Porsche has opened orders in Germany and other European markets for an 11 kW wireless charging pad for the Cayenne Electric, at EUR 6,961.49 for the floor pad and the car-side hardware together, with efficiency of up to 90%. The pad must be permanently installed in the ground, and Europe’s rules on installing home charging are weaker than the phrase right to plug suggests.

Porsche has opened orders for a wireless charging pad for the Cayenne Electric in Germany and other European markets, the first offered on a car in either Europe or North America, InsideEVs reported.

It delivers up to 11 kilowatts at an efficiency Porsche puts at up to 90%, against roughly 94% for a cable. That is enough to fill the 113 kWh battery overnight, and well ahead of the 70% to 80% a phone manages.

In Germany the three-phase floor pad costs EUR 5,116.99 and the car-side hardware EUR 1,844.50, which is EUR 6,961.49 together. Ordering only the pre-installation, for a later retrofit, costs EUR 226.10.

The pad weighs about 50 kilograms, is waterproof and takes the weight of the car. Radar sensors cut the power if they find metal, an animal or a person.

Park assist lines the car up over the pad. The receiver is liquid-cooled, the transmitter air-cooled, and the system sends direct current straight to the battery, going around the onboard charger entirely.

It also has to be fixed to the ground.

That makes it a building alteration rather than a plug, and Europe’s right to plug is thinner than the phrase suggests.

Article 14(8) of the recast buildings directive asks member states to streamline and accelerate installation for tenants and owners alike. Transposition fell due in May, and there is no binding requirement to pre-equip existing blocks.

Transport and Environment calls that too weak to count as a right, because a request can be refused on serious and legitimate grounds the directive never defines.

France is the strongest. Co-owners there get three months to object, and only on grounds of technical infeasibility or existing shared infrastructure.

Germany, Italy, Poland and Spain have partial rules, typically covering owners but not tenants. Britain has no specific provision at all.

A Cayenne Electric starts at EUR 105,200, so the early buyers will mostly own the floor they are drilling into. The car itself is built at Volkswagen’s plant in Bratislava, where series production began in February.

Porsche will take the pad to its other markets in stages, with one exception. China, where inductive charging is already deployed and Xiaomi is about to sell a robotic arm that plugs the cable in for you, is not on the list.

Passport-style foldables are returning, but in a foldable format. Samsung completely changed direction with the Galaxy Z Fold 8, Xiaomi followed with the 18 Fold, and Apple has now entered the category with the iPhone Duo. Even though the original Google Pixel Fold explored the same short-and-wide idea years ago, this is looking like the new smartphone trend in 2026.

After spending years with book-style foldables, I am warming up to this decision. I prefer the idea of keeping the phone compact when closed and opening it only when I need more room.

Someone recently told me they thought the iPhone Duo looked beautiful. Their only complaint was that they wished it ran Android. Don’t get me wrong, I like what Apple has done with the Duo in plenty of places. The software transitions are gorgeous. Still, the iPhone Duo is incredibly squat when closed. The outer display does match the inner one in terms of aspect ratio, but I can’t help but feel like the design lags behind.

Passport foldables aren’t all the same

Put the two phones next to each other, and they initially look like variations on the same concept. The Galaxy Z Fold 8 has a 5.5-inch 10:16 cover display and opens into a 7.6-inch 4:3 canvas. Samsung designed the outer screen for quick scrolling and messaging, then lets the inner display handle tasks that need more immersion.

Apple does essentially the same thing with the Duo: a 5.4-inch outer display opens into a 7.6-inch inner screen. Apple even claims that the outer display is compact enough for one-handed use while the inner screen handles multitasking and entertainment.

Overall, the Duo is a little shorter and heftier, not to mention wider too. Those numbers explain quite a lot about how differently the two devices come across in the hand. Samsung’s Fold 8 is wide enough to feel distinct from a conventional slab without tipping too far into miniature-square territory. The Duo goes farther, and that extra width combined with the weight makes the whole thing look and feel more substantial when you’re simply trying to use the outer screen.

