The IEEE is warning that China’s export controls on rare earth minerals could start to impact datacenters, as shipments of some key materials are down 75 percent and Beijing is due to review its policies this November. The techie org's official publication, IEEE Spectrum, focuses on two rare earths in particular, erbium and yttrium, which are used in components for IT equipment. Exports of yttrium are down by about 75 percent this year in comparison with 2025. Yttrium was one of seven medium and heavy rare earth elements that China placed under mandatory licensing in its first wave of restrictions in 2025. Yttrium is used in white LED lights and displays, microwave filters, and solid-state lasers, and also in ceramic capacitors found in pretty much all electronic kit. Erbium is used in the amplifier circuits that boost optical signals in fiber-optic links. The Chinese government enacted restrictions on the overseas sale of rare earth minerals last April, as reported by The Register. This was part of retaliatory measures against the Trump administration’s slapdash trade tariffs. It upped the ante later in the year with tougher measures, including laws that require companies to apply for a license before they ship any goods containing rare earths sourced in China to anywhere in the outside world. This latter rule is a mirror of US laws like those used to block the export of ASML chipmaking equipment to China. That second wave of measures – which was to have included increased export controls of five new elements including erbium – was suspended in November 2025 for 12 months, following trade talks between the US and China. When the year is up this November, Beijing will decide whether to drop the tougher measures or re-apply them, perhaps extending them to all or most of the rare earth minerals it controls. According to the International Energy Agency (IEA), the supply of rare earths remains among the least geographically diversified among all critical minerals. For those minerals used in magnets, China accounted for about 60 percent of global mining output in 2024, and its dominance is even greater in the separation and refining stages, making up about 91 percent of global production. But for yttrium and erbium used in IT kit, China is effectively the sole source, IEEE Spectrum claims. The country mines 90 percent of the world’s yttrium, but it processes all of the world’s mined ore into an industrially usable form such as yttrium oxide, and likewise supplies all erbium oxide. Washington has been taking some steps to try and offset China’s virtual monopoly of key rare earth materials. Recently, the US Department of Defense announced a $750 million investment to secure supplies of rare earth elements for magnets from a production site in central Brazil, while the Department of Energy announced $500 million for seven selected projects to expand critical mineral and material processing, battery manufacturing, and recycling. The US signed agreements with representatives of 54 countries at the 2026 Critical Minerals Ministerial meeting in February this year, as well as talking up commitments to build secure and resilient supply chains for such materials. Also in February, President Trump launched Project Vault, a supply chain security initiative establishing an American Strategic Critical Minerals Reserve stockpile, with funding of up to $10 billion from the federal Export-Import Bank of the United States. But many of these initiatives will take time to have any impact, and China’s impending decision will put these to the test, should it decide to take a tougher stance. Relations between Washingon and Beijing remain strained because of trade and other factors, and a lot could be riding on a summit between President Trump and President Xi Jinping next month. ®

