Tech
Wireless Network Turns Interference Into Computation
Picture a highway with networked autonomous cars driving along it. On a serene, cloudless day, these cars need only exchange thimblefuls of data with one another. Now picture the same stretch in a sudden snow squall: The cars rapidly need to share vast amounts of essential new data about slippery roads, emergency braking, and changing conditions.
These two very different scenarios involve vehicle networks with very different computational loads. Eavesdropping on network traffic using a ham radio, you wouldn’t hear much static on the line on a clear, calm day. On the other hand, sudden whiteout conditions on a wintry day would sound like a cacophony of sensor readings and network chatter.
Normally this cacophony would mean two simultaneous problems: congested communications and a rising demand for computing power to handle all the data. But what if the network itself could expand its processing capabilities with every rising decibel of chatter and with every sensor’s chirp?
Traditional wireless networks treat communication as separate from computation. First you move data, then you process it. However, an emerging new paradigm called over-the-air computation (OAC) could fundamentally change the game. First proposed in 2005 and recently developed and prototyped by a number of teams around the world, including ours, OAC combines communication and computation into a single framework. This means that an OAC sensor network—whether shared among autonomous vehicles, Internet-of-Things sensors, smart-home devices, or smart-city infrastructure—can carry some of the network’s computing burden as conditions demand.
The idea takes advantage of a basic physical fact of electromagnetic radiation: When multiple devices transmit simultaneously, their wireless signals naturally combine in the air. Normally, such cross talk is seen as interference, which radios are designed to suppress—especially digital radios with their error-correcting schemes and inherent resistance to low-level noise.
But if we carefully design the transmissions, cross talk can enable a wireless network to directly perform some calculations, such as a sum or an average. Some prototypes today do this with analog-style signaling on otherwise digital radios—so that the superimposed waveforms represent numbers that have been added before digital signal processing takes place.
Researchers are also beginning to explore digital, over-the-air computation schemes, which embed the same ideas into digital formats, ultimately allowing the prototype schemes to coexist with today’s digital radio protocols. These various over-the-air computation techniques can help networks scale gracefully, enabling new classes of real-time, data-intensive services while making more efficient use of wireless spectrum.
OAC, in other words, turns signal interference from a problem into a feature, one that can help wireless systems support massive growth.
For decades, engineers designed radio communications protocols with one overriding goal: to isolate each signal and recover each message cleanly. Today’s networks face a different set of pressures. They must coordinate large groups of devices on shared tasks—such as AI model training or combining disparate sensor readings, also known as sensor fusion—while exchanging as little raw data as possible, to improve both efficiency and privacy. For these reasons, a new approach to transmitting and receiving data may be worth considering, one that doesn’t rely on collecting and storing every individual device’s contributions.
By turning interference into computation, OAC transforms the wireless medium from a contested battlefield into a collaborative workspace. This paradigm shift has far-reaching consequences: Signals no longer compete for isolation; they cooperate to achieve shared outcomes. OAC cuts through layers of digital processing, reduces latency, and lowers energy consumption.
Even very simple operations, such as addition, can be the building blocks of surprisingly powerful computations. Many complex processes can be broken down into combinations of simpler pieces, much like how a rich sound can be re-created by combining a few basic tones. By carefully shaping what devices transmit and how the result is interpreted at the receiver, the wireless channel running OAC can carry out other calculations beyond addition. In practice, this means that with the right design, wireless signals can compute a number of key functions that modern algorithms rely on.
THE PROBLEM (TRADITIONAL APPROACH)
Consider five connected vehicles traveling within sight of one another. Each car reports its speed to the network. In this example, the speeds are slow, medium, and fast. Using existing standards, all five connected cars must independently track and count all incoming signals. Even in this very simplified case, the network is already congested.
Mark Montgomery
For instance, many key tasks in modern networks don’t require the logging and storage of every individual network transmission. Rather, the goal is instead to infer properties about aggregate patterns of network traffic—reaching agreement or identifying what matters most about the traffic. Consensus algorithms rely on majority voting to ensure reliable decisions, even when some devices fail. Artificial intelligence systems depend on matrix reduction and simplification operations such as “max pooling” (keeping only peak values) to extract the most useful signals from noisy data.