The UI debate

Apple knows the Duo’s proportions create a software challenge. Its own developer guidance explains that the Duo’s wider aspect ratio creates more horizontal space but reduces the amount of useful vertical room. Apple therefore moves controls that normally sit at the top and bottom of an iPhone onto the side of the interface, where they preserve vertical space and become easier to reach.

It also reinforces why I’m not entirely sold on the hardware shape. On a normal iPhone, developers have spent years assuming a tall display. We’re all familiar with how navigation bars go along the top, while tab bars sit at the bottom, and your thumb moves through an interface built around those proportions. Apple deserves credit for actually changing up this formula.

I already like how iOS 27 adapts across the Duo, and the software is one of the device’s biggest strengths. But Samsung’s Fold 8 has a simpler advantage with its 10:16 cover display that is still tall enough.

Samsung’s Galaxy Z Fold 8 is meant to be your main device

The ergonomics are another part of this conversation that gets lost when we obsess over diagonal screen sizes. The difference between 81.9mm on the Fold 8 and 84.1mm on the Duo looks tiny on a spec sheet. Once you combine it with the Duo’s shorter shape, 11.3mm folded thickness, and 254g weight, the device becomes a much chunkier object to move around in your palm.

Something that really impressed me was just how much Samsung’s phone weighs. At just 201 grams, it is surprisingly light for a book-style foldable. I’d argue that this is what the pinnacle of foldables should look like. All the specs and features aside, having a phone that feels handy is much better than a phone that is a chore to hold after a while.

Samsung can give me the unusual passport proportions without making every quick interaction remind me that I’m holding two halves of a folding phone. Not saying it’s as light as the truly compact phones like the Galaxy S26 and Pixel 11 Pro, but it gets realistic enough.

I’d pick the Z Fold 8 any day

I’ve already argued that compact, wide foldables could solve one of the biggest problems with small phones. You get something manageable for calls, notifications, and quick interactions, then unfold it whenever you need more room for gaming, email, reading, or multitasking.

The question is how compact you make that outer experience. The Duo embraces a much squatter display and then uses thoughtful software to make that unfamiliar canvas work. Samsung’s Fold 8 feels a little closer to a conventional phone without losing the passport design. Its best part is still that it’s lighter and thinner, which makes the shape easier to drive daily.

I might change my mind once I try out the Duo… maybe. Even so, the Galaxy Z Fold 8 is much closer to what I want from a passport foldable.

Meta’s camera-equipped smart glasses have proven more successful than other entrants into the market, but they have also deeply disturbed certain consumers who see them as invasive emblems of a dystopian surveillance society run amok. Now, as the company weathers complaints that it’s selling “pervert glasses,” it has reportedly decided to sell a pair that doesn’t come with integrated spy equipment.

The Information reports that Meta is developing a new smart glasses model, dubbed Luna, that, sans cameras, comes equipped with a convenient system to communicate with the company’s AI chatbot and Muse, its AI consumer agent. The glasses include six built-in microphones so users can communicate with the chatbot, as well as a button on the side of the glasses that, when pressed, activates the AI system.

Luna may be unveiled as soon as Meta Connect, Meta’s annual hardware/developer event happening in Menlo Park next week, the outlet notes.

TechCrunch reached out to Meta for more information.

The smart glasses industry has grown over the past few years, with Meta positioned near the front of the pack of providers. However, concerns over usability, cost, and privacy have dogged the business, with many consumers still unsure of how, why, or if they should use the devices. Meta’s Reality Labs, which is responsible for developing its smart glasses line, is still losing a gargantuan amount of money, as its earnings report from April revealed.

The most important technology trends in 2026 are not simply new inventions. They are technologies crossing practical thresholds in autonomy, computing infrastructure, device intelligence, security, digital trust, robotics, and connectivity.

These trends are not equally mature. The numbering below identifies their position in this article only; it is not a best-to-worst ranking. Some technologies are already suitable for selective production use, while others are better treated as technologies to pilot, prepare for, or monitor.

What Makes a Technology Trend Worth Watching in 2026?

A useful technology trend is more than a subject receiving attention. Something important should have changed in its capability, deployment model, supporting standards, economics, or infrastructure.

