Technology
AI smart glasses could generate fake photos instantly
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Smart glasses are gaining new momentum thanks to artificial intelligence (AI). Companies like Google, Meta, Samsung and possibly Apple are exploring AI-powered glasses that combine cameras, speakers, voice assistants and computer vision in a wearable device.
At first glance, the features sound familiar. Smart glasses can take photos, give directions, answer questions and help you navigate the world hands-free. However, a recent demo hints at something much bigger.
These glasses may soon generate or alter photos instantly. In other words, the image you capture may no longer reflect what was actually there.
That raises an important question: If AI can change a photo the moment it is taken, how do we know what is real anymore?
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Google product lead Dieter Bohn demonstrates prototype AI smart glasses during a demo showing how the device can capture and modify photos using generative AI. (X/ @backlon)
A new AI trick inside smart glasses
During a demo of upcoming smart glasses, Google’s Dieter Bohn showed how the device could capture a photo and modify it using AI. The prototype, shown as Android XR glasses with a display, connects to Google’s generative AI tools, including Google Gemini and an experimental image generator called Nano Banana.
In the demonstration, Bohn asked the glasses to take a photo of people in the room. Then he gave another command. He asked the system to place those people in front of the famous church in Barcelona that he could not remember by name.
Within moments, the AI produced a new image showing the group standing in front of the Sagrada Família. The people in the photo never traveled to Spain. The background came from AI. To someone viewing the image later, it could look like a real travel photo.
Smart glasses are following the same playbook
The hardware approach behind these devices looks similar across the industry.
Most smart glasses include:
- A built-in camera
- Speakers for audio feedback
- A microphone and a voice assistant
- Computer vision powered by AI
- Navigation and contextual information
- Optional displays inside the lenses
This design mirrors products like the Ray-Ban Meta Smart Glasses, which combine sunglasses with an AI assistant and camera. Those glasses already allow users to capture photos, livestream video and ask questions using voice commands. However, the editing tools currently available inside Meta’s glasses focus more on artistic effects. For example, the system can transform photos into a cartoon or painting style. The goal is creative expression rather than photorealistic manipulation. Google’s demo hints at something different. It shows how AI can place people into entirely new scenes that never happened.
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A close-up of prototype Android XR glasses with a built-in display, part of Google’s concept for AI-powered smart glasses. (X/ @backlon)
Why this matters for photography
AI-generated images already exist across social media. Smartphones have also introduced powerful editing tools. Google’s Pixel phones, for example, have leaned heavily into AI photography with tools that remove objects, adjust lighting and generate backgrounds.
The difference with smart glasses is speed. The technology removes the delay between taking a photo and editing it. Instead of capturing an image and opening editing software later, the AI can change the photo immediately. That could make altered images far more common. Photos that once served as proof of where someone was or what happened may become harder to trust.
The demo still leaves open questions
It is important to note that the Google demo was short and carefully staged. The company acknowledged that parts of the video were edited. That suggests the AI process may take longer in real-world conditions.
There is also the question of reliability. Generative AI tools sometimes produce mistakes, strange artifacts or unrealistic details. Still, even an imperfect system could change how people interact with cameras and images. As the technology improves, the gap between real and AI-generated photos may shrink.
What this means for you
Smart glasses could soon become another everyday device. That means the way we capture and share images may shift again. If these tools become common, you may start seeing photos that were generated or heavily modified by AI. A picture posted online may look like a real moment from someone’s life. In reality, it could be a mix of real people and AI-generated scenery. That does not mean every image is fake. It does mean digital images may carry less proof than they once did. Understanding how AI editing works can help you approach viral photos, travel shots or dramatic images with a healthy level of skepticism.
Ray-Ban Meta smart glasses combine cameras, speakers and an AI assistant, showing how wearable devices are bringing artificial intelligence into everyday eyewear. (Meta)
How to spot AI-generated or altered photos
AI editing tools are becoming easier to use. That means altered images may appear more often online. A few habits can help you avoid being misled.
1) Question images that look too perfect
If a photo looks unusually polished or dramatic, pause before assuming it is real. AI images often create scenes that feel cinematic or unusually clean.