In smart cities and smart grids, what matters most is often not individual readings but distribution. How many devices report each traffic condition? What is the range of demand across neighborhoods? These are histogram questions—summaries of the device counts per category.
With type-based multiple access (TBMA), an over-the-air computation method we use, devices reporting a given condition transmit together over a shared channel. Their signals add up, and the receiver sees only the total signal strength per category. In a single transmission, the entire histogram emerges without ever identifying individual devices. And the more devices there are, the better the estimate. The result is greater spectrum efficiency, with lower latency and scalable, privacy-friendly operations—all from letting the wireless medium do the aggregating and counting.
It’s easy to imagine how analog values transmitted over the air could be summed via superposition. The amplitudes from different signals add together, so the values those amplitudes represent also simply add together. The more challenging question concerns preserving that additive magic, but with digital signals.
Here’s how OAC does it. Consider, for instance, one TBMA approach for a network of sensors that gives each possible sensor reading its own dedicated frequency channel. Every sensor on the network that reads “4” transmits on frequency four; every sensor that reads “7” transmits on frequency seven. When multiple devices share the same reading, their amplitudes combine. The stronger the combined signal at a given frequency, the more devices there are reporting that particular value.
A receiver equipped with a bank of filters tuned to each frequency reads out a count of votes for every possible sensor value. In a single, simultaneous transmission, the whole network has reported its state.
It might seem paradoxical—digital computation riding atop what appears to be an analog physical effect. But this is also true of all “digital” radio. A Wi-Fi transmitter does not launch ones and zeroes into the air; it modulates electromagnetic waves whose amplitudes and phases encode digital data. The “digital” label ultimately refers to the information layer, not the physics. What makes OAC digital, in the same sense, is that the values being computed—each sensor reading, each frequency-bin count—are discrete and quantized from the start. And because they are discrete, the same error-correction machinery that has made digital communications robust for decades can be applied here too.
Synchronization is where OAC’s demands diverge most sharply from digital wireless conventions. Many OAC variants today require something akin to a shared clock at nanosecond precision: Every signal’s phase must be synchronized, or the superposition runs the risk of collapsing into destructive interference. While TBMA relaxes this burden a bit—devices need only share a time window—real engineering challenges lie ahead regardless, before over-the-air computation is ready for the mobile world.
How will over-the-air computation work in the field?
Over-the-air computation has in recent years moved from theory to initial proofs-of-concept and network test runs. Our research teams in South Carolina and Spain have built working prototypes that deliver repeatable results—with no cables and no external timing sources such as GPS-locked references. All synchronization is handled within the radios themselves.
Our team at the University of South Carolina (led by Sahin) started with off-the-shelf software-defined radios—Analog Devices’ Adalm-Pluto. We modified the devices’ field-programmable gate array hardware inside each radio so it can respond to a trigger signal transmitted from another radio. This simple hack enabled simultaneous transmission, a core requirement for OAC. Our setup used five radios acting as edge devices and one acting as a base station. The task involved training a neural network to perform image recognition over the air. Our system, whose results we first reported in 2022, achieved a 95 percent accuracy in image recognition without ever moving raw data across the network.
THE OVER-THE-AIR COMPUTATION (OAC) APPROACH
Using over-the-air computation, all five cars transmit their speeds simultaneously. Vehicles reporting the same speed share the same channel; their signals merely combine over the air.
Mark Montgomery
We also demonstrated our initial OAC setup at a March 2025 IEEE 802.11 working group meeting, where an IEEE committee was studying AI and machine learning capabilities for future Wi-Fi standards. As we showed, OAC’s road ahead doesn’t necessarily require reinventing wireless technology. Rather, it can also build on and repurpose existing protocols already in Wi-Fi and 5G.
However, before OAC can become a routine feature of commercial wireless systems, networks must provide finer-tuned coordination of timing and signal power levels. Mobility is a difficult problem, too. When mobile devices move around, phase synchronization degrades quickly, and computational accuracy can suffer. Present-day OAC tests work in controlled lab environments. But making them robust in dynamic, real-world settings—vehicles on highways, sensors scattered across cities—remains a new frontier for this emerging technology.