Shots were fired at the Hot Chips conference in California this week as Nvidia announced its new Groq-3-based LPX racks had entered production, with early tests showing the systems churning an eye-watering 3,400 tokens a second in Gemma 4 31B. That's four times faster than rival Cerebras. A day later, Cerebras fired back, touting nearly equivalent performance from its next-gen CS-4 accelerators revealed last week. These top-line performance figures make inference feel instantaneous relative to the chatbots we've grown accustomed to over the past four years. But the two companies are essentially arguing over numbers their customers will probably never see in production. To be clear, neither is lying. If you wanted to recreate these results, you certainly could — Artificial Analysis, the team responsible for both sets of benchmarks, knows what they're doing — but beyond a marketing gimmick, no inference-as-a-service model operator in their right mind would run either system this way. Not unless you've somehow figured out how to make a profit serving one request at a time. In reality, these numbers are more like the top speed on a race car. It makes for great marketing but you probably aren't driving that fast on a regular basis, and if you did, you wouldn't get very far before your tank runs dry. These aren't the numbers that matter Unsurprisingly, the economics of "premium" or "ultra-low latency" inference are a bit more nuanced, but ultimately come down to how efficiently you can scale that performance at the rightmost end of the Pareto frontier. We've shown the graphic below before. It charts the performance characteristics of how different Nvidia B300 configurations perform across a Pareto front. As you can see, GPUs are great for high-throughput, low-interactivity applications, but run out of steam quite quickly as per-user generation rates climb. Chips like Nvidia's Groq-3 LPUs or Cerebras' dinner plate-sized accelerators offer massive bandwidth thanks to their SRAM-heavy architectures, so they can extend and push the Pareto curve out to the right. Unfortunately, the same thing that makes them so fast also limits their ability to scale that performance to large numbers of users. To understand why we need to walk through a little math. We're going to pick on Gemma 4 31B, in part because we have rough numbers for both Nvidia and Cerebras, but also because it's a small model and therefore presents a best-case scenario. Each Groq-3 accelerator is equipped with 500 MB of on-chip memory capacity. Nvidia achieved its 3,400 tok/s per user run at 8-bit precision. So to run a 31 billion-parameter model, we need about 31 GB of memory or about 64 LPUs. But that's just to hold the model's weights. Since it's running as a standalone system, we also have to account for the KV caches generated during the prefill stage in which the prompt is processed. According to LMcache's KV calculator, at 8-bit precision, a 100,000-token input sequence is going to chew up another 8 GB of memory, and that's per sequence. So for every additional 100,000 token input, that's another 16 LPUs worth of memory. By our estimate, that means the most a single LPX rack with its 256 LPUs can manage on its own before running out of memory is a batch size of 12 at a 100,000 token input length each. The numbers look a little different for Cerebras' CS4, but the conclusion is largely unchanged. Each CS4 rack contains three massive WSE-3T accelerators with 44 GB of SRAM apiece, totaling 132 GB of capacity. That leaves the system a bit more headroom, but we're still looking at a maximum batch size of 12. To be clear, that's not a compute limitation. The systems simply don't have enough memory to support larger batches without adding additional racks or cutting the prompt size. Sure, we're oversimplifying a bit. We're assuming batch inference with fixed input sequences, not concurrent users hitting the systems asynchronously, and with different input and output sequences each time. For a chatbot, especially one with a limited context window — think the model's short term memory — a single CS4 or LPX rack could conceivably serve far more users than the 12 noted here. Lifting the curve Even if both systems can hit 3,400 tok/s, the better platform is going to be the one that delivers better scale at a lower cost and power consumption. The benchmark figures touted by Nvidia and Cerebras this week are really measuring the top speed the systems could run on, not the speed customers will actually run them. In fact, customers probably won’t run these systems on their own. These SRAM-heavy architectures work a lot better as decode accelerators, which is exactly why Nvidia spent $20B to license Groq's tech and poach its engineering team. It's also why Cerebras recently teamed up with AWS and AMD. We've discussed these kinds of heterogeneous compute architectures in the past, but in a nutshell they involve GPUs or other compute heavy XPUs, like Amazon's Trainium chips, with something like Groq's LPUs, Cerebras' waferscale accelerators, or SambaNova's SN-series parts. This combination largely eliminates, or at least minimizes, the KV cache and compute overheads that made scaling Cerebras' and Groq's chips so difficult. As decode accelerators, they only really need to hold the model weights, as almost everything else can get on just fine on a GPU. Again, top line AI performance makes for great headlines, but the far right of the Pareto is rarely where you'll want to be. As is usually the case with Pareto curves, the sweet spot usually presents itself as a notable hump or knee pushing toward the upper right corner of the chart. Here you'll be trading some per-user interactivity for better concurrency, throughput, and economics. Combining GPUs with Cerebras or Groq accelerators is what Nvidia, AMD, and AWS are all counting on to make "premium inference" cost-effective. There's a better benchmark for this We've yet to see benchmarks combining Cerebras' or Groq's chips with Nvidia, AMD, or AWS' respective GPUs and XPU platforms, but these are the metrics that are actually going to matter. SemiAnalysis' InferenceX offers a better representation of whether or not adding a CS4 or LPX rack would even help, as we can see exactly how each system performs across the full Pareto, ranging from high-volume low-interactivity "bulk" tokens on the left, to ultra-low-latency but also lower-volume tokens on the right. In fact, while Nvidia and Cerebras opted for Artificial Analysis' simpler test methodology, OpenAI actually opted for InferenceX to show how its spicy new Jalapeño accelerators perform across bulk and premium inference regimes. So why didn't Nvidia and Cerebras do the same? If we had to guess, it's because their LPX and CS4 racks are still best suited toward low-latency inference and wouldn't look as impressive on the left and middle sections of the Pareto curve. We fully expect that both companies will share InferenceX results for their combined GPU and LPX/CS4 systems when they're ready, but no marketer ever got a bonus for making their product look worse than it really is, so we'll just have to wait. In any case, the next time you see someone boasting of some impossibly fast inference accelerator, it's worth asking where on the Pareto that number came from. ®

