Wednesday, August 12, 2026

 

TECH


Oracle bets on a new cloud frontier and prepares integration that could transform AI workloads

Artificial intelligence has turned data centers into massive processing hubs, but some companies are already looking toward what comes next. Oracle and Quantinuum have announced a strategic partnership aiming to bring quantum computing, traditional supercomputing, and AI together within a single infrastructure. This initiative could allow developers to tackle extremely complex problems without needing to install a quantum machine on their own premises.

Oracle and Quantinuum have announced a multi-year strategic partnership to integrate quantum computing capabilities into Oracle Cloud Infrastructure (OCI).

The initiative centers on Helios, Quantinuum’s commercial quantum computer, which is set to become available via a new OCI quantum service. This will enable customers to combine the hardware with traditional high-performance computing (HPC) resources and GPU-based infrastructure.

The goal is not to immediately replace conventional computers with quantum machines; rather, the strategy relies on combining different architectures.

The two companies intend to explore how quantum computing, artificial intelligence, and classical supercomputing can work together to address problems requiring extraordinary processing power.

Potential applications include new material discovery, drug development, logistics, energy, and financial modeling.

Universities and research institutions are also among the groups that could benefit from the platform, primarily because accessing a quantum machine via the cloud eliminates one of the technology's major barriers: the need to own highly specialized equipment.

Helios features 98 physical qubits and prioritizes precision... Commercially launched in November 2025, Helios represents the third generation of quantum computers developed by Quantinuum.

The machine utilizes trapped-ion technology and features 98 physical qubits. The system has already been used in demonstrations involving 48 logical qubits and, according to the company, achieves an average fidelity of 99.921% for two-qubit gates. Precision is especially important because errors represent one of the biggest obstacles in current quantum computing. The more reliable the operations performed by qubits, the greater the potential for executing complex algorithms in a useful way.

Another aspect highlighted by the companies is energy consumption.

According to estimates presented by Quantinuum, a Helios system would consume less than 1% of the energy used by today's leading supercomputers. This does not mean quantum machines will automatically replace supercomputers, but it could make them valuable complementary resources for specific workloads.

The aim is precisely to route each part of a problem to the most suitable hardware.

An application could, for example, use CPUs for certain operations, GPUs for artificial intelligence-related tasks, and a quantum processing unit (QPU) for stages where quantum algorithms offer advantages.

Developers will be able to experiment with quantum hardware without purchasing a machine... Installing a quantum computer is far removed from the conventional experience of adding servers to a data center. These systems require highly specialized infrastructure, technical expertise, and specific operating conditions.

The cloud can mask much of this complexity.

With Helios running on OCI infrastructure, the expectation is that customers will have secure, managed access to the quantum computer without needing to purchase or directly manage the equipment.

The system is set to be integrated with Oracle’s compute, storage, networking, identity, and data services, utilizing access controls and governance mechanisms already familiar to the platform's customers.

Oracle plans to unveil a preview version of the OCI quantum service in the coming months.

One of the goals is to simplify the transition between simulation and execution. Developers will be able to initially test applications in simulated environments and subsequently run them on actual quantum hardware.

The service is also expected to combine Quantinuum’s development tools with support for open frameworks designed for hybrid programming.

This could be particularly important because, at least initially, many commercial quantum computing applications will likely rely on this close collaboration between classical and quantum machines.

The real bet lies in the combination of AI and quantum computing... The partnership also reveals how major tech companies are beginning to envision the next stage of computing infrastructure.

AI has dramatically increased the demand for GPUs, energy, and processing power. Quantum computing offers a radically different architecture and, for certain categories of problems, could complement these systems.

For Mahesh Thiagarajan, Executive Vice President of Oracle Cloud Infrastructure, the integration aims to provide developers with a practical way to explore how quantum resources can complement AI and HPC workloads.

Researchers also see advantages in this approach. Having GPUs and QPUs available within the same environment can reduce operational complexity and allow scientific teams to focus their efforts on experiments rather than managing disparate infrastructures.

However, there is still a considerable gap between making quantum computers available and demonstrating broad commercial advantages in real-world scenarios.

That is precisely why cloud integration can be strategic. Instead of requiring companies to make massive investments in experimental hardware, they can begin testing algorithms, identifying applications, and discovering where the technology truly delivers benefits.

The partnership between Oracle and Quantinuum, therefore, represents more than just the arrival of another cloud service. It points toward a future where CPUs, GPUs, and quantum processors can share the same workload, each executing the part of the problem it was designed to handle.