That distinction matters because many technologies once described as emerging are now ordinary parts of computing. Cloud infrastructure, Internet of Things deployments, 5G, virtual reality, augmented reality, blockchain, and low-code tools can still be important, but their existence alone does not make them defining 2026 trends.

The better question is whether a technology has crossed a new threshold. That may mean moving from research into production, gaining an implementable industry standard, becoming practical on consumer hardware, developing a clearer deployment model, or encountering a new constraint that changes how systems must be designed.

A similar maturity-first approach is useful when evaluating web development trends, where production readiness can matter more than novelty.

The table is best read as a maturity map rather than a prediction scoreboard. The technologies attracting the most publicity are not automatically the ones closest to dependable, large-scale deployment.

How These Technology Trends Connect

The seven trends are easier to understand as parts of the same changing technology stack rather than as isolated inventions.

AI agents increase the amount of work software can attempt autonomously, but that work still needs computing infrastructure. Some inference will remain in large data centers, while other workloads move toward phones, computers, vehicles, machines, and edge systems. Physical AI then connects software intelligence to machines that sense and act in the physical world.

As automated systems create and transform more digital content, provenance can provide useful origin and modification-history signals. At the same time, post-quantum cryptography addresses a longer-term change in the assumptions beneath digital security. Satellite D2D extends connectivity into locations where terrestrial coverage may be unavailable or disrupted.

The practical pattern is convergence. Computing, networking, AI, physical systems, security, and trust infrastructure are becoming more interdependent. A useful technology strategy therefore needs to consider not only whether a new capability works, but also what infrastructure, standards, safeguards, and operational changes it requires.

What to Watch Beyond 2026

The safest way to evaluate emerging technology is to look for evidence of deployment rather than confident predictions. A technology becomes more consequential when reliability improves, standards stabilize, costs become workable, supporting infrastructure expands, and organizations can operate it without depending on exceptional conditions.

For AI agents, watch whether performance improves on long, interdependent workloads and whether permissions, evaluation, and human-review systems become easier to manage. For robotics, watch deployments beyond tightly controlled settings. For AI infrastructure, follow efficiency alongside electricity demand, processor availability, cooling requirements, grid connections, and financing.

For on-device AI, pay attention to which useful workloads can run locally without unacceptable battery, memory, thermal, or performance costs. For quantum technology, separate experimental computing milestones from the much more immediate work of PQC migration. For content provenance, interoperability and preservation of credentials across tools and platforms matter more than whether an individual product displays a badge. For satellite D2D, the important signals are service capabilities, supported devices, available capacity, regulation, spectrum coordination, and integration with terrestrial operators.

That maturity-based view also prevents an old technology from being relabeled as a new trend simply because it remains popular. The strongest technology trends to watch beyond 2026 are the ones producing observable changes in what systems can do, where they can operate, how they are secured, and what infrastructure is required to support them.

This article is brought to you by VicOne.

Robot safety has traditionally asked: Can a machine remain safe when something goes wrong? Physical AI raises a harder question: Can a machine remain safe when an attacker changes what it sees, decides, or does even when nothing appears to have failed?

As AI and robotics continue to advance at an unprecedented pace, modern robots perceive through multimodal sensors, interpret context using AI models, and translate those interpretations into physical action. As they move into dynamic environments, their safety increasingly depends on the integrity of the data guiding their decisions.

That dependence creates risks that conventional safety assessments may not fully capture. Recent research has demonstrated that manipulating what a robot sees, hears, or interprets can influence its behavior without requiring direct control.

Such manipulation can occur anywhere across its complex sensing and decision-making system — a layered attack surface encompassing training pipelines, system infrastructure, and runtime perception.

Layer One: Corrupting intelligence at its source

In 2017, BadNets demonstrated that a model could behave normally under most conditions, yet fail in the presence of a specific hidden trigger. In one example, a subtle pattern caused a stop sign to be misclassified as a speed limit sign without affecting the model’s behavior on other inputs.

What began as a classification vulnerability has since evolved into action manipulation.

