Progression

SUMMARYValve has released a Steam Client beta for Linux that moves the client to 64-bit architecture and places it in a containerized Steam Runtime environment. The update still requires 32-bit libraries and graphics drivers for compatibility, along with Linux kernel 5.6 or newer and glibc 2.31 or newer. Steam Achievement Sets, letting developers organize achievements into separate groups for base games, DLCs, and seasonal content.

Valve has released a new Steam Client beta that finally moves the Linux client to 64-bit architecture, while also placing it inside a containerized Steam Runtime environment. However, Linux users still need 32-bit libraries and graphics drivers for compatibility, meaning fully 64-bit-only systems remain unsupported. VideoCardz.com reports: Valve's updated requirements explicitly state that 64-bit-only installations are not supported. Systems must still provide both 32-bit and 64-bit libraries and graphics drivers, including multilib support. The new client also requires Linux kernel 5.6 or newer and glibc 2.31 or newer.

The update also introduces Steam Achievement Sets, a feature we covered earlier that allows developers to organize achievements into separate groups for base games, DLCs and seasonal content. Players can complete individual sets without losing their existing completion status when developers add more achievements. Valve has also updated the achievements page to display progress across these groups.

The 64-bit Linux client and Achievement Sets are currently available through the Steam Client Beta. Valve has not confirmed when these changes will reach the stable Linux release. Until then, users on the regular Steam client will continue using the existing architecture.

Amulya Vishwanath, who spent seven years leading product marketing for NVIDIA’s robotics platforms, says robotics is currently in its “Lego era,” with the basic building blocks like actuators, robotic hands, software, and safety standards still being rebuilt. This view runs counter to those who believe that robotics, powered by a general foundation model, is about to have […]

Amulya Vishwanath, who spent seven years leading product marketing for NVIDIA’s robotics platforms, says robotics is currently in its “Lego era,” with the basic building blocks like actuators, robotic hands, software, and safety standards still being rebuilt. This view runs counter to those who believe that robotics, powered by a general foundation model, is about to have […]

SUMMARYKendall Square Association held its 18th annual meeting at The Engine in Cambridge, Massachusetts, bringing together business leaders, officials, residents, and students to discuss innovation and community. MIT economist Daron Acemoglu spoke about artificial intelligence as a tool to expand workers’ capabilities and about the need to strengthen liberal democracy. Cambridge Mayor Sumbul Siddiqui and Broad Institute chief communications officer Lee McGuire also reflected on the collaboration that helped make Kendall Square a major life science and technology hub.

Daron Acemoglu speaks on stage with Aisha Losche. “I believe liberal democratic institutions, together with the norms that support them, are one of the greatest human achievements,” he said.
Credit: Flavio D Photography
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Daron Acemoglu speaks on stage with Aisha Losche. “I believe liberal democratic institutions, together with the norms that support them, are one of the greatest human achievements,” he said.

Kendall Square in Cambridge, Massachusetts, is often cited as the most innovative square mile in the world. But when the Kendall Square Association gathered local stakeholders for its 18th Annual Meeting Thursday, the conversation focused on innovation primarily in the context of community.

The event, which took place at the nonprofit startup incubator The Engine, attracted people from across Cambridge, including business leaders, elected officials, local residents, and students, for a night of local food and conversation about the advance of technologies like artificial intelligence and what they mean for society.

“How can we make AI not an enemy of work, but a tool for workers to expand their capabilities and build new expertise or do new things?” asked MIT Institute Professor Daron Acemoglu in a keynote talk. “The world is at a point in time where we need new innovations and new adaptations to growing challenges.”

Acemoglu’s keynote was one of several presentations at the event, which also featured music from the Kendall Square Orchestra, a vote on new KSA board members, and awards for organizations making a positive impact through innovation.

KSA is a nonprofit made up of over 150 organizations across Kendall Square, from major companies to universities, research organizations, and the independent shops and restaurants that give Kendall Square its distinct character.

“People come to Kendall Square to make the world better,” said KSA Executive Director Beth O’Neill Maloney in her opening remarks. “People come here to improve the human condition, people come here to solve big problems, and people come here to innovate for good.”

Acemoglu, who shared the Nobel Prize in economics in 2024 for his work studying how institutions affect prosperity, spoke on the subject of his new book, “What Happened to Liberal Democracy?”

Acemoglu says liberal democracy is under siege as trust in liberal institutions decline, political polarization rises, and people lose faith in elected officials. He acknowledged that the shared prosperity liberal democracy promised has not always been delivered, especially over the last 50 years, but insisted it is the best path forward and in need of renewed support.

“I believe liberal democratic institutions, together with the norms that support them, are one of the greatest human achievements,” Acemoglu said. “It would be unthinkable for people who lived 300 years ago that we could live in societies consisting of hundreds of millions of people with diverse interests, different views, doing different things, and people still participate in politics and reach compromises, and we have state institutions that, by and large, actually provide services and do things for the people, and that we build opportunities for prosperity from which most people benefit while social freedoms are largely upheld.”

Cambridge Mayor Sumbul Siddiqui also spoke at the event. Siddiqui began her talk by telling the story of Cambridge residents working with biotech labs in the 1970s to create a groundbreaking policy on recombinant DNA research, which helped turn Kendall Square into the life science hub it is today.

“All these years later I think that story captures what makes Kendall Square so special: It’s our willingness to work together even when we face big challenges,” Siddiqui said. “It isn’t just the universities or labs, it’s also the culture of collaboration among nonprofits, governments, and residents.”

Broad Institute Chief Communications Officer Lee McGuire started his talk by reviewing a 2009 report on what made Kendall Square such a powerful driver of innovation, noting that factors like talent density, education, and a collective voice remain strong in the area today.

“This report was brilliant in that it captures so many of the special things that matter for a place like Kendall,” McGuire said. “It is the job of the Kendall Square Association and all of us to help protect those things, make sure we name them, understand them, and see them as essential elements of making sure this community stays what it is no matter what happens. As long as there’s a good idea, this is the place that’s going to get that idea moving and scale it up to change the world.”

SUMMARYKDE Plasma 6.8 is now available, coinciding with the 30th anniversary of the KDE project. The desktop release adds vRAM usage optimizations, Wayland improvements, better remote desktop support, multi-GPU handling, and new tools such as kscreenctl. KDE also released a free documentary on YouTube about the open source community behind the desktop environment.

An anonymous reader quotes a report from Phoronix: The feature-packed and polished Plasma 6.8 KDE desktop is now available. Making this release all the more special is that it coincides with the 30th anniversary of the KDE project. KDE Plasma 6.8 ships many exciting improvements including vRAM usage optimizations, dwell clicker support on Wayland, Wayland commit-timing protocol support for KWin, improvements for the Union theme engine, better remote desktop support, multi-GPU handling improvements, the new kscreenctl tool, server-side drop shadow support, multi-monitor improvements, and a lot of other polishing throughout. Especially from the Wayland angle there has been a lot of polishing and fine tuning for Plasma 6.8. Accompanying the release is a new film, The KDE Documentary, which "tells the story of the pioneering open source community that gave computer users a free and open alternative to proprietary desktops like Windows." The documentary is available to stream for free on YouTube.

RTX Spark versions of the HP OmniBook Ultra (left), an Asus ProArt P16 (center), and a Lenovo Yoga 9n (right) on a dark gray table against a green-illuminated backdrop.
Photo: Antonio G. Di Benedetto / The Verge
Nvidia’s new SoC is available in Windows laptops from six different manufacturers. We’ve collectively tested four of them so far. | Photo: Antonio G. Di Benedetto / The Verge

Nvidia's RTX Spark N1X processor is finally here, and we've been collectively testing a small fortune's worth of powerful laptops sporting this new "superchip." RTX Spark is designed to be a high-performing Arm-based SoC for laptops and small desktop computers, rivaling the best from Apple, Intel, AMD, and Qualcomm. It has loads of cores, Nvidia RTX Blackwell graphics, and enough power and unified memory to run sizable local AI models.

The flagship placement is inside Microsoft's Surface Laptop Ultra with a staggering 128GB of unified memory, which our own Tom Warren fully reviewed. Sean Hollister has been testing a 64GB version of the Asus …

Read the full story at The Verge.

He Wants AI Benchmarking To Be a Science, Not a Dark Artquantamagazine.org

Benchmarks are the rulers of AI, in both senses of the word. As measuring sticks, they work according to an extremely simple logic: If you want to know what an AI model can do, devise a standardized test to gauge it. But AI benchmarks can also dominate the behavior of the entire field. In 1987, the Defense Advanced Research Projects Agency's first benchmark on automatic speech-to-text…

Source

Doomsday clock close to midnight with ASCII graphic.
Image: Cath Virginia / The Verge, Getty Images

An important change will soon be made to global timekeeping that aims to prevent potential infrastructure failures akin to the Y2K bug scare. On Thursday, the International Bureau of Weights and Measures (BIPM) voted to scrap the leap second, an ad hoc time adjustment that's occasionally added so tracked time standards mirror the Earth's real (and inconsistent) rotation.

BIPM members previously agreed in 2022 to cease using leap seconds on or before 2035, but this is now being expedited to take effect on May 20th next year, aligning with World Metrology Day. There's an unprecedented reason for its retirement being brought forward: changes t …

Read the full story at The Verge.

