TECH

Hot and cold climate extremes push UK’s energy system to its limits, new report reveals

The arrival of cooler weather following a summer of heatwaves, is a timely reminder that the UK electricity system must be resilient to the effects of temperature extremes at both ends of the thermometer.

The Royal Meteorological Society has released a new report that highlights how recent weather conditions have influenced electricity generation, demand and the infrastructure that connects them.

Authored by experts from the society, the Met Office and multiple UK universities, the State of the Climate for the UK Energy Sector Report 2025-26 shows that more energy is being provided by weather-dependent renewable sources. But high and low temperatures will continue to put the energy grid’s capacity and infrastructure to the test.

Data from the National Energy System Operator (Neso) shows that renewable energy formed a higher percentage of overall energy generated in the UK over the reporting period (April 2025 – March 2026) than any other year on record. The proportion coming from the combination of solar and wind increased, providing more than 38% of the nation’s electricity. The proportion of gas-powered generation reduced to 25%.

However, the report highlights how extreme weather tests the resilience of the grid. The conditions that lead to very high and low temperatures create different challenges through increasing electricity demand, limiting generation and damaging network infrastructure. The UK’s energy network is having to adapt to cope with increasingly extreme temperatures. In cold conditions, the network is put under strain due to increased heating demand. This requires more energy at short notice, increasing reliance on non-renewable sources.

For those responsible for balancing the electricity system, including Neso, these weather extremes can create operational challenges. This makes it harder to match energy supply with demand.

In early January 2026, strong northerly winds brought cold Arctic air, snow and ice into large parts of the UK. Initially these winds provided up to 20 gigawatts (GW) of power towards the system, a significant proportion of the demand.

But as the freeze reached its peak on the evening of January 6, the wind died down and wind generation fell to less than a quarter of the levels seen in the preceding days. Simultaneously, electricity demand peaked, with the increase in heating needs seeing demand peak an additional 5GW higher than the previous day.

Electricity supply and demand have to be kept in balance in real time. When demand rises or available generation falls, the energy system operator can maintain that balance by using additional generators to increase their output, for example. On this occasion, gas-powered electrical generation filled the gap by providing more than 25GW to the system at it’s peak.

This meant the demand was comfortably met, but this was an expensive strategy that meant the operator was paying up to £700 per megawatt-hour (MWh) for this generation. This was due to the higher cost of turning to gas generation, and the need for additional generation at short notice which costs more than generation that can be planned further in advance. This compares to the usual rate of just over £100 per MWh for the rest of January.

At the other end of the spectrum, hot temperatures are increasingly becoming more of a concern for the sector.

The summer of 2025 was the warmest on record at the time, with temperatures 1.51°C higher than average. During warmer temperatures, the network operator often limits the amount of power that transmission lines carry around the country to prevent components overheating. This reduces the risk of lines expanding more with heat which would make them sag and potentially short out on nearby vegetation or structures beneath.

Nevertheless, several faults in the network were attributed to heat causing infrastructure damage, leading to power cuts across parts of England, especially during two periods of heatwaves that occurred at the end of June and start of July.

In Europe, where temperatures also spiked, nuclear power plants were forced to limit output or shut down altogether because the water used to cool them with, taken from nearby rivers, was too warm. Increased temperatures and below-average rainfall also increased fire risks. The largest area lost to wildfire burning in the UK since satellite records began included a “mega-fire” in Scotland. Several of these fires led to localised power cuts across the country.

Preparing for future extremes...The UK’s new grid upgrade plan from the government, which aims to expand and modernise the British grid system to allow for connections to new generation sources and upgrades of current infrastructure, needs to consider the consequences of extreme temperatures. This includes ensuring that upgraded infrastructure can withstand the extreme heat we are now seeing more regularly in UK summers, as well as ensuring that capacity for transmission of electricity from generation sources to population centres is increased.

Delays to electricity grid upgrades risk higher consumer bills as the operator is required to pay wind farms to stop generating because electricity produced cannot be be carried to where it is needed, replacing it with more local gas-powered generation instead.

The resilience of the UK grid has stood up well to the challenges it faced from the weather in the past year. But maintaining that resilience requires continued investment and adaptation as the climate, energy needs of the nation and profile of energy generation all continue to change.

The Royal Meteorological Society’s annual report has revealed that extreme heat and cold are pushing the UK’s energy system to its limits. The document highlights the severe impact these temperature fluctuations have on energy infrastructure and underscores the urgent need to modernize the sector.

Key impacts on the energy system:

• Transmission constraints due to heat: During heatwaves, the grid operator must limit the amount of electricity flowing through transmission lines to prevent components from overheating. Heat causes cables to expand and sag, creating a risk of short circuits should they come into contact with vegetation.

• Localized blackouts and fires: The summer of 2025 saw temperatures 1.51°C above average. Extreme heat caused physical damage to infrastructure and triggered wildfires—including a "mega-fire" in Scotland—resulting in localized power outages across parts of England.

• Challenges for European nuclear power generation: Extreme heat also forced nuclear power plants in continental Europe to reduce output or shut down entirely, as the river water used for cooling had become too warm.

• Higher costs for consumers: Due to delays in upgrading the transmission grid, the operator is frequently forced to pay wind farms to halt clean energy production—since the power cannot be transported—and replace it with energy from local gas-fired plants, which drives up electricity bills.

Adaptation plans and requirements: The British government’s new grid upgrade plan faces the challenge of ensuring that modernized infrastructure can withstand frequent extreme heat, while also providing greater capacity to transport electricity from new generation sources to urban centers. The regulatory body Ofgem has also launched investigations to assess the performance of the market and the electrical system—managed by the NESO—during recent heat spikes.