At NeurIPS 2025, researchers introduced BadVLA a backdoor attack targeting Vision-Language-Action (VLA) models that allow robots to see, interpret instructions, and produce coordinated physical movement. Rather than altering a single label, the attack caused conditional deviations in the robot’s action trajectory when a trigger was present. Without the trigger, the model largely preserved normal task performance, while the backdoor remained effective under task transfers and model fine-tuning.

A related study in 2025, GoBA, showed that ordinary objects such as a coffee mug could serve as a reliable trigger. The researchers reported a 97 percent attack success rate without degrading performance on clean inputs.

A critical safety question today is whether Physical AI models remain within their task and safety boundaries under adversarial conditions.

These studies expose a blind spot in model validation: A model may pass testing yet produce corrupted behavior when a hidden trigger appears in operation.

So a critical safety question today is whether Physical AI models remain within their task and safety boundaries under adversarial conditions. Simulation tools such as NVIDIA Isaac Sim, when paired with VicOne Radeis, can test the effects of manipulated inputs before deployment.

VicOne LAB R7 demonstrates Radeis, a Physical AI safety validator for NVIDIA Isaac Sim that tests how adversarial visual inputs affect robot behavior before deployment.VicOne

Layer Two: System vulnerabilities as gateways to AI control

Even a securely trained model can be subverted if the surrounding system stack is vulnerable.

In September 2025, researchers disclosed UniPwn, a Bluetooth exploit chain affecting quadruped and humanoid robots from a major manufacturer. Hardcoded cryptographic keys allowed traffic decryption, authentication checks were bypassed, and command injection enabled root-level execution. The exploit is also described as “wormable.” A compromised robot could scan nearby units and potentially affect an entire fleet.

VicOne Lab R7’s demo shows how chaining three wireless exploits can trigger uncontrolled robot behavior within 60 seconds, resulting in operational disruption.VicOne

Middleware creates another exposure point. Vulnerabilities in ROS 2 and DDS-based systems can enable arbitrary code execution or abuse unauthenticated topics to deliver malicious commands. With sufficient access, an attacker could override motor commands or replace AI model weights without directly attacking the model architecture.

In this case, the components may still function as designed. What has changed is the trustworthiness of the commands flowing through the system. Vulnerability management can help teams identify known risks before deployment, while continuous monitoring can surface emerging threats.

Layer Three: Manipulating perception and reasoning at runtime

At runtime, manipulating inputs that shape perception or reasoning may require neither firmware modification nor a network breach.

In 2024, RoboPAIR demonstrated how carefully structured prompts could redirect LLM-controlled robots into unsafe trajectories. BadRobot exposed a deeper architectural weakness: in several cases, a robot verbally refused a dangerous command while its motion controller executed the action anyway.

Vision-based manipulation is equally powerful. VLAttack showed that an adversarial patch within the camera’s view could reduce a VLA model’s task success rate to zero. FreezeVLA showed that a single adversarial image could freeze a robot’s decision-making loop, making it unresponsive to subsequent instructions.

Runtime assurance must therefore look beyond whether individual components remain available and assess whether cyber events are beginning to affect physical behavior.

In each case, the camera may still work, the model may still run, and the controller may still respond. Yet the resulting behavior can be unsafe because the robot is acting on manipulated perception or reasoning.

Runtime assurance must therefore look beyond whether individual components remain available and assess whether cyber events are beginning to affect physical behavior. Security event correlation, behavioral-impact assessment, and policy-bounded response supported by edge AI, can help contain the affected path without unnecessarily stopping the entire robot fleet.

From point-in-time safety to lifecycle assurance

The risks across these three layers reveal the missing layer in robot safety assurance: cybersecurity. Functional safety addresses failures and unexpected operating conditions; cybersecurity extends that assurance to deliberate manipulation, including attacks that may leave the underlying system apparently functional.

This requires assurance across the robot’s lifecycle. During design, teams need to understand which cyber risks could invalidate assumptions behind intended behavior. Before deployment, they should test whether realistic attacks can cause a robot to deviate from its task or safety boundaries. In operation, monitoring should identify whether cyber events are beginning to affect behavior, contain the affected path, and preserve safe operation where possible.