If you’re going to build a custom AI accelerator, inference is a good place to start. The clusters are smaller, the chips can be simpler, and at the end of the day they only need to do one thing: serve tokens. OpenAI’s spicy new Jalapeño inference chips are just the latest example. Social media magnate Meta is bucking this trend. Its first proper generative AI accelerator, the MTIA 400 — short for Meta Training and Inference Accelerator — is aimed squarely at LLM training. The Facebook parent is no stranger to custom silicon. But, much like Amazon and Google, its first AI accelerators weren’t built to run AI chatbots or train generative AI models. They were built to serve ads. The MTIA 400, teased earlier this year and detailed at the annual Hot Chips semiconductor development conference this week, will perform some inference duties. Just not of the GenAI variety. Instead, it’ll be saddled with running the ad recommender systems that actually pay Meta’s bills. The combination of LLM training and the deep learning recommender model (DLRM) inference used for serving ads is unusual, as the two have wildly different performance demands. LLM training is enormously compute-intensive, often requiring tens or even hundreds of thousands of accelerators to train models in a reasonable amount of time. DLRM inference, on the other hand, is a predominantly memory-bound job, which means most of the FLOPS that make the chip good at training are going to be left sitting idle. But given how much cash Meta is burning on compute these days, it’s probably not a bad thing for its chips to pull double duty – even better if one of the two use cases is highly profitable. While MTIA may play a bigger role in how Meta serves its generative AI workloads, its in-house silicon probably won’t replace AMD or Nvidia’s GPUs any time soon. The two chip designers' GPUs are currently much better suited to LLM inference and are almost certainly what Meta Superintelligence Labs is using to train frontier models like Muse Spark. Application-specific hardware has always been better suited to well-understood workloads, and Meta’s accelerators are no exception. But enough about market positioning and workloads. Let’s dig into the chip itself. Dissecting the MTIA 400 At first blush, the MTIA looks a lot like either Nvidia’s Rubin GPUs or AMD’s MI355X accelerators. The MTIA 400 is based on a heterogeneous multi-die architecture, which means it is built from a collection of different chips each with their own job. It features two compute dies, two I/O dies, and an SoC die that handles host connectivity and workload orchestration — all pretty standard stuff. Broadcom’s influence here is hard to miss. The chip almost certainly was built using the IP house’s XPU tech, which we explored in detail last year. Building a competent AI accelerator isn’t a trivial endeavor. So, if you’re trying to bring one to market quickly, it makes sense to focus on what makes your chip special and let someone like Broadcom handle the rest. Digging deeper into the MTIA 400’s heart, the compute chiplets are built on a 3nm process tech, presumably from TSMC, and feature a 6x8 grid of processing elements responsible for the bulk of the accelerator’s AI performance. Combined, the two chiplets are capable of outputting 12 petaFLOPS of MXFP4 compute at 1.7 GHz. To put that in perspective, the MTIA 400 is about 20 percent faster than Nvidia’s top-specced Blackwell accelerators at the higher precisions more commonly used to train models, while sucking back roughly the same power. But the parts don’t hold up nearly as well when compared to Nvidia and AMD’s latest chips – the MTIA 400 is between 3x and 3.3x slower than Rubin and the Instinct MI455X, respectively. Meta’s latest accelerator is fed by eight 36 GB HBM3e stacks that deliver 288 GB of memory and about 9.2 TB/s of bandwidth. Again, that’s about 15 percent faster than Nvidia and AMD’s last-gen parts, but with less than half the bandwidth of their new GPUs. This is probably why Meta is positioning the part as a training chip. It has much better and faster options for LLM inference. The MTIA 400 features a pair of I/O chiplets that provide 1.2 TB/s of chip-to-chip bandwidth over RDMA. We don’t know what transport tech Meta is using at this point, but given Broadcom’s involvement, Ethernet would be the obvious choice. Scaling up MTIA 400’s physical resemblance to Nvidia Rubin and AMD MI350-series parts also extends to the system design. Each compute blade features four MTIA 400 accelerators connected via a PCIe switch to an x86 CPU and a scale-out NIC. A single rack is equipped with 18 compute blades and eight switch blades for a total of 72 accelerators in a single unified domain. Meta shared a pic of the rack earlier this year, so while the compute blade is highly reminiscent of AMD's Helios blades, it's not using the same double wide OCP racks. Meta hasn't shown how large a cluster its chips can support just yet — the slides simply state "multi-thousand accelerator scaling" — but even at rack scale the systems should be quite competent relative to Nvidia’s GB200 and GB300 rack systems for training. More on the way While the MTIA 400 is aimed primarily at LLM training, Meta is already working on an inference-optimized version of the chip. Disclosed back in March, the MTIA 450 will double the chip’s memory bandwidth, presumably by swapping HBM3e for much faster HBM4. That part is expected to enter production next year, and should be extremely well suited to running those LLM-based recommender models Zuck and crew have been talking about the past few quarters. Meanwhile, the MTIA 500, which is also slated for 2027 release (probably in H2 if we had to guess), will increase memory bandwidth by another 50 percent — likely using 4 additional HBM4 stacks — and double the number of compute chiplets. ®

Xbox PC games, distributed through the Xbox app, fail to run on Linux because of Microsoft's proprietary GDK runtime environment. This also breaks Game Pass even though the company supports cloud streaming Game Pass titles. A new open-source project from the developers of Heroic Launcher, called "Xodus," is aiming to fix this by reverse engineering and emulating the necessary components required for Xbox PC games on Linux.

Xodus primarily targets modern, GDK-based Xbox PC titles and their MSIXVC packages; not older, UWP-based releases like Gears of War 4 and early Forza Horizon games. The problem with those isn't the DirectX API or x86 instructions; Proton and DXVK/VKD3D can already translate those. That's also the reason why you can still run Xbox PC games on Linux if you somehow get your hands on the DRM-free executables.

The real issue is the trifecta of Microsoft's proprietary GDK (Game Development Kit), Xbox identify services, and encrypted MSIXVC packages. This framework is responsible for verifying licenses for the games you own through the Xbox app. Without it running in the background, the games will simply crash right as you try to open them, or not launch at all. This is where Xodus comes into play.

The Xodus team says the project can already log into Xbox services, download game packages and obtain game licenses. It includes its own open-source implementation of the xgameruntime.dll and custom forks of both Wine and Proton, along with xal-rs, which is an Xbox authentication library for Rust. Xodus uses proxy libraries to interface with GDK games and intercepts API calls to transmit valid Xbox Live tokens.

Comment

For now, efforts are focused on emulating the Xbox Gaming Runtime from the Xbox GDK through Wine, then the project will move on to actually launching and playing Xbox PC titles locally. Considering they've already solved the Xbox/Microsoft authentication, license check, and package decryption hurdles, it shouldn't be long before we see PC Game Pass running natively on Linux.

BedrockonLinux 2.0, another open-source project that brings Minecraft Bedrock to the platform, already relies on similar reverse-engineering tech to handle these components since Microsoft migrated the game to GDK. This allows the game to talk to Xbox Live in real-time through a secure doorway to authenticate tokens despite the game running in a sandboxed environment like SteamOS (Linux).

