A team led by Dr. Dae-Yoon Kim at the Korea Institute of Science and Technology (KIST) Composite Materials Research Institute has built an electric motor that uses a coil made only of carbon nanotubes (CNTs), with no metals. In tests, the team could control the motor’s revolutions per minute (RPM) in line with changes to the input voltage. That shows a motor can perform its basic job, turning electrical energy into rotational force, without using metal conductors.

CNTs are one-dimensional, tube-shaped nanomaterials with carbon atoms arranged in a hexagonal honeycomb structure. They are much lighter than common metals and are known for high electrical conductivity, strong mechanical strength, and good thermal conductivity. Even so, CNTs have faced hurdles in real-world use. A major issue is leftover catalyst metals from the manufacturing process. These metal particles stick to CNT surfaces and reduce electrical performance, which directly affects motor parts.

The KIST team developed a new CNT purification process that uses the alignment behavior of liquid crystals, a “fourth state of matter” that sits between liquid and solid. As the CNTs align, the process naturally breaks up clumps and helps remove metallic particles from the surface. The key point is that it can selectively remove impurities without damaging the CNT nanostructure. This sets it apart from many liquid- and gas-phase purification methods. The result is CNTs with much better conductivity, high enough to work in actual electric motors.

The researchers then formed coils from the purified CNTs and ran motors that showed stable RPM control with different voltages. If this approach scales, lighter coils could reduce motor weight and overall system mass. It could also ease dependence on copper and limit exposure to price and supply risks. Future work will need to compare power density, efficiency, heat handling, and cost with copper-based designs under real operating conditions.

"By developing a new concept of CNT high-quality technology that has never existed before, we were able to maximize the electrical performance of CNT coils to drive electric motors without metal," said Dr. Dae-Yoon Kim of KIST. "Based on the innovation of CNT materials, we will take the lead in localizing materials such as conductive materials for batteries, pellicles for semiconductors, and cables for robots."

Source: KIST | Image via Depositphotos

This article was generated with some help from AI and reviewed by an editor. Under Section 107 of the Copyright Act 1976, this material is used for the purpose of news reporting. Fair use is a use permitted by copyright statute that might otherwise be infringing.

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Posted Monday 18 August 2025 at 2:42 pm AEST (my time).

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It's fun to think about the fundamental physical constants. These are special values used in our models of the physical universe. They include things like the speed of light, the gravitational constant, and Planck’s constant, and they’re “fundamental” in the sense that we can't derive them theoretically, we can only measure them.

We use these in solving physics problems all the time, so it’s easy to take them for granted. But why are there such numbers in nature, and why do they just happen to have those specific values? Because, listen, if they were only slightly different, the universe might be incapable of supporting life. Did some cosmic clockmaker set these parameters? Isaac Newton thought so.

One of the most basic of these numbers is the electric constant, k. It's a value that lets us calculate the forces between electric charges. That’s a big deal when you consider that all matter is made of just three things—electrons, neutrons, and protons, two of which have an electric charge. The interaction between electrons is what forms molecules to create you and everything around you. Otherwise it would all be just some undifferentiated soup.

But how do we know the value of the electric constant? Also, what does it have to do with other fundamental constants? And for that matter, is it really fundamental? Let's investigate.

Coulomb’s Law and Constant

When we say something has an electric charge, we mean it has a different number of protons and electrons. If your clothes dryer removes some electrons from your socks, they become positively charged. If they gain electrons, they’ll be negatively charged. (Note: You can't take away protons, since they’re in the nucleus of the atom. It would involve a nuclear reaction, which nobody wants.)

If you have two objects with opposite charges, they attract. If they have the same charge, they repel. Here's a demo you can do yourself: Take a piece of clear tape and place it on a smooth table. Then put a second piece on top of that one, and pull them off together. Now, if you separate them, one will be positive and one will be negative; hold them in proximity and they will bend toward each other.

If you repeat the process, you’ll have two positive and two negative tapes. Hold two with similar charges near each other, and you’ll see that they repel, like in the picture below:

The smaller the distance between the tapes, the greater the repelling force. If you increase the charge on either (or both) tapes, the force will also get stronger. In 1785, Charles-Augustin de Coulomb modeled this electrostatic force, so we call it Coulomb's law. This is a famous equation that every chemistry and physics student learns. It looks like this:

Here two objects are separated by a distance r. The values of their charges are q₁ and q₂ in units of, well, coulombs. In order to get the force in newtons, the standard unit for measuring a force (F), we need a constant of proportionality—that's k—the electric constant, also known as Coulomb’s constant. In these units it has a value of k = 8.987 x 10⁹ nm²/C² (newton-meters squared per coulomb squared … don’t worry about it).

That’s a big number, and it shows how strong electric interactions are—much stronger, in fact, than gravitational interactions. Surprised? It’s not something you notice, because all objects contain both positive and negative charges at the molecular level, so they have a roughly equal number of attractive and repulsive forces that mostly cancel. The gravitational interaction that keeps you pinned to the Earth is more obvious because it involves only an attractive force (you can’t have negative mass), and because we are puny specks on a giant rock.