Royal Meteorological Society

 

TECH

S&P warns of “off-balance-sheet” AI debt among tech giants

S&P Global believes it is likely that major technology companies carry financial liabilities linked to artificial intelligence—referred to as “AI debt”—that are not fully visible in their public financial disclosures. This warning concerns financing structures used to build data centers and support AI infrastructure companies.

The concern was raised by Mark Habib, global head of digital infrastructure at S&P Global Ratings, during a meeting with journalists in London on October 19. According to Reuters, the analyst acknowledged that the agency may not have visibility into all the financial liabilities taken on by large tech firms, particularly those arising from transactions that are neither disclosed nor directly assessed.

This warning comes at a time when investors are questioning the financial sustainability of the expansion into artificial intelligence. Infrastructure-focused companies, such as CoreWeave, have faced pressure in the debt markets, while major cloud service providers continue to invest heavily in the construction of data centers.

AI financing creates liabilities that are difficult to assess...The issue identified by S&P relates to financing structures that distribute financial commitments across various companies and legal entities.

For instance, a technology firm might enter into long-term contractual commitments to utilize capacity in a data center financed by third parties. It might also provide guarantees for infrastructure projects or participate in ventures involving smaller companies.

While these structures do not necessarily constitute debt incurred directly by the tech company, they can create financial obligations that the firm must honor—even if demand for artificial intelligence services falls short of expectations.

This distinction is significant for the assessment of credit risk. Traditional debt appears on a company’s financial statements, whereas certain contractual commitments and guarantees require further analysis to determine the actual economic exposure.

S&P had already identified this complexity in a report released in August, which highlighted the growing use of debt, lease agreements, guarantees, and special-purpose entities to finance AI infrastructure.

$1.65 trillion in off-balance-sheet AI debt...Kohei Yamada wrote an article for Nikkei Asia titled Five US tech giants’ hidden debts soar to $1.65tn on opaque AI funding in July 2026.

“Hidden debt at U.S. tech giants swelled eightfold in roughly four years to an estimated $1.65 trillion as artificial intelligence investments ballooned., a Nikkei study shows, exceeding actual [reported] debt and making it tougher for investors to assess risk.”

The article is behind a paywall. However, Hedgie posted further details on Twitter.

“A Nikkei investigation found that Alphabet, Microsoft, Amazon, Meta, and Oracle have $1.65 trillion in debt that doesn’t appear on their balance sheets, more than the $1.35 trillion they officially report. These are GPU contracts, data center leases, and joint ventures that don’t count as debt under accounting rules until the facilities go live. Meta’s hidden debt is $420 billion, triple its reported debt. Oracle’s grew 30-fold in four years. All five declined to comment.”

“These companies owe more off their balance sheets than on them, and the accounting rules let them keep it that way until the data centers go live. That’s legal, but it means investors looking at quarterly earnings this week are seeing less than half the picture.”

“But when those data centers start operating, the leases hit the books all at once.”

Hidden debt (off balance sheet)
Meta	~$420B
Oracle	~$273B
Amazon	~$350B
Microsoft	~$350B
Alphabet	~$250B
TOTAL	$1.65 Trillion

S&P estimates that Amazon, Microsoft, Alphabet, Oracle, Meta, and SpaceX will collectively invest more than seven trillion dollars in data centers and other assets related to artificial intelligence between 2025 and 2030.

This figure represents projected capital expenditures for the period, not the total debt held by these companies.

The agency also anticipates that this group of six companies will post negative free cash flows during 2026 and 2027, driven by the scale of investments required to expand computing capacity.

The primary risk lies in the gap between the pace of infrastructure construction and the ability to generate sufficient revenue to justify these investments.

This issue becomes particularly significant given the expansion of projects such as Google’s new data centers in Finland, which entail long-term financial commitments and a guaranteed supply of energy.

S&P does not foresee immediate changes to credit ratings...Despite these concerns, S&P Global does not deem it necessary to immediately revise the financial ratings of the companies analyzed.

In July, the agency had already downgraded Oracle to BBB—the lowest level within the investment-grade category—due to financial pressures linked to AI infrastructure expansion and uncertainty regarding future profitability.

Mark Habib explained that a reassessment might become necessary if these investments cease to be sustainable—whether due to further increases in spending or competition that limits revenue growth. The scale of financial liabilities that are not immediately visible, however, remains to be determined. S&P acknowledges that it lacks sufficient information to calculate the potential magnitude of these additional commitments.

The core issue, therefore, goes beyond simply how much large technology companies are investing in artificial intelligence. It also entails understanding what financial obligations they have taken on to support this expansion—and the extent to which future results will enable them to meet those obligations.

The top five US tech giants (Alphabet, Microsoft, Amazon, Meta, and Oracle) have accumulated $1.65 trillion in off-balance-sheet AI infrastructure obligations, surpassing their $1.35 trillion in recorded on-balance-sheet debt. Across a broader group of major tech companies, hidden commitments reach an estimated $3 trillion.

Key scale and figures:

• The big five hidden debt: Alphabet, Microsoft, Amazon, Meta, and Oracle hold $1.65 trillion in off-balance-sheet liabilities (growing roughly eightfold over four years).

• Meta's exposure: Meta leads with approximately $420 billion in hidden obligations—nearly triple its reported balance-sheet debt—driven by projects like the Hyperion data center joint venture.

• Oracle's growth: Oracle's off-balance-sheet commitments have surged 30-fold since 2022, placing pressure on its credit ratings and default insurance costs.

• Broader industry backstops: Hardware and chip providers have also stepped in; Nvidia has provided backstops and guarantees covering up to $300 billion in debt used by customers to buy its AI chips.