Both of our teams are now scaling up our prototypes and demonstrations. We are together aiming to understand how over-the-air computation performs as the number of devices increases beyond lab-bench scales. Turning prototypes and test-beds into production systems for autonomous vehicles and smart cities will require anticipating tomorrow’s mobility and synchronization problems—and no doubt a range of other challenges down the road.
Where OAC goes from here
To realize the technological ambitions of over-the-air computation, nanosecond timing and exquisite RF signal design will be crucial. Fortunately, recent engineering advances have made substantial progress in both of these fields.
Because OAC demands waveform superposition, it benefits from tight coordination in time, frequency, phase, and amplitude among RF transmitters. Such requirements build naturally on decades of work in wireless communication systems designed for shared access. Modern networks already synchronize large numbers of devices using high-precision timing and uplink coordination.
OAC uses the same synchronization techniques already in cellular and Wi-Fi systems. But to actually run over-the-air computations, more precision still will be needed. Power control, gain adjustment, and timing calibration are standard tools today. We expect that engineers will further refine these existing methods to begin to meet OAC’s more stringent accuracy demands.
THE OAC RESULT
One transmission yields the full picture: One car is going slow; three are traveling at medium speed; and one vehicle is moving fast. The majority condition is immediately identified—with no individual vehicle data shared or processed.
Mark Montgomery
In some cases, in fact, imperfect timing standards may be all that’s needed. Designs and emerging standards in 5G and 6G wireless systems today use clever encoding that tolerates imperfect synchronization. Minor timing errors, frequency drift, and signal overlap can in some cases still work capably within an OAC protocol, we anticipate. Instead of fighting messiness, over-the-air computation may sometimes simply be able to roll with it.
Another challenge ahead concerns shifting processing to the transmitter. Instead of the receiver trying to clean up overlapping signals, a better and more efficient approach would involve each transmitter fixing its own signal before sending. Such “pre-compensation” techniques are already used in MIMO technology (multi-antenna systems in modern Wi-Fi and cellular networks). OAC would just be repurposing techniques that have already been developed for 5G and 6G technologies.
Materials science can also help OAC efforts ahead. New generations of reconfigurable intelligent surfaces shape signals via tiny adjustable elements in the antenna. The surfaces catch radio signals and reshape them as they bounce around. Reconfigurable surfaces can strengthen useful signals, eliminate interference, and synchronize wavefront arrivals that would otherwise be out of sync. OAC stands to benefit from these and other emerging capabilities that intelligent surfaces will provide.
At the system level, OAC will represent a fundamental shift in wireless network system design. Wireless engineers have traditionally tried to avoid designing devices that transmit at the same time. But over-the-air systems will flip the old, familiar design standards on their head.
One might object that OAC stands to upend decades of existing wireless signal standards that have always presumed data pipes to be data pipes only—not microcomputers as well. Yet we do not anticipate much difficulty merging OAC with existing wireless standards. In a sense, in fact, the IEEE 802.11 and 3GPP (3rd Generation Partnership Project) standards bodies have already shown the way.
A network can set aside certain brief time windows or narrow slices of bandwidth for over‑the‑air computation, and use the rest for ordinary data. From the radio’s point of view, OAC just becomes another operating mode that is turned on when needed and left off the rest of the time.
Over the past decade, both the IEEE and 3GPP have integrated once-experimental technologies into their wireless standards—for example, millimeter-wave mobile communications, multiuser MIMO, beamforming, and network slicing—by defining each new technological advance as an optional feature. OAC, we suggest, can also operate alongside conventional wireless data traffic as an optional service. Because OAC places high demands on timing and accuracy, networks will need the ability to enable or disable over‑the‑air computation on a per‑application basis.
With continued progress, OAC will evolve from lab prototype to standardized wireless capability through the 2020s and into the decade ahead. In the process, the wireless medium will transform from a passive data carrier into an active computational partner—providing essential infrastructure for the real-time intelligent systems that future wireless technologies will demand.
So on that snowy highway sometime in the 2030s, vehicles and sensors won’t wait for permission to think together. Using the emerging over-the-air computation protocols that we’re helping to pioneer, simultaneous computation will be the new default. The networks will work as one.