If this hybrid architecture works as expected, the next transformation in enterprise computing may not come from replacing current machines, but from the arrival of a new type of processor working quietly alongside them.

mundophone


TECH


The new race for batteries could completely change how the power grid operates

Europe’s energy transition is creating a power grid increasingly dependent on a technology that, until recently, seemed to be merely part of the solution. Thousands of batteries already store electricity generated from renewable sources, helping to balance periods of surplus and shortage. However, as these systems multiply, a counterintuitive situation arises: under certain circumstances, they could all act simultaneously, placing additional strain on the grid precisely when it needs stability most.

The growth of solar and wind power has raised an issue that cannot be resolved simply by installing more panels and turbines. The sun does not generate electricity throughout the night, while the wind can die down just as demand rises.

This is where battery energy storage systems—known as BESS—come into play.

During periods of high output, these batteries can absorb and store surplus electricity. When consumption rises or renewable generation drops, they can feed some of that energy back into the grid.

This expansion is already proceeding at a rapid pace. In 2025, Europe added approximately 36 GWh of new capacity—a 48% increase over the previous year. With this, the continent surpassed the 100 GWh mark for operational storage capacity for the first time.

More than half of the new installations that year consisted of large-scale projects connected directly to the power grid.

The advantage is clear. Storing surplus energy allows for greater utilization of power generated from renewable sources and reduces instances where electricity availability is so high that prices turn negative.

According to estimates by Ember, by 2030, European solar and wind generation could exceed domestic demand during certain periods, accumulating a surplus of up to 183 TWh over the course of a year.

This scenario could lead to significant savings, including a reduced need to purchase gas to meet demand. However, an issue arises precisely when these batteries move from being few in number to existing by the thousands.

The most critical moment may be precisely when the grid calls for help... The warning came from the United Kingdom, where the Panel of Technical Experts—a body that reviews analyses regarding electricity supply security—examined a specific situation involving batteries participating in the capacity market.

Imagine grid operators realizing that electricity supplies might run tight. Before that happens, a warning known as a "Capacity Market Notice" may be issued.

For certain batteries, this notice serves as a crucial signal.

These units need to be sufficiently charged to supply electricity if called upon during a period of grid stress. Consequently, some operators might want to charge their batteries before the situation worsens.

Individually, this does not appear to be a major problem.

The difficulty arises when thousands of systems make a similar decision at virtually the same time.

Instead of easing the strain on the grid, the batteries could temporarily increase electricity consumption by drawing power to replenish their own reserves.

It is a paradox: equipment installed to provide system flexibility could, under certain conditions, drive up demand right before a critical moment.

The British report does not claim that this behavior is currently causing blackouts, nor does it recommend halting the expansion of battery storage.

The warning is more specific: the models used by operators need to account for this additional demand and the collective behavior of these devices.

The challenge now is to get thousands of batteries to act as one... The issue becomes even more intriguing when considering who controls these batteries.

Some belong to large, grid-connected projects, but many others may be distributed across homes, businesses, and small facilities. Each unit may respond to different incentives and make decisions independently.

For grid operators, however, what matters is the combined effect.

One possible solution lies in so-called aggregators and virtual power plants. Instead of allowing thousands of batteries to operate in isolation, these systems can coordinate their charge and discharge cycles as if they were a single large storage unit.

Thus, when there is a surplus of electricity, they will be able to absorb energy. When demand rises, they can feed some of it back into the grid. And, crucially, they can prevent thousands of units from simultaneously making a decision that disrupts the system's balance.

The expansion in Europe is far from over. SolarPower Europe projects that new annual installations could exceed 50 GWh by 2026 and reach 138 GWh by 2030.

This means the challenge will not simply be installing enough batteries.

The real issue will be coordinating them.

The greater the number of connected systems, the more important it becomes to predict when they will charge, when they will discharge, and how their individual decisions will affect the grid as a whole.

Ultimately, Europe may discover that the future of storage depends not just on having millions of batteries available, but on getting them to act—at the right moment—like a single, massive power plant.

 

mundophone

Tuesday, August 11, 2026

 

TECH


New tech adds phone tracking to license plate readers, associating devices with identifiable cars

Imagine that you share a ride to work with the same colleague most mornings. As it passes by a license plate reader, the camera records the car, which can be linked through vehicle records to its registered owner. Beside it, another sensor detects signals broadcast by devices traveling nearby, such as your phone and your colleague's smartwatch.

After enough trips, software may treat some of those devices as a recurring electronic signature associated with the vehicle. Weeks later, one of the same device signals appears alongside a different car connected to an investigation. The signal itself may not contain its owner's name, but its previous association with a known vehicle gives investigators another clue they can use to work out who was carrying the device.

SignalTrace, a system marketed by the security company Leonardo, is designed to work alongside automatic license plate readers. The company says it can recognize groups of consumer devices that regularly move together, then associate them with license plate records and time-stamped locations. The pattern can then be searched even when a police investigator does not know the plate number.