Mechanisms behind the debt:

• Uncommenced leases: Long-term data center and real estate leases that do not legally trigger balance-sheet reporting rules until the facilities actually go live (totaling over $1.2 trillion across providers).

• Take-or-Pay & supply commitments: Multi-year contractual agreements to purchase GPUs, computing power, and energy sources extending decades into the future (such as Alphabet's long-term infrastructure commitments).

• Special purpose vehicles (SPVs) & Joint Ventures: Off-balance-sheet corporate structures (such as private credit or institutional vehicles involving firms like Blue Owl or Blackstone) used to finance data centers and energy plants away from parent-company balance sheets.

Risks to Investors and markets:

• Opaque leverage: Traditional financial metrics capture only half of the actual financial exposure, masking how much capital is tied up in speculative AI expansion.

• Demand shortfalls: If commercial AI revenue fails to scale up as aggressively as projected, uncancelable take-or-pay and lease commitments could convert into massive impairment charges.

• Private credit and refinancing strain: Much of this financing relies on private credit and investment-grade bond markets, which face rising pressure as high interest rates and massive debt supply test borrower solvency.

mundophone

TECH

“Cooling without electricity or water”: DGIST develops “self-cooling film” for thermal management in AI-era electronic devices

A research team led by Professor Seong Kyun Kim of the Department of Physics and Chemistry at DGIST (President Kunwoo Lee) has developed a next-generation “passive cooling film material” that utilizes moisture in the air to cool electronic devices —no water or electricity is required. The technology is drawing attention as a promising, environmentally friendly solution to thermal management challenges in AI data centers, mobile devices, and electric vehicle (EV) batteries, which consume substantial water and electricity.

Recent advances in AI technology have driven the surge in data centers, and securing the electricity and water resources required for their thermal management has emerged as a global challenge. Likewise, mobile devices and EV batteries require technologies that can efficiently dissipate heat within confined spaces. However, conventional active cooling methods that operate pumps or fans require electrical energy and a coolant (water), and their complex systems entail significant maintenance costs.

Accordingly, passive cooling technologies that require no external energy input—particularly, evaporative cooling technologies that utilize airborne moisture—have emerged as an alternative. However, as most conventional hygroscopic materials—that is, materials that absorb moisture—are rigid crystalline solids, they do not adhere firmly to the surfaces of electronic devices, and induce corrosion. These are significant limitations to their commercialization.

Professor Seong Kyun Kim’s research team achieved a major breakthrough in addressing these limitations by combining “nanocellulose,” which possesses excellent moisture storing capacity, with organic ionic molecules with robust hygroscopic properties to synthesize a novel flexible, adhesive film material.

The developed material maintains strong adhesion and flexibility even when completely dry, enabling firm, gap-less adherence to various electronic device surfaces, including metals, semiconductors, and glass. Even in dry environments, it absorbs and stores substantial airborne moisture, which evaporates when the device generates heat during operation, thereby lowering the surface temperature in real time. A key advantage of the material is that it does not induce corrosion despite containing moisture, enabling direct application to device surfaces without any additional coating.

When the research team tested the film under actual conditions of continuous electronic device operation, the developed film material demonstrated exceptional cooling performance, stably reducing the device’s surface temperature by up to 18.2°C (from 72.3°C to 54.1°C) for more than 12 hours.

“The significance of this study goes beyond merely developing an environmentally friendly material. It simultaneously addresses multiple limitations of conventional passive cooling materials, including corrosiveness and insufficient flexibility and adhesion,” explained Professor Seong Kyun Kim of the Department of Physics and Chemistry at DGIST.

This research was led by doctoral student Hyeondo Kim of the Department of Physics and Chemistry, with support from the Ministry of Science and ICT’s Individual Basic Research Program and the DGIST International Joint Research Program. The findings were published in the internationally renowned journal Small Structures in September 2026.

A film has been developed that can cool electronic devices without using electrical energy or separate refrigerants. It is flexible and transparent, and in a dry state adheres well to metal, semiconductor, and glass surfaces, drawing attention as a supplementary cooling material that could help solve thermal management issues in artificial intelligence (AI) data centers and electric vehicle batteries.

Daegu Gyeongbuk Institute of Science and Technology (DGIST) announced on the 6th that a research team led by Professor Kim Sung-kyun of the Department of Chemical Physics has developed a next-generation "passive cooling" film material that autonomously dissipates heat from electronic devices by using moisture in the air. The research results were published on September 17 (local time) in the international journal "Small Structures."

A common challenge for data centers, mobile electronic devices, and electric vehicle batteries, all of which are seeing growing demand, is heat management. Conventional active cooling methods that operate pumps or fans require electrical energy and water as a refrigerant, and their complex equipment results in high maintenance costs.

Among passive cooling technologies that require no external energy input, evaporative cooling, which utilizes moisture in the air, is emerging as an alternative. However, existing hygroscopic materials that readily absorb moisture are often rigid solids, making it difficult for them to closely conform to electronic device surfaces, and they can also cause corrosion of the devices.

Professor Kim's team combined a nanocellulose material with excellent moisture storage capacity and an organic ionic liquid to synthesize a film-type material that is flexible and highly adhesive.

Operating principle of the passive cooling film. The film attached to an electronic device absorbs and stores moisture from the air, then releases it when heat is generated during device operation, continuously cooling the device. Provided by DGIST

The developed film maintains its adhesion and flexibility even when completely dry, allowing it to firmly stick to various surfaces such as metal, semiconductors, and glass. It absorbs and stores moisture from the air, and when the device generates heat, it evaporates the stored moisture, lowering the device surface temperature in real time. Even when it contains moisture, it does not corrode the device, so it can be attached directly to the surface of components without any additional coating process.