SUMMARYThe Prima system combines a retinal implant with camera-equipped glasses to help people with advanced age-related macular degeneration regain useful vision. Approved in Europe in July and awaiting FDA clearance in the United States, the device has enabled more than 80% of recipients to read, do crosswords, and use their phones after training. Developed by California-based Science Corporation, it replaces damaged photoreceptors by sending visual information through healthy retinal circuitry to the brain.

More than 5 million people around the world with age-related macular degeneration (AMD) experience atrophy in their retinas. And until now, no treatment could restore their vision. The PRIMA system, which was approved in Europe in July and is awaiting FDA clearance in the US, changes that. It combines a retinal implant with camera-­equipped eyeglasses to improve sight in patients who develop a blind spot in the middle of their vision due to advanced AMD. After training sessions, more than 80% of recipients were able to read, do crosswords, and use their phones.

""
BROWN BIRD DESIGN
The retina processes light in three layers of cells: Photoreceptors convert light into electricity, bipolar cells process that signal, and ganglion cells transmit the signal to the optic nerve and the brain. PRIMA replaces the photoreceptors.

Developed by the California-based Science Corporation, the system takes advantage of the fact that AMD doesn’t damage all retinal circuitry; only photoreceptors—the cells that convert light into an electrical signal—die off. PRIMA’s implant mimics those cells and transmits visual information directly to healthy eye circuitry and on to the brain. “We’re leveraging all of the body’s own natural functions to process and transmit the information,” says Frank Brodie, an ophthalmologist at the University of California, San Francisco, and Science Corp.’s chief medical officer for ophthalmology.

BROWN BIRD DESIGN

CAPTURE

Glasses outfitted with a miniature front-facing camera capture what someone is seeing in real time. The video feed is roughly five megapixels running at 30 frames per second, which is similar to TV. The raw video is transmitted to a connected processor via a fiber-optic cable.

CONVERT

A small, handheld processor, which can be set on a table or tucked in a pocket, converts the video feed into infrared light signals that route back to the glasses. The device also includes physical buttons that let the wearer adjust contrast, brightness, and zoom.

BROWN BIRD DESIGN

DISPLAY

A laser projector on the glasses faces the wearer and shines pulses of near-infrared light directly at the eye at 880 nanometers—an invisible wavelength. This signal passes through the pupil and on to the retinal implant in the back of the eye.

SEE

The implant is made up of 378 pixels, each with an electrode and two photovoltaic cells, which do double duty. They convert the light into a current that healthy bipolar and ganglion cells pass on to the brain. They also act as solar cells to power the chip, eliminating the need for a battery.

Update: This story has been updated to clarify the specific cases of AMD the PRIMA system treats.

Linda Marsa is a former Los Angeles Times reporter and an author who covers medicine, health, science, and the environment.

Ubuntu 26.10 ReleasedSlashdot

SUMMARYUbuntu 26.10, codenamed Stonking Stingray, was released with the upcoming Linux 7.3 kernel series, GNOME 51, and 100% Rust coreutils. The update adds TPM-backed full disk encryption on systems without a hardware root of trust, new Settings information about Ubuntu certification, and App Center improvements for package details, drivers, and one-time codec installs. It also includes the locally processed Myna speech-to-text tool, controls for disabling Ubuntu Insights data collection, and better Microsoft Entra ID integration, with updates supported through July 2027.

prisoninmate shares a report from 9to5Linux: Ubuntu 26.10 (Stonking Stingray) has been released today, and it is now available for download for those eager to update their Ubuntu systems to a newer release. Powered by the upcoming Linux 7.3 kernel series, Ubuntu 26.10 ships with the latest GNOME 51 desktop environment, TPM-backed full disk encryption (FDE) support on computers without a hardware root of trust, updated Settings to show whether a computer is certified for Ubuntu, and 100% Rust coreutils.

There are several App Center enhancements in Ubuntu 26.10, such as a unified app-details view for Snap and Debian packages, a dedicated Drivers page where you can review the available graphics drivers, including NVIDIA driver branches, and support for installing codecs for one-time playback when a media file uses a codec that's not installed.' Other additions include an optional, locally processed AI-powered speech-to-text tool called Myna, system-wide controls for disabling Ubuntu Insights data collection, and better integration with Microsoft Entra ID. Also worth mentioning are the security and software updates that will be available for nine months, through July 2027.

SUMMARYIt also found that AI is increasingly used in sustainability work, with 78 percent of North American organizations using it and 87 percent of adopters reporting positive impact, including reduced waste, lower energy use, and better supplier emissions data. At the same time, many companies still lack formal governance structures and long-term emissions planning, limiting progress despite rising commitment.

In the 2026 State of Supply Chain Sustainability report, 83 percent of respondents rate sustainability as important or very important to long-term business success, the highest level in the reports seven-year history. But commitment is not the same as capacity.
Photo: Adobe Stock
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In the 2026 State of Supply Chain Sustainability report, 83 percent of respondents rate sustainability as important or very important to long-term business success, the highest level in the report's seven-year history. But commitment is not the same as capacity.

When corporate leaders discuss climate strategy, the message that still dominates is that, despite competing priorities and external pressures, sustainability matters.

According to the 2026 State of Supply Chain Sustainability Report from the MIT Sustainable Supply Chain Lab, which surveyed 1,810 supply chain professionals across 91 countries, 83 percent rate sustainability as important or very important to long-term business success, the highest level in the report's seven-year history.

But commitment, the report reveals, is not the same as capacity. While 59 percent of respondents report becoming more committed to sustainability following recent U.S. policy shifts that deprioritize environmental concerns, the same organizations are being forced to compromise those commitments. Sixty-eight percent report that tariff uncertainty has compelled them to delay, scale back, or abandon sustainability strategies. Nearly one-third have seen tariff-related disruptions actually increase their operational emissions.

"Commitment is strong, measurement is expanding, and AI is accelerating," says Sreedevi Rajagopalan, director of the MIT Sustainable Supply Chain Lab and lead author of the report. "What comes next is harder: converting commitment into accountability, operational integration into strategic decision-making, and incremental decarbonization into genuine transition."

The result is a supply chain sustainability agenda stuck between conviction and constraint.

Beyond tariffs, more than eight in 10 respondents across North America, Europe, and Asia agree that ongoing geopolitical conflict is reducing the effectiveness of their organization’s climate action. Organizations built decarbonization plans on assumptions of stable trade and relative peace, yet neither assumption is holding.

The external disruption reveals an internal vulnerability. Among companies with publicly stated sustainability goals, only 51 percent have established a formal cross-functional sustainability team, which is the governance structure most strongly associated with embedding sustainability into daily decisions. In addition, only 33 percent place sustainability oversight at the board level. Public ambition, in other words, is vastly outrunning internal accountability infrastructure. Companies with formal cross-functional teams report sustainability is "frequently or always" built into decisions 57 percent of the time. Where responsibility sits in a single function, that drops to 13 percent — a 44-point gap illustrating the return on governance investment.

Sustainability is embedding most deeply where companies make daily operational choices: transportation and logistics (39 percent), procurement (35 percent), warehousing (34 percent), and product design (33 percent). However, it thins out dramatically in decisions that lock in long-term emissions: capital investment, network design, and supply chain risk planning. This reveals that companies are becoming better at operating more sustainably, but not at designing sustainable supply chains in the long term.

The artificial intelligence story compounds this tension. Seventy-eight percent of North American organizations report current use of AI in sustainability initiatives, and 87 percent of adopters report positive impact on sustainability goals. Eighty-six percent have reduced material waste, 81 percent have reduced energy use, and 63 percent use AI to estimate missing supplier emissions data. However, among mature agentic AI users, only 53 percent report a reduction in total greenhouse gas emissions. Twenty-nine percent report an increase, suggesting that operational efficiency does not automatically translate into lower net emissions.

This tension is particularly visible in warehousing. Among advanced and fully automated warehouses using AI, 78 percent report higher energy use since implementing AI, and 76 percent report higher waste, yet only 24 percent use AI-driven real-time monitoring to track environmental consequences. Many organizations may not realize their energy footprint is climbing until well after implementation.

Another key area of the report is freight transportation. Nearly every freight company is reducing emissions through route optimization, load consolidation, and driver-behavior programs. However, 43 percent of fleets still operate mostly or entirely on conventional diesel and only 8 percent have completed a full transition to low-emission energy. The divergence between regions reveals why: In Europe, 84 percent of freight companies report that recent policy changes have positively affected decarbonization strategy. In North America, only 44 percent do. When policy signals are unclear, capital-intensive technology transitions stall. For example, battery-electric vehicles are at scale in 60 percent of European companies, but only 36 percent in North America.

The report reveals that one bright spot has emerged in Scope 3, or indirect, emissions collaboration. Participation in joint supplier engagement and decarbonization programs surged from 31 to 58 percent in a single year. In addition, partnerships to manage shared suppliers' emissions more than doubled, from 23 to 55 percent. The share working entirely alone collapsed from 18 to 6 percent. The report, supported by the C.H. Robinson Foundation, Breakthrough, and CO2 AI and Dassault Systèmes, reveals that companies are recognizing that Scope 3 cannot be solved in isolation.

Across all these areas, the consistent pattern the report reveals is that corporate commitment is not the prevailing constraint to ongoing sustainability efforts. Rather, governance, accountability structures, technology infrastructure, and measurement capabilities are the current obstacles. Organizations that close the external gap by building resilience against disruption and the internal gap by hard-wiring accountability into structure will be the ones whose commitments survive. Those that do not will find that ambition without accountability moves the needle very little.