2) Look closely at small details
AI systems sometimes struggle with small elements. Check hands, reflections, shadows and background objects for strange shapes or mismatched lighting.
3) Check where the image came from
If a photo spreads quickly online, try to trace the original source. Reverse image search can reveal if the picture appeared somewhere else first.
4) Be cautious with viral travel or event photos
AI tools can place people into locations they have never visited. A convincing background does not guarantee that the moment actually happened.
5) Watch for photos used in scams or misinformation
AI-generated images can appear in fake travel posts, romance scams or misleading news claims. If a photo appears alongside urgent requests for money or emotional stories, take time to verify it before reacting. Avoid clicking suspicious links and consider using strong antivirus software that can block malicious websites and scam pages before they load. Get my picks for the best 2026 antivirus protection winners for your Windows, Mac, Android & iOS devices at Cyberguy.com
6) Treat photos online as information, not proof
Photos once served as strong evidence of where someone was or what occurred. With generative AI, an image may be a mix of real people and computer-generated scenes.
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Kurt’s key takeaways
Smart glasses promise convenience, hands-free computing and powerful AI tools. At the same time, they blur the line between photography and digital creation. Technology keeps pushing toward a world where capturing a moment and generating one can happen in the same instant. The devices themselves may become smaller and smarter. The challenge may be deciding how much we trust the images they produce.
So here is the question worth asking. If AI glasses can create realistic photos of places you’ve never visited, will pictures still count as proof of reality? Let us know by writing to us at Cyberguy.com
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Technology
Microsoft’s carbon emissions went up 25 percent last year
Microsoft may once again be struggling to keep up with its own climate goals, according to its 2026 sustainability report. As reported by GeekWire, the report states that Microsoft’s carbon emissions increased 25 percent in 2025, totalling 34 million metric tons “without select interventions.” Microsoft says this was “driven primarily by the expansion of our datacenter infrastructure,” as well as the company’s decision last February to stop purchasing “non-additional, unbundled renewable energy certificates.”
Several years ago, Microsoft set itself a goal to be carbon negative by 2030, meaning it will need to remove more carbon emissions than it produces. This isn’t the first time Microsoft has faced setbacks toward accomplishing that goal, as its 2024 sustainability report showed a similar rise in climate pollution. This year’s report admits that, “While AI infrastructure is driving demand for energy, water, land, and materials, sustainability solutions are not scaling fast enough to meet demand.”
Technology
Google turns old phones into cloud servers
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That old phone sitting in your drawer may have more life left in it than you think. You may look at it and see a dead battery, an outdated camera or a screen that no longer feels worth using. Google and researchers at the University of California San Diego see something else: a tiny computer that may still have useful processing power.
Their idea is called phone cluster computing. Instead of treating retired smartphones as electronic waste, researchers remove the motherboard and redeploy it as part of a low-carbon computing system.
Google says UC San Diego plans to launch a data center built from 2,000 Pixel smartphones in fall 2026. The goal is to provide low-cost cloud computing for students and researchers while reducing the need for newly manufactured server hardware.
That means the next chapter for an old phone may not be a junk drawer. It may be a server rack.
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Researchers plan to launch a 2,000-phone data center at UC San Diego in fall 2026 to support students and research workloads. (Kurt “CyberGuy” Knutsson)
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What is phone cluster computing?
Phone cluster computing takes retired smartphones and turns their core hardware into a computing platform. The process starts by stripping each phone down to the motherboard. That board holds the processor, memory and storage. The display, battery, cameras, chassis and other phone-specific parts are removed.
That step is important because a full phone does not belong in a data center. Batteries can create safety issues. Screens and cameras waste space. The motherboard is the part that still offers computing value.
Once the board is removed, researchers load a general-purpose Linux system onto it. Android already runs on Linux at its core, but Android is built for mobile apps and personal devices. A data center needs something more flexible for cloud workloads. After that, the phone boards can be grouped into clusters. Many small boards then work together like a collection of tiny servers.
Why Google wants old Pixel phones for cloud computing
The AI boom has created a huge appetite for computing power. Data centers need more chips, more electricity and more cooling. At the same time, billions of phones fall out of use around the world.