When its cooling performance was tested on operating electronic devices, the film stably reduced the device surface temperature by up to 18.2°C, from 72.3°C to 54.1°C, for more than 12 hours.

The research team stated, "These results show that the film can serve as a supplementary cooling device that alleviates the burden on existing electronic cooling systems, which consume large amounts of water and electricity," adding, "It can be used as an eco-friendly, high-efficiency energy-saving solution for the AI era."

Self-cooling films have emerged as a critical breakthrough for managing thermal loads in AI-era electronic devices. As artificial intelligence models demand sustained, high-intensity processing, AI chips and data center architectures generate immense heat densities that push traditional cooling systems beyond their limits. Self-cooling passive films offer an eco-friendly, zero-energy solution to this "thermal wall" without requiring electricity, pumps, or mechanical fans.

Recent breakthroughs utilize two distinct methodologies to solve electronic overheating: hygroscopic evaporative films and passive radiative cooling films.

1. Moisture-absorbing evaporative cooling films...A prominent breakthrough in October 2026 comes from a research team led by Professor Seong Kyun Kim at the Daegu Gyeongbuk Institute of Science and Technology (DGIST).

• The core mechanism: The film operates like a bio-inspired sweat system. It continuously extracts humidity from the surrounding ambient air even when dry. When the device undergoes intense AI workloads and heats up, the trapped water evaporates to absorb and carry the heat away in real time. When the device cools down, the film self-regenerates by re-absorbing moisture from the air.

• Material composition: It is an all-bio-based hydrogel combining nanocellulose (providing structure and immense moisture-holding capability) with hygroscopic organic ionic liquids (attracting water and ensuring flexibility).

• Thermal performance: Under continuous device operation, it consistently reduces surface temperatures by up to 18.2°C (from 72.3°C down to 54.1°C) with continuous cooling lasting over 12 hours.

• Key semiconductor advantage: Unlike historical moisture-based materials that are rigid and cause rust, this hydrogel remains highly adhesive and strictly non-corrosive when dry. It fits perfectly onto glass, semiconductors, and metals with zero air gaps.

2. Metamaterial passive radiative cooling films...Another dominant category includes ultra-thin metamaterial films that use the principles of photonics to reject and dump thermal energy.

• The core mechanism: These films work via a dual-action process. They block incoming ambient radiation/sunlight while simultaneously emitting internal device heat into the mid-infrared spectrum (the "atmospheric window"), effectively shedding heat into the cold sink of deep space with zero input power.

• Material composition: These typically consist of layered polymer structures embedded with nanoparticles (such as silicon dioxide, diamond microparticles, or boron nitride) to enhance both thermal conductivity and broadband infrared emissivity.

• Commercial integration: For example, Moguang New Energy—utilizing tech developed at Nanjing University—mass-produces atomic-layer radiative films for smartphones (adopted by brands like Apple and Xiaomi), which drops internal temperatures by 5°C to 10°C and boosts hardware reliability by up to 40%.

DGIST

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SAMSUNG

Samsung launches affordable 5G phone with 90Hz AMOLED display, 50MP OIS camera and 2TB expandable storage

Samsung has launched the Galaxy F70 5G in India with an Exynos 1330 processor and a 6.7-inch Super AMOLED display. Its 50 MP main camera supports optical image stabilization, and the phone has a 5,000 mAh battery with 25 W charging.

Samsung has expanded its Galaxy F70 series in India with the launch of the Galaxy F70 5G, following the Galaxy F70e 5G in February 2026 and the Galaxy F70 Pro 5G in August 2026.

The Galaxy F70 5G features a 6.7-inch Super AMOLED display with a resolution of 2,340 × 1,080 pixels and a 90Hz refresh rate. Corning Gorilla Glass Victus protects the screen, while an IP54 rating provides resistance to dust and splashes. The phone measures 164.4 × 77.9 × 7.5 mm (6.47 × 3.07 × 0.30 inches) and weighs 192 g (0.423 lb).

Samsung pairs its Exynos 1330 octa-core processor with 4 GB or 6 GB of RAM and 128 GB of storage. A microSD card can expand storage by up to 2 TB. The phone runs Android 15 with Samsung's One UI 7.

The rear camera system consists of a 50 MP main camera with optical image stabilization (OIS), a 5 MP ultrawide camera and a 2 MP macro camera. A 13 MP front camera handles selfies and video calls. Samsung promotes the main camera's stabilization with its "No Shake Cam" branding.

The Galaxy F70 5G has a 5,000 mAh battery, 1,000 mAh less than the Galaxy F70 Pro, and supports 25 W wired charging. Other features include Circle to Search, Google Gemini, Samsung Wallet and Samsung Knox security.

Despite sharing key specifications, including the processor and display, the Galaxy A17 5G (currently available on Amazon), which we have reviewed, offers longer software support, with six generations of Android OS upgrades and six years of security updates. The Galaxy F70 5G is limited to four generations of OS upgrades and five years of security updates.

A stabilized camera and AMOLED display...Samsung’s latest Galaxy F handset offers several hardware and software features for photography, entertainment, and everyday use.

Camera system. A 50MP main camera uses optical image stabilization (OIS) to reduce blur caused by hand movement, a feature the tech giant calls the No Shake Cam. A 5MP ultrawide camera captures wider scenes, while a separate 2MP macro camera handles close-ups. A 13MP front camera handles selfies and video calls.

