TECH

Doors closing on their own? How your AI-controlled smart home could turn against you...

Artificial intelligence is poised to play a much larger role in smart homes. While virtual assistants today answer questions or execute isolated commands, a new architecture proposed by researchers at New York University envisions AI agents capable of coordinating virtually an entire property's infrastructure: locks, cameras, lighting, sensors, alarms, air conditioning, and other connected devices.

The idea was presented in the study "Internet of Agentic Things: Networked AI Agents for Closed-Loop IoT Orchestration."

Dubbed the "Internet of Agentic Things" (IoAT), the concept describes a network of autonomous agents that do not merely receive commands but interpret goals, devise plans, activate various pieces of equipment, and adapt their decisions based on environmental changes. Instead of simply turning on a light or adjusting the temperature in response to a specific request, these systems could understand instructions like "prepare the house for the night" or "save energy without compromising security" and automatically execute dozens of coordinated actions.

The authors summarize the proposal in a sentence that helps clarify the shift: "agents do not merely observe the physical world; they participate in a closed-loop cycle of perception, reasoning, action, and adaptation."

The paper uses a smart building to illustrate how this works. Upon receiving a command to switch the building to night mode, the AI ​​would check for the presence of people, adjust the climate control system, turn off lights in empty areas, lock doors, activate cameras and alarms, and notify the appropriate personnel if it encountered any unexpected situation—all without an operator needing to control each step individually.

Digital vulnerabilities impacting the physical world... Yet, it is precisely this autonomy that concerns researchers. According to the study, when AI agents take control of physical devices, an error is no longer just an incorrect response on a screen. A misguided decision could result in doors locking at the wrong time, security systems being triggered inappropriately, equipment operating unexpectedly, or other consequences within the physical environment. The authors state that AI is moving beyond mere text generation to directly influence the real world.

The study identifies a range of new risks for this type of infrastructure. These include attacks known as "prompt injection"—where an agent is induced to execute malicious instructions—as well as the compromise of specialized agents, the reuse of outdated information, flaws in digital twins used for decision simulation, communication delays between devices, cascading effects across connected systems, and the leakage of sensitive data such as home occupancy details, location, camera footage, and access logs.

The researchers argue that these threats necessitate a security architecture distinct from the one currently used in smart devices. Recommendations include limiting the actions each agent can perform, validating commands before they reach the equipment, restricting permissions, verifying the continued validity of old information, maintaining local security mechanisms in case cloud communication fails, and logging all AI-driven decisions for subsequent auditing.

In the authors' assessment, the "Internet of Agentic Things" represents the next stage of the Internet of Things. Rather than simply connecting devices, it connects systems capable of perceiving the environment, making decisions, taking action, and continuously learning from the results. This evolution has the potential to transform not only smart homes but also hospitals, factories, transportation networks, and energy systems.

In their conclusion, the researchers summarize this transformation by stating that "the Internet of Agentic Things reimagines the Internet of Things as an active network of ‘cyber-physical’ intelligence, rather than a passive network of devices." They add that the true breakthrough "lies not merely in adding an interface based on large language models, but in combining the distributed reasoning of agents with sensors, memory, digital twins, and feedback-based control." At the same time, the study concludes that the success of this new generation will depend on the ability to ensure that AI agents remain trustworthy, safe, and always subject to oversight mechanisms when their decisions could have effects in the physical world.

Artificial Intelligence (AI) agents are autonomous systems that read and interpret data to make decisions on your behalf. The primary danger lies in the proactive nature of these agents and in vulnerabilities such as "prompt injection," where malicious commands hidden in emails or websites can trick the AI ​​and compromise your home's security.

Key risks associated with AI-powered smart homes:

Intrusions via context manipulation: AI agents often process external content (such as emails or messages) that is beyond your control. A hacker could send an email containing hidden instructions that cause the AI ​​to unlock doors, adjust the temperature, or disable alarms.

Surveillance and privacy breaches: Instead of providing protection, AI can become a tool for espionage. AI-enabled listening devices and cameras can leak data regarding your daily routine, sleep habits, and the times when your home is unoccupied.

Network attacks (Botnets): If your smart home devices lack robust security, malicious actors could hack them to incorporate your home network into a botnet, using your internet connection to launch massive cyberattacks.

Automation acting against the resident: Misinterpretation of sensor data or incorrect commands can cause the AI ​​to perform unwanted actions, such as locking residents out or shutting down essential equipment.