How He Got It

To come up with this, Coulomb made an instrument called a torsion balance. It had a thin horizontal rod hanging from a fiber so it could rotate freely—all contained in a glass cylinder to shield it from errant breezes. Then he had two small metal balls, one stationary and one on the end of the rod (plus a counterweight on the other end so it balanced).

He then gave the two balls similar charges so they repelled, and he measured the deflection of the rod. Then, to vary the charges, he took one ball and touched it to an identical but uncharged ball, cutting its charge in half, and he remeasured. The rod moved away half as far.

This showed that the electric force (F) was proportional to the product of the charges (q₁q₂). Then, by varying the distance between the balls he found that F was inversely proportional to the distance squared (r²). That meant, e.g., that an attractive force between two charges grows very fast as they get closer to each other (i.e., as r gets smaller).

But how did he find the magical number k? You won’t like this answer, but Coulomb didn't know the value of Coulomb’s constant—which meant he couldn’t quantify the electric force (F). All he could say was that it was all proportional. His problem was that there was no way at the time to measure electrical charges. There were no coulombs in Coulomb’s day.

But by running similar experiments over time, later scientists gradually zeroed in on the value of the electric constant, which we now know is k = 8.987 x 10⁹ nm²/C².

The Permittivity of Free Space

We could stop there, but hey, science never stops. You know that. It turns out there's another constant that is related to Coulomb’s constant. We call it the “permittivity of free space” (ε₀), which sure sounds like fun. It tells us how hard it is to create an electric field in a vacuum. A smaller ε₀ , or lower permittivity, would mean you’d get a greater electric field from the same charge. Yes, that seems backwards, but it’s just how they defined it. It’s too late to change.

Is there a permittivity value for nonempty space too? Yup. We call that the dielectric permittivity (ε), and it depends on the type of material. For example, it's harder to generate an electric field in water than it is in glass, so water has a higher ε.

With this permittivity constant, we can rewrite Coulomb's law as the following:

All I’ve done is replace k with ¼πε₀, where ε₀ = 8.854 x 10^–12 C²/(nm²). That might seem like a pointless digression. But this enables us to do something pretty wonderful: We can create relationships with other fundamental constants. In particular, there’s a very cool relationship between permittivity (ε₀ )and the speed of light (c).

Here, the Greek letter mu, μ₀, is the magnetic constant, aka the permeability of free space. I’m going to do a whole other piece next week on this one, so stay tuned. For now, suffice it to say that both constants are in there because light is an electromagnetic wave.

This relationship holds for non-empty space too, where light has to travel through a medium like, say, water. But both constants would be much higher, which means light would travel much slower in water.

Remember when I said up top that physics constants were “fundamental”—they couldn’t be derived, only measured empirically? Well, as you can see, that wasn’t entirely true. The equation above places a constraint on these three particular constants, so we only need to measure two of them, and then we can compute the third. If we know the speed of light and the permeability, we can derive the permittivity and by extension the electric constant, k.

I know that sounds crazy, but at some point you have to realize that all of our units and constants are arbitrary. We have to pick some place to start finding values and then build our units like a house of cards. If you change one of them, the whole thing comes crashing down.

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Posted Monday 18 August 2025 at 2:46 am AEST (my time).

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The original version of this story appeared in Quanta Magazine.

There are precision measurements, and then there’s the Laser Interferometer Gravitational-Wave Observatory. In each of LIGO’s twin gravitational wave detectors (one in Hanford, Washington, and the other in Livingston, Louisiana), laser beams bounce back and forth down the four-kilometer arms of a giant L. When a gravitational wave passes through, the length of one arm changes relative to the other by less than the width of a proton. It’s by measuring these minuscule differences—a sensitivity akin to sensing the distance to the star Alpha Centauri down to the width of a human hair—that discoveries are made.

The design of the machine was decades in the making, as physicists needed to push every aspect to its absolute physical limits. Construction began in 1994 and took more than 20 years, including a four-year shutdown to improve the detectors, before LIGO detected its first gravitational wave in 2015: a ripple in the space-time fabric coming from the faraway collision of a pair of black holes.

Rana Adhikari, a physicist at the California Institute of Technology, led the detector optimization team in the mid-2000s. He and a handful of collaborators painstakingly honed parts of the LIGO design, exploring the contours of every limit that stood in the way of a more sensitive machine.

But after the 2015 detection, Adhikari wanted to see if they could improve upon LIGO’s design, enabling it, for instance, to pick up gravitational waves in a broader band of frequencies. Such an improvement would enable LIGO to see merging black holes of different sizes, as well as potential surprises. “What we’d really like to discover is the wild new astrophysical thing no one has imagined,” Adhikari said. “We should have no prejudice about what the universe makes.”

He and his team turned to AI—in particular, a software suite first created by the physicist Mario Krenn to design tabletop experiments in quantum optics. First, they gave the AI all the components and devices that could be mixed and matched to construct an arbitrarily complicated interferometer. The AI started off unconstrained. It could design a detector that spanned hundreds of kilometers and had thousands of elements, such as lenses, mirrors, and lasers.

Initially, the AI’s designs seemed outlandish. “The outputs that the thing was giving us were really not comprehensible by people,” Adhikari said. “They were too complicated, and they looked like alien things or AI things. Just nothing that a human being would make, because it had no sense of symmetry, beauty, anything. It was just a mess.”