Display and durability. The phone features a 6.7-inch Full HD+ Super AMOLED screen, Corning Gorilla Glass Victus protection, and an IP54 rating for dust and splash resistance. The device measures 7.5mm thick.

Performance and battery. An Exynos 1330 processor powers the phone, with microSD support for expandable storage. A 5,000mAh battery supports 25W wired charging.

Software and connectivity. Circle to Search lets users search for content directly from their screens, and Google Gemini provides AI assistance. Samsung Wallet supports contactless payments with compatible cards and terminals. Quick Share enables wireless file transfers between supported Galaxy devices and Windows computers.

Several AI functions depend on internet access or account sign-in. Language and regional support can also affect which options are available.

Two configurations and launch discounts in India...Both configurations provide 128GB of internal storage. The 4GB RAM version costs ₹19,999 (about US$211), compared with ₹22,999 (about US$242) for the 6GB model.

Eligible launch bank promotions can lower the entry price to ₹17,999 (about US$190). Shoppers should verify their payment eligibility and final checkout total before relying on the advertised discount.

Sales begin Oct. 20 at noon IST through Flipkart and Samsung India’s website. Bold Black and Vivid Violet are the available colors, and a compatible 25W charging adapter is sold separately. International availability has not been announced

What buyers should check before choosing a Galaxy F70...A newer release is not necessarily a better fit for your daily routine.

Samsung’s earlier announcement identifies a 6,000mAh battery and 120Hz HD+ screen on the F70e, compared with the new handset’s higher-resolution AMOLED panel and optical camera stabilization. The F70e offers greater battery capacity, but comparable battery-life tests are needed to establish which phone lasts longer between charges. Frequent photographers might prefer the stabilized camera, although actual image quality still needs independent testing.

The 6GB model costs ₹3,000 (about US$32) more without adding storage. Buyers who frequently switch between work apps may prefer the extra RAM, but neither configuration’s performance has been established here through hands-on testing. Before paying the premium, consider the apps you use and how long you expect to keep the phone.

Long-term ownership also depends on software support. Samsung’s six-year OS and security-update promise for the F70e should not be assumed to apply to the standard F70. Confirm the exact model’s Android upgrade commitment, security-update frequency, and support end date before purchasing.

Pricing and availability...The Galaxy F70 5G starts at ₹19,999 (approximately $211) for the 4 GB RAM and 128 GB storage variant, while the 6 GB RAM and 128 GB model costs ₹22,999 (approximately $242). Launch offers reduce the starting price to ₹17,999 (approximately $190) on Flipkart. It comes in Vivid Violet and Bold Black, with sales starting in India on October 20. Samsung has not yet announced whether it will launch the smartphone in other countries.

 

by: mundophone

TECH

KAIST develops AI that reconstructs cloud-covered ground in satellite images with photo-like clarity

Satellite images of the Earth are not always easy to use. Clouds can block the view of the ground, and images captured with certain imaging methods look different from ordinary photographs, which makes them difficult to interpret. A KAIST research team has developed an artificial intelligence (AI) model that learns the appearance of diverse terrain and cities. The model can restore cloud-covered images and convert radar images into images that resemble ordinary photographs. It applies what it learned while generating satellite images to a range of image-processing tasks, so it is expected to expand the use of satellite data in disaster response and environmental monitoring.

KAIST (President Choongsik Bae) announced on October 20 that a research team led by Professor Munchurl Kim of the School of Electrical Engineering has developed GeoCore-9B, an AI model that can be used to generate, restore, and convert satellite images. During training, the model’s core image-generating component learns image features by adjusting about 9 billion internal values, known as parameters. GeoCore-9B is pretrained on a large volume of satellite data and can then be adapted to a variety of tasks. For this reason, it is classified as a ‘foundation model,’ a type of AI model that serves as the basis for a wide range of AI technologies.

Satellite images are essential for monitoring changes in forests and cities and for responding to disasters such as floods and wildfires. However, optical images, which record sunlight reflected from the Earth’s surface, cannot clearly capture the ground when clouds are thick or at night. Synthetic aperture radar (SAR) observes the ground by transmitting radio waves and measuring the signals reflected back. It can acquire images of the Earth’s surface at night and in cloudy weather. However, SAR images differ from ordinary photographs in brightness and patterns, which makes them difficult to interpret.

To create a common basis for processing these different types of satellite data, the research team trained the core image-generating model from scratch on Earth observation data. Instead of adapting the core component of a model built to generate ordinary photographs, the team trained a new model on overhead satellite views of terrain, forests, ports, and cities.

The model was trained on 10 million pairs of satellite images from around the world and sentences describing each image. For example, an image of a port was paired with a description stating that ships and warehouses are located there. An image of a rural area was paired with a description stating that a road runs between fields. By learning from this large collection of described images, the AI learned the features of diverse terrain and urban areas.

A key feature of this study is that the AI learned not only what an image contains, but also which location on Earth the image shows and how large an area it covers. In satellite images, objects with similar shapes may be small buildings or large industrial facilities, depending on their actual size. It is therefore important to take into account both where an image was taken and its spatial scale.

The team trained the model using latitude, longitude, and ground sample distance (GSD) together with the descriptive sentences. Latitude and longitude indicate a position on Earth. GSD indicates the size of the ground area represented by a single pixel, the smallest unit of an image. For example, at a GSD of 1 meter, one pixel represents an area of about 1 meter by 1 meter on the ground. Using this information, the AI learned to generate images that match a given location and spatial scale.

The team also applied a training technique called ‘Geospatial Semantic Alignment,’ which helps the model represent the structure of terrain and cities more accurately. In this technique, the generative model learns by referring to features extracted by an AI specialized in satellite imagery. These features serve as a training reference that helps the model learn structural elements of an image, such as how roads connect and where farmland boundaries lie. The specialized AI is used only during training, so it does not add computation when the model generates images.