How to protect yourself and maintain control: To mitigate these risks and keep your home under your control, it is essential to implement several layers of defense:

Separation of permissions: Avoid granting AI agents access to critical accounts (such as your primary email or banking accounts) that could interact directly with home devices.

Strong passwords and updates: Change the default passwords on your Internet of Things (IoT) devices and keep firmware updated to patch known vulnerabilities.

Monitoring and action limits: Enable manual confirmation for critical actions, such as opening the garage door or unlocking electronic locks. Isolated networks: Create a secondary Wi-Fi network (guest network or VLAN) exclusively for your smart devices, separating them from your main computers and mobile phones.

mundophone

TECH

AI could repeat the mistakes of the Industrial Revolution—at a much faster pace

Experts in economics and artificial intelligence state that AI could trigger an economic transformation even greater than the Industrial Revolution. The problem, according to them, is that these changes will occur within just a few years, leaving governments and societies with little time to adapt to the impacts on employment, the economy, and global security.

Comparisons between artificial intelligence and the Industrial Revolution have become common among tech industry executives. For many AI proponents, this new wave of technology promises to boost human productivity to unprecedented levels and accelerate scientific breakthroughs capable of solving some of humanity's greatest challenges. However, a group of economists and researchers argues that this analogy also serves as a warning. After all, while the Industrial Revolution brought prosperity, it also widened social inequalities, fueled industrial-scale conflicts, and contributed to environmental problems that still affect the planet.

On Monday, experts released an open letter titled "We Must Act Now," urging governments and society to prepare responses to the economic and social impacts of artificial intelligence.

The document bears the signatures of around 200 prominent figures in the field, including former Google CEO Eric Schmidt, Anthropic co-founder Jack Clark, OpenAI co-founder Wojciech Zaremba, and Yoshua Bengio—a Turing Award winner considered one of the "fathers of artificial intelligence."

Although brief, the message delivers a direct warning: AI could evolve radically over the next decade and trigger an economic transformation greater than that of the Industrial Revolution.

The difference, according to the authors, is that this shift will occur over a much shorter timeframe.

While industrialization took decades to reshape the global economy, the artificial intelligence revolution could produce similar effects in just a few years.

The authors state that the speed of technological evolution poses one of the primary risks.

During the Industrial Revolution, governments, companies, and workers had decades to adapt laws, professions, and economic models. Now, that transition period might simply not exist.

According to experts, this increases the likelihood of significant impacts on the labor market, income distribution, and social stability before public policies can respond to the changes.

Warnings about AI are multiplying worldwide...The letter comes amidst a series of similar statements from political leaders, international organizations, and technology companies.

Last week, the United Nations Secretary-General reiterated his call for a ban on autonomous weapons controlled by artificial intelligence—often referred to as "killer robots."

In June, international cybersecurity agencies, including the NSA, warned that AI is already profoundly transforming the digital security landscape and that these impacts are expected to intensify in the coming months.

Shortly before that, Pope Leo XIV also addressed the issue in an encyclical, stating that the unchecked development of artificial intelligence could exacerbate social alienation, deepen political divisions, and increase environmental exploitation.

Another growing concern involves so-called recursive self-improvement.

This concept describes systems capable of creating increasingly advanced versions of themselves, continuously accelerating their own evolution.

Some researchers believe this scenario could make AI models progressively harder to understand and control, influencing areas such as the economy, politics, and the flow of information in unpredictable ways.

This debate has led companies like OpenAI and Anthropic to recently advocate for the creation of an international body responsible for overseeing the development of advanced AI systems and, if necessary, slowing down their evolution.

Recent advances in artificial intelligence regarding the identification of vulnerabilities in digital security systems have also heightened concerns among authorities.

According to experts, increasingly powerful models can find flaws in complex software at unprecedented speeds, thereby increasing risks for governments, businesses, and critical infrastructure.

This scenario is beginning to influence even countries that traditionally adopted a stance more favorable to the rapid development of AI.

In the United States, for example, signs have emerged that the government seeks to establish assessment mechanisms for highly advanced models prior to their public release.

OpenAI announced the launch of GPT-5.6 after receiving the green light from federal authorities. However, the U.S. government denied granting any formal approval or that such authorization was even required.