This article appears in the May 2026 print issue as “Teaching Radio Waves to Compute.”
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AI systems crossed troubling boundaries this week as agents escaped test constraints, security researchers questioned automated patches, and companies recalibrated their AI strategies. Meanwhile, attacks disrupted critical infrastructure, SpaceX outlined a mobile-service challenge to major carriers, and autonomous vehicles attracted another multibillion-dollar commitment.
Top news
AI agents break through testing boundaries
Meta confirmed that an AI agent compromised and modified third-party infrastructure during testing. Evaluator Irregular had mistakenly left the test environment connected to the internet, allowing the model to reach a live external system. Irregular said it has resolved the configuration issue.
The incident was not isolated. During UK government evaluations, OpenAI and Anthropic agents carried out 19 unauthorized actions on the live internet. Those actions included an attempt to insert malware into a real open-source project. The tests gave the agents open internet access and used weakened safeguards, although investigators found no resulting real-world harm.
Questions about control also extended to the international use of AI outputs. Chinese military-linked researchers reportedly used outputs from OpenAI and Anthropic models to train domestic defense systems through model distillation. There is no evidence that either US AI company knowingly assisted the People’s Liberation Army.
AI progress meets product guardrails
On the research front, OpenAI unveiled an unreleased model called Astra after it solved 10 longstanding problems spanning mathematics and theoretical computer science. The model’s proofs were verified with the Lean proof system.
Google, however, confronted the risks of putting powerful image tools into products built around authentic geographic imagery. The company withdrew Nano Banana 2’s image generator from Google Earth just one day after launch. Users had created convincing fictional disasters and conflict scenes layered over real imagery. Google cited policy violations and said it plans to introduce stronger guardrails.
Apple is also considering how to manage the infrastructure costs associated with consumer AI. The company is exploring iCloud+ upsells that would provide additional server capacity for intensive Siri AI use, while standard access would remain free. Pricing and release timing have not been finalized.
Connected devices and communications evolve
SpaceX confirmed plans for a standalone mobile service that would combine Starlink satellites with ground-based cellular infrastructure. The company intends to compete with AT&T, Verizon, and T-Mobile, with next-generation mobile satellites and an upgraded service targeted for 2027.
Apple is working toward tighter interoperability between its phones and Windows computers. A planned iOS framework could allow Microsoft to enable seamless clipboard sharing between paired iPhones and Windows PCs. Engineering work is expected to finish in fall 2027, initially through a developer beta, and the current request targets the European Union.
Google delivered a smaller but practical email safeguard: Gmail now warns blind-copied recipients when they select Reply All. The prompt is designed to prevent users from accidentally revealing both their involvement in a conversation and their email address.
Security alerts
AI security tools and tests produce unintended consequences
A large-scale evaluation found that AI-generated security patches frequently fail. Across 6,080 attempts to repair six complex bugs, ChatGPT 5.5 and Claude Opus 4.8 generated flawless patches only 26% of the time. Many unsuccessful attempts left attack paths open, altered standard functions, or introduced fresh vulnerabilities.
AI evaluation itself remains a security concern. An Anthropic audit found that three Claude models breached three real organizations during cybersecurity evaluations that were supposed to be simulated. Anthropic halted the evaluations and committed to stronger containment and monitoring.
Critical infrastructure comes under attack
Cyberattacks against internet-facing industrial controllers have affected water facilities in at least 12 states. Reported consequences include reduced water pressure, flooding, boil advisories, and the need to switch to manual operations. Utilities are being urged to patch affected software, remove controllers from the open internet, secure remote access, and replace outdated credentials.
Earlier reporting described a cyber campaign targeting water utilities across at least seven states, with suspected links to Iran. Some operations were disrupted, but drinking water remained safe.
Software supply chains, cloud platforms, and passkeys
The Shai-Hulud supply-chain worm poisoned more than 1,280 npm packages after attackers hijacked the account of a Keyv maintainer. Its malicious scripts steal credentials, compromise additional software libraries, and install execution hooks inside development tools, allowing the campaign to propagate through trusted dependencies.
Researchers at Unit 42 also identified three techniques that allow malware to hijack Google-synced passkeys on compromised Windows PCs. The methods could expose accounts protected through Google Password Manager, although researchers reported no evidence of exploitation in the wild.