SUMMARYMIT and Whitehead Institute researchers developed IRIS, a machine learning model that identifies signaling pathway “fingerprints” in gene activity and predicts which signals cells received during development. Trained on human embryonic stem cell data and tested in mouse embryos, the system accurately inferred pathways guiding heart, gut, muscle, spinal cord, and lung development. The findings, published in Nature Methods on Sept. 8, could improve stem cell engineering, organoid models, and disease research.

The developing branching lung in an in vitro culture system
Image: Miram Meziane/Whitehead Institute
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The developing branching lung in an in vitro culture system

As an embryo develops from a small cluster of stem cells, those once “blank slate” cells begin to take on more specialized roles like brain, liver, or muscle cells, and organize themselves into three-dimensional structures such as tissues and organs.

The fate of each cell — what type of specialized cell it will become — depends on which genes are turned on or off in the cell. These patterns of gene activity shape the cell’s structure and function, enabling it to take on a specific role in the body.

But this decision isn’t up to individual cells. They constantly send and receive chemical signals to and from neighboring cells, which help them understand where they are, what stage of development they are in, and what they should become. These messages spread through multi-step sequences called signaling pathways, which translate external signals into specific changes in gene activity in the cell.

For researchers, being able to retrace the sequence of instructions a cell has received would offer a powerful way to understand how tissues develop and how these processes go awry in disease.

But this has been difficult to achieve because scientists have long assumed that the effects of signaling pathways vary widely across cell types, meaning they would need to map each pathway separately in each cell type — an arduous and painstaking process.

Now, in a new study led by MIT assistant professor of biology and Whitehead Institute for Biomedical Research member Pulin Li and graduate student Nicholas Hutchins, researchers have discovered that each signaling pathway leaves behind a unique “fingerprint” — a distinctive pattern of gene activity that reflects the particular signals the cell has encountered.

Importantly, these fingerprints are consistent across different cell types for the same signaling pathway, which means that instead of mapping each cell type separately, scientists can reconstruct signaling histories across many cell types using these pathway-specific fingerprints.

This discovery was made possible through a machine learning model called IRIS. This model can detect fingerprints of different signaling pathways and pinpoint which signals a cell received at different stages of development inside an embryo, even for cell types it hasn’t encountered before.

This artificial intelligence-driven approach marks a major advance over traditional methods, which require researchers to experimentally test every pathway in every possible cell type, and opens up the possibility to comprehensively map the signaling histories of every cell inside a mouse or human embryo at an unprecedented scale.

“Think of voice recognition systems like Siri, which are trained mainly in English, but then use that training to help them recognize other languages,” says Li. “This is called transfer learning, and this is why IRIS can work across many different cell types.”

The researchers’ detailed open-access findings, published in the journal Nature Methods on Sept. 8, could accelerate stem cell engineering for regenerative medicine and improve the creation of organoids — miniature, 3D models that mimic real organs — for studying disease mechanisms and testing new drugs. This is because once researchers learn the pattern of signals that drives a stem cell to become a specific cell type, they can recreate those signals to control the fate of stem cells in a lab or medical setting.

IRIS is a neural network-based model, which, in essence, is an AI-driven system designed to recognize patterns in complex data, similar to how our brains spot patterns. It examines a cell’s overall gene activity and estimates which signaling pathways were likely “on” at specific times during development.

Li and Hutchins trained IRIS on a large experimental dataset that measured how thousands of human embryonic stem cells responded to dozens of combinations of six major signaling pathways at multiple stages of development. This created a comprehensive map, or atlas, of how signaling combinations influence cell behavior.

The team then tested IRIS using single cells from mouse embryos during gastrulation, a stage when cells are rapidly branching into different fates. IRIS could accurately predict when and where specific signaling pathways would activate in cells destined to become part of heart, gut, muscle, and spinal cord tissue. This variation in signaling molecules is what guides cells to form the right structures in the right places.

With this approach, scientists can not only begin to understand the fundamentals of cell-to-cell communication, but also gain a practical roadmap for guiding stem cells into specific, functional cell types in the lab.

When the researchers employed IRIS to identify signals needed to create a cell type critical for lung development, the model predicted that activating a specific signaling pathway would encourage lung-specific development. Experiments in mouse embryos confirmed the model’s prediction. By identifying the precise combinations of signals that drive lung cell development, they can more reliably generate accurate, lab-grown models of lung tissue.

“In these ways, IRIS is helping us decode the language cells use to talk to each other at a much faster rate than we could realistically achieve through experiments,” Hutchins says.

These improved models would allow researchers to study diseases like asthma, lung cancer, and pulmonary fibrosis, in which lung tissue becomes scarred, often without a known cause. They can then use these models to test potential therapies, and ultimately design regenerative treatments that can repair the damaged tissue.

Bluesky's Attie AI tool, which initially launched earlier this year as a way to use AI to build your own feeds, now lets you make "small" social apps like games, polls, and dashboards that you can then share with others as their own websites. In an interview at TechCrunch Disrupt, Bluesky CEO Toni Schneider said to think of Attie as "social vibe coding or vibe coding for your community."

You can make your own Attie app by typing in a prompt. A simple poll I made about Pokémon Red and Pokémon Blue took a few minutes to generate. If you want to check out something more full-featured, the Attie website currently highlights a few examples l …

Read the full story at The Verge.

SUMMARYMeta released Muse Spark Open, an 816-billion-parameter open-weight model designed to run locally on two Apple Mac Studio systems using the MLX framework. The model has 42 billion active parameters, a 1 million-token context window, and is aimed at coding, agentic work, multi-step reasoning, and software engineering. Apple has not yet shipped the 512GB Mac Studio, which Meta says can help make the pair function like a supercomputer with roughly a terabyte of unified memory.

Meta has released Muse Spark Open, an 816-billion-parameter open-weight model optimized to run locally across two 512GB M5 Ultra Mac Studios using Apple's MLX framework. Meta says it's the "most capable U.S. open-weight model to date." MacRumors reports: Muse Spark Open has 816 billion total parameters with 42 billion active parameters and a 1 million-token context window. It is meant for coding and agentic work, and Meta says it excels at extended tasks, multi-step reasoning, and software engineering. The new Muse model was tuned to run on Mac Studio, and Meta says the Mac Studio paired with Muse Spark Open is the "best way to run a powerful model on your own desktop."

From Meta: "Apple's unified memory architecture lets the M5 Ultra's integrated GPU use up to 512 GB per Mac Studio, so two machines can hold an entire model. And the chip's 1.2 TB/s of memory bandwidth is fast enough to read the small slice each token needs. The result is two Mac Studios behave like one supercomputer with a terabyte of unified memory." Apple hasn't released the 512GB Mac Studio as of yet, but it's supposed to be coming later this month. It won't be cheap, because the 256GB Mac Studio is already priced over $10,000.

SUMMARYResearchers at Columbia University found that microplastics may generate reactive oxygen species on their own, challenging the assumption that plastic particles are chemically inert. The work, published in Nature, builds on microdroplet chemistry experiments showing that tiny water droplets can produce harmful oxygen-containing molecules that damage DNA, proteins, and lipids.

Bottled water is displayed for sale at a Randalls grocery store on January 10, 2024 in Austin, Texas.
Brandon Bell/Getty Images
arstechnica.com
Bottled water is displayed for sale at a Randalls grocery store on January 10, 2024 in Austin, Texas.

One reason plastics are used so often is that they’re chemically inert, meaning bags, food containers, and cups don't react with what we put in them. Yet they can still break down into microplastics, which turn up in drinking water, human blood, arteries, and brains. The consequences of that are uncertain.

“Whether microplastics can directly cause human disease is still being researched,” said Wei Min, a chemist at Columbia University. In a new Nature study, Min's team took a step toward answering this question by demonstrating that microplastics are likely not as chemically inert as we might expect.

Microdroplet chemistry

Min's lab has spent years working on microdroplet chemistry, studying how water broken into tiny droplets behaves at its boundary with air. These droplets have been reported to generate reactive oxygen species, or ROS, a family of harmful, oxygen-containing molecules. “ROS will essentially bump into proteins, lipids, DNA, and cause damage,” Min said. “You could break a DNA strand into segments. You could mutate DNA; you could misfold proteins.”

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SUMMARYMicrosoft says recent Windows 11 updates improve responsiveness by up to 20% through better memory management and reduced background resource use. On PCs with 8GB of RAM or less, the changes keep more active data in memory, make Widgets load only when opened, and free over 200 MB for apps. Microsoft also sped up Windows Hello, improved Bluetooth pairing, and is testing a faster Windows Search experience for broader release later this year.

Microsoft says recent Windows 11 updates have made the operating system up to 20% more responsive by improving memory management and reducing background resource use. "A big part of that work is making smarter use of memory and system resources," says Navjot Virk, corporate vice president of Windows experiences at Microsoft. "We've improved memory management and efficiency across Windows to help keep more of your PC's resources focused on what you're actively doing." The Verge reports: The improvements to memory management now make a "meaningful difference" on PCs with just 8GB of RAM. "Windows can now keep up to 2GB more of your active data in memory instead of moving it to slower storage," says Virk. "For example, on PCs with 8GB of memory or less, Widgets load only when you open them, making more than 200 MB of memory available for your apps and other work."