Microsoft itself brought four original Xbox titles to PC last month and it says more are coming, along with leaked documents suggesting Xbox 360 titles also releasing on PC next year. These games come with a baked-in Xbox 360 emulator. It's not clear if these games use the same GDK stack as native Xbox PC titles, however.

The economist John Maynard Keynes once remarked, “In the long run we are all dead.” From an astronomical standpoint, this is true for the Earth itself. In roughly 5 billion years, the Sun will exhaust the hydrogen at its core and enter the next phase of its life as a Red Giant, where it will swell up large enough to engulf and destroy the Earth.

Currently, the Sun is still in its main-sequence phase, where it fuses hydrogen into helium in its core. Although it remains relatively stable during this phase, it will gradually grow brighter with time. As the Sun shines brighter, the increased heat and radiation will raise Earth’s surface temperature, potentially pushing it past the threshold for life to survive. 

One of Earth’s geological processes that helps regulate its surface temperature is the carbon cycle. Over millions of years, carbon moves from the Earth’s interior into the atmosphere as carbon dioxide or CO₂, where it functions as a greenhouse gas that traps heat. Plants take in this CO₂ through photosynthesis and move carbon through the biosphere. 

Meanwhile, rain and rock weathering draw carbon into the oceans and rocks. By pulling CO₂ out of the atmosphere, the carbon cycle could mitigate Earth’s warming as the Sun brightens over time. Today, human activities are increasing atmospheric CO₂ and warming the planet. However, over billions of years, the carbon cycle could gradually remove enough CO₂ from the atmosphere that eventually too little would remain to support photosynthesis. 

With these challenges to life on Earth in mind, the researchers Jacob Haqq‐Misra and Eric Wolf investigated how long Earth’s biosphere could last in the distant future. The team used computer models to calculate the balance of energy that Earth would receive and emit over time, accounting for the effects of increasing sunlight and changing atmospheric CO₂ concentrations. They followed this up with calculations using the ExoCAM model to determine the temperature and atmospheric conditions of future Earth across different latitudes. They related these conditions to a habitability metric to determine their impact on the biosphere.

To estimate the biosphere’s maximum possible lifespan, the team conducted 29 simulations representing the planet’s conditions over the next 2 billion years. In one set of simulations, the Earth’s carbon cycle contributed little to regulating surface temperature, with the atmosphere’s CO₂ concentration fixed at approximately modern levels of 400 parts per million (ppm) and surface temperatures continuing to increase. In another, the carbon cycle worked to keep Earth’s average surface temperature fixed at the modern average of approximately 59℉ (15℃), no matter how much it had to reduce CO₂ in the atmosphere. 

In the scenario with a fixed CO₂ concentration, the team found that in 1.7 billion years, Earth’s surface reached an average of 122°F (50°C), which is too hot for most land plants. After 1.9 billion years, it reached 149°F (65°), becoming too hot for all land plants to survive as temperatures continued to rise. 

They also found that in the fixed average surface temperature scenario, atmospheric CO₂ dropped below the 150 ppm level that most plants require for photosynthesis within 500 million years. After 1.4 billion years, CO₂ levels fell below 10 ppm, leaving only a few land photosynthesizers and aquatic plants alive. After about 1.8 billion years, atmospheric CO₂ dropped to 1 ppm, leaving only microbes capable of photosynthesis.

The researchers’ findings generally extend the estimated lifetime of Earth’s future biosphere compared with earlier, simpler models that suggested maximum lifespans of 100 million to 1.5 billion years. However, they clarified that other scientists should verify their results by running tests with other models, especially under extreme conditions of high incoming solar radiation and low atmospheric CO₂. 

Lastly, Haqq‐Misra and Wolf noted that their model did not account for major evolutionary changes that could help life adapt to future conditions. Over time, plants could evolve to tolerate higher temperatures or lower atmospheric CO₂ levels. Future humans or another intelligent species might also engage in large-scale geoengineering projects to prevent the end of life on Earth. If life on Earth proves adaptable enough, the biosphere may endure until a Red Giant fills the daytime sky.

The post The long-term fate of Earth’s biosphere appeared first on Sciworthy.

Windows is in a tough spot right now, with years of neglect and stagnation reaching a boiling point with customers. Lack of optimization, bloat, ads, forced AI slop, and persistent tracking have forced Microsoft to admit its missteps and commit to fixing the OS at large. Windows Latest's new testing shows that the built-in weather app is a perfect representation of the state of Windows. The "app" consumes up to 1.2GB of RAM while idling, and it serves up a bunch of ads while you check the temperature.

MSN Weather is the default weather app that ships with Windows, which explains why it's filled with promotions throughout, despite being part of a paid OS. To be clear, the app looks very modern and has all the data you could ask for, such as live radar overlays, hourly wind and precipitation breakdowns, air quality index, and moon phases. It's also accurate because the data is sourced from a bunch of different providers across the world, but mostly Foreca.

The author explains that getting accurate forecasts is not a cheap endeavor, so it's not like Microsoft is running a charity. But the comparison falls apart when you look at what the competition is offering. Apple's native weather app on macOS is just as beautiful, detailed, and accurate, yet it's free of ads. It also only consumes about 250MB of memory to show all that data, so 5x less than Windows. This is because MSN Weather is technically not even an app to begin with; it's a web wrapper that's pinging a bunch of browser tabs in real-time.