This Google-backed project takes that conversation in a different direction by asking whether some useful computing can come from hardware we already made.
The project focuses on embodied carbon. That means the emissions created before a device ever turns on. Mining, manufacturing and shipping all add to that carbon footprint.
If a phone motherboard already exists, reusing it can avoid some of the environmental cost tied to manufacturing new hardware. Google says the motherboard accounts for about half of a phone’s embodied carbon, which makes it the most valuable part to recover.
How retired smartphones become low-carbon servers
You cannot plug a pile of old phones into a rack and call it a data center. The process requires careful teardown, new software and a way to manage many boards at once. Google says the project uses containerized applications managed by Kubernetes. That helps coordinate the work across many devices.
The phones are organized into self-managing clusters of about 25 to 50 boards. Each board works as a small Linux machine. Together, they can handle tasks that would otherwise run on traditional cloud servers. That does not make one phone equal to one server. A server has many more processor cores, more memory and data center-grade hardware. A phone board has fewer resources and tighter limits. Still, some jobs do not need a giant machine. They need enough compute to run efficiently without wasting resources.
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Google and UC San Diego are testing a cloud computing system built from retired Pixel phone motherboards, giving old smartphones a possible second life. (Google)
Can old phone processors handle cloud workloads?
The technical case is stronger than you may expect. Google says the single-threaded performance of modern smartphone performance cores can match or beat the per-core performance of some modern multicore servers. In one comparison, a 2023 Pixel Fold was tested against an ASUS RS720A-E11 server using SPEC benchmarks. The Pixel Fold’s performance cores beat the baseline data center server core on many of the tests. That sounds impressive, but there is an important catch.
A smartphone board has a smaller memory limit and fewer cores. It also lacks the management tools and hardware durability that servers are built around. So the project needs the right workloads.
UC San Diego is starting with educational and research computing. That makes sense because many classroom tasks can run on small cloud instances. Google says early experiments showed that a 20-phone cluster could support peak submission rates for a class of more than 75 students. The grading latency also came in below the default AWS backend used in the comparison.
Why UC San Diego is testing a 2,000 Pixel phone data center
UC San Diego plans to use the 2,000-phone cluster to support computer science classes and research workloads. Google says the deployment could support about 100 classes at once. It also describes the system as providing about 50 server-equivalents worth of compute at a fraction of the usual cost.
For a university, that could be a major advantage. Cloud computing costs can rise quickly, especially when many students submit assignments at the same time. If a reused phone cluster can handle some of that load, schools may save money while reducing demand for newly manufactured servers.
This also gives researchers a chance to test phone-based computing at scale. A small lab demo can look promising. A 2,000-board deployment will show much more about reliability, maintenance and day-to-day performance.
Phone cluster computing still has big limits
Phone cluster computing sounds promising, but it still has a lot to prove. Your smartphone was made for daily use in your hand, not nonstop work inside a data center. Data center servers are built to run for years with steady cooling, fast repairs and constant monitoring. Phone motherboards come from devices made for pockets, backpacks and kitchen counters. That alone raises some big questions.
The boards could fail faster than expected. Cooling may also become a challenge once thousands of tiny processors run side by side. Then there is the labor problem, because someone has to safely remove batteries, screens and other parts before the boards can be reused. Cost will be the deciding factor. If teardown, maintenance and replacement work get too expensive, this idea may stay in the research lab.
Phone clusters also will not replace the massive GPU systems that power advanced AI training. They make more sense for smaller cloud jobs, classroom tools and research tasks that fit within smartphone hardware limits. That still leaves plenty of useful work. After all, not every cloud task needs the newest chip.
Why old smartphones could help cut e-waste
The world’s e-waste problem is growing fast. The Global E-waste Monitor projects that electronic waste could climb to 82 million tonnes by 2030, while formal collection and recycling rates are expected to fall to 20%. Old phones are a big part of that problem because many never make it to a proper recycling program. They sit in drawers, land in closets or get tossed out with valuable parts still inside. Even when a phone no longer feels useful to you, its processor, memory and storage may still have work left to do.