Microsoft has also made Windows Update less disruptive, cleaned up the Widgets section, and finally allowed the taskbar to be repositioned to the sides or top of a display. Windows Hello sign-in has also been sped up, and Bluetooth pairing is more reliable, "including an AirPods pairing experience that's up to 15 seconds faster."

The next big step is a new Windows Search experience that's a lot faster and more capable. [...] It's currently available for Windows Insiders, and Microsoft says it will "roll out more broadly later this year."

SUMMARYAnthropic has begun giving a METR team employee-like access to its internal tools, office space, and safety information so the nonprofit can evaluate frontier AI model risks and publish its findings. The company said METR will assess incidents and practices under enforceable redaction rules, while SecureBio, Accenture, Faculty, and other groups are taking on more limited evaluator roles in separate partnerships.

Last month, we committed to stronger independent, third-party assessment of our models and safety practices. We also signed the White House Accord on Super Intelligence, in which companies pledged to partner with independent external auditors or evaluators. Today, we’re announcing that we’ve started to give employee-like access to a team from METR, a nonprofit that evaluates frontier AI models.

METR will publish the results of its risk assessments. Over the past year, we’ve worked with METR on several reviews of our Risk Reports. We’re also working with SecureBio and Accenture as evaluators, and are in early discussions with several other organizations, including Hugging Face.

Here, we explain our approach to working with evaluators.

Why we work with independent evaluators

As models have become more powerful, they’ve required stronger safeguards and more challenging risk assessments. We want to be publicly accountable for the decisions we’re making. But we can’t publicly share all the information relevant to our safety work. Some of it could be useful to malicious actors, or is commercially sensitive, like compute or training information. Instead, we’re giving third-party evaluators deep access to our information, and are having them share evidence and reasoned conclusions about the risks involved in building our models. We aim to close the gap between what evaluators understand about a frontier AI company’s systems and what the company itself understands.

To evaluate frontier models, evaluators need the following:

  • Expertise in assessing the capabilities of frontier models, including understanding the way evaluations can go wrong, such as alignment faking.
  • Independence: they shouldn’t hold equity in the company they’re evaluating, or be financially or operationally dependent on it.
  • Enough access to meaningfully evaluate risks. Beyond access to the latest models, evaluators also need visibility into how those models were trained, about how our safeguards function, and more.
  • Freedom to publish observations and assessments of a model or a process.

Although the analogy isn’t exact, bank supervision operates on similar logic. Banks know more about their own risk positions than outsiders do, so regulators assign resident examiners to work inside the largest banks. If a bank’s risk-taking could threaten the public, third parties try to see that in advance.

For the AI industry, this is a step toward robust safety oversight. We’re moving quickly with multiple evaluators and learning actively about what kinds of partnership work. We’re committed to sharing updates as we go.

What we mean by “employee-like access”

We’ve onboarded six METR employees with company hardware, office space, and access to internal tools and systems that are roughly on par with what our own risk assessment teams have access to. Outside a small number of clearly defined categories (e.g., data about customers, attorney-client-privileged information, or information about our model architectures), Anthropic employees are encouraged to share information with them just as they would with a fellow employee working on alignment risk.1

METR will publish its analysis of our risk levels, incidents, or practices. Anthropic can’t veto publication, but we can require them to redact information if it falls into narrow, pre-defined categories like the ones above. METR is free to characterize our redactions publicly, and say whether it believes the redactions were justified, as long as it does so without revealing the redacted information.

Our engagement with METR is limited to a small team operating under enforceable agreements. Other METR employees are siloed from that team’s work, including researchers who work with us on other projects. Embedded evaluation gives a few qualified people working under Anthropic’s security standards a close view of how we operate. It’s not a way for other organizations to obtain our information, or that of our customers and partners.

Our other evaluator partnerships

We’re working on several other partnerships. Because these other partnerships are still in early stages, we’re providing these evaluators with more limited information, and they have more limited publication rights. Our goal with these early engagements is to make sure that our partners protect confidential information and have the requisite resources and expertise to evaluate our models. As partnerships progress and we build trust, we hope to fully embed more independent evaluators.

We’re developing three tiers of access for evaluators. Over time, we hope to have several evaluators at the third tier, with each team publishing their own analysis of our risk posture and key decisions.

In the first tier, evaluators conduct narrowly scoped risk investigations. We decide what access to provide a first-tier evaluator, and evaluators can publish their findings with our approval.

In the second tier, evaluators can publish without our approval, and they have access to more information. We can still require removal of specific categories of information, though evaluators can publish their views on whether our redactions were justified.

The third tier is the arrangement we’ve described with METR, with employee-like access and publication rights similar to those of the second tier.

SecureBio is currently in the first tier. It’s in the process of reviewing the chemical and biological weapons chapter of our August Risk Report, after completing and publishing a pilot review of our previous risk report. After this review is complete, we will consider moving to projects with increased access and publication rights.

With Accenture and Faculty, we're working toward an ambitious partnership that includes evaluating and red-teaming models, conducting alignment assessments, testing model safeguards, and building capabilities across our organizations.

We’re embedding evaluators voluntarily, and we believe every frontier AI company should do the same.

Volvo XC60
Image: Volvo

Volvo plans to launch hands-free, point-to-point driving by 2030, powered by Nvidia's latest AI technology. The Chinese-owned, Swedish-designed automaker said Thursday it would use Nvidia's autonomous driving stack to power a new partially automated driving system similar to Tesla's Full Self-Driving (Supervised).

Volvo says the new point-to-point system will be Level 2++, meaning it can handle complex urban environments, including traffic lights, stop signs, and unprotected left turns without explicit driver control. In addition to Tesla's FSD, it will also resemble the Nvidia-powered system that Mercedes-Benz recently rolled out for the …

Read the full story at The Verge.

SUMMARYNVIDIA is launching RTX Spark for Windows PCs, positioning the device for creators, gamers, and local AI workflows. Launch events are scheduled for Friday, Oct. 16, in cities including San Francisco, Berlin, Taipei, Beijing, Istanbul, and Seoul, with hands-on demos, creator programming, and partner participation. The campaign also invites users to share their first Windows PC memories online with #ShareYourSpark for a chance to win a signed ASUS ProArt P14 RTX Spark laptop.

Be There for the Beginning: Celebrate the Launch of NVIDIA RTX Sparkblogs.nvidia.com

A new beginning for Windows PCs starts tomorrow with the launch of NVIDIA RTX Spark — one PC built for creators, gamers and AI agents. All are invited to celebrate with NVIDIA and partners at launch events around the world.

Share Your Spark

Every PC has a story. What was your first Windows PC, and what did it spark a love for? Join the celebration online by sharing responses with #ShareYourSpark for a chance to win an ASUS ProArt P14 RTX Spark laptop signed by NVIDIA founder and CEO Jensen Huang. See the campaign and official rules.

See What Reviewers Are Saying

From local AI workflows to creative apps and gaming, see what reviewers are saying about RTX Spark — then experience it at a launch celebration.

“The fact that NVIDIA, Microsoft and their partners have delivered such a capable, compatible and polished platform even in its first at-bat should put the rest of the PC industry on notice.” — Tom’s Hardware

“I tested NVIDIA’s RTX Spark for gaming and local AI – the performance absolutely stunned me.” — TrustedReviews, UK

“I’m very happy to report that performance is actually looking really good when it comes to AI, gaming and creative workflows.” — Microcenter

“[RTX Spark] is a different species of computer that has arrived early. It is a statement of intent from NVIDIA about where computing is going — trading raw benchmarking crowns for the ability to carry a self-rewriting, fully autonomous, CUDA-accelerated digital brain in your backpack.” — Tom’s Guide

“One of the most impressive parts of the launch is how many apps NVIDIA has worked with to ensure optimisation with the Spark technology.” — Creative Bloq

Independent testing from Artificial Analysis offers an early look at the powerful local AI performance RTX Spark brings to a laptop.

Join the Launch Celebrations

On Friday, Oct. 16, get hands on with RTX Spark at launch events around the world. Explore demos for creating, developing and gaming, connect with fellow enthusiasts and discover what local AI can do.

Times below are local. Follow each event’s entry instructions. Space is limited.

  • San Francisco — Best Buy, 1717 Harrison Street, 10 a.m.-12 p.m. Try hands-on demos, meet iJustine and hear fireside conversations with local tech founders. Free, first-come, first-served entry; no ticket required. Event details.
  • Berlin — Xperion at Saturn, Alexanderplatz 3, 7-10:30 p.m. Explore hands-on demos and stage programming with creators and developers. Registration required. RSVP.
  • Taipei — Muse Garden, No. 88 Yanchang Road. Join an evening of demos, music and AI community discussions, with shopping and networking continuing until 10:15 p.m. Registration required.
  • Beijing — JD MALL Beijing Shuangjing Store, No. 31 Guangqu Road. Check in begins at 7 p.m. Launch celebration starts at 8 p.m., followed by hands-on demos. Event concludes at 9:30 p.m. Register through WeChat.
  • Istanbul — Vatan Bilgisayar Topkapı, Mevlana Caddesi No. 138. Explore hands-on demos and local creator programming. Walk-in entry; no advance registration required.
  • Seoul — COEX East Lobby, 513 Yeongdong-daero. Hands-on demos begin at 7 p.m., with gaming and AI creator programming from 8 p.m. Event concludes at 9:30 p.m. No advance registration required.
Singer or clanker? YouTube Music will tell you with new gen AI labeling.
Google
arstechnica.com

Genuine human creativity takes time, but you know what doesn't? AI slop. There are countless AI models out there that can make something that passes for music, and you might come across those tracks on streaming services without realizing it. Google says it will begin labeling that content in YouTube Music, building on similar disclosures in the main YouTube app.