When the author clicked on the Task Manager entry for MSN Weather, they saw 8 Chromium-based subprocesses, confirming that they're just looking at a website being rendered via WebView 2. For context, native Windows apps are supposed to adhere to the WinUI framework, which the company is slowly adopting over Win32 and UWP. Microsoft is committed to updating all the native apps Windows ships with to Win32, which should significantly improve their optimization, but we don't know if the ads will suddenly disappear as well.

The author saw Adobe Acrobat ads while checking the forecast, and we saw two ads — one for LendingTree and another for Spotify. Apart from that, scrolling around the app and clicking on the different menus and boxes was fast enough. We have to emphasize that the app really is granular and well-built from an aesthetic point of view; Microsoft gets full points for that, or is it MSN? That distinction is another issue that makes the weather app conundrum a bit more confusing.

When Microsoft promised to rebuild all native Windows 11 apps, it didn't explicitly say those would include MSN-branded services too, like MSN Weather and MSN News. Seeing as though they're simply called by their utilitarian names in the OS, there's a strong chance that these memory hoggers will also be eventually upgraded. For now, just stick to your phone, especially if you were among those who immediately Googled how to remove the weather widget from your taskbar that fateful day.

Scientists have discovered China’s first known freshwater cave snail, an eyeless species so rare that only three living adults have been found. Deep inside a mountain cave in southwestern China, scientists found an animal that appears built for a world where sunlight never reaches. The tiny freshwater snail has no eyes, almost no color, and [...]

More than five months after the United States and Israel launched Operation Epic Fury against Iran, the Strait

WASGAMUWA, Sri Lanka – Prior to the 1940s and the Green Revolution, Sri Lankan paddy farmers cultivated traditional rice, locally known as purana haal. These rice cultivars were resilient and known to possess various nutritional and medicinal properties yet were soon replaced by new improved rice varieties to obtain better quality and bigger yields. Karu Herath, an heirloom paddy farmer in the village of Dunuwila, bordering the Wasgamuwa National Park located within the Matale and Polonnaruwa districts, has cultivated heirloom paddy varieties for the past 27 years. He told Mongabay that fewer than 30 varieties remain out of the estimated 2,500 varieties of heirloom rice that once existed, a claim supported by rice researchers. According to researchers, many of these rice varieties are long-aged, tall and low-yielding. Therefore, traditional farmers would only cultivate them during one harvesting cycle, known as the Maha season, which runs from September through March. With the introduction of new, improved rice varieties and fertilizers after the 1940s, Sri Lanka lost much of its Indigenous rice varieties and traditional knowledge of Indigenous farming practices. Image courtesy of Pethum Bandara. Herath follows this practice and cultivates only during the monsoon season. “During the Yala season [May to August], when it’s dry, we let the soil recover and grow heirloom cereals and vegetables such as kurakkan [finger millet] and mung [mung bean],” he said. “This draws different nutrients and requires less water than rice. This was the traditional land use system, which was changed by British colonialists who…This article was originally published on Mongabay

First the Oxygen Theory, now the Feces Theory. But how much experience do we really have with feces creating new genetic information?

Source

The federal government is ending its contract with a Kentucky nonprofit that it says pressured medical workers to remove organs from patients who were getting better.

Globally, about 1 billion people live near glaciers and depend on glacial water. As temperatures continue to climb due to global warming, glaciers can become unstable and hazardous to nearby communities. These communities risk exposure to a series of linked processes, like ice collapse, flooding, and landslides, which could have life-threatening consequences. Scientists call these events catastrophic glacier hazard chains, or CGHC. So, a team of scientists in China sought to understand the driving forces behind these dangerous phenomena. 

The team focused on a CGHC event that occurred in 2018 at the Sedongpu Glacier, located in the Eastern Himalayas. During this event, the glacier obstructed the flow of 30 million square meters (more than 300 million square feet) of the Yarlung Tsanpo River, one of the main rivers within the region. 

To reconstruct the event, the team observed satellite images of the Sedongpu glacier over time, using a process called remote sensing. They used the images to calculate ice volumes, glacier velocities, and glacier movement between 1961 and 2018, to determine the glacier’s long-term physical properties and how they changed over time. They found that from 1968 to 2013, the Sedongpu Glacier shrank, or retreated, by over 6 football fields. It also lost ice and water volume and increased its velocity.

The scientists also measured earthquake waves on the Earth’s surface, or seismicity, to characterize any downslope rock or debris movements caused by the glacial retreat. They measured seismicity across 11 different seismic stations within 580 kilometers (about 350 miles) of the glacier. Then, they used this data to identify 2 distinct phases of the CGHC event on Sedongpu Glacier: the ice-rock avalanche and the debris flow.

When the ice-rock avalanche occurred, the team detected noticeable increases in seismicity, suggesting it lasted over 30 seconds. During those 30 seconds, over 8 million cubic meters (more than 280 million cubic feet) of ice fell onto the main glacier. The team recorded even more increases in seismicity during the debris flow, which lasted nearly 5 minutes. The debris from the avalanche hit the main valley glacier at nearly 300 kilometers (200 miles) per hour.

The researchers combined these data to describe how the 2018 CGHC event unfolded. First, the backward movement and shrinkage of the glacier produced an unstable sheet of ice hanging over a cliff face. The steep slope and large cracks in the ice caused an ice-rock avalanche. Debris from the avalanche then accumulated on the main glacier, causing it to move faster. As the main valley glacier moved downslope, it picked up even more debris from the bottom and sides of the glacial valley. The melting ice also increased the glacier’s velocity, and its movement eventually transitioned into a debris flow, which obstructed the Yarlung Tsangpo River. 