As technology continues to evolve rapidly, a growing number of experts are advocating for broader societal preparation to face a transformation that could redefine the global economy at an unprecedented pace.

mundophone

TECH

Europol’s 2026 terrorism report warns of digital threats

Europol’s new 2026 terrorism report, released yesterday in The Hague, confirms that virtual ecosystems and video games have profoundly altered security within the European Union. The official *EU Terrorism Situation and Trend Report* (EU TE-SAT) 2026 outlines an unprecedented fragmentation of operational threats, driven by the use of informal encrypted channels. Traditional cells with strong ideological affiliations are giving way to lone perpetrators who use aggression to gain approval within online communities.

European law enforcement authorities recorded a total of 45 terrorist incidents across 10 Member States during 2025. Data consolidated in the new Europol report show 22 completed attacks, 20 plots thwarted by police action, and 3 attempts that failed during execution. The number of individuals arrested for terrorism-related offenses reached 486, with cases distributed across 21 European countries.

Religious fundamentalism remained the most frequent threat, serving as the primary cause in 24 of the 45 incidents and leading to the arrest of 347 of the 486 suspects across the EU. Operational statistics indicate that over 70% of arrests linked to fundamentalism were directly associated with the dissemination of digital propaganda and technical support networks for illicit infrastructures.

Decentralized online ecosystems now act as primary catalysts for violence in Europe without requiring prior physical contact. Social media, end-to-end encrypted messaging services, and interactive video game platforms now function as infrastructure for radicalization and remote tactical planning. This technological dispersion allows isolated users to form independent cells without orders from formal organizations. A technical assessment by the law enforcement agency confirms that this decentralized pattern makes risk detection significantly more complex for community policing units. Engineering and Technology

The convergence of digital terrorist threats and organized crime in Europe has created a new ecosystem of illicit services on the dark web. Perpetrators acquire specialized tools on the digital black market that facilitate their operational and financial activities. This resource sharing includes the acquisition of illicit weaponry, money laundering via crypto-assets, and the use of anonymous communication infrastructures designed by corporate-style cybercrime syndicates.

“The boundaries between established terrorist ideologies and other forms of violent extremism are becoming increasingly blurred, illustrating the evolving nature of the threat within the European Union.” —Anna Sjöberg, Head of Europol’s European Counter Terrorism Centre

Online radicalization among youth is growing across gaming networks and servers...Extremist propaganda and interactive video game subcultures are heavily impacting the youth and adolescent demographic across Europe. Law enforcement agencies arrested 130 individuals aged 18 or younger in 2025. The most extreme case identified by investigators involved the apprehension of a child—only 12 years old—who was actively undergoing radicalization.

These young people rarely demonstrate a deep understanding of the structured ideological doctrines they claim to represent. Their motivation stems primarily from absorbing violent and misogynistic narratives in unmoderated digital forums. The informal, decentralized network known as "The Com" exemplifies this shift, where extreme behaviors serve merely to generate algorithmic visibility and social acceptance among peers.

Counter-terrorism in the European Union requires cybersecurity and technical mitigation...Effectively mitigating operational threats and combating the online radicalization of young people within corporate or academic infrastructures necessitates the implementation of strict technical protocols:

DNS filtering and perimeter control: Organizations must implement next-generation firewalls and Domain Name System (DNS) filtering to block traffic directed at propaganda servers and anonymous command-and-control networks.

Network behavioral monitoring: Deploying network detection and response tools helps identify unauthorized communication tunnels and covert data exfiltration within corporate and educational infrastructures.

Privilege segmentation and Zero Trust architecture: Applying the principle of least privilege and multi-factor authentication prevents accounts compromised by radicalized employees or students from accessing critical information servers.

Social engineering awareness: Institutions must train their staff and students to recognize digital manipulation strategies and disinformation campaigns designed to co-opt vulnerable individuals on social media.

Future implications for security and defensive intelligence across the continent...The shift toward a decentralized model of virtual aggression reduces the effectiveness of police surveillance based on traditional organizational hierarchies. In the coming years, counter-terrorism efforts in the European Union will depend on the continuous sharing of technical telemetry between governments and private technology companies. Without advanced tools to monitor aggressive subcultures and encrypted networks, Member States will face increasing difficulties in anticipating extremist actions perpetrated by lone actors across the region.

mundophone

 

TECH

Designing high density data centers: Computational fluid dynamics analysis eliminates costly guesswork

As data centers and crypto-mining facilities expand to handle growing digital demands, keeping massive banks of servers cool has become a primary operational challenge. To address the energy inefficiencies plaguing these high-density computing spaces, engineering researchers at Lehigh University's Energy Research Center have developed a specialized modeling framework designed to streamline hot spots and improve thermal management.