The researchers then fine-tuned GeoCore-9B separately for cloud removal and for radar image conversion. They used LoRA (Low-Rank Adaptation), a method that keeps the core model fixed and trains only a small number of additional parameters. This approach reduces the burden of retraining an entire large AI model from scratch for each task.

In evaluations using publicly available satellite datasets, GeoCore-9B outperformed existing task-specific models at restoring cloud-covered images. It scored higher on the key metrics that measure brightness, color, and structural similarity to the reference images. In converting radar images into optical images, it also achieved the best results on some of the metrics that assess the quality and fine detail of the generated images.

These results demonstrate that knowledge gained from generating satellite images can also be applied to restoring and converting actual observation images. The model is expected to make greater use of data whose value has been limited by cloud cover or imaging methods. It is also expected to support the assessment of conditions in disaster areas and the monitoring of changes in forests, farmland, and cities. In addition, adapting a single common model to multiple tasks can reduce the cost and time required to develop a separate AI for each task.

The team plans to validate the model’s performance across a wider range of sensors and regions. To apply the model to real-world disaster response, the team also plans to expand its research to accurately predicting changes on the ground, such as floods, building damage, wildfires, and urban expansion. The team will also explore defense applications such as surveillance and reconnaissance.

“By training the AI on where each satellite image was taken and the actual size of the terrain it shows, we made it possible to use a single model for multiple tasks such as cloud removal and image conversion,” said Professor Kim. He added that he expects the work to make satellite data limited by weather or imaging methods more widely usable, which will help with assessing disaster situations and monitoring changes in forests and cities.

Recent artificial intelligence models can reconstruct cloud-covered ground in satellite imagery with high clarity by combining optical data with radar sensing, historical archives, and specialized generative foundation models.

Key AI technologies for cloud removal and ground reconstruction:

• KAIST GeoCore-9B: Developed by researchers as a 9-billion-parameter generative foundation model trained specifically on Earth observation data, this model performs tasks like cloud removal and SAR-to-optical image translation with consistent layout and sharp boundaries.

• Microsoft SpaceEye: Uses Synthetic Aperture Radar (SAR) from the Sentinel-1 mission (which penetrates clouds) paired with historical optical data to generate daily cloud-free predictions of what the ground looks like underneath.

• ClearSKY Vision: Merges optical and radar (SAR) data to reconstruct missing Sentinel-2 data and deliver analysis-ready, cloud-free imagery.

• SenseNet & CMSN: Deep denoising and frequency-domain learning models (such as coarse-to-refine Residual FFT-Convolution and attention-based networks) isolate and remove cloud/haze structures while reconstructing underlying textures.

• Google AlphaEarth Foundations: Functions as a "virtual satellite" that integrates petabytes of multi-modal Earth observation data to map persistent cloud-covered regions (such as parts of Ecuador or Antarctica).

KAIST

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DIGITAL LIFE

Online Safety Act drives VPN interest and raises privacy concerns

People's online behavior has changed in response to legislation to prevent children from viewing harmful content—raising possible privacy and security risks, research suggests.

A new study examined how individuals have responded to age-verification checks enforced by the Online Safety Act (2023) and evaluated the potential risks from bypassing the rules.

The Online Safety Act is a set of U.K. laws and duties that require social media companies and search engines to protect users, especially children, from illegal content and harmful material.

VPN interest surged around age checks...Researchers from the University of Edinburgh, in partnership with the Universities of Newcastle and Durham, studied data from Google Trends and Reddit, a forum-based social media platform.

They found that U.K. users' online discussions about virtual private networks (VPNs)—tools used to circumvent the new restrictions—increased by 145%, while U.K. Google searches for VPNs rose by 147%, using statistical analysis to compare with a typical day.

Discussions relating to the act in U.K. political communities on Reddit also increased by 1,481%.

The increases were concentrated around July 25, 2025, when age checks for adult websites and some social media platforms came into force, researchers say.

While online discussions do not translate directly into VPN usage, the team used this as a proxy for interest, as they were not able to access data on the number of VPN downloads.

Avoiding checks can introduce privacy risks...Age verification may require users to disclose sensitive information about themselves, such as facial scans, identity documents or payment details.

A VPN creates a secure, encrypted connection between users' devices and the internet. It hides individual IP addresses and jumbles data so internet providers cannot track a location or online activity.

However, people who seek to gain access to restricted sites without submitting personal data by using VPN services may be putting themselves at risk, experts say. This is because some high-risk VPN services track, retain and share user data with third parties.

The increase in VPN interest matters because people using these services may not understand the difference between low- and high-risk providers, experts say.

Researchers say there is a need for greater understanding of the privacy risks of VPNs to help keep everyone safe online.

The paper appears in the journal Proceedings on Privacy Enhancing Technologies and was also released on the arXiv preprint server.

Privacy concerns shape users' choices...Dr. Tuğrulcan Elmas, lecturer in the School of Informatics, University of Edinburgh, said, "The sharp rise in interest in VPNs highlights an important unintended consequence: users seeking to avoid sharing sensitive information for age verification could unknowingly use services that collect and sell their data."

Dr. Marc Juarez, lecturer in cybersecurity and privacy, University of Edinburgh, said, "It surprised us that people trust VPN providers over the companies who have been certified to run the checks, especially as user interest also increased for high-risk VPNs. We urgently need to raise awareness of the privacy risks of VPNs and highlight that not all VPN providers are created equal."