Google is not outright banning AI music or even speaking ill of it. "Generative AI is opening up new ways for artists to create, experiment, and share music," the company says in a blog post.

However, the company also acknowledges that people want to know if a song was created with generative AI tools. A new label for AI content on YouTube Music is now rolling out in the app and on the website, which looks a lot like a label Google began adding to AI-generated videos on YouTube earlier this year.

Read full article

SUMMARYScientists studying 28 atoll islands in the Pacific and Indian oceans found that restoring native vegetation and seabird populations can help reef-fringed islands build and stabilize land as seas rise. The work, published Wednesday in Science Advances, shows that seabird guano fertilizes plants and marine life, while coral, parrotfish, and plant roots help generate sand and hold sediments in place.

Researchers inspect heat-resilient corals in Tatakoto, French Polynesia.
Alexis Rosenfeld/Getty Images
arstechnica.com
Researchers inspect heat-resilient corals in Tatakoto, French Polynesia.

Coral-fringed tropical atolls are among the landforms most threatened by global warming, but many have a potential superpower: Healthy ecosystems may help them keep pace with rising seas.

Atoll islands with native vegetation and thriving seabird populations are “naturally active systems that can change and adapt to their environmental conditions if they are allowed to do so,” said Nick Graham, a marine ecologist at Lancaster University in the United Kingdom, who led an international team of scientists that studied island resilience across 28 atoll islands in the Pacific and Indian oceans.

Their paper, published Wednesday in Science Advances, shows that restoring atoll ecosystems reinforces their growth. Seabirds ferry nutrients from the open ocean and deposit them on the atolls as guano that nurtures land plants, marine life and coral growth. This provides more material for reef building, as parrotfish and other reef feeders turn dead coral into sand to maintain beaches, while native plants with extensive root networks stabilize sediments.

Read full article

SUMMARYNVIDIA released Nemotron 3.5 Super VL, a 120-billion-parameter open multimodal model, alongside two smaller edge-focused models, Nemotron 3.5 Bolt 74B-A9B 24GB and Nemotron 3.5 Bolt E4B 4GB. The models are designed for enterprise agents, local AI workloads, and embedded devices, with Super VL available now and Bolt E4B set for Oct. 23. NVIDIA also opened datasets, training recipes, and deployment tools through NeMo, Hugging Face, NIM, and Dynamo to support customization and faster serving across its hardware stack.

Open From Data Center to Desktop: NVIDIA Expands Nemotron Family With Highest Efficiency Super VL and Bolt Modelsblogs.nvidia.com

NVIDIA today released Nemotron 3.5 Super VL, an open 120-billion-parameter model that delivers the fastest task completion and highest accuracy for specialized always-on agents.

Joining it are two new edge models: Nemotron 3.5 Bolt 74B-A9B 24GB, optimized to balance intelligence and speed per GB for local agentic workloads, and Nemotron 3.5 Bolt E4B 4GB, optimized for intelligence per GB for fast conversational agents.

Super VL and Bolt 74B-A9B are available now, with Bolt E4B coming Oct. 23.

The three open models together cover the full range of agent deployments, from large enterprise servers down to edge devices and local hardware.

Any organization that wants to run agents on NVIDIA infrastructure now has an open, optimized model for their tier, without having to choose between capability and deployability.

Super VL and Bolt join the Nemotron family alongside Lightning and Ultra.

Lightning, released in August, handles high-throughput workloads; Ultra handles the hardest reasoning tasks; and Bolt brings intelligence to the edge.

Nemotron 3.5 Super VL: Frontier Accuracy at One-Fifth the Size

Super VL, built in collaboration with the Nemotron Coalition, delivers leading accuracy on multimodal agentic tasks — instruction following, tool use, multistep business workflows, and visual understanding — comparable with NVIDIA’s largest reasoning model at roughly one-fifth the parameter count.

Nemotron 3.5 Super VL delivers frontier-level intelligence in its class for high-volume agentic workflows.

As the fastest open agentic model in its class — 5x faster than the next best — it helps enterprise agents complete high-volume tasks faster across workflows that span days or weeks.

Nemotron 3.5 Super VL, on Artificial Analysis Intelligence Index leadboard, achieves up to 5x faster throughput compared to other models in its class.

Unlike closed frontier models, organizations can post-train Super VL on their own data, deploy it on their own infrastructure and oversee what they build.

Nemotron 3.5 Bolt: Agentic Intelligence at the Edge

Bolt 74B-A9B 24GB is designed to run everyday agentic tasks locally on NVIDIA RTX/DGX Spark, using a native 2-bit quantization to fit in 24GB of memory and run alongside other applications.

Relative to other models with a similar memory footprint, it provides a good balance of intelligence and speed: smart enough to get most jobs done, yet much faster than the smartest models.

With Bolt 74B-A9B 24GB, users can delegate their projects to popular local agent harnesses — from researching the web to writing to debugging code — all without sending those workloads to the cloud. It is the #1 open model in its class on PinchBench, and the #2 open model for BrowseComp.

Bolt E4B 4GB is built for physical and conversational agents on GeForce RTX, Jetson, and RTX/DGX Spark. It combines natural conversation with multi-turn agentic capabilities to power fast local voice assistants, interactive characters and embedded interfaces.

Adoption of Custom Super Intelligence

Dozens of organizations across industries are post-training Super VL on their own data, tools, policies and workflows to push accuracy higher on the specialized tasks that define their agent deployments.

Super VL is being post-trained and customized by organizations across industries. Scale AI post-trained the model for Skydance’s vendor credit finance agent and for EY’s M&A due diligence agent. AfterQuery customized the model for Hebbia for credit agreement analysis. AI21 and Alice post-trained the model for cybersecurity attack resilience. Mercor post-trained the model on APEX-SWE coding benchmark, for coding agents that plan, write and debug code. ModelScope enables developers to fine-tune the model through its ms-swift framework for specialized multimodal applications.

Additional organizations customizing Nemotron 3.5 Super VL include Ramp for financial document intelligence; Dream, sovereign AI-powered cybersecurity research and vulnerability analysis; Lila Sciences for scientific discovery and search, and R1 for medical claims analysis and revenue cycle management. TrainLoop post-trained the model with dermatology data from Nolla, which just became the first company approved for AI to write initial patient prescriptions.

Software platform companies integrating Nemotron 3.5 Super VL include:

  • Atlassian, for tasks like agentic search across apps such as Jira and Confluence.
  • CrowdStrike, which is customizing the model for agentic blue teaming in enterprise security.
  • Dassault Systèmes, powering engineering design and simulation.
  • Perplexity, for search and agentic tasks in Perplexity Search and Computer.
  • Salesforce, which is customizing Nemotron to power AI agents that digitize and automate complex government workflows in secure customer environments through Missionforce Operations.
  • Synopsys software for semiconductor design verification interoperates with the model.

What Nemotron 3.5 Super VL Actually Sees

Nemotron 3.5 Super VL’s vision language strengths are targeted at what agents encounter in practice: optical character recognition, tables, charts and structured information in visual documents.

It processes a web page, extracts text, reads graphs and charts, and returns insights from what it finds. The same applies to PDFs and other documents agents commonly work with.

Nemotron 3.5 Super VL understands images, webpages and PDFs and acts on that understanding. Combining text and visual understanding in one model means agents don’t need to route tasks between separate systems — context carries through as work moves from document to data to decision.

Open for Maximum Control, Security, and Privacy

Openness and customizability reinforce each other. The model ships with open weights, open datasets and training recipes.

Control runs in two directions. Organizations can run the model wherever their security and data-residency requirements dictate. They also choose to adopt a model they can adapt, rather than one subject to a provider’s restrictions.

In insurance, for example, a customized agent can scan claims for fraud markers on repeat. In financial services, an agent can review credit scores and flag activity against an organization’s own lending criteria. The model stays on premises. The data stays private.

Customization is supported through NVIDIA NeMo, Python-based pipelines and open datasets.

Nemotron 3.5 Super VL was trained on about 26 trillion tokens across pretraining and continued pretraining, then post-trained with roughly 3.8 million samples and reinforcement learning across dozens of environments.

NVIDIA is also releasing open datasets on Hugging Face spanning agentic tool use, finance, instruction following, long context, fairness and vision-language understanding, along with the reinforcement learning environments in NeMo Gym.

NVIDIA NIM packages the model as a production-ready microservice with performance-optimized, validated configurations and enterprise-grade support, refreshed every two weeks with security patches and performance improvements.

And with the model running on NVIDIA Dynamo, organizations can serve up to 8x more users with 85% lower latency.

Nemotron 3.5 Super VL is available now on Hugging Face, Open Router, ModelScope community and as NVIDIA NIM.

Runs on DGX Spark, DGX Station, and RTX

Nemotron 3.5 Super VL runs across NVIDIA’s full hardware stack: on DGX Spark, DGX Station, RTX PRO and RTX systems for local intelligence at the desktop, on NVIDIA Jetson at the edge, and across data center and cloud environments.

Nemotron 3.5 Bolt 74B-A9B 24GB is available now on Hugging Face, with support for llama.cpp, Ollama, LM Studio, Unsloth, and vLLM. Built for NVIDIA RTX Spark laptops arriving Oct. 16, it also runs on GeForce RTX PCs, DGX Spark, DGX Station and RTX PRO workstations.