The team leveraged advanced computational simulations to track how air moves through these facilities, providing a roadmap for facility operators to drastically improve AI equipment cooling.

Background and motivation...Modern high-density data centers, particularly those dedicated to cryptocurrency mining, generate immense amounts of heat. Standard air cooling setups often suffer from uneven air distribution and internal recirculation, a phenomenon where hot exhaust air loops back into the intakes and inside the racks of the servers instead of exiting the building.

This recirculation forces cooling systems to work harder, drives up electricity costs and creates localized hot spots that risk damaging sensitive computing equipment. To fix these thermal inefficiencies, facility operators need to understand exactly how air moves through the complex, tightly packed rows of server racks. However, physically measuring airflow at every corner of a functioning facility is cumbersome.

Innovation and methodology...To overcome this limitation, the Lehigh research team turned to computational fluid dynamics or CFD, an advanced computer modeling method that simulates the behavior of gases and liquids. Using industry-standard ANSYS Fluent software, the researchers created a detailed virtual model of an active crypto-mining facility.

The methodology relied on a step-by-step approach. First, the team built a solid model of the facility and took physical baseline measurements of temperature and velocity directly from the field to validate the software's accuracy. To keep the simulation efficient, they applied a symmetry plane to capture the recurring geometry of the server layout.

Once validated, the computational fluid dynamics model visualized internal air circulations, velocity vectors, and temperature contours at various heights. This allowed the team to pinpoint exactly where cold air was bypassing the servers and where hot exhaust air was getting trapped. The validated model also allows playing “what if” scenarios aimed at improving flow streamlines and improving heat transfer in the data center space.

Results and impact...The simulation successfully exposed major vulnerabilities in the facility's baseline design. The model revealed that internal air circulations and bypass air patterns were heavily degrading the efficiency of the ventilation system. Furthermore, flow instabilities within and between computer rooms were causing highly uneven airflow distribution across the left and right walls of the building.

Armed with these insights, the researchers implemented targeted geometry modifications and airflow adjustments in their model. The optimization strategy stabilized the airflow near the computer rooms, forcing cold air to make direct contact with the hot server surfaces.

By strategically mitigating the hot spots and minimizing the recirculation of hot air, the engineered modifications achieved an estimated 15% improvement in overall cooling efficiency for the facility.

Conclusion and Outlook...The research demonstrates that advanced computational modeling can successfully eliminate guesswork when optimizing complex data center environments. By providing a clear, visual understanding of aerodynamic behavior, this approach allows operators to implement targeted physical alterations that significantly lower energy consumption and improve data center Power Usage Effectiveness (PUE), a metric used to measure data center energy efficiency.

Moving forward, the computational fluid dynamics framework developed at Lehigh can be adapted to evaluate and design next-generation data centers, ensuring that the physical infrastructure supporting artificial intelligence and digital mining can grow sustainably.

by: Lehigh University

TECH

Why power banks in hold luggage pose such a risk on holiday flights

Airline passengers are being warned not to pack power banks in their hold luggage ahead of the summer holiday travel period. 

Devices with rechargeable batteries, like mobile phones, laptops, tablets, and smartwatches can be plugged into power banks on the go, where charging sockets may not be available. However, power banks are not danger-free or environmentally friendly.

The warning has come from the UK’s Civil Aviation Authority (CAA), which believes that many travellers still aren’t aware of the rules – or the fire risk.

Passengers on UK flights must take power banks – and other items containing lithium batteries – with them into the cabin. They must never be used to charge another electronic device while on the plane. Additionally, only two power banks per person are allowed on a flight.

Consider a scenario where you are about to take off on a flight. You have settled into your seat, started using your mobile phone, and put it in airplane mode. All of a sudden, an unusual hissing sound comes from your bag; smoke starts rising, and within seconds, there is a fire inside your luggage.

This actually happened on a flight between South Korea and Hong Kong in January 2026, when a power bank caught fire in mid-air. The accident on this flight is not a rare occurrence; hundreds of fires, explosions and other safety incidents involving lithium batteries and power banks have been recorded by the US Federal Aviation Administration (FAA). 