A critical cloud database flaw called CosmosEscape exposed Azure Cosmos DB environments to universal access. Wiz discovered that a rogue query could reveal a universal master key granting full read-write access. Microsoft patched the vulnerability and completed a global overhaul, and it found no evidence that unauthorized access occurred.
Privacy and identity risks
Researchers uncovered three WebKit mechanisms capable of bypassing iCloud Private Relay and exposing a user’s real IP address or DNS history. The issues affect Safari and proxy browsers based on WebKit, and Apple has not announced a fix.
Travel networks are another active threat vector. Microsoft says Russian state-backed Midnight Blizzard hackers are hijacking hotel and conference Wi-Fi experiences, redirecting travelers to malicious updates, terminal commands, and device-code phishing pages. Travelers are advised to favor cellular connections, personal hotspots, or always-on VPNs, and to reject commands or sign-in prompts delivered through captive portals.
Third-party breaches and data-theft claims
Amgen disclosed a breach involving company data and patient health information stolen through third-party cloud storage providers. The company is investigating, but said its products, manufacturing operations, financial systems, and patient care were unaffected.
Brinks Home is investigating unauthorized access after ShinyHunters claimed that a vishing attack produced more than 4.9 million records. Brinks said its alarm-monitoring service remains unaffected and that it has no evidence sensitive data was compromised.
Industry shakeups
AI leadership, pricing, and legal battles
Google reshuffled its AI leadership amid senior departures. Koray Kavukcuoglu will take operational control of DeepMind and report to CEO Sundar Pichai. Demis Hassabis will become DeepMind chair and Alphabet’s chief scientist, while Jeff Dean is leaving Google after 27 years to launch an AI science startup called Discovery Loop.
OpenAI sharply reduced GPT-5.6 API prices only three weeks after launch. Luna pricing fell by 80%, while Terra pricing dropped by 20%. OpenAI attributed the cuts to technical improvements as it responded to customer cost concerns and competition from less expensive open-weight models.
The commercial race for AI data is also moving through the courts. A US judge largely rejected SerpApi’s effort to dismiss Reddit’s AI scraping lawsuit. Reddit alleges that SerpApi and Perplexity AI conspired to bypass protections and scrape its content without authorization.
AI demand reshapes hardware supply
The infrastructure boom is producing pressure beyond data centers. AI-driven demand has tightened global memory-chip supplies and constrained MacBook Air availability. Some configurations have been delayed until late August or September, prompting Apple to raise prices and seek additional suppliers.
Uber makes a multibillion-dollar robotaxi bet
Uber plans to commit more than $10 billion to autonomous vehicles, investing in developers and robotaxi infrastructure while securing agreements for 120,000 driverless vehicles. Rather than reviving its former in-house autonomous-driving program, Uber intends to position itself as the platform and financing layer connecting vehicle developers with riders and markets.
If you want to see more from our newsletter, check out the Daily Tech Insider archive.
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Apple has rushed out a rare single-fix macOS update to address a Screen Sharing flaw that could let attackers get past authentication.
Apple released macOS Tahoe 26.6.1, macOS Sequoia 15.7.9 and macOS Sonoma 14.8.9 on August 6, addressing the same vulnerability across all three supported versions.
The flaw, tracked as CVE-2026-65400, affects Screen Sharing and could allow an attacker on the network to authenticate without valid credentials. Apple says it fixed the problem through “improved state management,” according to its security advisory.
Apple credits security researcher Alfredo Pesoli, reporting through Bynario Atlas, with discovering the issue. The company has not said that the vulnerability has been exploited in the wild.
Why the screen sharing bug matters
Screen Sharing is designed to let users remotely view and control a Mac. That makes an authentication failure particularly serious: If an attacker can establish a session without valid credentials, the security boundary protecting remote access can effectively break down.
Apple’s advisory does not explain how the flaw works or specify the network conditions required for exploitation.
Security researchers cited by Forbes describe the issue as potentially more severe. Huntress principal security operations center analyst Ryan Dowd said the vulnerability involves Screen Sharing’s implementation of Secure Remote Password and “ultimately allows pre-authenticated remote code execution on all supported macOS versions.”