In total, the CGHC event in the Sedongpu Glacier travelled over 10 kilometers (6 miles) and moved down in elevation for over 3 kilometers (about 2 miles) at a velocity of about 100 kilometers (about 70 miles) per hour. The glacier accumulated enough debris and ice to fill thousands of Olympic-sized swimming pools. Imagine what this could do to a nearby village!

It’s difficult for scientists to estimate when CGHC events will occur, but this team proposed several factors that could help predict them. These factors included the size of the ice-rock avalanche and the glacier velocity, as well as the occurrence of earthquakes, temperature changes, and the melting of the glacier’s underside. They stated that these factors can combine to create a domino effect that drives the CGHC process. They recommended consistent glacial monitoring as temperatures continue to climb, in the Himalayas and globally. 

The team concluded that understanding CGHC events can help scientists mitigate glacial hazards and keep people safe, especially in mountainous areas such as the Eastern Himalayas. They stated that their findings illustrate the dangerous processes behind glacial melting, but further research is needed to accurately assess those processes and ensure nearby communities remain safe.

The post Can melting ice increase glacial hazards? appeared first on Sciworthy.

In the Bolivian Altiplano, fewer Aymara farmers are relying on local weather knowledge to schedule farming tasks, like choosing the best dates to plant crops and predicting a frost or drought. At the same time, there is growing doubt about whether these traditional indicators remain relevant today in the context of rapid social, economic, and climatic changes. 

Farmers are struggling because the National Weather Service of Bolivia (SEHNAMI) fails to provide useful weather forecasts due to the geographical complexity of the Andes and a scarcity of weather stations. In addition, many farmers can’t access this information because SEHNAMI lacks local outreach programs to deliver reports directly to them. In a region with a weak technical forecasting system, local knowledge is a vital resource, but its use is declining.

Scientists in the past focused on preserving local weather knowledge or discussing how it might help communities adapt to climate change. However, very few researchers have scientifically validated local weather indicators, since doing so requires many years of historical meteorological data to establish statistical “skill” in local forecasting. 

Faced with this gap, researchers in the US and Bolivia recently set out to validate indigenous indicators in 2 Bolivian municipalities: Umala in the Central Altiplano and Ancoraimes in the Northern Altiplano. To do this, they paired each traditional weather sign with a measurable variable, like temperature, that could approximate it. This approach allowed them to directly compare traditional observations with scientific data.

The researchers wanted to determine whether traditional weather knowledge is still accurate and relevant under current conditions, since validating these methods would strengthen local knowledge and benefit the schools and policies that promote it. To test this, the researchers worked with 6 Aymara communities. First, they conducted workshops with local leaders and experts to compile a set of weather-forecast indicators. Then, they surveyed 95 farmers to rank the reliability of these indicators. 

Through discussions with these communities, the team identified 13 weather indicators in the Central region and 20 in the Northern region. These indicators included specific plants, animals, and physical factors like constellations or winds that the farmers used to decide when and where to plant crops, and to predict weather conditions for the next season. The researchers focused on 2 key indicators that the farmers ranked as most reliable: the presence or absence of moisture under rocks on the Fiesta de San Juan on June 24th, and the flowering patterns of specific plants, called Thola and Sank’ayu. The farmers used the San Juan indicator to predict whether the upcoming year would be rainy or dry, and the plants to determine the most favorable dates for planting to avoid agricultural risks like frosts.

Finally, the researchers compared forecasts based on these 2 signs with over 30 years of meteorological data from nearby weather stations. In both cases, they used the minimum daily temperature as the measurable way to represent these local signs scientifically. Their results showed that the minimum daily temperature on the Fiesta de San Juan could explain more than half (55.5%) of the changes in rainfall during the growing season. They also confirmed that severe frosts that “burned” Thola and Sank’ayuthe flowers were followed by periods without rain, validating the farmers’ strategy of delayed planting.

The researchers concluded that local weather indicators used by Aymara farmers are most reliable for seasonal planning, especially in predicting the start of the rainy season. They stated that this result helps legitimize traditional knowledge and empower the community. For example, these communities now hold regular meetings to discuss forecasts and share this information with their neighbors via WhatsApp groups. 

However, the team acknowledged that local knowledge was limited to short-term forecasting, as it only provided warnings a few hours in advance. Farmers need alerts several days in advance to effectively reduce their vulnerability to events such as frosts or hail. For this reason, the researchers suggested that the next step will be to co-produce forecasts by combining meteorological science with traditional knowledge.

The post Testing local weather knowledge in the Bolivian Altiplano appeared first on Sciworthy.

Macrobiological features have been cited as irreducibly complex, including animal joints and the trap mechanisms of carnivorous plants, even the cell itself.

Source

The first study of its kind shows that ecosystems experience far more cumulative heat than standard measurements reveal. A marine heatwave may have an official beginning and end, but the warm water affecting an ecosystem often does not. Like a pot that continues absorbing heat over time, coastal waters can remain unusually warm for weeks [...]

Bentham Science Launches Two New Journals to Accelerate Research in Wireless Communications and Engineering

Bentham Science Publishers has announced the launch of two new peer-reviewed journals designed to capture the rapid transformation of modern technology: Wireless and Communication Letters and Current Engineering Letters and Reviews. Both publications are now open for manuscript submissions, offering researchers an international platform to share emerging discoveries in communication systems, engineering technologies, and interdisciplinary innovation. The launches arrive as advances in artificial intelligence, sixth-generation wireless networks, satellite systems, advanced materials, and sustainable engineering continue to reshape scientific research and industrial development.