VicOne’s lifecycle approach combines AI model and vulnerability scanning, simulation-based validation, and continuous monitoring to help secure robots from development through operation.VicOne

While cybersecurity does not replace functional safety, it helps ensure that Physical AI remains within acceptable boundaries even when what it sees, decides, or does is under attack.

For a deeper look at the cybersecurity risks and defense strategies shaping autonomous robotics, download our whitepaper “Securing the Rise of AI Robots: Cyber Risks, Real-World Threats, and Defense Strategies.”

Amazon Prime Day events are some of the most confusing shopping occasions in existence: It’s not even a single “day” anymore. Amazon promises “millions of deals”—but the displayed discounts are often misleading, and while it’s advertised as a members-only event, some deals are available to people who don’t subscribe to Prime. Add in the frenzy of limited-time Lightning Deals and you’ve got a perfect recipe for spending too much money on stuff you don’t even really want.

Fear not! I’ve been covering deals for over a decade and am here to help. WIRED’s Reviews team is familiar with common shopping pitfalls, and we closely track the best Prime Big Deal Days prices. What time do sales start and end? How do you tell whether a deal is actually a deal? We pooled our collective expertise to get you prepared for the latest Amazon Prime Day Event, which is technically dubbed “Amazon Prime Big Deal Days” and will be on October 6 and October 7 this year.

When Is Amazon Prime Day?

Amazon Prime Day has a main sale in the summer and a secondary sale—called Prime Big Deal Days—in the fall. This year, Prime Big Deal Days will take place on Tuesday and Wednesday, October 6 and October 7.

When Do Prime Day Deals Start?

The event kicks off at 3:01 am Eastern time (midnight Pacific) and runs for 48 hours. New deals will drop three times each day of the event, at 3 am, 11 am, and 4 pm ET, with Lightning Deals going live sporadically as well. WIRED will cover the best deals from both Amazon and retailers that have competing sales.

Are Prime Day Deals Only for Prime Members?

That’s the official line: You need to be an Amazon Prime member to shop Amazon Prime Day deals. There is a free 30-day trial available for eligible new accounts. (Prime membership comes with a lot of perks, and we’ve rounded up all of them here.) The trial will let you get in on the sale—just remember to cancel your membership to avoid any subsequent $15 monthly renewal charges.

However, there are usually plenty of discounts available if you’re not a subscriber. Other major retailers like Best Buy, Target, and Walmart typically hold competing sales during Prime Days. The prices are often close to what Amazon is offering on the same products, and sometimes the competing sales match the Prime Day price exactly. This is a good way to save even if you object to shopping on Amazon.

Is Prime Day Worth It?

It depends. For some items, Prime-exclusive event prices tend to be among the lowest we see all year. That’s especially true for Amazon hardware, like Kindles, Fire tablets, Fire TV sticks, and Echo devices. The kicker is that prices on nearly everything fluctuate throughout the year, and some products are discounted on a frequent basis. Even if the price is good, a deal on a product that goes on sale all the time diminishes the overall quality of that offer.

The sheer volume of deals promoted by Amazon during sales like Prime Day is a blessing and a curse. The truly standout discounts can be difficult to pinpoint—there’s so much stuff on sale that just browsing the site can feel overwhelming. But if you’re in the market for something specific, there’s a good chance the item you want will be discounted. We’ve seen some fantastic Prime-exclusive discounts in the past, ranging from dirt-cheap Kindles and video doorbells to elusive price drops on gaming consoles and office furniture. The tricky part is finding the diamonds in the rough.

WIRED covers legitimately good deals all year long, including during Prime Day. Our policy is to only cover deals on products someone from our team has personally used and would buy or has bought themselves, to avoid promoting cheap junk. Maybe it’ll be a product we’ve reviewed or an item we use in our day-to-day lives. We also only cover actual deals—if the price isn’t lower than it normally is, we don’t include it. We aim to provide pricing context as well. Our tips below will help you find those great discounts on your own—in the same ways that we would. No gatekeeping here.