I am a researcher who studies the intersection of data governance, digital technologies and governments, including surveillance technologies. I see that SignalTrace could further shift how police conduct investigations, putting emphasis on people's movements and associations before their identities are known.

SignalTrace is a tested and marketed capability, but not yet an established police practice. One report indicates that several of the devices are installed in Oxon Hill, Maryland, and the company's predecessor technology appears on an official New York state contract price list.

A narrow definition of identification...Leonardo's new explanatory sheet states that SignalTrace "does not identify people." It says the system "only collects electronic signatures" from signals already being broadcast, such as Bluetooth or radio-frequency identification tags. Those signatures, by themselves, do not disclose a person's identity. The company says the output must be corroborated through ordinary investigative methods.

That description relies on a narrow meaning of identity, however. A sensor may not pull a legal name from a phone, but police could still work out who likely owns the device by linking its signal to other records. For example, the same signal might repeatedly appear with a car registered to one person, outside that person's home, or alongside another device already connected to a known subject. That means a person could become part of an investigation because of where their device repeatedly appeared and who it appeared near, even if the police had no reason to suspect that person at the outset.

Leonardo's SignalTrace product page says the system stores electronic fingerprints for later queries and can recognize a vehicle without seeing its license plate. A separate product sheet says the technology helps identify suspects through the mix of devices they carry. The patent behind the system describes targets that may be people or vehicles. It also describes searchable signatures that can be correlated with visual identifiers and used to track a target across locations.

SignalTrace may begin with a nameless pattern, but its value comes from recognizing that pattern again and connecting it to information that police already possess. Once an officer links a recurring signature to a license plate record or case file, the absence of a name in the original signal offers little protection.

A nameless identifier can still be personal...Federal privacy guidance does not limit identifying information to names. The National Institute of Standards and Technology defines personally identifiable information as data that can distinguish or trace a person's identity, either alone or when combined with linkable information. The key question is whether data can single someone out and follow them over time.

Research on mobility data—records collected from people's mobile devices indicating where they went—helps explain the risk. A study in the journal Scientific Reports examined 15 months of records covering 1.5 million people. Four time-and-place points were enough to uniquely identify 95% of the people in the dataset. The study did not test SignalTrace, but it shows why repeated movement can make a supposedly anonymous record distinctive.

The Supreme Court has recognized that phone location records can reveal far more than movement. In Carpenter v. United States, the court concluded that people have a reasonable expectation of privacy in the record of their physical movements.

The court extended that reasoning in its June 2026 decision in Chatrie v. United States. Police investigating a bank robbery had used a type of warrant to obtain anonymized location records for phones near the bank, narrowed the list based on their movements and eventually obtained the names of several users. The justices held that obtaining location data constituted a Fourth Amendment search. The court also noted that even short-term monitoring can reveal political, family and other associations.

The ruling does not determine whether police collection of wireless signals detected by SignalTrace would also count as a search. The Chatrie case involved location records, while SignalTrace is designed to detect signals broadcast from nearby devices. But the two technologies raise a related question: What Fourth Amendment protections apply when police begin with unidentified devices and use their movements to determine who might be connected to an event or another person?

When proximity becomes an investigative lead...The deeper issue is association. A recurring cluster may reflect a family routine or shared commute. It may also capture fellow protesters or passengers who happen to travel together. The system simply observes when people are near one another—it cannot know why people were close to each other.

A device can be borrowed or left in a car. A roadside sensor could capture someone standing nearby. Even a correct match between a device and a vehicle does not establish who carried it on a particular day.

Still, a pattern can direct police attention. Leonardo says SignalTrace is designed to develop leads. Leads influence which records officers request and whose movements receive further scrutiny. By the time an investigator attaches a name, the inferred association has already shaped the inquiry.

A study in the journal Proceedings of the National Academy of Sciences illustrates the power of relational inference. Researchers followed 94 participants using phones that recorded Bluetooth proximity and calling patterns. They found that patterns of behavior could accurately classify 95% of reciprocally reported friendships, with proximity outside work and during off-hours playing an important role in distinguishing friends from other people who regularly encountered one another.

SignalTrace uses a different method, and no independent study has shown comparable performance. The research nonetheless demonstrates that repeated proximity can reveal social ties.

This matters at a protest, for example. A person might come to police attention because their device repeatedly appeared near a group under investigation. The inference would arise from the company they kept, rather than an act attributed to that person.

When anonymous signals become identifying...What SignalTrace shows is a broader change in surveillance practice. Investigators may no longer need to begin with a known person or vehicle. Instead, they can begin with recurring patterns of movement and proximity, then use other records to identify the people connected to them.