The researchers figured out how to clean up the AI’s outputs to produce interpretable ideas. Even so, the researchers were befuddled by the AI’s design. “If my students had tried to give me this thing, I would have said, ‘No, no, that’s ridiculous,’” Adhikari said. But the design was clearly effective.

It took months of effort to understand what the AI was doing. It turned out that the machine had used a counterintuitive trick to achieve its goals. It added an additional three-kilometer-long ring between the main interferometer and the detector to circulate the light before it exited the interferometer’s arms. Adhikari’s team realized that the AI was probably using some esoteric theoretical principles that Russian physicists had identified decades ago to reduce quantum mechanical noise. No one had ever pursued those ideas experimentally. “It takes a lot to think this far outside of the accepted solution,” Adhikari said. “We really needed the AI.”

If the AI’s insights had been available when LIGO was being built, “we would have had something like 10 or 15 percent better LIGO sensitivity all along,” he said. In a world of sub-proton precision, 10 to 15 percent is enormous.

“LIGO is this huge thing that thousands of people have been thinking about deeply for 40 years,” said Aephraim Steinberg, an expert on quantum optics at the University of Toronto. “They’ve thought of everything they could have, and anything new [the AI] comes up with is a demonstration that it’s something thousands of people failed to do.”

Although AI has not yet led to new discoveries in physics, it’s becoming a powerful tool across the field. Along with helping researchers to design experiments, it can find nontrivial patterns in complex data. For example, AI algorithms have gleaned symmetries of nature from the data collected at the Large Hadron Collider in Switzerland. These symmetries aren’t new—they were key to Einstein’s theories of relativity—but the AI’s finding serves as a proof of principle for what’s to come. Physicists have also used AI to find a new equation for describing the clumping of the universe’s unseen dark matter. “Humans can start learning from these solutions,” Adhikari said.

Apart but Together

In the classical physics that describes our everyday world, objects have well-defined properties that are independent of attempts to measure those properties: A billiard ball, for example, has a particular position and momentum at any given moment in time.

In the quantum world, this isn’t the case. A quantum object is described by a mathematical entity called the quantum state. The best one can do is to use the state to calculate the probability that the object will be, say, at a certain location when you look for it there.

What is more, two (or more) quantum objects can share a single quantum state. Take light, which is made of photons. These photons can be generated in pairs that are “entangled,” meaning that the two photons share a single, joint quantum state even if they fly apart. Once one of the two photons is measured, the outcome seems to instantaneously determine the properties of the other—now distant—photon.

For decades, physicists assumed that entanglement required quantum objects to start out in the same place. But in the early 1990s, Anton Zeilinger, who would later receive the Nobel Prize in Physics for his studies of entanglement, showed that this wasn’t always true. He and his colleagues proposed an experiment that began with two unrelated pairs of entangled photons. Photons A and B were entangled with each other, as were photons C and D. The researchers then devised a clever experimental design made of crystals, beam splitters and detectors that would operate on photons B and C—one photon from each of the two entangled pairs. Through a sequence of operations, the photons B and C get detected and destroyed, but as a product, the partner particles A and D, which had not previously interacted, become entangled. This is called entanglement swapping, which is now an important building block of quantum technology

That was the state of affairs in 2021, when Krenn’s team started designing new experiments with the aid of software they dubbed PyTheus—Py for the programming language Python, and Theus for Theseus, after the Greek hero who killed the mythical Minotaur. The team represented optical experiments using mathematical structures called graphs, which are composed of nodes connected by lines called edges. The nodes and edges represented different aspects of an experiment, such as beam splitters, the paths of photons, or whether or not two photons had interacted.

Krenn’s team started by first building a very general graph, one that modeled the space of all possible experiments of some size. The graph had output features that represented some desired quantum state—say, two particles exiting the experimental setup that had never interacted but were now entangled.

The question, then, was how to modify all the other parts of the graph to produce this state. To figure this out, the researchers formulated a mathematical function. It took in the state of the graph and calculated the difference between the output of the graph and the desired quantum state. They then iteratively modified the graph’s parameters, which represented the experimental configuration, to reduce this discrepancy to zero.

When Krenn’s student Soren Arlt tried to use this approach to find the best way to do entanglement swapping, he noticed that the experimental configuration was unrecognizable—nothing at all like Zeilinger’s design from 1993. “When he showed it to me, we were confused,” Krenn said. “I was convinced that it must be wrong.”

The optimization algorithm had borrowed ideas from a separate area of study called multiphoton interference. By doing so, it created a simpler configuration than Zeilinger’s. Krenn’s team then did a separate mathematical analysis of the final design. It confirmed that the new experimental design would in fact create entanglement among particles with no shared past.

In December 2024, a team in China led by Xiao-Song Ma of Nanjing University confirmed it. They built the actual experiment, and it worked as intended.

Finding the Hidden Formula

Experimental design isn’t the only way that physicists are using AI. They’ve also put it to work parsing experimental results.

“Right now, I’d say it’s like teaching a child how to speak,” Kyle Cranmer, a physicist at the University of Wisconsin-Madison, said of the budding efforts to use AI to do physics. “We’re doing a lot of baby-sitting.” Even so, machine learning models trained on real-world and simulated data are discovering patterns that might otherwise have been missed.