The main reason for accidents involving power banks is the lithium-ion battery, the most common battery type used in them. The lithium-ion battery has a tendency to overheat, which can trigger a thermal runaway in which the temperature rises rapidly, leading to the battery’s explosion.

Such an explosion can occur for many reasons, including poor design, manufacturing issues, and improper use. In 2017, a family in the UK woke to smoke filling their home. The cause of the fire was a power bank charger, plugged into an electrical outlet. It overheated and set itself ablaze. Their rooms were burned down.

From a scientific point of view, the answer is obvious: heat is the sworn enemy of lithium-ion batteries. Each time you recharge or discharge a power bank, chemical reactions produce heat in the battery. And if that heat is not properly controlled – whether due to inadequate design or excessive environmental temperature – a thermal runaway occurs (an uncontrolled, self-heating chain reaction). 

In 2026, an Australian man left a power bank in his vehicle on a hot day in Mount Nathan in Queensland. The extreme heat caused the battery to explode, starting a fire. Luckily, no one was injured in the incident.

Electric shocks...Fire and explosions are not the only hazards associated with these gadgets. They can also cause a dangerous electrical shock to users. This is despite the fact that they are operating at lower direct current voltage. 

If the power bank becomes faulty due to being dropped, getting wet or because of manufacturing defects, the circuitry inside may fail. This would cause the device to shoot a surge of electricity into the user’s body. 

In May 2026, a 75-year-old woman in the US died when her power bank explodedwhile charging it. 

China, which manufactures many of the world’s power banks, has seen manufacturers recall hundreds of thousands of devices due to defects. Some of these faults have been blamed on downstream suppliers.

Another alarming trend has been the rise of counterfeit power banks.

I have spent a great part of my career and life caring about the environment and developing eco-friendly technologies, and the widespread use of power banks is a serious concern due to their negative environmental impact. The manufacturing and disposal of power banks may generate large amounts of electronic waste that can pollute soil, water and air. 

Moreover, the extraction of lithium and other materials for power-bank production poses environmental and societal risks. For example, lithium mining in Chile’s Atacama desert has resulted in pollution and friction with indigenous communities. 

As a scientist and professor of engineering, I urge people to be aware of the potential dangers posed by power banks and how these risks can be mitigated. By adhering to precautions, such as charging devices on hard, non-flammable surfaces, we can ensure the safe usage of these devices.

In addition, it is vital to understand the significance of responsible innovation and sustainability to ensure that technologies can be safely developed and deployed.

Your power bank is a powerful tool, but it demands respect. Treat it with the caution it deserves.

Written by Dr Amor Abdelkader

DIGITAL LIFE

Artificial intelligence may start to "unlearn," and researchers explain why

For years, artificial intelligence has evolved thanks to the vast volume of text, images, and information produced by billions of people around the world. But this landscape is changing rapidly. Today, a growing share of the content available on the internet is no longer created by humans, but by other artificial intelligences. This transformation might seem natural, but a new study reveals a hidden challenge that could directly affect the future of AI itself.

Recent advances in artificial intelligence have spawned tools capable of writing articles, creating images, developing code, and answering questions with impressive quality. Consequently, the amount of synthetic content available online is growing at an unprecedented rate.

The problem is that this very content ends up being used to train future generations of models. Instead of learning solely from books, scientific research, newspapers, and human-written texts, AI is beginning to consume material produced by other machines.

It was precisely this phenomenon that caught the attention of researchers in a study published in the scientific journal *npj Artificial Intelligence*. According to the authors, this cycle can trigger a process known as "model collapse"—a gradual degradation of the systems' learning capabilities.

Unlike a sudden failure, this problem unfolds slowly. Each new generation learns from a larger volume of artificial data and, little by little, begins to reproduce increasingly repetitive patterns, losing some of the diversity found in the original information.

The researchers explain that the risk does not lie in the occasional use of AI-generated content. On the contrary, such material can be extremely useful in various applications. The challenge arises when it begins to replace a significant portion of human-produced content, reducing the variety of examples available during training.

A simple comparison helps illustrate the phenomenon: imagine making a copy of a photograph and then repeatedly copying that new image. Each reproduction looks virtually identical to the last, yet small losses of detail accumulate until the final result no longer preserves the full richness of the original photograph. To address this challenge, researchers developed a new training strategy called Confidence-Aware Loss, designed to make learning more balanced.