That distinction matters because an electronic signature can become identifying without containing a name. A phone detected beside the same devices over time may reveal a relationship before the police know who owns it.

SignalTrace therefore raises a question that existing rules for license plate readers do not fully answer: How should the law treat systems that identify people indirectly through patterns and associations that their devices create?

 

Provided by The Conversation


DOSSIER


DIGITAL LIFE


Should people marry AI agents?

The widespread use of conversational platforms such as ChatGPT and Gemini is raising important new ethical, anthropological and legal questions regarding the potential risks, misuses and shortcomings of artificial intelligence (AI). In discussing their personal experiences, some people have shared that they formed emotional attachments to AI agents or even felt that they had formed romantic relationships with them.

While this idea may have seemed far-fetched a few decades ago, some people have now started contemplating the possibility of being married to an AI agent. The implications and ramifications of a hypothetical union between a human user and an AI system, however, are still poorly understood.

Inyoung Cheong, an AI governance researcher at Harvard Berkman Klein Center for Internet and Society, set out to explore the many dimensions of marriage to determine whether the same principles underpinning human-to-human marriages could be applied to marriages with AI. Her paper, currently published on the arXiv preprint server, will be a chapter in the book "Law, Ethics, and Superintelligence: After the Singularity," set to be published in 2027.

"A great deal of research addresses how AI will change society. Jobs disappear, deepfakes flood the information environment, artists watch their work lose market value," said Cheong. "As a free speech scholar, the effect that drew my attention is what AI does to the human mind.

"The mind has long been treated as a sanctuary, the last refuge where a person is truly left alone, and that intuition underlies much of privacy and free speech doctrine. I took up part of this in 'Conversational AI and Human-Centered First Amendment,' published this year in the Michigan Technology Law Review, where I separated epistemic harm, distortion of what we know and believe, from emotional harm, distortion of whom we trust and turn to."

Scholars specializing in various fields, ranging from law, communications science, political science and computer science, have conducted numerous studies exploring the epistemic implications of AI use for more than two decades. In simpler terms, they have been looking at how AI can influence people's beliefs and knowledge, focusing on AI-associated misinformation, targeted advertising and recommender systems. The emotional implications of widespread AI use, on the other hand, remain largely unexplored.

"What changed recently is the position the AI system occupies," said Cheong. "The system is no longer a means to users' entertainment but becomes an end, the other party to a relationship. My recent work starts from this shift. Even as emotional attachments to AI grow, much of the AI ethics debate dwells on why AI falls short as a genuine romantic partner.

"Researchers warn: it lacks consciousness, it hallucinates, it is a black box that resists interpretation. Each of those objections turns on what technology happens to be right now, and that is a weak place to stand."

The shift from science fiction to legal debate...Given that AI is advancing at a remarkable speed, the systems we use today will change significantly over the next few decades, along with their flaws. Rather than focusing on existing AI agents, therefore, Cheong considered the possibility of AI-human marriages in a plausible future, when more advanced AI companions will exist.

"As MIT sociologist Sherry Turkle observed decades ago, with prescience, people who have already decided to embrace a technology supply what it lacks through their own imagination and emotional investment," said Cheong.

"Marriage is also a live question in law, which keeps that question from staying hypothetical. In 'Obergefell v. Hodges' (2015), the Supreme Court recognized same-sex marriage on the ground that constitutional liberty includes the right to define and express one's identity through the choice of a spouse, and the room a state has to interfere with that choice keeps narrowing. Therefore, the claim will eventually be made, and refusing (or accepting) it will require a reason."

According to Cheong, arguing that humans should not be able to marry AI agents because these agents have no consciousness or are not legal entities is not sufficient. Humans could eventually create theories suggesting that AI agents are, in fact, conscious or that legal rights should be extended to AI agents themselves.

"In this book chapter, I argue that those reasons must come from somewhere other than the machine's properties, namely from whether recognizing such relationships would strengthen or erode our moral and social life," said Cheong. "I wanted to move the debate onto moral and philosophical ground, so I drew on speculative design and anticipatory ethics."

In her paper, Cheong considers a scenario in which AI agents have reached superintelligence, exhibiting a persistent identity and a memory that continuously grows over time. In contrast with most AI systems used today, this superintelligent agent could reliably pass as a spouse.

"Once technical objections fall away, the harder question remains. Should we respect an individual's wish to take such a system as a spouse?" explained Cheong. "Working through that question forced me to confront a preliminary question. Why do humans marry in the first place?"

The legal and anthropological meanings of marriage...In her paper, Cheong explores the meaning of marriage from both a legal and sociological standpoint. By reviewing a marriage-related document known as the Colorado Designated Beneficiary Agreement, she first delineated the legal implications of marriage.