For example, Cranmer and his collaborators used a machine learning model to predict the density of clumps of dark matter in the universe, based on observable properties of other such nearby clumps. Such calculations are necessary to understand the growth of galaxies and galaxy clusters. The system arrived at a formula to describe the density of dark matter clumps that better fit the data than a human-made one. The AI’s equation “describes the data very well,” Cranmer said. “But it’s lacking the story about how you get there.”

Sometimes it’s enough of a proof of principle to show that AI can rediscover things that people already know.

Rose Yu, a computer scientist at the University of California, San Diego, and colleagues have been training machine learning models to find symmetries in data. A symmetry implies that the data either remains unchanged or changes predictably and simply under a transformation. For example, a circle has rotational symmetry—it is invariant under rotation. Yu and her team applied their technique to data collected at the Large Hadron Collider and identified so-called Lorentz symmetries, which are crucial to Einstein’s theories of relativity. These are changes in perspective that leave the applicable laws of physics unchanged. For example, the rate of production of pairs of particles at the collider should not change at different times of day. If the rate varied, it would imply some dependence on Earth’s rotation and hence a preferential direction in space-time. “We showed that, without knowing any physics, the model can discover the Lorentz symmetry purely from data,” Yu said.

Cranmer and Yu point out that while such methods are good at discovering patterns, making sense of those patterns and coming up with hypotheses or the physics to explain them remains elusive for today’s AI models. But Cranmer thinks that the advent of large language models like ChatGPT could change that. “I think there’s a huge potential for language models to be useful to help automate that construction of hypotheses,” he said. “It’s kind of around the corner.”

Steinberg agrees that while AI has yet to invent new concepts, AI-aided discoveries of new physics could conceivably become reality. “We really might be crossing that threshold, which is exciting,” he said.

Original story reprinted with permission from Quanta Magazine, an editorially independent publication of the Simons Foundation whose mission is to enhance public understanding of science by covering research developments and trends in mathematics and the physical and life sciences.

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Posted Monday 18 August 2025 at 2:43 am AEST (my time).

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A satellite image of Erin shortly after becoming a Category 5 hurricane on Saturday.  

Credit: NOAA

After several days of working its way across the open and at times hostile Atlantic Ocean this week, Hurricane Erin found more favorable conditions and exploded in intensity on Friday night. Shortly before noon on Saturday, the National Hurricane Center declared that Erin had reached Category 5 status, the most powerful kind of hurricane.

This determination is based on sustained winds, which were measured by a US Air Force Hurricane Hunter aircraft on Saturday at 160 mph.

There is some good news: Erin is threading a needle with its projected track. Although it should pass close to several landmasses between now and next Thursday, Erin should remain far enough away to avoid catastrophic damage. Erin is presently passing to the north of the Caribbean islands, and will turn northward before reaching the Bahamas and the Eastern United States. Later next week it should follow a path that takes it between Atlantic Canada and Bermuda.

Forecasters have a reasonable amount of confidence in this track as trusted models have become fairly consistent in their output.

Getting big, fast

There is a sobering side to all of this as well. Erin only became a hurricane at 11 am ET on Friday, as it tracked north of the Leeward Islands. It was the first hurricane of the Atlantic season, which has been relatively slow to rumble to life this year.

Forecast track for Hurricane Erin.

Credit: National Hurricane Center

However, Erin's growth since then has been historic. Although the Category of a hurricane is based on its sustained winds, a more accurate measurement of a storm's intensity is its central pressure, measured in millibars. The standard pressure at the surface of the Earth is 1,013.25 mb. As they intensify, the central pressure of hurricanes drops, and the lower the pressure the more intense the storm.

According to meteorologist Sam Lillo, Erin deepened by 70 millibars in 24 hours from Friday morning to Saturday morning. This makes Erin the most rapidly intensifying hurricane, before Sept. 1, ever measured in the Atlantic Ocean.

With a central pressure of 917 mb on Saturday, Erin ranks as the second-most intense Atlantic in the last 50 years prior to today's date, behind only Hurricane Allen in 1980.

Rapid intensification becoming more common

Storms like Erin are predicted to become more common due to climate change, scientists say. One study in 2019 found that, for the strongest 5 percent of Atlantic hurricanes, 24-hour intensification rates increased by about 3–4 mph per decade from 1982 to 2009. "Our results suggest a detectable increase of Atlantic intensification rates with a positive contribution from anthropogenic forcing," the authors of the study, in Nature Communications, wrote.

Hurricane scientists generally agree that although the overall number of tropical storms and hurricanes may not increase in a warmer world, such background conditions are likely to produce more intense storms like Erin.

According to the US government's Climate.gov website, this increase in intensity of tropical cyclones (TCs) is happening due to human-caused climate change.

"The proportion of severe TCs (Category 4 & 5) has increased, possibly due to anthropogenic climate change," a coalition of authors wrote. "This proportion of intense TCs is projected to increase further, bringing a greater proportion of storms having more damaging wind speeds, higher storm surges, and more extreme rainfall rates. Most climate model studies project a corresponding reduction in the proportion of low-intensity cyclones, so the total number of TCs each year is projected to decrease or remain approximately the same."