Dhyey Mehta, an undergraduate student from the University of Edinburgh, said, "What stood out from our findings was that users did not frame VPNs as a way to bypass restrictions, but as a way to preserve privacy amid identity checks, facial scans and surveillance. Future policies should account for how people actually respond and address the concerns that drive them toward circumvention."

Interest in virtual private networks (VPNs) has risen following the introduction of the Online Safety Act, but Edinburgh academics have warned of the ‘privacy risks’ in using such platforms.

A new study led by the University of Edinburgh examined how individuals have responded to age verification checks enforced by the Online Safety Act and evaluated the potential risks from bypassing the rules.

The 2023 legislation is a set of UK laws and duties that require social media companies and search engines to protect users, especially children, from illegal content and harmful material.

Researchers found UK users’ online discussions about VPNs – tools used to avoid restrictions – increased by 145 per cent, whilst Google searches for VPNs rose by 147 per cent, using statistical analysis to compare with a typical day.

The academics, worked with colleagues from the universities of Newcastle and Durham, studied data from Google Trends and Reddit, the online forum and message board.

On Reddit, discussions relating to the act in UK political communities increased by 1,481 per cent, the study showed.

The increases were concentrated around 25 July 2025, when age checks for adult websites and some social media platforms came into force, researchers say.

Without data on VPN downloads, the team used online discussions as a ‘rough proxy’ for interest, even though discussion doesn’t directly reflect usage.

Age verification may require users to disclose sensitive information about themselves, such as facial scans, identity documents or payment details.

A VPN encrypts the connection between your device and the internet, hiding your IP address and scrambling your data so internet providers can’t see where you are or what you’re doing online.

But experts warn that people using VPNs to reach restricted sites without handing over personal details could be putting themselves at risk.

Some riskier VPN services track, store and share user data with third parties, and many users may not know how to tell safe providers from risky ones, and the researchers said people need to better understand VPN privacy risks to stay safe online.

Dr Tuğrulcan Elmas, lecturer in the School of Informatics, University of Edinburgh, said: “The sharp rise in interest in VPNs highlights an important unintended consequence: users seeking to avoid sharing sensitive information for age verification could unknowingly use services that collect and sell their data.”

Dr Marc Juarez, lecturer in cybersecurity and privacy, University of Edinburgh, added: “It surprised us that people trust VPN providers over the companies who have been certified to run the checks, especially as user interest also increased for high-risk VPNs. We urgently need to raise awareness of the privacy risks of VPNs and highlight that not all VPN providers are created equal.”

The implementation of age-verification guidelines mandated by the UK’s Online Safety Act has triggered a significant side effect: a massive surge in interest in Virtual Private Networks (VPNs) and the emergence of new privacy and digital security risks.

A study published in October 2026 by researchers from the universities of Edinburgh, Durham, and Newcastle revealed how user behavior shifted following the introduction of mandatory age checks.

The VPN interest boom...To map the public's reaction, the researchers analyzed data from Google Trends and discussions on the platform Reddit. Key findings indicate that:

• Google searches: Searches for VPNs in the UK spiked by 147% compared to a typical day.

• Forum discussions: Discussions about VPNs on Reddit rose by 145%, while threads concerning the legislation within British political communities surged by 1,481%.

• Critical moment: This spike in interest was heavily concentrated around July 25, 2025—the date when strict age-verification requirements for adult websites and certain social media platforms came into effect.

Why did users turn to VPNs? The Online Safety Act requires digital platforms to employ "highly effective" systems to prevent minors from accessing harmful content. In practice, this necessitates that users provide highly sensitive information, such as facial scans (biometrics), identification documents, or credit card details.

Many adults and young people have opted to use VPNs to mask their IP addresses, making it appear as though they are browsing from outside the UK. By doing so, they are able to access websites directly, bypassing the data-verification process. 

New privacy risks...Although users adopt VPNs with the goal of protecting their identities and avoiding the exposure of documents on web portals, experts warn that this strategy has created a new privacy hazard:

1. Use of malicious providers: Many users—especially those using such tools for the first time—cannot distinguish between secure services and high-risk or "free" providers.

2. Data collection and sale: Numerous low-quality VPNs profit precisely by tracking, retaining, and selling users' browsing history and personal data to third parties.

3. Shifting the risk: As highlighted by the study's authors, in attempting to protect minors by restricting access, regulators have inadvertently pushed the general population toward services that compromise their digital security.

Government response...Faced with this situation, some lawmakers even suggested restricting or blocking tools used to bypass access controls. However, following intense pressure from digital rights organizations such as the Open Rights Group, the British government backed away from plans to ban VPNs or impose age restrictions on them, acknowledging them as legitimate and essential cybersecurity tools for remote work, journalists, and the general public.

Provided by University of Edinburgh 

 

TECH

The iPhone 18 Pro’s variable aperture is unnecessary for most people

The new camera on the iPhone 18 Pro introduced a feature that garnered significantly more attention at launch than anything else: a variable aperture system for the main (48 MP) lens, capable of switching between f/1.48 and f/4.0. While the company’s marketing might make this sound revolutionary, the reality is that the mechanism will have an almost imperceptible impact on the daily lives of the vast majority of users.

For those who have mastered professional photography and use manual controls, a variable aperture offers precise adjustments over light intake and the natural optical blur (bokeh) of a scene.

However, for the average user who relies solely on automatic mode, the system will remain locked at an f/1.8 aperture almost all the time—behaving exactly as it did in previous iPhone generations.

Is there any real advantage for those who use automatic mode? Furthermore, this feature is far from new to smartphones—even setting aside the Samsung Galaxy S9, which featured a simpler system capable of switching between only two, much more limited, aperture settings.