How Do I Know Whether a Deal Is Good?

ABC: Always be checking (prices, that is). Researching an item’s price is the most important aspect of determining the quality of a discount. Don’t fall prey to deceptive marketing language and inflated MSRP prices. The easiest step is to take a second to Google the items you’re considering so you can see the price across multiple stores. Amazon product pages now feature a Price History link to see up to 365 days of pricing history, though it may not always be accurate.

One tool we use is CamelCamelCamel, which tracks Amazon’s prices over time. Paste the Amazon link or ASIN (found in the Product Information section on the Amazon product page) into CamelCamelCamel’s search bar to see the item’s lowest recorded price and its average price, and how frequently the price fluctuates. Some deals, such as Lightning Deals, are excluded from the pricing history, but this works for most items. It’s useful to see what an item has sold for in the past. And while Amazon’s Alexa for Shopping chatbot has price history information, it isn’t always reliable and often misses context (as evidenced by our personal testing). We also like Keepa, which has an extension (available for multiple browsers) that shows the recent price history for products directly on the Amazon page so you don’t have to open a new tab. When in doubt, check multiple sources.

Meet PitchFly, WIRED’s latest editorial recruit.

He has 165,112 neurons, and they’re all trained to generate story ideas. A sampling of his early output: “The Hidden Weather Problem Inside Surveillance”; “The Engineers Who Think Elon Musk Needs Less Computer Security”; and my personal favorite, “Everyone Wants Cooking. Nobody Has Solved Donald Trump.”

PitchFly uses a detailed map of the brain of a male drosophila—the common fruit fly. Developed by researchers from Google and a number of academic institutions, the map, known as a connectome, captures the way that 166,000 neurons and 125 million connecting synapses fire in response to stimuli. In essence, you can use it to simulate how a fly would respond to lots of stuff—it’s a very simple version of artificial intelligence based on charting real biological intelligence.

Because the researchers open-sourced it, you can easily use AI to import the connectome into a project with a little prompting. For PitchFly, I vibe coded a project in which the tiny digital drosophila brain generates story ideas. (I’m not sure why the fly has a little hat on, but I like its style.) This involved scraping together hundreds of the most popular story headlines from the site from the past year and feeding them into the connectome. I had Codex do the hard work, and it decided that the most efficient approach was to turn the headlines into words and phrases, then transform them into a representation that a neural network could understand. The connectome was fed the best-performing stories and told to generate its own ideas based on that.

In other words, this isn’t a fly-based language model—although someone apparently created one of those. The fly brain has no idea what any of the words mean, or if any of it makes sense. It’s just remixing the patterns it has seen in pleasing new ways. A cynic might suggest this is exactly how some journalists generate their own pitches, but I think that’s a bit unfair—and judging by its lunatic ideas, PitchFly won’t be replacing me anytime soon:

• The Tiny Shift in Agentic AI Is Rewriting the Rules of Food and Drink
• What Security News Is Quietly Doing to Donald Trump
• The Race to Reinvent Privacy Before Artificial Intelligence Breaks
• Is China About to Make Digital Syndication Obsolete?

In the future, perhaps I could have the program continue to learn by reading new WIRED headlines. For now, though, this seems like a decent proof of concept, not to mention evidence at last that the average WIRED writer is intellectually superior to a fruit fly.

After the connectome’s release in early September, dozens of other weird and wonderful projects powered by fruit-fly intelligence sprang up.

An X user called Lyra Bubbles, for instance, demo’d a project that involved training the virtual fly brain to play the VR game Beat Saber. Alex Wormuth, a software engineer at Coinbase, created StonkFly, which uses the fly’s tiny brain to decide how to trade stocks. (It’s losing money, but it’s doing surprisingly well, all things considered.)

“The fly brings lighthearted, humorous relief” at a time when everyone is worried about the existential risks of AI, Wormuth told me in a DM. He says he found playing with the fruit fly connectome philosophically fascinating, too. “It sparks questions about ethics of this and whether there is any consciousness [in the replication of fly’s brain],” he says.

Several employees have said they’re leaving the studio.