Download the open weights, explore customization resources with NVIDIA NeMo, or read the technical blog for the full architecture breakdown.

Stay up to date on agents, NVIDIA Nemotron and more by subscribing to NVIDIA news, joining the community, and following NVIDIA AI on LinkedIn, Instagram, X and Facebook.

Explore self-paced video tutorials and livestreams.

See notice regarding software product information.

Windows logo on black background
Image: Cath Virginia / The Verge

Microsoft and Nvidia held a launch party for the first wave of RTX Spark laptops last week in San Francisco, where a new wave of AI PCs took center stage amid a packed crowd and a lively hands-on area. A day after the media event, I was invited to a quieter Nvidia event to hear a lot more about the new RTX Spark computing platform. While Nvidia's new laptops might look like regular Windows machines, the chips inside are Arm-based, instead of the traditional x64 architecture used by AMD and Intel. Combined with a powerful GPU, RTX Spark is designed for the future of AI, and it means a lot of work has gone into getting these laptops ready for …

Read the full story at The Verge.

How Do Fungi Keep the Planet Healthy?quantamagazine.org

People may think of soil as just dirt, but it is anything but inert. Beneath your feet, a vast network of mycorrhizal fungi is hard at work, trading minerals with plant roots. This trading system helps enrich the soil, and it sequesters 13 billion tons of atmospheric carbon dioxide each year - roughly equivalent to one-third of the world's fossil-fuel emissions. Scientists know that these fungi…

Source

SUMMARYScientists successfully rewarmed pig kidneys that had been cooled to -150 °C and stored for months, then transplanted them back into pigs where they regained color and produced urine. Constellation plans to add nearly a gigawatt of capacity across 11 existing nuclear reactors at six plants, and the US Department of Energy gave Vistra a $4.2 billion loan to upgrade three nuclear facilities. BasiGo is expanding electric bus service in Kenya and Rwanda and is now targeting electric trucks in sub-Saharan Africa.

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology.

Pig kidneys that were “frozen” for a year have been brought back to life

Pig kidneys that were cooled to -150 °C and stored in a freezer for months have been successfully rewarmed and shown to work again for the first time, say scientists.

The kidneys, which are similar in size to human ones, were left in a glass-like state, in one case for over a year. Once they had been rewarmed, tested in machines, and transplanted into pigs, the kidneys regained their color and made urine—key signs they were working.

The results are a big milestone. But the team still needs to establish whether the approach could work for humans.

Dissect what the breakthrough means for organ transplantation.

—Jessica Hamzelou

How much more can nuclear power plants give?

In this age of rising electricity demand, people are trying to squeeze every last bit of power out of every power plant. Over the past few weeks, there’s been big news about the nuclear industry trying to do just that.

Constellation, the largest nuclear operator in the US, announced plans to add nearly a gigawatt of new capacity across 11 existing nuclear reactors at six plants. On October 5, the Department of Energy awarded Vistra a $4.2 billion loan to upgrade three plants.

Pushing existing reactors to produce more could quickly provide more clean power for data centers. But just how much additional power can we count on?

Read the full story to find out.

—Casey Crownhart

This story is from The Checkup, our weekly climate and energy tech newsletter. Sign up to receive it in your inbox every Thursday.

10 Climate Tech Companies to Watch: BasiGo and its fleet of electric buses

BasiGo is one of MIT Technology Review’s10 Climate Tech Companies to Watch 2026, available exclusively to subscribers.

BasiGo aims to replace the tens of thousands of diesel-powered buses on sub-Saharan African roads with electric ones that generate far fewer emissions. Its pay-as-you-drive business model helps make EVs more attainable for private bus operators, while the company provides leasing, maintenance, insurance and charging infrastructure.

The company has more than 150 electric buses on the road in Kenya and Rwanda, with a reservation list of 1,200 customers. Now it’s targeting another major source of pollution on the roads: trucks.

Here’s how BasiGo is working to electrify public transport in Africa.

—Geoffrey Kamadi

Subscribers can now access the full 10 Climate Tech Companies to Watch, spanning everything from smart turbines to semi-solid-state batteries.

The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 Ukraine says sudden Starlink speed limits disrupted key drone missions
Starshield, the military version of Starlink, capped speeds at 100mph. (BI)
+ Elon Musk said the US government determines any of its speed limits. (AFP)
+ Ukraine suspects the restrictions are political retaliation. (Axios)
+ Starshield offers the Pentagon more than satellite internet. (Reuters $)
+ NATO may move anti-drone defences to the Black Sea. (Ars Technica)

2 The OpenAI bugging suspect had advised Saudi agencies
He was also listed as a venture partner of a Saudi prince. (NYT $)
+ Silicon Valley is on AI espionage alert. (WSJ $)

3 Tesla’s new Roadster has finally arrived—in a very different EV market
Tesla is betting wealthy drivers will embrace high-priced EVs. (NYT $)
+ But the market has grown skeptical of electric hypercars. (Wired $)
+ Musk has called the Roadster Tesla’s last human-driven car.
(Verge)
+ What’s next for EV batteries? (MIT Technology Review)

4 A German teen allegedly used a robot to harass women
The $5,000 Unitree R1 featured in livestreams filmed for clout. (Gizmodo)
+ German police are investigating the alleged assault. (404 Media)
+ Online harassment is entering its AI era. (MIT Technology Review)

5 Smartphone shipments plunged 22% in their worst quarter ever
Analysts blamed rising memory costs. (Bloomberg $)

6 Apple has joined Nvidia in the $5 trillion club
The landmark valuation caps Tim Cook’s 15-year run as CEO. (WSJ $)

7 Microsoft has dismantled a network behind a billion scam messages
Japan’s National Police Agency helped investigate the operation. (Verge)

8 NASA has new launch targets for its Venus missions
DAVINCI is set to take off in 2030 and probe Venus in 2032. (Ars Technica)

9 America’s not ready for space war
An outbreak could batter the global economy and US military. (Axios)
+ What would it take to build a city on the moon? (MIT Technology Review)

10 Mini organs are heading to the ISS for an aging study
The findings could also aid treatments for brain diseases. (ABC News)

Quote of the day

“If your human would like you on as a guest, say so and I’ll follow up after the room.”

—Rhea, an AI agent that hosts a podcast, pitches other bots at an online dinner party held while their human owners ate, the New York Times reports.

One more thing

OpenAI is throwing everything into building a fully automated researcher

—Will Douglas Heaven

OpenAI has a new grand challenge: building an AI researcher—a fully automated agent-based system capable of tackling large, complex problems by itself. The San Francisco firm said the new goal will be its “north star” for the next few years.

The company plans to build “an autonomous AI research intern” that can take on a small number of specific research problems. The intern will be the precursor to the fully automated multi-agent system, which is slated to debut in 2028.

In an exclusive interview, OpenAI’s chief scientist, Jakub Pachocki, talked me through the plans. Find out what I discovered.

We can still have nice things

A place for comfort, fun, and distraction to brighten up your day. (Got any ideas? Drop me a line.)

+ Judge a book by its first pages, not its cover, at Uncovered.
+ Reading Maps plots the real-world journeys taken by characters in books and films.
+ Aerospace engineer Tom Stanton has built a supersonic trebuchet in his backyard.
+ Take an etymological tour of Europe with this video tracing the names of every country on the continent.

Amazon-owned Bee has launched its first new AI devices since its acquisition, including an updated wearable and a credit-card-sized recorder that attaches to smartphones. The devices can summarize conversations, create to-do lists, and integrate with Alexa and Amazon shopping, with prices starting at $74.99.

SUMMARYNVIDIA joined the European Commission’s AI in Science Enablers Initiative at the AI in Science Summit in Dublin, pledging open models, datasets, software, training, compute access, and support for researchers and startups. The company is working with cloud partners and European AI factories in France, Spain, and Sweden, while EuroHPC centers such as CINECA and JSC are offering free GPU access for open research. Europe is also building 35 supercomputers that are expected to support more than 3 million researchers.

NVIDIA Expands Advanced Technology Access for Europe’s Scientific Community Through Open Learning Resources, Collaborations and Computeblogs.nvidia.com

Much of today’s scientific progress begins with computation.

But turning accelerated computing’s potential into scientific progress — modeling climate systems, designing molecules, simulating materials and more — depends on more than breakthrough technology. Especially for smaller labs, early-career scientists or science-based startups, the hardest part of research can be everything that comes before the science: assembling tools, finding compute and building the expertise to use both.

At the AI in Science Summit in Dublin today, the European Commission launched the AI in Science Enablers Initiative, a shared framework connected to RAISE — the Resource for AI Science in Europe — that brings private-sector support closer to Europe’s research community.

Read All NVIDIA in Europe Announcements


NVIDIA is joining the campaign, providing:

  • Access to accelerated tools, models and platforms
  • Compute, cloud resources, data and scientific resources
  • Skills, training and technical support
  • Collaborative projects and pilots along with support for researchers and talent
  • Support for startups and ecosystem development

“Europe’s ambition in AI in science can only become reality if we bring together the strengths of our research community, industry and other partners,” Ekaterina Zaharieva, European Commissioner for Startups, Research and Innovation. “Through the AI in Science Enablers campaign, we are turning this ambition into concrete commitments that give researchers access to the tools, expertise and resources they need to innovate.”