CyberGuy has covered related second-life ideas before, including old smartphones being turned into tiny data centers and repurposed EV batteries helping power AI data centers. The common theme is hard to ignore. Some of the hardware already in circulation may still have useful work left to do.
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Google says reusing smartphone motherboards could cut hardware waste and reduce the carbon cost of building new data center servers. (Yawar Nazir/Getty Images)
How to safely recycle or reuse your old phone
This research does not mean you should toss your old phone into a random donation bin tomorrow. Before you recycle, donate, trade in or sell an old phone, you need to protect your data. Back up anything you want to keep. Then sign out of your accounts and securely wipe the device.
CyberGuy has a helpful guide on how to securely get rid of your old cell phone. Privacy comes first whenever you part with a device.
You can also consider trade-in programs, certified refurbishers or reputable electronics recycling programs. If the phone still works, buying refurbished can also keep devices in use longer. CyberGuy has covered what to know before buying refurbished electronics, which is helpful if you want to save money without taking a gamble. The key is to avoid letting old devices sit forgotten forever. A phone in a drawer helps no one.
What this means to you
That old phone in your drawer may not be as useless as it looks. Even if the battery is tired or the camera feels outdated, the processor inside may still have real value.
Now, you probably will not be mailing your old phone to a Google data center anytime soon. Still, this project points to a bigger shift in how we think about retired tech. Instead of sending every old device straight to recycling or letting it collect dust, companies, schools and researchers may find smarter ways to reuse the parts that still work.
There is also a money lesson here. If your current phone still runs well, you may not need to rush into an upgrade just because a newer model comes out. A battery replacement, trade-in or refurbished option could save you money while keeping perfectly good hardware in use longer. To me, that is the real takeaway. The phone you forgot about could possibly still have a job to do.
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Kurt’s key takeaways
Google and UC San Diego are testing how to turn retired Pixel phone motherboards into a low-carbon cloud computing platform. The project could give old smartphones a second life while reducing the need for newly manufactured servers. That is important as AI data centers keep demanding more computing power and more electricity. The first major test is expected in fall 2026 with a 2,000-phone data center at UC San Diego. If it works, the cluster could support students and researchers at a lower cost than traditional cloud infrastructure. However, this idea still has to prove it can handle the grind of daily use. Reliability, cooling, teardown labor and maintenance will determine whether phone cluster computing can grow beyond just research. To me, the most relatable part is sitting in your junk drawer. That old phone may seem useless, but its processor could still be powerful enough to help run cloud jobs. Maybe the future of computing starts with hardware we already forgot we owned.
Would you feel good knowing your old phone could help power cloud computing? Let us know by writing to us at CyberGuy.com.
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Technology
Google’s Nest Thermostat has hit its best price of the year
If you’re looking for a relatively affordable way to cut down on cooling costs, Google’s Nest Thermostat can help. It’s packed with smart controls and energy-saving features, and right now it’s on sale in white for $79 ($50 off), which is its best price of the year, at Amazon.
The smart thermostat is quick to install and makes it easy to adjust your home’s temperature whether you’re relaxing in bed or on your way home thanks to the Google Home app. You can also create schedules and control it with your voice using Google Assistant, Alexa, or another Matter-compatible voice assistant.
Once it’s set up, the Nest Thermostat can automatically turn the temperature down when you’re away to help reduce unnecessary energy use, while Google’s Savings Finder feature suggests additional ways to save over time. It also monitors your HVAC system and can alert you if something doesn’t seem right, making it easier to stay on top of maintenance before small issues become bigger, more expensive ones. If you’re eligible, Nest Renew can also automatically shift some of your heating and cooling to times when electricity is cleaner or cheaper.
That said, this is Google’s entry-level model from 2020, so you do miss out on some of the premium features found on the latest Nest Learning Thermostat. Unlike the flagship version, it won’t learn your schedule automatically over time, for example, and lacks support for Nest Temperature Sensors that let you prioritize the temperature in a specific room. Even so, if all you want is an easy way to adjust your home’s temperature remotely and potentially lower your energy bills, the Nest Thermostat is still a solid investment at this price.
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