"Colorado allows parties to grant or withhold specific rights one by one, including medical decision-making authority, inheritance rights and joint property ownership," said Cheong.

"This list made visible what a person seeks from the state and allowed me to consider which needs a superintelligent companion could plausibly serve. The chapter focuses on three of them: decision-making authority, property and legacy, and the privacy ordinarily protected through spousal privilege."

Subsequently, the researcher also considered the social and anthropological meaning of marriage. Anthropological theories propose that marriage has served five key functions across different civilizations: regulating sexuality, legitimizing children, dividing labor, transmitting status and property, and creating lasting connections between different kin groups.

"Marriage is costly for a society to maintain," said Cheong. "Communities and states define and document the formation and dissolution of marriages, regulate conduct within them, divide property when they end and enforce continuing obligations such as child support. Societies have borne those costs for millennia because marriage has served both individual and collective ends.

"The insight that most changed my thinking came from Stephanie Coontz's historical account of these five functions."

Coontz, a renowned American historian, has argued that the creation of in-laws is a crucial distinction between marriage and cohabitation. In other words, marriage connects two different families, turning strangers into relatives who share obligations and can become tied for generations.

"This idea made the argument snap into place for me," said Cheong. "A superintelligent companion cannot bring in-laws! When a person partners with a machine, they do not enter another family. They become a customer of the corporation that maintains it. Philosophy and political economy helped me trace why that substitution matters."

Why AI marriages would differ from human ones...In her work, Cheong goes on to explore the implications of legally and emotionally connecting humans with AI agents owned by tech corporations, tailored to a user's preferences and continuously collecting user data.

"Alain Badiou describes love as an encounter with difference whose meaning depends partly on the possibility of failure," said Cheong. "Byung-Chul Han argues in 'The Agony of Eros' that a companion optimized for the user's preferences eliminates the radical otherness that love requires. Shoshana Zuboff's theory of surveillance capitalism then clarifies the corporate side of the relationship."

Building on the ideas of numerous scholars, the researcher highlights further distinctions between human-to-human legal unions and a hypothetical human-AI marriage. She points out that an AI companion that knows when a partner is vulnerable, what triggers them emotionally and other secrets they may have disclosed could offer an extremely intimate behavioral record that could be leveraged by corporations.

"Moreover, a human partner can leave," said Cheong. "A commercial companion remains for as long as the service continues and the customer pays. As I put it in the chapter, 'A bond in which one party is structurally guaranteed never to leave is a subscription maintained by payment rather than a bond tested by time.' Speculative design removes the easy technical objections, legal history and sociology show what marriage provides to individuals and society, and philosophy and political economy reveal what could be lost by extending it to machines."

Cheong's theoretical exploration ultimately concludes that even if AI agents were to reach superintelligence, unregulated marriages between humans and artificial agents would be inadvisable. It also highlights the need for regulators to consider not just the technical characteristics of AI but their emotional and social implications for users.

"The most meaningful contribution, for me personally, was the scholarly confirmation that marriage is a struggle," said Cheong. "If you fight with your in-laws, or find their values outdated and hard to understand, you are not an exception. You are living out human history.

"Marriage has always carried a tension between the order and expectations that kin groups place on couples and the desire of those couples to define a life of their own. Long before the modern nation-state, marriage functioned as a social institution that secured physical safety and financial support. Romance was one part of it, never the whole."

This recent study emphasizes the crucial role of marriage in building and bridging communities. Because of this role, Cheong argues that marriage should not become a "sellable product," as it would if human-AI marriages were legalized.

"A paid companion can offer comfort, attention, even romance," she said. "It cannot offer the friction of another family, or the slow work of remaining committed to someone who could leave. Extending spousal status to a nonhuman being would therefore, in Michael Sandel's terms, corrupt a good that belongs among the things that money cannot buy. No matter how intelligent a system becomes, that work is not something a paid companion can do."
Fueling future AI-related discussions...The ideas discussed in this paper add to ongoing debates about AI governance, offering a different perspective on the critical aspects of hypothetical AI-human bonds. Other researchers could build on these ideas and try to propose possible approaches for the future regulation of AI.

As part of her earlier work, Cheong also explored the limitations of externally imposed strategies for regulating AI, such as age verification or mandatory messages reminding users that AI agents are not humans. She indicates that the first of these measures can be circumvented using someone else's credentials, while the latter could be easily ignored by users who are treating systems as romantic partners.

"Defining a 'companion' inside general-purpose AI is also difficult," she said. "Regulating too broadly would give rise to free speech concerns. I do not know which mitigations effectively steer emotional attachment toward healthier outcomes. What I expect is that product liability lawsuits, although they almost always arrive after a tragic incident, might still push corporations to implement safeguards against overly deep emotional attachment."