To date this year the tropical Atlantic has seen lower overall activity than usual. But with Erin's longevity and intensity this season should soon reach and surpass normal levels of Accumulated Cyclone Energy, a measurement of a season's total activity. The Atlantic season typically peaks in early September, with the majority of storms forming between early August and early October.

Forecast models indicate the likely development of more hurricanes within the next two weeks, but there is no clear consensus on whether they will impact land.

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Posted Sunday 17 August 2025 at 6:56 am AEST (my time).

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Everything we see around us, from the ground beneath our feet to the most remote galaxies, is made of matter. For scientists, that has long posed a problem: According to physicists’ best current theories, matter and its counterpart, antimatter, ought to have been created in equal amounts at the time of the Big Bang. But antimatter is vanishingly rare in the universe. So what happened?

Physicists don’t know the answer to that question yet, but many think the solution must involve some subtle difference in the way that matter and antimatter behave. And right now, the most promising path into that unexplored territory centers on new experiments involving the mysterious subatomic particle known as the neutrino.

“It’s not to say that neutrinos are definitely the explanation of the matter-antimatter asymmetry, but a very large class of models that can explain this asymmetry are connected to neutrinos,” says Jessica Turner, a theoretical physicist at Durham University in the United Kingdom.

Let’s back up for a moment: When physicists talk about matter, that’s just the ordinary stuff that the universe is made of—mainly protons and neutrons (which make up the nuclei of atoms), along with lighter particles like electrons. Although the term “antimatter” has a sci-fi ring to it, antimatter is not all that different from ordinary matter. Typically, the only difference is electric charge: For example, the positron—the first antimatter particle to be discovered—matches an electron in its mass but carries a positive rather than a negative charge. (Things are a bit more complicated with electrically neutral particles. For example, a photon is considered to be its own antiparticle, but an antineutron is distinct from a neutron in that it’s made up of antiquarks rather than ordinary quarks.)

Various antimatter particles can exist in nature; they occur in cosmic rays and in thunderclouds, and are produced by certain kinds of radioactive decay. (Because people—and bananas—contain a small amount of radioactive potassium, they emit minuscule amounts of antimatter in the form of positrons.)

Small amounts of antimatter have also been created by scientists in particle accelerators and other experiments, at great effort and expense—putting a damper on science fiction dreams of rockets propelled by antimatter or planet-destroying weapons energized by it.

When matter and antimatter meet, they annihilate, releasing energy in the form of radiation. Such encounters are governed by Einstein’s famous equation, E=mc²—energy equals mass times the square of the speed of light — which says you can convert a little bit of matter into a lot of energy, or vice versa. (The positrons emitted by bananas and bodies have so little mass that we don’t notice the teeny amounts of energy released when they annihilate.) Because matter and antimatter annihilate so readily, it’s hard to make a chunk of antimatter much bigger than an atom, though in theory you could have everything from antimatter molecules to antimatter planets and stars.

But there’s a puzzle: If matter and antimatter were created in equal amounts at the time of the Big Bang, as theory suggests, shouldn’t they have annihilated, leaving a universe made up of pure energy? Why is there any matter left?

Physicists’ best guess is that some process in the early universe favored the production of matter compared to the production of antimatter — but exactly what that process was is a mystery, and the question of why we live in a matter-dominated universe is one of the most vexing problems in all of physics.

Crucially, physicists haven’t been able to think of any such process that would mesh with today’s leading theory of matter and energy, known as the Standard Model of particle physics. That leaves theorists seeking new ideas, some as-yet-unknown physics that goes beyond the Standard Model. This is where neutrinos come in.

A neutral answer

Neutrinos are tiny particles without any electric charge. (The name translates as “little neutral one.”) According to the Standard Model, they ought to be massless, like photons, but experiments beginning in the 1990s showed that they do in fact have a tiny mass. (They’re at least a million times lighter than electrons, the extreme lightweights among normal matter.) Since physicists already know that neutrinos violate the Standard Model by having mass, their hope is that learning more about these diminutive particles might yield insights into whatever lies beyond.

Neutrinos have been slow to yield their secrets, however, because they barely interact with other particles. About 60 billion neutrinos from the Sun pass through every square centimeter of your skin each second. If those neutrinos interacted with the atoms in our bodies, they would probably destroy us. Instead, they pass right through. “You most likely will not interact with a single neutrino in your lifetime,” says Pedro Machado, a physicist at Fermilab near Chicago. “It’s just so unlikely.”

Experiments, however, have shown that neutrinos “oscillate” as they travel, switching among three different identities—physicists call them “flavors”: electron neutrino, muon neutrino, and tau neutrino. Oscillation measurements have also revealed that different-flavored neutrinos have slightly different masses.

Neutrino oscillation is weird, but it may be weird in a useful way, because it might allow physicists to probe certain fundamental symmetries in nature—and these in turn may illuminate the most troubling of asymmetries, namely the universe’s matter-antimatter imbalance.