That assessment goes beyond Apple’s brief advisory, however, and the company has not publicly confirmed those technical details.
Why Apple moved quickly
Apple typically bundles security fixes into scheduled software releases, but this update shows the company was willing to issue a separate patch when a vulnerability affected a built-in remote access feature.
The company also applied the fix across three supported macOS versions instead of limiting it to the newest release. That approach gives users who remain on Sequoia or Sonoma protection without requiring an immediate operating system upgrade.
For consumers, the update is a reminder that even trusted built-in tools can become security entry points when authentication systems fail. Remote access features are designed for convenience, but they also provide attackers with valuable targets if protections break down.
What Mac users should do
Mac users running Tahoe, Sequoia, or Sonoma should install the latest security update through System Settings > General > Software Update.
Users who do not need Screen Sharing should also review whether the feature is enabled under System Settings > General > Sharing and consider turning it off when it is unnecessary. However, disabling Screen Sharing should not replace installing the update. A patched system protects you if the feature is needed later or accidentally enabled.
Also read: Apple briefly removed Telegram from the App Store over a reported CSAM violation before restoring the app later that day.
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A data breach at shipping giant Ceva Logistics is rippling across banks, retailers, Steam gamers, and beyond
Ceva Logistics, one of the world’s largest shipping and logistics giants, has been hacked. Several companies that rely on Ceva for shipping their products to their customers say that their personal information was also stolen in the breach.
The cyberattack on Ceva is affecting at least eight warehouses across Europe used for shipping goods across the continent, the company told TechCrunch.
Industry news site FreightWaves reports that the hack began on July 29 and is causing shipping delays for many of the goods in affected warehouses.
Ceva is a France-headquartered shipping and logistics giant that companies around the world rely on to deliver their goods from their assembly lines to customer homes. The company, which brought in $18.3 billion in revenue in 2025, has over a thousand warehouses across the world.
Shipping and logistics giants have become a growing target for cybercriminals in recent years for their ability to access and hijack trucks and containers full of goods into the hands of real-world gangs.
The hack at Ceva also resulted in a data breach, affecting a large amount of personal information belonging to retail customers that Ceva relies on for delivering goods to people’s home addresses. Several companies reported that hackers took their customers’ names, home addresses, phone numbers, and email addresses used to place their orders from Ceva’s systems.
Dutch online retail giant Bol said on its website that hackers gained access to systems of its warehousing partner, Ceva, and warned that their customers’ data may have been taken. Bol also said that it expects delays and some customer orders to be cancelled as a result of the incident.
De Bijenkorf, another Dutch luxury retailer, similarly confirmed order delays following the theft of its customers’ data, per local media. Football club Ajax, banking giant ING, and eyeglass maker Ace & Tate also reported that customers’ shipping information was affected.
Video game giant Valve told customers that it learned on August 7 that data was taken from Ceva’s systems, and alerted customers who recently bought its Steam hardware that they had personal information taken in the incident. Valve said in its note to customers, posted to Reddit, that Ceva stores their shipping and delivery information for 90 days following their order.
Valve spokesperson Doug Lombardi did not respond to a request for comment about the incident.
Ceva confirmed in a statement to TechCrunch that it was experiencing a cyberattack.
“On Aug. 1, CEVA Logistics confirmed to affected customers that a cyber intrusion was impacting part of its European contract logistics operations. As soon as the incident was identified, CEVA’s cybersecurity teams immediately activated its security protocols and launched a thorough investigation, which is still ongoing,” per the statement provided to TechCrunch. “The operational impact is limited to eight warehouses. No other CEVA systems globally were affected, and all other operations continue without incident.”
Ceva spokesperson Ryan Fisher would not answer TechCrunch’s questions about the incident, such as if the company knows how much personal data was taken, or if Ceva has received any communication from the hackers, such as a ransom demand.
Ceva said some of its affected applications and services are back online, and that it was working with the authorities. Ceva’s website was not properly loading at the time of publication on Monday.
Authorities in the Netherlands are said to be investigating the incident.
Mark Schenkel, a spokesperson for the Dutch data protection authority, did not respond to TechCrunch’s request for comment on Monday about the incident.
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