Wireless and Communication Letters is focused on the technologies that enable today’s increasingly connected world. The journal will publish original letters, full-length research articles, comprehensive reviews, mini-reviews, and guest-edited thematic issues addressing both theoretical developments and practical applications. Its scope covers the complete communication chain, from antennas and radio-frequency hardware to signal processing, network architecture, cybersecurity, and intelligent software. By emphasizing the efficient dissemination of research, the journal aims to provide a rapid channel for findings that could influence the next generation of wireless infrastructure.

The technical challenges addressed by the journal are central to the future of digital connectivity. Fifth-generation networks have already introduced high-speed mobile broadband, ultra-reliable low-latency communication, and massive machine-type connectivity, but researchers are now investigating 6G systems capable of supporting even greater data rates, extremely precise sensing, and seamless integration with artificial intelligence. These systems may combine terahertz frequencies, reconfigurable intelligent surfaces, distributed antennas, edge computing, and advanced machine-learning algorithms. Such technologies require new approaches to spectrum allocation, energy efficiency, network coordination, and data security.

The journal also welcomes research on the Internet of Things and machine-to-machine communication, areas in which billions of sensors and devices are expected to exchange data with minimal human intervention. In these environments, communication protocols must operate reliably despite limited power, unpredictable radio conditions, and enormous numbers of connected nodes. Research into low-power wide-area networks, intelligent scheduling, network virtualization, and secure device authentication could help support applications ranging from industrial automation and smart cities to remote healthcare and environmental monitoring.

A further component of the journal’s scope involves the physical science of communication. Antenna design, electromagnetic propagation, microwave engineering, optical links, and satellite communication determine how information travels through real environments. Engineers must account for obstacles, atmospheric conditions, interference, polarization, bandwidth limitations, and the movement of users or spacecraft. Developments in compact antennas, beamforming, optical wireless communication, and satellite-terrestrial integration could improve connectivity in rural regions, disaster zones, transportation systems, and future space missions.

Wireless and Communication Letters is led by Editor-in-Chief Dr. Nasimuddin of the Antenna and Optical Department at the Institute for Infocomm Research in Singapore. Supported by an international editorial board, the journal states that it will apply a rigorous and objective peer-review process. This is particularly important in a field where theoretical claims must often be tested through simulations, prototypes, channel measurements, or performance comparisons. Research involving modulation, coding, information theory, cognitive radio, software-defined networking, artificial intelligence, privacy, and communication protocols will be considered within the journal’s broad technological remit.

Alongside the communications title, Bentham Science has introduced Current Engineering Letters and Reviews, an interdisciplinary journal intended to connect research across the full spectrum of engineering sciences. Announced on 3 August 2026, the journal will publish research articles, short communications, comprehensive reviews, mini-reviews, and thematic issues. Its mission is to bring together discoveries that are often separated into specialist fields, reflecting the reality that many modern technologies emerge from collaboration among mechanical, electrical, materials, chemical, biomedical, environmental, and computer engineers.

The new engineering journal will cover aerospace, civil, structural, transportation, manufacturing, energy, robotics, automation, nanotechnology, artificial intelligence, and digital engineering. It will also address sustainable engineering, renewable energy systems, smart materials, advanced manufacturing, and biomedical technologies. These subjects are increasingly connected: an electric vehicle, for example, depends simultaneously on materials science, power electronics, software, communications, manufacturing, and transportation engineering. An interdisciplinary publication can provide a forum for examining such systems as integrated technological platforms rather than isolated components.

The scientific importance of this approach is becoming more visible as engineers confront challenges involving climate change, resource efficiency, resilient infrastructure, and automation. Renewable energy systems require improved storage, power conversion, and grid management; smart materials can respond to changes in temperature, pressure, or electromagnetic fields; and artificial intelligence can optimize industrial processes by identifying patterns in large streams of sensor data. At the same time, engineering research must demonstrate reliability, scalability, safety, and economic feasibility if laboratory innovations are to produce measurable benefits in society and industry.

Both journals invite contributions from researchers, engineers, scientists, academics, and industry professionals worldwide. Bentham Science says that information about open-access policies, article processing charges, waiver eligibility, editorial policies, and complaints and appeals procedures is available through the respective journal websites. With their emphasis on rapid communication, technical rigor, and interdisciplinary exchange, the two publications seek to become new hubs for research at the intersection of connectivity, intelligent systems, sustainable technology, and engineering innovation.

Subject of Research: Wireless communications, communication engineering, interdisciplinary engineering research, emerging technologies, artificial intelligence, sustainable engineering, and advanced technological systems.

Article Title: Bentham Science Launches Two New Journals to Accelerate Research in Wireless Communications and Engineering

News Publication Date: 3 August 2026 (for the announcement of Current Engineering Letters and Reviews; no publication date is provided for Wireless and Communication Letters).

Keywords

Wireless communications, 5G, 6G, Internet of Things, satellite communications, antenna design, signal processing, artificial intelligence, engineering research, sustainable engineering, robotics, renewable energy, smart materials, advanced manufacturing.