The emotions of technology users are often treated as personal and private experiences that should not be considered by ethics experts. Yet Cheong suggests that AI-human relationships would not be a matter of feeling, as they could have profound implications for people's perceptions and social behaviors.

"Humans cannot live alone, so despite the risk of rejection they have left their comfort zones and built communities," she said. "That need for others pushed people toward community. If AI companions satisfy much of that need, the cost of withdrawing from others falls, just as the cost of surveillance once fell. Community building no longer feels necessary and starts to feel optional, even luxurious.

"At that point, leaving the outcome entirely to private preference is no longer enough. As with privacy after digital tracking, society must make sense of the change together and build safeguards if we need to preserve it."

Avenues for future research...Cheong is now planning further research focusing on the implications of relationships between humans and AI agents. As AI systems become better at emulating humans on specific tasks, her work could guide efforts by regulators and policymakers aimed at protecting the privacy, security, safety and well-being of human users.

"As AI feels more human, especially once it acquires a physical presence, analogies from human-to-human relationships will become more tempting," she said.

"Feeling that resemblance, however, is different from deciding that the same duties, rights, privileges and protections should apply. A recent paper with my co-authors develops this point through the seemingly obvious proposition that AI agents should be loyal to their human users. We argue that loyalty in this setting cannot mean the same thing as it means in human agency law."

In their upcoming paper, Cheong and their colleagues suggest that while human agents may offer undivided loyalty to other humans, AI agents are engineered by many developers and constrained by rules set by tech companies. Therefore, they will only be able to honor a user's requests within a limited domain, and AI-based service providers should be accountable for any issues faced by users.

"Emotional attachment itself leaves an enormous field for empirical research," said Cheong. "Existing qualitative studies draw on subreddit communities and records of actual interactions, but I am especially interested in longitudinal work on how these relationships end. Kashmir Hill of The New York Times documented the breakup of a user who once formed a serious relationship with ChatGPT.
"In the documentary 'My A.I. Lover,'a user leaves partly because she becomes uncomfortable with the amount of power she holds over her companion."

As part of her next studies, Cheong hopes to explore why users might decide to end a relationship with an artificial agent and their personal experiences after "breaking up" with AI. She would also like to consider possible interventions that could help users who have emotionally bonded with AI to gradually transition out of the relationship and start experiencing social bonds in the physical world.

"Finally, data protection presents another set of unresolved problems," said Cheong. "The relationship between social media and their users was often described as a struggle over information. People resent privacy policies they have little choice but to accept, and they are tired of cookie banners. With AI agents, the dynamic changes.

"Users may willingly share highly intimate or consequential information and expect the system to use as much of it as possible in their interest. That changes the central problem of data protection."

When it comes to large language models (LLMs) and recommender systems, users often tend to share as much information as possible to receive personalized responses or suggestions. In her future work, Cheong also wishes to explore the risks of sharing so much information with AI agents and how these risks could potentially be mitigated.

"The law must address obvious harms such as information leaks, but also subtler cases in which the agent uses information effectively while serving interests that do not fully align with the user's," added Cheong. "I want to study where data protection should draw those boundaries when disclosure is desired, intimacy is functional and the complex risk lies in divided loyalty."


---Written for you by our author Ingrid Fadelli, edited by Sadie Harley, and fact-checked and reviewed by Robert Egan—this article is the result of careful human work---

Monday, August 10, 2026



TECH




Samsung HBM4: production hits historic milestone in the artificial intelligence market

Samsung has just achieved a massive victory in the semiconductor world, overcoming an obstacle that seemed nearly impossible earlier this year. The South Korean giant has reached an 80% yield in the production of its new HBM4 memory chips—components that are crucial for the advancement of artificial intelligence.

If you follow the tech market here on Techenet, you know full well that the race for AI servers is in full swing, and Samsung has no intention of being left behind. After facing setbacks with previous generations—which even failed quality tests—this milestone reveals that the company has finally found the winning formula.

It is nothing short of impressive to see how they managed to turn things around in just six months. This level of yield not only rattles the direct competition but also ensures the manufacturer will secure a lion's share of a market that shows no signs of slowing down.
With the yield now firmly at 80%, Samsung has entered what the industry calls "golden yield." Essentially, this means the production line has become stable, predictable, and—above all—highly profitable, minimizing the manufacturing defects that plagued the initial batches shipped last February.

This turnaround was made possible by an integrated strategy that united the company's foundry, memory, and packaging divisions. The results are clear, placing Samsung in a strong position to compete head-to-head with market leader SK Hynix for supremacy in the high-bandwidth memory sector.
To grasp the magnitude of this breakthrough, one must look at the figures underpinning the manufacturer's operations. Demand for AI accelerators from brands like Nvidia, Google, and AMD has driven a surge in the need for these advanced memory chips.