For neutrino researchers, a key symmetry is called charge-parity or CP symmetry. It’s actually a combination of two distinct symmetries: Changing a particle’s charge flips matter into antimatter (or vice versa), while changing a particle’s parity flips a particle into its mirror image (like turning a right-handed glove into a left-handed glove). So the CP-opposite version of a particle of ordinary matter is a mirror image of the corresponding antiparticle. But does this opposite particle behave exactly the same as the original one? If not, physicists say that CP symmetry is violated—a fancy way of saying that matter and antimatter behave slightly differently from one another. So any examples of CP symmetry violation in nature could help to explain the matter-antimatter imbalance.

In fact, CP violation has already been observed in some mesons, a type of subatomic particle typically made up of one quark and one antiquark, a surprising result first found in the 1960s. But it’s an extremely small effect, and it falls far short of being able to account for the universe’s matter-antimatter asymmetry.

In July 2025, scientists working at the Large Hadron Collider at CERN near Geneva reported clear evidence for a similar violation by one type of particle from a different family of subatomic particles known as baryons—but this newly observed CP violation is similarly believed to be much too small to account for the matter-antimatter imbalance.

Experiments on the horizon

So what about neutrinos? Do they violate CP symmetry—and if so, do they do it in a big enough way to explain why we live in a matter-dominated universe? This is precisely the question being addressed by a new generation of particle physics experiments. Most ambitious among them is the Deep Underground Neutrino Experiment (DUNE), which is now under construction in the United States; data collection could begin as early as 2029.

DUNE will employ the world’s most intense neutrino beam, which will fire both neutrinos and antineutrinos from Fermilab to the Sanford Underground Research Facility, located 800 miles away in South Dakota. (There’s no tunnel; the neutrinos and antineutrinos simply zip through the earth, for the most part hardly noticing that it’s there.) Detectors at each end of the beam will reveal how the particles oscillate as they traverse the distance between the two labs—and whether the behavior of the neutrinos differs from that of the antineutrinos.

DUNE won’t pin down the precise amount of neutrinos’ CP symmetry violation (if there is any), but it will set an upper limit on it. The larger the possible effect, the greater the discrepancy in the behavior of neutrinos versus antineutrinos, and the greater the likelihood that neutrinos could be responsible for the matter-antimatter asymmetry in the early universe.

For Shirley Li, a physicist at the University of California, Irvine, the issue of neutrino CP violation is an urgent question, one that could point the way to a major rethink of particle physics. “If I could have one question answered by the end of my lifetime, I would want to know what that’s about,” she says.

Aside from being a major discovery in its own right, CP symmetry violation in neutrinos could challenge the Standard Model by pointing the way to other novel physics. For example, theorists say it would mean there could be two kinds of neutrinos—left-handed ones (the normal lightweight ones observed to date) and much heavier right-handed neutrinos, which are so far just a theoretical possibility. (The particles’ “handedness” refers to their quantum properties.)

These right-handed neutrinos could be as much as 10¹⁵ times heavier than protons, and they’d be unstable, decaying almost instantly after coming into existence. Although they’re not found in today’s universe, physicists suspect that right-handed neutrinos may have existed in the moments after the Big Bang — possibly decaying via a process that mimicked CP violation and favored the creation of matter over antimatter.

It’s even possible that neutrinos can act as their own antiparticles—that is, that neutrinos could turn into antineutrinos and vice versa. This scenario, which the discovery of right-handed neutrinos would support, would make neutrinos fundamentally different from more familiar particles like quarks and electrons. If antineutrinos can turn into neutrinos, that could help explain where the antimatter went during the universe’s earliest moments.

One way to test this idea is to look for an unusual type of radioactive decay — theorized but thus far never observed—known as “neutrinoless double-beta decay.” In regular double-beta decay, two neutrons in a nucleus simultaneously decay into protons, releasing two electrons and two antineutrinos in the process. But if neutrinos can act as their own antiparticles, then the two neutrinos could annihilate each other, leaving only the two electrons and a burst of energy.

A number of experiments are underway or planned to look for this decay process, including the KamLAND-Zen experiment, at the Kamioka neutrino detection facility in Japan; the nEXO experiment at the SNOLAB facility in Ontario, Canada; the NEXT experiment at the Canfranc Underground Laboratory in Spain; and the LEGEND experiment at the Gran Sasso laboratory in Italy. KamLAND-Zen, NEXT, and LEGEND are already up and running.

While these experiments differ in the details, they all employ the same general strategy: They use a giant vat of dense, radioactive material with arrays of detectors that look for the emission of unusually energetic electrons. (The electrons’ expected neutrino companions would be missing, with the energy they would have had instead carried by the electrons.)

While the neutrino remains one of the most mysterious of the known particles, it is slowly but steadily giving up its secrets. As it does so, it may crack the puzzle of our matter-dominated universe — a universe that happens to allow inquisitive creatures like us to flourish. The neutrinos that zip silently through your body every second are gradually revealing the universe in a new light.

“I think we’re entering a very exciting era,” says Turner.

This article originally appeared in Knowable Magazine, a nonprofit publication dedicated to making scientific knowledge accessible to all. Sign up for Knowable Magazine’s newsletter.

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Posted Sunday 17 August 2025 at 6:54 am AEST (my time).