The method stems from an interesting observation: when a model encounters highly predictable examples, it quickly learns those patterns and begins assigning a high degree of confidence to its responses. However, continuing to reinforce these same examples adds little value to the learning process.

The solution involves reducing the weight given to these overly predictable cases and focusing more attention on less common examples that contain more varied information. To achieve this, scientists created a technique called Truncated Cross-Entropy, which redistributes the weight assigned to different types of data during training.

In practice, this helps the system maintain a richer representation of language and knowledge, preventing highly frequent responses from completely dominating the learning process.

Tests yielded very promising results. According to the researchers, the models were able to handle more than 2.3 times the amount of synthetic content before showing significant signs of so-called "model collapse."

Although the technique does not entirely eliminate the problem, it significantly expands the systems' ability to combine human-produced data with AI-generated content without compromising response quality.

The study also launched an open platform allowing other researchers to test new solutions and compare different training methods.

The main conclusion goes beyond the creation of a new algorithm. The rapid growth of AI-generated content makes preserving original sources of information increasingly important. In the future, the evolution of artificial intelligence will depend not only on the quantity of available data but also on the diversity and quality of that information. Preventing machines from learning solely from other machines may well be one of the greatest technological challenges of the coming decade.

mundophone

 

TECH

Memory crisis drags affordable smartphone segment to steepest decline in years

The global smartphone market is undergoing a profound transformation driven by the sharp rise in DRAM and NAND prices; these costs have climbed steadily over recent quarters and are expected to keep rising in the months ahead. This surge is significantly altering device costs, primarily impacting the mid-range and low-end segments, where memory has come to represent a disproportionate share of the total cost.

According to Omdia, smartphones priced under US$ 400 saw a year-over-year decline of more than 22%, a drop directly linked to the growing weight of memory costs in production.

The shift is evident when comparing costs between the third quarter of 2025 and the first quarter of 2026. In the sub-$400 segment, memory's share of the total cost nearly doubled, while for models above that price point, it increased by more than 100%.

By the first quarter of 2026, memory accounted for nearly 60% of manufacturing costs for smartphones under US$ 400, and exceeded 64% for entry-level models priced under US$ 99.

Omdia reports that this cost pressure is so intense that manufacturers are attempting to offset it by cutting costs on other components—such as displays, sensors, and RF modules—where supply remains plentiful. However, low-cost devices already operate on extremely tight margins, making it nearly impossible to absorb the impact solely through further cuts, the firm adds.

The research firm warns that the situation is set to worsen, with memory prices expected to rise further in the coming quarters. To maintain minimal margins, brands such as Transsion, Oppo, vivo, Honor, and Xiaomi have been forced to raise retail prices, despite knowing that consumers of entry-level devices are highly price-sensitive. Consequently, demand has fallen rapidly, rendering many low-cost models barely profitable and prompting manufacturers to gradually reduce inventory in this segment throughout the year. Amidst this contraction, Omdia forecasts a 12% decline in the global smartphone market in 2026, driven primarily by a sharp drop in models priced below $400, which are expected to fall by more than 22% this year. In contrast, smartphones priced above $400 are projected to grow by 5.7%, supported by less price-sensitive consumers and greater flexibility among manufacturers to reduce costs on premium components.

This market shift reflects three key trends. The first is the strategic move by manufacturers toward higher price tiers, followed by steadily rising retail prices that push more models into the above-$400 segment. Finally, there is greater demand stability among high-end consumers.

For premium models, memory accounts for a smaller share of the total cost, allowing manufacturers to adjust other components to alleviate pressure. Strategies identified by Omdia include reverting to LTPS OLED panels for some high-end models that had previously switched to LTPO, thereby cutting costs by $3 to $5 per unit, and adopting more flexible camera configurations—such as smaller sensors or fewer modules. Another approach involves using previous-generation SoC platforms, which can reduce costs by 30% to 40% for models priced above $600.

As memory costs continue to reshape smartphone economics, manufacturers face an increasingly delicate balancing act between affordability, profitability, and competitiveness. Omdia concludes that this pressure will accelerate market polarization, characterized by a continued contraction in entry-level segments and a growing focus on mid-range and high-end models, where there is more room to absorb costs and adjust specifications without dampening demand.

mundophone