “Hard Fork” at The New York Times, spoke with Andrew Marley, executive director for Effective Altruism DC, about how much water A.I. data centers use.

    By ‘HARD Fork’

    December 23, 2025

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    ‘HARD Fork’

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  • Instacart ending AI price tests for retailers

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    Instacart says its ending its controversial system of using AI price tests for retailers. Earlier this month, an investigation by Consumer Reports and progressive think tank Groundwork Collaborative found that Instacart’s algorithmic pricing charged various prices for the same item from the same store. Jo Ling Kent reports.

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  • Instacart to end AI price tests for retailers following investigation

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    Instacart said Monday that it would halt the use of an AI-powered tool that allowed retailers to charge customers different prices for identical items on the grocery delivery platform.

    “Effective immediately, Instacart is ending all item price tests on our platform,” an Instacart spokesperson told CBS News in an email statement. “Retailers will no longer be able to use Eversight technology to run item price tests on Instacart.”

    The announcement comes after a recent investigation by Consumer Reports and Groundwork Collaborative, an nonprofit advocacy group, found evidence that retailers such as Albertsons, Costco, Kroger, Safeway, Sprouts Farmers Market and Target were testing the AI pricing system

    The organizations based their findings on data gathered from more than 400 volunteers during online shopping sessions in September. During one test conducted for a Safeway in Seattle, the price for a box of Wheat Thins varied by as much as 23%. 

    Retailers will continue to set their own prices on the delivery website, and they may still offer different prices at different brick-and-mortar locations, Instacart said Monday in a blog post.

    Instacart acquired Eversight, an AI-enabled pricing platform, in 2022, and began offering pricing software to retail companies in 2023. 

    Instacart claims the AI pricing tests did not include customers’ personal, demographic, or user-level behavioral characteristics. The decision to end the use of its pricing tool was made in response to feedback from Instacart customers, a company spokesperson said Monday.

    Reuters reported on Dec. 17 that the Federal Trade Commission was probing Instacart over its AI pricing tests. The FTC decined to comment on the report, but said in a statement that it was “disturbed by what we have read in the press about Instacart’s alleged pricing practices.”

    The FTC did not immediately respond to a request for comment on Instacart shelving its AI pricing technology.

    In a separate case last week, Instacart agreed to pay $60 million in customer refunds to settle federal allegations of deceptive practices after the FTC accused Instacart of falsely advertising free deliveries and not clearly disclosing service fees.

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  • World shares are mixed and Japan’s yen slips after AI stocks push higher on Wall Street

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    World shares were mixed on Monday after a rebound in AI-related stocks like Nvidia spurred a late-in-the-week rally on Wall Street.

    Germany’s DAX edged 0.1% higher to 24,315.90, while the CAC 40 in Paris slipped 0.2% to 8,135.23. Britain’s FTSE 100 shed 0.3% to 9,864.71.

    The future for the S&P 500 was up 0.4% while that for the Dow Jones Industrial Average gained 0.2%.

    In Asian trading, Tokyo’s Nikkei 225 gained 1.8% to 50,402.39, helped by hefty gains for computer chip makers and other companies benefiting from the boom for artificial intelligence.

    Semiconductor maker Tokyo Electron jumped 6.3% while chip testing equipment maker Advantest gained 4.5%.

    Financial companies and exporters also saw gains after the Bank of Japan raised its key policy rate on Friday to its highest level in 30 years. Instead of causing the Japanese yen to strengthen as might be expected, it has fallen.

    Early Monday, the dollar bought 157.45 yen, down from 157.60 late Friday. Heavy selling of the yen for dollars caused a top Finance Ministry official in charge of foreign exchange issues, Atsushi Mimura, to warn that regulators would act to curb any excessive fluctuations in the currency.

    Hong Kong’s Hang Seng picked up 0.4% to 25,901.77. The Shanghai Composite index advanced 0.7% to 3,917.36.

    China’s central bank left its 1-year and 5-year loan prime rates unchanged, as expected.

    Elsewhere in Asia, South Korea’s Kospi added 2.1% to 4,105.93 and Taiwan’s Taiex was 1.6% higher, helped by a 2.5% gain for chip maker TSMC.

    In Australia, the S&P/ASX 200 picked up 0.9% to 8,699.90.

    “Asian equity markets are stepping onto the floor with a constructive bias, taking their cue from Friday’s solid rebound in U.S. stocks and the growing belief that the final stretch of the year still belongs to the bulls,” Stephen Innes of SPI Asset Management said in a commentary.

    On Friday, the S&P 500 rose 0.9%, edging 0.1% higher for the week. The Dow Jones Industrial Average rose 0.4%, while the Nasdaq composite index advanced 1.3%, nothing a 0.5% gain for the week.

    Nvidia was the biggest force driving the market higher, with a 3.9% gain. Broadcom jumped 3.2%.

    The technology sector has been fueling Wall Street throughout the year as companies with outsized values like Nvidia exert more pressure on markets. But, those pricey stock values have come under more scrutiny from investors wondering whether they are justifiable.

    Oracle rose 6.6% on news that it, along with two other investors, had signed agreements to form a new TikTok U.S. joint ventur e. Oracle, Silver Lake and MGX each get a 15% share in the popular social video platform, ensuring that it can continue operating in the U.S.