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Subscriptions. Subscriptions. It seems they are hard to escape these days. The average UK citizen, for instance, juggles three subscriptions per month for everything from video streaming to meal kits. Well, if you are one of those people and you buy a Volkswagen, that number might be about to become four, at least if you want to unlock the full power of the Volkswagen car you just bought.

According to Volkswagen, this optional power upgrade for its electric ID.3 range in the UK comes in at around £16.50 per month or £165 annually. A customer can also choose a £649 "lifetime" subscription, but that is tied to the car, not the individual. If you sell your car and buy another ID.3, you would have to pay the fee again. Paying for the upgrade will increase the horsepower of the ID.3 Pro and Pro S models from their standard 201bhp to the full 228bhp the hardware is capable of delivering.

Volkswagen, in a statement to the BBC, defended the decision by claiming the ability to purchase more power was "nothing new". A spokesperson for the car manufacturer drew a parallel to the past, stating, "Historically, many petrol and diesel vehicles have been offered with engines of the same size, but with the possibility of choosing one with more potency."

Volkswagen claims the option allows customers to get a "sportier" driving experience at any time without committing to a higher initial vehicle price.

Still, the idea of paying a monthly fee to essentially flip a boolean somewhere in the car's software might not sit right with people who believe they should get everything the hardware they paid for can offer. With these kinds of software-locked features becoming more common, it will probably not be long until someone figures out a jailbreak to unlock the performance without paying the recurring fee.

In case you missed it, a few days ago, another electric car manufacturer, Hyundai, came under fire for charging UK owners of the Ioniq 5 for a critical cybersecurity patch. That update was meant to fix a major security flaw that made the Ioniq 5, Kia EV6, and Genesis GV60 some of the most stolen cars in the country. You can check out our full coverage here.

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Posted Saturday 16 August 2025 at 6:00 pm AEST (my time).

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SpaceX is continuing with final preparations for the 10th full-scale test flight of the company's enormous Starship rocket after receiving launch approval Friday from the Federal Aviation Administration.

Engineers completed a final test of Starship's propulsion system with a so-called "spin prime" test Wednesday at the launch site in South Texas. Ground crews then rolled the ship back to a nearby hangar for engine inspections, touchups to its heat shield, and a handful of other chores to ready it for liftoff.

SpaceX has announced the launch is scheduled for no earlier than next Sunday, August 24, at 6:30 pm local time in Texas (23:30 UTC).

Like all previous Starship launches, the huge 403-foot-tall (123-meter) rocket will take off from SpaceX's test site in Starbase, Texas, just north of the US-Mexico border. The rocket consists of a powerful booster stage named Super Heavy, with 33 methane-fueled Raptor engines. Six Raptors power the upper stage, known simply as Starship.

With this flight, SpaceX officials hope to put several technical problems with the Starship program behind them. SpaceX is riding a streak of four disappointing Starship test flights from January through May, and and the explosion and destruction of another Starship vehicle during a ground test in June.

These setbacks followed a highly successful year for the world's largest rocket in 2024, when SpaceX flew Starship four times and achieved new objectives on each flight. These accomplishments included the first catch of a Super Heavy booster back at the launch pad, proving the company's novel concept for recovering and reusing the rocket's first stage.

Starship's record so far in 2025 is another story. The rocket's inability to make it through an entire suborbital test flight has pushed back future program milestones, such as the challenging tasks of recovering and reusing the rocket's upper stage, and demonstrating the ability to refuel another rocket in orbit. Those would both be firsts in the history of spaceflight.

These future tests, and more, are now expected to occur no sooner than next year. This time last year, SpaceX officials hoped to achieve them in 2025. All of these demonstrations are vital for Elon Musk to meet his promise of sending numerous Starships to build a settlement on Mars. Meanwhile, NASA is eager for SpaceX to reel off these tests as quickly as possible because the agency has selected Starship as the human-rated lunar lander for the Artemis Moon program. Once operational, Starship will also be key to building out SpaceX's next-generation Starlink broadband network.

A good outcome on the next Starship test flight would give SpaceX footing to finally take a step toward these future demos after months of dithering over design dilemmas.

The FAA said Friday it formally closed the investigation into Starship's most recent in-flight failure in May, when the rocket started leaking propellant after reaching space, rendering it unable to complete the test flight.

"The FAA oversaw and accepted the findings of the SpaceX-led investigation," the federal regulator said in a statement. "The final mishap report cites the probable root cause for the loss of the Starship vehicle as a failure of a fuel component. SpaceX identified corrective actions to prevent a reoccurrence of the event."

Diagnosing failures

SpaceX identified the most probable cause for the May failure as a faulty main fuel tank pressurization system diffuser located on the forward dome of Starship's primary methane tank. The diffuser failed a few minutes after launch, when sensors detected a pressure drop in the main methane tank and a pressure increase in the ship's nose cone just above the tank.

The rocket compensated for the drop in main tank pressure and completed its engine burn, but venting from the nose cone and a worsening fuel leak overwhelmed Starship's attitude control system. Finally, detecting a major problem, Starship triggered automatic onboard commands to vent all remaining propellant into space and "passivate" itself before an unguided reentry over the Indian Ocean, prematurely ending the test flight.