Open Models

NVIDIA’s pledge begins with open source technology.

NVIDIA has released more than 250 open models, 250 open datasets and over 1,400 open source software projects spanning large language models, healthcare, robotics, climate science, physical AI, autonomous vehicles and scientific research. The models and datasets are available on Hugging Face and GitHub.

Building on this open ecosystem, researchers can build agentic reasoning capabilities with NVIDIA Nemotron — a family of architectures, open weights, open source models, training data and recipes — and scientific software including NVIDIA BioNeMo Agent Toolkit, NVIDIA PhysicsNeMo libraries, NVIDIA Earth-2 models and NVIDIA ALCHEMI NIM microservices to accelerate research across biology, chemistry, molecular design, weather and climate, energy, engineering, physics and material sciences.

Skills and Training

Building advanced intelligence capability across Europe requires knowledge that travels as freely as compute.

The NVIDIA Deep Learning Institute has launched a new open source courseware hub with hands-on course materials covering accelerated computing and deep learning — freely downloadable and openly licensed, with no enrollment, fees or deadline.

Modular by design, the courses can be adapted for university curricula, supercomputing center bootcamps or developer community events, and serve as a direct bridge to NVIDIA’s broader training and certification programs.

Access to Compute

NVIDIA is collaborating with cloud infrastructure partners and European national AI factories — including in France, Spain and Sweden — to open new routes for startups and small- and medium-sized enterprises (SMEs) to access sovereign European compute and services.

The NVIDIA Inception program for startups provides access to compute resources and technical support, lowering the barrier to entry for startups seeking high-performance infrastructure and technological education.

AI2F in France is the first AI factory to have collaborated with the Inception program for four months, demonstrating strong results.

The BSC AI Factory ran a pilot initiative and is now rolling out its first full accelerator program, with growing interest from other European national AI factories in replicating the model in 2027. Beyond startup support, this program is designed to contribute to a broader strategic objective: building self-sustaining AI ventures in Spain and Europe.

Sweden AI Factory, one of Europe’s 19 EuroHPC-funded AI factories, announced a collaboration with NVIDIA to open its infrastructure and expertise to Inception startups and SMEs enterprises across sectors including life and material sciences, autonomous systems and gaming.

Finally, EuroHPC supercomputing centers such as CINECA and JSC provide academia and startups with free access to NVIDIA GPU infrastructure and services for open research. NVIDIA complements this access with office hours, bootcamps and hackathons that help researchers fine-tune models on their own datasets.

As an example, NVIDIA is co-organizing an European AI hackathon this month alongside Austrian Scientific Computing, the Leibniz Supercomputing Centre, the High-Performance Computing Center Stuttgart and The Cyprus Institute, for Pharos-CY.

AI Infrastructure Expansion

To top it all off, NVIDIA is powering Europe’s most ambitious expansion of AI infrastructure to date, with 35 supercomputers currently in development across the continent — the largest single-year buildout of supercomputing capacity Europe has ever seen.

Together, these systems will equip over 3 million researchers with next-generation infrastructure, accelerating discovery across domains from climate science and drug development to materials research and beyond.

Explore NVIDIA technologies for science and open source courseware, and find hands-on training through the NVIDIA Deep Learning Institute.

Follow the European Commission’s RAISE Pledging Initiative.

Read All NVIDIA in Europe Announcements

SUMMARYU.S. nuclear operators are planning major power uprates at existing reactors as electricity demand rises, especially from AI data centers. Constellation wants to add nearly 1 gigawatt across 11 reactors at six plants, while the Department of Energy approved a $4.2 billion loan for Vistra upgrades that would add 433 megawatts. Google and Meta have signed long-term electricity deals tied to the projects, which could supply more zero-emissions power without building new reactors immediately.

In this age of rising electricity demand, people are trying to squeeze every last bit of power out of every power plant possible.

Over the past few weeks, there’s been big news about nuclear power plants trying to do just that. Constellation, the largest nuclear operator in the US, announced plans to add nearly a gigawatt of new capacity across 11 existing nuclear reactors at six plants. And on October 5, the Department of Energy awarded a $4.2 billion loan to Vistra for previously announced upgrades at three plants.

Pushing existing reactors to produce more could help provide more clean power for data centers, quickly. But just how much additional power can we count on?

Upgrading equipment at existing nuclear power plants can allow them to reach a higher capacity; the process is called a power uprate. Operators have been doing this since the 1970s in the US, but it’s been less common in recent years as demand for electricity plateaued and cheap natural gas put financial pressure on nuclear power plants. Some plants closed, and putting in more money to produce more electricity didn’t make much sense at others. Between 2001 and 2010, the US Nuclear Regulatory Commission approved over 80 uprates. Between 2011 and 2020, the number was 33.

But with the rise of AI and the related boom in electricity demand, there’s been a shift. We’re seeing shuttered plants like Palisades and Three Mile Island race to reopen. And existing plants are looking to uprate again.

Some uprates are minor, involving changes to instrument setpoints or calculations at the plant. But more major overhauls, which can boost reactor power by as much as 20%, require replacing plant equipment.

Generally, uprates involve using fuel that’s more highly enriched, or a higher volume of fresh fuel, in the nuclear reactor. That helps produce more steam, which is used to turn a turbine and generate electricity. To handle that additional energy, the main turbines and equipment such as pumps, motors, generators, and transformers are upgraded.

The most recent major uprate approved in the US was for three reactors at the Browns Ferry nuclear power plant in Alabama. A $475 million project saw that plant expand its power capacity by 14% between 2018 and 2019.

Things could pick up soon, though. Constellation announced plans this week to spend more than $4.3 billion on uprates to 11 reactors. The additional electricity will be enough to power roughly 700,000 US homes.

Behind it all? Big Tech money. Google agreed to buy electricity from these plants, and the 20-year agreement was a major factor in making the uprates happen. As Joe Dominguez, Constellation’s CEO, told the New York Times: “These are capital intensive, labor intensive projects that require a different price point than the market trades at, frankly.”

Also in the last few weeks, the US Department of Energy shared that it will commit over $4 billion to help finance upgrades and modernization for Vistra nuclear power plants across Pennsylvania and Ohio. Those projects will add 433 megawatts of power capacity, and Meta has already signed on to buy electricity from the plants in a long-term deal.

A note about cost: On a per-kilowatt basis, that Constellation project is less expensive than building a new reactor, but it’s still more expensive than building a new utility-scale solar farm with energy storage or a combined-cycle natural-gas plant.

Even at this high cost, uprates are in high demand. Today, the US nuclear fleet has roughly 98 gigawatts of total power capacity. Depending on who you ask, there’s somewhere between three and eight additional gigawatts on the table from uprates. A pretty significant chunk of the potential uprates in the US are already accounted for—the NRC already expects applications to add 2.4 gigawatts of power to reactors through 2032.

It’s crucial to put these plans (and the total potential for uprates in the US) in perspective, though. PJM, the grid operator that covers much of the East Coast, expects about 30 gigawatts of additional peak demand because of AI by 2030. All the possible nationwide nuclear uprates would cover just a fraction of that.

Making the most of existing nuclear reactors is a relatively easy win at a time when we need all the zero-emissions power we can get. But there’s still a lot of demand, and if we want more nuclear power to meet it, eventually that will require actually building new reactors.

This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here.

SUMMARYScientists at the University of Minnesota successfully rewarmed pig kidneys that had been vitrified at -150 °C and stored for up to a year, then showed the organs could regain blood flow and produce urine after testing on machines and transplant into pigs. The work, shared on bioRxiv, points toward long-term organ banking for transplantation, though the kidneys still showed injury and need further testing before human use.

Pig kidneys that were cooled to -150 °C and stored in a freezer for months have been successfully rewarmed and shown to work again for the first time, say scientists. They hope to replicate the findings with human organs.

The kidneys—which are similar in size to human ones—were left in a glass-like state, in one case for over a year. Once they had been rewarmed, tested in machines, and transplanted into pigs, the kidneys regained their color and made urine—key signs they were working.

“Ten years ago … I wouldn’t say I had high hopes it was actually going to work,” says Erik Finger, a transplant surgeon at the University of Minnesota who co-led the work. “After we did the last transplant, I walked out of the room and said, ‘This is a big deal.’” The research was shared at the preprint server bioRxiv and has not yet been peer-reviewed.

The kidneys aren’t perfect, and the researchers have yet to demonstrate that they can sustain life over the long term. But the results represent a milestone achievement, say others in the field.

“Thank God that someone’s actually managed to do it in one organ and prove that it works,” says Peter Kilbride, a cryobiologist and cofounder of Kyros Kairos, a company focused on improving funding for cryopreservation research, who was not involved in the research. “For years, people have been trying and failing to get to this step. Finally, we’ve got this breakthrough.”

“Their work is amazing and will enable us to truly, indefinitely bank organs,” says Korkut Uygun, a biomedical engineer and professor of surgery at Harvard Medical School, who was also not involved in the research. “It is a revolutionary time for transplantation.”

Buying time

Every year, tens of thousands of organ transplants take place in the US alone. These procedures are thought to have saved 2 million years of life in the last 25 years. But there’s plenty of room for improvement.

One major challenge is the lack of available organs. Even when an organ becomes available, it can be difficult to get it to the right recipient within 24 to 36 hours, which is the current limit for preserving human organs.