    Homebuilders fell following a report showing that home sales slowed from a year earlier for the first time since May. KB Home fell 8.5%.

    A survey from the University of Michigan showed that consumer sentiment in December improved slightly from November, but is deeply diminished from a year earlier.

    Consumer confidence has been weakening throughout the year as persistent inflation squeezes consumers. The job market is also slowing while retail sales weaken. Businesses and consumers are also worrying about the continued impact of a wide-ranging U.S.-led trade war that has targeted key partners including China and Canada.

    Inflation is still above the Federal Reserve’s 2% target. The central bank cut its benchmark interest rate at its most recent meeting. It has been concerned about the slowing job market hurting the economy. But cutting interest rates could add more fuel to inflation, which could also stunt economic growth.

    The Fed has maintained a cautious stance about interest rate policy heading into 2026 and Wall Street is mostly betting that it will hold steady on rates at its next meeting in January.

    In other dealings early Monday, U.S. benchmark crude oil gained 57 cents to $57.09 per barrel. Brent crude, the international standard, was up 58 cents at $61.05 per barrel.

    The euro climbed to $1.1726 from $1.1720.

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  • The rise of deepfake cyberbullying poses a growing problem for schools

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    Schools are facing a growing problem of students using artificial intelligence to transform innocent images of classmates into sexually explicit deepfakes.

    The fallout from the spread of the manipulated photos and videos can create a nightmare for the victims.

    The challenge for schools was highlighted this fall when AI-generated nude images swept through a Louisiana middle school. Two boys ultimately were charged, but not before one of the victims was expelled for starting a fight with a boy she accused of creating the images of her and her friends.

    “While the ability to alter images has been available for decades, the rise of A.I. has made it easier for anyone to alter or create such images with little to no training or experience,” Lafourche Parish Sheriff Craig Webre said in a news release. “This incident highlights a serious concern that all parents should address with their children.”

    Here are key takeaways from AP’s story on the rise of AI-generated nude images and how schools are responding.

    The prosecution stemming from the Louisiana middle school deepfakes is believed to be the first under the state’s new law, said Republican state Sen. Patrick Connick, who authored the legislation.

    The law is one of many across the country taking aim at deepfakes. In 2025, at least half the states enacted legislation addressing the use of generative AI to create seemingly realistic, but fabricated, images and sounds, according to the National Conference of State Legislatures. Some of the laws address simulated child sexual abuse material.

    Students also have been prosecuted in Florida and Pennsylvania and expelled in places like California. One fifth grade teacher in Texas also was charged with using AI to create child pornography of his students.

    Deepfakes started as a way to humiliate political opponents and young starlets. Until the past few years, people needed some technical skills to make them realistic, said Sergio Alexander, a research associate at Texas Christian University who has written about the issue.

    “Now, you can do it on an app, you can download it on social media, and you don’t have to have any technical expertise whatsoever,” he said.

    He described the scope of the problem as staggering. The National Center for Missing and Exploited Children said the number of AI-generated child sexual abuse images reported to its cyber tipline soared from 4,700 in 2023 to 440,000 in just the first six months of 2025.

    Sameer Hinduja, the co-director of the Cyberbullying Research Center, recommends that schools update their policies on AI-generated deepfakes and get better at explaining them. That way, he said, “students don’t think that the staff, the educators are completely oblivious, which might make them feel like they can act with impunity.”

    He said many parents assume that schools are addressing the issue when they aren’t.

    “So many of them are just so unaware and so ignorant,” said Hinduja, who is also a professor in the School of Criminology and Criminal Justice at Florida Atlantic University. “We hear about the ostrich syndrome, just kind of burying their heads in the sand, hoping that this isn’t happening amongst their youth.”

    AI deepfakes are different from traditional bullying because instead of a nasty text or rumor, there is a video or image that often goes viral and then continues to resurface, creating a cycle of trauma, Alexander said.

    Many victims become depressed and anxious, he said.

    “They literally shut down because it makes it feel like, you know, there’s no way they can even prove that this is not real — because it does look 100% real,” he said.

    Parents can start the conversation by casually asking their kids if they’ve seen any funny fake videos online, Alexander said.

    Take a moment to laugh at some of them, like Bigfoot chasing after hikers, he said. From there, parents can ask their kids, “Have you thought about what it would be like if you were in this video, even the funny one?” And then parents can ask if a classmate has made a fake video, even an innocuous one.

    “Based on the numbers, I guarantee they’ll say that they know someone,” he said.

    If kids encounter things like deepfakes, they need to know they can talk to their parents without getting in trouble, said Laura Tierney, who is the founder and CEO of The Social Institute, which educates people on responsible social media use and has helped schools develop policies. She said many kids fear their parents will overreact or take their phones away.

    She uses the acronym SHIELD as a roadmap for how to respond. The “S” stands for “stop” and don’t forward. “H” is for “huddle” with a trusted adult. The “I” is for “inform” any social media platforms on which the image is posted. “E” is a cue to collect “evidence,” like who is spreading the image, but not to download anything. The “L” is for “limit” social media access. The “D” is a reminder to “direct” victims to help.

    “The fact that that acronym is six steps I think shows that this issue is really complicated,” she said.

    ___

    The Associated Press’ education coverage receives financial support from multiple private foundations. AP is solely responsible for all content. Find AP’s standards for working with philanthropies, a list of supporters and funded coverage areas at AP.org.

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