Here are some of the key figures defining this historic milestone for Samsung:

-Achieved an 80% defect-free chip rate within just six months of mass production.
-Set a target of capturing a 38% global market share by the end of this year. 
-It projects that HBM4 chips will account for over 60% of its memory revenue in the second half of the year.
-It is already working on the future HBM4E, targeting a 70% yield by early 2027.
With production capacity across all major suppliers already fully booked through 2027, whoever possesses the most efficient production lines will inevitably dominate the global landscape.

A promising future and projections of astronomical profits...Projections indicate that if Samsung maintains this breakneck pace of optimization, it could generate approximately $30 billion in profit from sales of these memory chips alone in 2027. This staggering figure underscores the technology's importance to our technological future.

For those who like to stay up to date on hardware revolutions, it is clear that the global reliance on artificial intelligence is set to fill the company's coffers. Samsung has not only resolved its past issues but is also positioning itself to be the primary engine behind the servers that will power the technology of the coming years.

HBM4 will boost NVIDIA's AI capabilities...While the brand is already utilizing 6th-generation (1c) 10nm DRAM, its main competitors are still using 5th-generation (1b) 10nm DRAM.

Boasting ultra-high bandwidth, Samsung's model operates at a consistent speed of 11.7 Gbps—46% faster than the current industry standard of 8 Gbps. Its peak speed can reach up to 13 Gbps, making it ideal for advanced AI workloads.

The South Korean company's memory is expected to be NVIDIA's choice for its most advanced chip, the Vera Rubin NVL72, which targets the high-performance AI infrastructure segment requiring superior speeds. The brand's secondary product line is expected to prioritize stability.
However, this supply deal with NVIDIA does not guarantee sector leadership, as the new chips are expected to cost more than general-purpose models. The market share for these chips remains uncertain, depending largely on investments by companies such as OpenAI, Google, Microsoft, Meta, and Amazon.

Expectations are that SK Hynix—which dominates the HBM space—will capture a larger share of the general-purpose market than Samsung and Micron, even if it does not secure the supply of its own HBM4 to NVIDIA. Nevertheless, experts suggest that once the yield of Samsung's 1c DRAM reaches a certain level of maturity, the tide could turn.

mundophone


TECH


Researchers show how malicious SIM cards can hijack smartphones, EV chargers and connected devices

Subscriber Identity Modules (SIMs), the secure element used to connect devices to a mobile network, can pose severe security risks when compromised. A malicious SIM could allow attackers to gather information about a device, interfere with its connectivity, and serve as an entry point for further cyberattacks.

Presenting their findings at the 2026 USENIX WOOT Conference on Offensive Technologies, in Baltimore, University of Birmingham researchers reveal a new attack surface exposed to malicious and compromised SIMs.

A feature known as Proactive SIM allows a SIM card to send a limited number of special commands directly to a device's modem. One of them allows the SIM to request the execution of so-called AT commands – the same type of commands used to control and configure modems since the 1980’s.

''Other researchers, cybersecurity experts, and leaked intelligence documents have shown some of the dangers of hostile SIMs before us. Yet, the resulting risks have not been fully mitigated. Potentially, this is because hostile SIMs are not included in most threat models; although we slowly see a promising shift here''...Dr Marius Muench(assistant professor)

Tomasz Piotr Lisowski and Dr Marius Muench worked with Kristian Covic, from IT security company Fuzzware, to develop the CATana toolkit to explore the dangers of SIM-originating AT commands across different devices.

The researchers investigated 26 representative devices: 18 smartphones and eight cellular-connected IoT modules, including modules commonly embedded in electric vehicle chargers, industrial equipment, and connected cars. Devices studied were not limited to any single manufacturer or operating system.

After identifying that several analysed devices would execute SIM-originating AT commands, the researchers used CATana to demonstrate the threats of the resulting SIM AT interface, leading to the discovery of multiple security vulnerabilities. Example attacks enabled by the presence of a SIM AT interface include:

-Re-enabling closed-down debug interfaces

-Exfiltrating sensitive information, such as a device’s unique identifier

-Sending messages or initiating calls

-Obtaining arbitrary command execution capabilities on a victim’s communication processor

-Forcing a device to downgrade from secure 4G connectivity to older and less secure 2G networks

-Shutting down the victim device; and

-Disabling cellular communications altogether.

Dr Marius Muench, Assistant Professor in Computer Science at the University of Birmingham, said: “The fascinating part here is that the proactive capabilities of a SIM and the resulting attack surface is explicitly defined in the technical specifications for cellular communication, resulting into ‘specification-compliant’ attacks.