The only significant practical benefit occurs in extremely low-light environments. In such situations, the lens opens to its widest setting of f/1.48, allowing for greater physical light capture and faster shutter speeds, which helps reduce motion blur. Yet, this same result could be achieved by maintaining a fixed, wider physical aperture and adjusting exposure through image processing—without the need for a moving mechanical component inside the camera module.

For years, brands like Xiaomi and Huawei have incorporated lenses with variable apertures—offering settings similar to those found on the iPhone 18 Pro—into their own high-end smartphones. The most striking example is the Huawei Pura 80 Ultra, which combines this technology with a 1-inch sensor and continues to lead the global DxOMark camera rankings, pushing Apple’s latest release into second place.

If you aren’t a professional content creator—or don’t plan on using camera apps with advanced manual controls—you’ll be paying a premium for moving parts within the sensor that are unlikely to make any real difference to your final results. Your photos will still be excellent, but not because of any lens variability when shooting in automatic mode.

If you have any other questions about the device, check out our full review of the iPhone 18 Pro. In the meantime, we’d love to know: do you typically adjust your camera settings manually before taking a photo, or do you prefer to rely entirely on your phone’s automatic mode?

Testing the iPhone 18 Pro’s most-hyped feature The iPhone 18 Pro has a variable aperture. According to Apple’s keynote, it’s the brand’s «biggest camera improvement in years». Supposedly, it provides «more control for light intake and depth of field,» enabling «new levels of creativity». Well, well. That does sound great.

But is there any truth to these salesy promises? In a bid to find out, I put the feature under the microscope – and got a mixed first impression. In most situations, the variable aperture makes zero difference to your photos. But that doesn’t mean it’s entirely pointless.

Very little control over depth of field...If you’re a photography buff, you’ll be familiar with the concept of a variable aperture from using traditional cameras. It’s a mechanism that uses multiple blades to increase or decrease the size of the lens opening. On larger cameras, variable apertures are indispensable because they serve two important functions:

Controlling light intake: If you’re taking pictures in blazing sunlight, a fully open lens lets in so much light that the camera’s shutter can’t expose the sensor for a short enough period of time. As a result, photos turn out overexposed. A variable aperture solves that problem.

Controlling depth of field: The larger the lens opening, the smaller the area in focus. Photographers often want this, as it means the subject in focus stands out from the background. It’s a technique used in portrait photography, for instance. In other scenarios, however, every area of the photo needs to be equally sharp. Landscape photography is a prime example of this. Variable apertures allow you to control that depth of field.

On a smartphone, these functions are mostly unnecessary. This is down to the device’s tiny image sensor (1/12 of the size of a full-frame sensor) and its electronic shutter. It already achieves high enough shutter speeds – even in direct sunlight with the lens wide open. As a result, you don’t need a variable aperture to get proper exposure.

The small sensor also means that the focal plane is super wide anyway – especially with a wide-angle lens like the one on the iPhone’s main camera (24 mm 35 mm equivalent). The maximum aperture of ƒ/1.48 produces roughly the same depth of field as ƒ/5.2 on a full-frame camera. Photos come out pretty sharp all over, unless you get extremely close to the subject. The new aperture can only make the focal plane larger, not smaller. That means pronounced blurring (known as «bokeh») still has to be created digitally using Portrait Mode.

Strictly speaking, the «more control over exposure and depth of field» promised in Apple’s promotional materials isn’t a lie. However, on a smartphone, the benefits are far less significant than the company suggests.

That being said, the feature does have two minor uses. Firstly, the variable aperture allows you to deliberately increase exposure time to create motion blur. Though, only within a narrow range of ambient light. The iPhone’s aperture can be adjusted from just ƒ/1.48 to ƒ/4. Outdoors, in daylight, the shutter speed is still much too fast, even at ƒ/4. And in very low light, it doesn’t make any difference, because you’ll be opening the aperture all the way anyway. At best, it’ll make a difference in a handful of scenarios – and only at dusk.

The second benefit of the variable aperture is similarly limited. Videos look more natural when the shutter speed of individual frames is about half the frame rate. For example, 1/60 second at a frame rate of 30 frames per second (FPS). This is because our eyes expect some motion blur in videos. Again, in specific lighting situations, the variable aperture can be the deciding factor in whether to set the shutter speed to 1/250 or 1/60 of a second. In most cases, though, you’ll still need an ND filter if you want to pull this off.

The variable aperture on the iPhone 18 Pro (ranging from f/1.48 to f/4.0) has drawn mixed reactions; it is generally considered of little use to the average user, serving more as a niche feature for content creators and photography enthusiasts than as a revolutionary advancement for daily use.

Why don’t most people need it?

• Small sensor: Due to the tiny size of a smartphone sensor, the depth of field is naturally quite deep. The optical background blur (bokeh) produced at f/1.48 is limited—very similar to the effect that software-based portrait modes have been achieving for years.

• Over-reliance on automatic exposure: For everyday photography—such as quick snapshots of family, pets, or food—the iPhone’s automatic mode intelligently adjusts the image, eliminating the need for the user to manually manipulate physical aperture blades.

• Limitations in daylight: In very bright or sunny environments, even when stopping down to f/4.0, the phone’s shutter speed remains extremely fast; this does not fully replace the need for professional-grade filters (such as ND filters).

Who actually benefits from this feature?

• Videographers and content creators: Those who utilize manual controls—such as the 180-degree shutter rule—to achieve more natural, cinematic motion blur in their videos.

• Photography enthusiasts: Those who prefer using "Pro" mode to lock white balance and manually adjust light intake and sharpness for specific conditions (such as during twilight).

 

by mundophone