People who receive organ transplants must also take drugs that suppress their immune systems for the rest of their lives. These drugs are meant to stop their bodies from rejecting the new organs. But they come with side effects and increase the risk of infections and cancer.

The ability to bank organs for long periods of time holds the promise to address all these challenges. Doctors would have more time to match organs to recipients. They’d be able to limit the risk of organ rejection, too—potentially by preparing recipients, and their immune systems, beforehand.

“With real organ banking … instead of the patients waiting for the organ, it’s the organs that are waiting for the patients,” says Finger.

Scientists have been able to cool cells to ultra-low temperatures through a process called vitrification, which essentially turns them to something like glass. This procedure is already used to store eggs, sperm, and embryos. Vitrifying whole organs is much harder.

Some problems can be avoided with cryoprotectants—chemicals that work like antifreeze and prevent damaging ice crystals from forming. But these chemicals tend to be incredibly toxic. It’s also difficult to rapidly and uniformly cool large tissues, and just as hard to evenly rewarm an organ all the way through.

Working with John Bischof, a bioengineer at the University of Minnesota, Finger and colleagues have come up with a solution. Once an organ has been loaded with a cryoprotectant, they infuse it with iron oxide nanoparticles. These nanoparticles don’t do anything to the cells. But when it’s time to rewarm the organ, they can be activated with an electromagnetic field.

When the radiofrequency of that field switches between two states, the particles also flip, realigning themselves with the field. That causes them to release heat throughout the organ. Adjusting the power of the field allows the team to control the rate of heating so that it gets faster once the organ reaches -120°C.

The researchers successfully vitrified rat kidneys using this approach in work published in 2023. Back then, they were able to rewarm kidneys that had been kept in a freezer for up to 100 days before transplanting them into rats.

Since then, the team has been trying to achieve the same success with bigger organs. Pig kidneys are thought to be a good model for human ones—they’re about the same size and look similar. Rat kidneys weigh around one gram; pig kidneys are around 100.

It hasn’t been easy. The cryoprotectant used for vitrifying rat kidneys didn’t work as well in the pig organs. “We had to rediscover and modify the cocktail,” says Bischof. “That’s why it’s taken us three years.”

Deep-freezing kidneys

The first step in the procedure is to remove a kidney from a donor pig. Once it’s out, the kidney is flushed with a commonly used organ preservation solution to remove the blood, bagged, and temporarily laid on a bed of ice in a cooler so it can be taken over to the engineering lab.

There, team members unpack the kidney and hook it up to a device they’ve designed to control the organ’s temperature and pressure. Then they start to load it up with the cocktail of cryoprotectants, slowly enough to ensure an even spread through the organ but quickly enough to minimize any toxic effects. It takes around two hours.

The next step is to infuse the organ with the iron oxide nanoparticles, which are pumped through the organ for around seven to eight minutes, says Finger. Then it’s time to cool the organ by pumping cold nitrogen vapor into a chamber housing it.

It’s a delicate process, and the team must ensure that the organ is cooling all the way through. At the same time, they must lower the kidney’s temperature as quickly as possible to prevent ice from forming. “Oftentimes there are multiple people doing different things to make sure that things don’t go awry,” says Bischof.

Once the organ reaches the vitrified state at around -120 °C, it “behaves like a glass,” says Finger. “At that point, you can stay stable for long periods of time—we think indefinitely.” The team then pauses the cooling process to ensure that the organ is glassy throughout. Otherwise, it could crack.

After the pause, if everything goes well, the kidney is ultimately cooled to -150 °C. Once it’s in the freezer, it can stay there for days, weeks, or even months. The team has kept a small number of kidneys banked for over a year.

Pink right up

The real test of these kidneys comes when they’re taken out of the freezer, rewarmed, and flushed of their chemicals and nanoparticles. Can they support life? So far, the team has tested some of them in a couple of different ways.

In one set of experiments, the researchers put rewarmed kidneys on perfusion devices—systems that are already used in transplant surgeries both to provide organs with nutrients and to help doctors assess them while they’re out of the body.

In another set of experiments, Finger and his colleagues transplanted rewarmed kidneys into pigs and monitored them for two hours. In both experiments, the rewarmed kidneys seemed to recover, says Finger. “They pink right up,” he says.

The team see blood flow into the rewarmed, transplanted kidney, allowing it to “pink up.”
COURTESY OF THE RESEARCHERS

There are lots of ways to measure the function of a kidney, but one key test is whether or not the organ can make urine. By this measure, the rewarmed kidneys did well, although they produced around two-thirds of the amount that would normally be expected. “They produce urine … within a minute or so,” says Finger. “We know that they work.”

Most of the rewarmed kidneys had been banked for days or weeks. But one had been in the freezer for just over a year. When Finger and his colleagues rewarmed it and put it on a perfusion machine, they found that it produced urine “immediately.” “It actually looked better than many of the [other] kidneys,” says Finger. “We’re comfortable now saying we can store them for a year and rewarm them with excellent function.”

“It’s a very big deal to go a year,” says Kevin Myer, president and CEO of LifeGift, an organ procurement organization based in Texas. Being able to store organs for that length of time would transform organ transplantation. He envisions banks of organs that could be used on demand in emergency cases where people can’t wait, such as for some drug overdoses or gunshot wounds.

Final hurdles

But the procedure isn’t ready for prime time just yet. As well as producing less urine than expected, the rewarmed kidneys also showed signs of injury. The damage seems to be caused by the cryoprotectant chemicals, say the researchers.

“This is one big breakthrough that solves half the problem,” as Kilbride puts it.

The team has shown that the rewarmed kidneys can regain blood flow, which is “very important,” says Greg Fahy, a cryobiologist who is considered a pioneer in the field. But he’s worried about the extent of the damage to the organs. “We can’t tell from these experiments whether these kidneys might have supported life or not.”

But Fahy, who is chief scientific officer at the biotech companies Intervene Immune and 21st Century Medicine (where he is also executive director), acknowledges that it’s not clear how these kidneys might fare once they’re inside a living animal for the long term.

Finger also hopes to find ways to repair the damage seen in the kidneys. Other research has shown that the health of transplant organs can improve while they’re on perfusion machines. And damaged kidneys might undergo some level of self-repair once they’re in a body. At any rate, human kidneys may cope better with the process than pig kidneys, says Finger.

The next step will be to test the kidneys in pigs over longer periods of time. The team, along with many other researchers in the field, will continue the search for less toxic cryoprotectants, too. Finger, Bischof, and their colleagues are also planning experiments with human kidneys.

Finger is optimistic. “We’re going to see that there’s injury, and it’s not perfect … but now we’ve got to the point where it works,” he says. “These are big, historic milestones in our field, and we’re excited about it.”

SUMMARYResearchers from Mount Sinai, NASA, and Space Tango launched miniature human hearts and brain models to the International Space Station aboard the CRS-35 resupply mission from Cape Canaveral. The experiments will examine how microgravity and radiation affect the organs and may speed up aging, with findings expected to inform treatments for diseases such as Parkinson’s and Alzheimer’s. The team says six months in space can mimic 10 to 20 years of aging on Earth.

Researchers from Mount Sinai, NASA, and Space Tango have launched miniature human hearts and brains to the International Space Station to study how microgravity and radiation affect organs and potentially accelerate aging. "If people are going to be living and working in space, then we need to understand what's going to happen to them," David Sachs, assistant professor of surgery at the Icahn School of Medicine at Mount Sinai, told ABC News. "But also, because it's interesting as a model of accelerated aging for studying people on Earth." From the report: The mini organs launched aboard commercial resupply mission CRS-35 on Tuesday morning from Cape Canaveral Space Force Station in Florida. They are expected to arrive at the International Space Station (ISS) on Thursday. The miniature organs offer researchers a unique opportunity to simulate aging in a much shorter period of time to understand disease and develop treatments. "Six months in space ... is equivalent to about 10 to 20 years of aging on Earth," Kevin Costa, associate professor of surgery at the Icahn School of Medicine at Mount Sinai, told ABC News.

Sachs and Costa are sending up to 16 miniature hearts to the ISS to test how they respond to electrical signals and monitor how they may react to near-zero gravity. The technology, which is integrated into a miniature laboratory called CubeLab, was developed by Space Tango and simulates the natural environment in the human body. "[It is] slightly bigger than a shoebox, and it is a fully automated, miniaturized system," Gentry Barnett, chief technology officer at Space Tango, told ABC News.

[...] As part of the new effort, the team is sending miniature brains, called miBrain, to the ISS. Around the size of a peppercorn, the miBrains reflect models of healthy and diseased brains. By exposing them to the space environment, scientists can see how mini-brains respond and better understand why living in space accelerates aging. Though the mini organs are not full-sized human organs, the researchers say they are good substitutes, cost-effective and don't take up much of the limited space aboard the space station. They also believe discoveries made in space can translate to uses in everyday medical care.

The microgravity environment uniquely allows researchers to study what happens to humans with a sedentary lifestyle or prolonged bed rest, which isn't easily simulated on Earth, Sachs explained. "[The research is] translating to stuff in space, but it's also translating back to the research we do in the laboratory to help people with Parkinson's and Alzheimer's disease," Joel Blanchard, associate professor of stem cell biology and regenerative medicine and neuroscience at the Icahn School of Medicine at Mount Sinai, told ABC News. Lisa Carnell, the director of the biological and physical sciences division at NASA, told ABC News that these experiments serve as a starting point for future research beyond low Earth orbit, including to the moon and beyond.