Microsoft said that it’s planning to optimize Windows 11 for systems with 8GB of RAM and above as part of its promise to improve Windows 11 in March 2026. The company said in its latest update that the optimization is part of expanding its focus on operating system upgrades, which include a faster out-of-the-box experience, easier parental controls, and improved voice interactions.

Go deeper with TH Premium: AI shortages

• AI data centers are swallowing the world's memory and storage supply
• Chip scarcity assaults auto industry amid the worsening Nexperia and DRAM crisis
• Samsung and SK hynix shorten memory contracts as pricing power shifts back to suppliers
• Memory makers are set to earn $551 billion from the AI boom

While the official minimum specifications for Windows 11 sit at just 4GB of RAM, most PC builders advise getting at least 16GB if you want to have a smooth experience. In fact, Microsoft has previously recommended 32GB of RAM for Windows 11 for gamers, especially if they want a system that can handle games in the near future. Unfortunately, the RAMpocalypse has forced both users and manufacturers to stick with slower DDR4 memory and lower capacities. Some experts predict that the entry-level PC will disappear by 2028, and we’ve even seen some manufacturers, including Apple, reintroduce 8GB laptops just to hit a specific price point.

The resurgence of 8GB systems will likely deliver a bad experience for users who stick with Windows 11, which is the likely reason why Microsoft is pushing for the optimization of its operating system. If Windows 11 performs poorly on these systems, it could draw users towards macOS or Linux alternatives as they blame the operating system for underperforming on limited hardware. In fact, we’ve already seen this happen before — after Microsoft ended support for Windows 10, MacBooks saw an uptick in sales as users migrated towards macOS instead of going for Windows 11. SteamOS is also encouraging some gamers to ditch Windows, and Valve is working on a general release for the OS, which many say contains less bloat and is a bit snappier than what Microsoft offers.

The RAM shortage crisis, alongside increasing competition, is forcing Microsoft to do better with Windows 11. Hopefully, these optimizations arrive sooner and don’t introduce new bugs, allowing both new and existing users to get more out of their systems.

The Windows blog post also gave an update on what improvements the company has made to Windows 11 so far. This includes a better Windows Search experience, more Taskbar and Start customizations, a more responsive and reliable File Explorer, among others. Many of these changes are still in preview, though, so unless you’re part of the Windows Insider Program, you’ll have to wait a few more weeks to months before you can start enjoying these changes.

The Steam Machine helped grow the popularity of Linux gaming, including installations of Bazzite and other gaming-oriented Linux distributions. Valve seemingly doesn't want to stop its open-source development efforts anytime soon, and is now working on a port of the Mesa Radeon Vulkan driver (RADV) to Windows; It's already running Counter-Strike 2, according to developers at Collabora.

As cross-platform development is rather tricky, Valve opted to get a port of RADV to Windows going by way of sponsoring contractors at Collabora. In its blog post, Collabora explained the several hoops it had to jump through to accomplish this task.

With Windows 10 and WDDM 2.0, Microsoft improved the split between graphics drivers' userspace code (the vast majority of the driver itself) and the kernel-level portion that actually talks to the graphics card. This presented the opportunity to hook RADV to the AMD kernel card driver. That's easier said than done, however, as communication between those parts often carries non-standardized data that RADV needs to understand. And to understand the "conversation," it needs to be recorded and analyzed.

An earlier 2024 effort by Faith Ekstrand yielded a basic-but-valuable utility for logging WDDM 2.0 calls and reverse-engineering them to produce a basic RADV implementation. Out of both debugging necessity and as a development tool, Collabora built and expanded upon Ekstrand's work, improving the logger to the point where it can now fully analyze any Vulkan application that runs with AMD's official driver and dump all the data passing to the kernel.

After a lot of work getting to grips with how the AMD driver interacts with the kernel driver, including but not limited to reverse-engineering obscure data structures, the team made progress, and Windows RADV is now able to run some games, including Counter-Strike 2.

Despite the ongoing effort, Collabora explains that since user- and kernel-space driver are a matched pair, changes to those aren't guaranteed to be backwards-compatible, meaning that even a fully functional RADV could break at any point. For that reason, Collobora is requesting that AMD, Microsoft, or both provide a documented interface to the kernel driver or an intermediary compatibility layer.

AMD graphics driver development on Linux has coalesced around the Mesa Vulkan stack, with both company and community devs contributing to the RADV project. Over in the Windows world, the only option is AMD's proprietary driver, which can cause a lot of headaches when developing cross-platform games and applications.

AMD's Vulkan driver for Windows has developed a reputation for instability. Meanwhile, Linux RADV is generally praised for its stability and performance, sometimes running faster than the AMD Windows driver, especially on older cards. With a rapid development schedule, it also generally sees fixes and speed upticks often.

If at some point using RADV on Windows becomes viable, you'd be getting an arguably more stable, mature driver with active development. Games' graphical issues could become far easier to debug and patch thanks to the open nature of RADV, and studios developing with Linux in mind can target the one platform instead of two with different behaviors. Any developer or company can contribute to the project, too.

Furthermore, this lets Valve improve Windows compatibility layers, and any optimizations can be carried over to both operating systems. All told, this is likely one of the several moving parts to improve Linux — thus the Steam Deck, Steam Machine, and upcoming hardware — as a viable gaming platform. Even a future notion of gamers installing RADV on Windows to get a performance or stability boost isn't too far-fetched.

Additionally, RADV on Windows would also help keep discontinued cards usable, and given pricing right now, that certainly would be a good thing.