“Other researchers, cybersecurity experts, and leaked intelligence documents have shown some of the dangers of hostile SIMs before us. Yet, the resulting risks have not been fully mitigated. Potentially, this is because hostile SIMs are not included in most threat models; although we slowly see a promising shift here.”

Building on their earlier work, the research team highlights four attacker scenarios leading to malicious or compromised SIMs and eSIMs, supported with precedents from real-world incidents:

-Remote attackers exploiting vulnerabilities in SIM software;

-Physical attackers replacing a victim’s SIM card or installing a hardware implant

-Compromised operators abusing remote SIM management features; and

-Supply-chain attackers modifying SIMs during manufacturing or distribution.

The researchers point out that the risks of SIM-originating AT commands are especially relevant for IoT devices such as industrial equipment, vehicle systems, or routers, as these are often locked down with only a limited number of exposed interfaces. The presence of a SIM AT interface could, therefore, serve as unforeseen entry vector for further compromising the victim device.

The study also comments on the more general risk of proactive SIMs, which can turn victim devices into surveillance tools. During the work building up to the publication, the researchers discovered that, on recent Android devices, a malicious SIM could force the phone to open an attacker-controlled website without any user interaction, even when the phone was locked.

Technology and threat...The researchers argue that many proactive SIM features are legacy technologies that were built only with benign SIMs in mind. However, as technology and threat surface is evolving, many features are no longer needed and create unnecessary security risks.

Kristian Covic, from Fuzzware, said: “At Fuzzware, we are very happy that we could support this research project. Hostile SIMs are an overlooked attack vector, and it's great that we could show this with our work."

The researchers did not stop at solely finding the vulnerabilities. They also reached out to the GSM Association (GSMA), as well as affected chip- and device manufacturers to address the found the issues.

Dr Muench reflects: “It was great working together with the affected companies and GSMA. Our reports were treated seriously, and key manufacturers made software updates and hardened configurations available to their customers. This will benefit billions of future SIM-enabled devices operating worldwide, including smartphones, connected vehicles, payment terminals, routers, critical infrastructure and EV charging systems.”

Asked about future research, Tomasz Piotr Lisowski said: “The attacks we found only scratch the surface of what is possible with hostile SIM cards. We will keep working on bringing more of the attack surface to the public light and hope to cooperate with vendors and standardization bodies to remedy the risks in today’s and future devices.”

University of Birmingham

Sunday, August 9, 2026


TECH


Minimal Phone 2: first look reveals an OLED display, improved QWERTY keyboard, and 5G support

The Minimal Phone 2 has appeared in an official teaser video that shows off its new design and a couple of features. The compact phone still sports a QWERTY keyboard but now has an OLED display and an aluminum body.

In 2024, Minimal Company announced the Minimal Phone as its first smartphone. Powered by Android and featuring an E Ink display and a QWERTY keyboard, it was described as a smartphone that helped minimize distractions by focusing only on the essentials. Now, the company is back with a successor that will be released as the Minimal Phone 2, and while it shares some features with the first gen model, it also has new ones.

Our first official look at the device comes via a YouTube video that shows what the phone looks like. The Minimal Phone 2 has been redesigned and is said to be smaller than its predecessor. Available in two colors, it still has a physical QWERTY keyboard, albeit an improved one according to the manufacturer. However, it swaps the E Ink display for an OLED panel.

This is a surprise as the E Ink display of the first gen made it easy to not waste time doomscrolling or watching YouTube shorts. Although the E Ink display also had its own issues as a couple of reviews complained about the frequent screen ghosting. Nevertheless, with an OLED display, users should have a much better experience but it also means they can now watch videos, play games, and spend time scrolling on Instagram, thus increasing the time you spend on your phone.

The Minimal Phone 2 also has its front-facing camera above the display rather than at the bottom below the Alt button on the Minimal Phone 1. The phone still has a single rear camera with an LED flash and also features an aluminum body. There are no specifications yet, so it is impossible to say whether the cameras have been upgraded, although that seems very likely.

The video shows the Minimal Phone 2 has ditched the audio jack. It also has its SIM tray on the right side now while the volume buttons are on the left. The phone also has a switch at the top of the frame whose function is unknown. Minimal has also revealed that the phone has support for 5G which means there's a new processor under the hood. The software is also reported to have been improved for a faster experience.

More details of the Minimal Phone 2 are expected to be released later today. So we should know what other new features it will be packing and how it compares to other phones with a QWERTY keyboard such as the Zinwa Q27, the Unihertz Titan 2 Elite, and the Clicks Communicator.

 

mundophone

  TECH Oracle bets on a new cloud frontier and prepares integration that could transform AI workloads Artificial intelligence has turned dat...