Engineers recreated the diffuser failure on the ground during the investigation, and then redesigned the part to better direct pressurized gas into the main fuel tank. This will also "substantially decrease" strain on the diffuser structure, SpaceX said.

The FAA, charged with ensuring commercial rocket launches don't endanger public safety, signed off on the investigation and gave the green light for SpaceX to fly Starship again when it is ready.

"SpaceX can now proceed with Starship Flight 10 launch operations under its current license," the FAA said.

"The upcoming flight will continue to expand the operating envelope on the Super Heavy booster, with multiple landing burn tests planned," SpaceX said in an update posted to its website Friday. "It will also target similar objectives as previous missions, including Starship's first payload deployment and multiple reentry experiments geared towards returning the upper stage to the launch site for catch."

In the aftermath of the test flight in May, SpaceX hoped to fly Starship again by late June or early July. But another accident June 18, this time on the ground, delayed the program another couple of months. The Starship vehicle SpaceX assigned to the next flight, designated Ship 36, exploded on a test stand in Texas as teams filled it with cryogenic propellants for an engine test-firing.

The accident destroyed the ship and damaged the test site, prompting SpaceX to retrofit the sole active Starship launch pad to support testing of the next ship in line—Ship 37. Those tests included a brief firing of all six of the ship's Raptor engines August 1.

After Ship 37's final spin prime test Wednesday, workers transported the rocket back to a hangar for evaluation, and crews immediately got to work transitioning the launch pad back to its normal configuration to host a full Super Heavy/Starship stack.

SpaceX said the explosion on the test stand in June was likely caused by damage to a high-pressure nitrogen storage tank inside Starship's payload bay section. This tank, called a composite overwrapped pressure vessel, or COPV, violently ruptured and led to the ship's fiery demise. SpaceX said COPVs on upcoming flights will operate at lower pressures, and managers ordered additional inspections on COPVs to look for damage, more proof testing, more stringent acceptance criteria, and a hardware change to address the problem.

That was followed in March by another Starship launch that had a similar result, again scattering debris near the Bahamas. In May, the ninth Starship test flight made it farther downrange and completed its engine burn before spinning out of control in space, preventing it from making a guided reentry to gather data on its heat shield.

Mastering the design of Starship's heat shield is critical the future of the program. As it has on all of this year's test flights, SpaceX has installed on the next Starship several different ceramic and metallic tile designs to test alternative materials to protect the vehicle during its scorching plunge back into Earth's atmosphere. Starship successfully made it through reentry for a controlled splashdown in the sea several times last year, but sensors detected hot spots on the rocket's stainless steel skin after some of the tiles fell off during launch and descent.

Making the Starship upper stage reusable like the Super Heavy booster will require better performance from the heat shield. The demands of flying the ship home from orbit and attempting a catch at the launch pad far outweigh the challenge of recovering a booster. Coming back from space, the ship encounters much higher temperatures than the booster sees at lower velocities.

Therefore, SpaceX's most important goal for the 10th Starship flight will be gathering information about how well the ship's different heat shield materials hold up during reentry. Engineers want to have this data as soon as possible to inform design decisions about the next iteration of Starship—Version 3 or Block 3—that will actually fly into orbit. So far, all Starship launches have intentionally targeted a speed just shy of orbital velocity, bringing the vehicle back through the atmosphere halfway around the world.

Other objectives on the docket for Starship Flight 10 include the deployment of spacecraft simulators mimicking the size of SpaceX's next-generation Starlink Internet satellites. Like the heat shield data, this has been part of the flight plan for the last three Starship launches, but the rocket never made it far enough to attempt any payload deployment tests.

Engineers also plan to put the Super Heavy booster through the wringer on the next launch. Instead of coming back to Starbase for a catch at the launch pad—something SpaceX has now done three times—the massive booster stage will target a controlled splashdown in the Gulf of Mexico east of the Texas coast. This will give SpaceX room to try new things with the booster, such as controlling the rocket's final descent with a different mix of engines to see if it could overcome a problem with one of its three primary landing engines.

SpaceX tried to experiment with new ways of landing of the Super Heavy booster on the last test flight, too. The Super Heavy exploded before reaching the ocean, likely due to a structural failure of the rocket's fuel transfer tube, an internal pipe where methane flows from the fuel tank at the top of the rocket to the engines at the bottom of the booster. SpaceX said the booster flew a higher angle of attack during its descent in May to test the limits of the rocket's performance. It seems engineers found the limit, and the booster won't fly at such a high angle of attack next time.

SpaceX has just two Starship Version 2 vehicles in its inventory before moving on to the taller Version 3 configuration, which will also debut improved Raptor engines.

"Every lesson learned, through both flight and ground testing, continues to feed directly into designs for the next generation of Starship and Super Heavy," SpaceX said. "Two flights remain with the current generation, each with test objectives designed to expand the envelope on vehicle capabilities as we iterate towards fully and rapidly reusable, reliable rockets."

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Posted Saturday 16 August 2025 at 5:57 pm AEST (my time).

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Welcome to Edition 8.06 of the Rocket Report! Two of the world's most storied rocket builders not named SpaceX achieved major successes this week. Arianespace's Ariane 6 rocket launched from French Guiana on its third flight Tuesday night with a European weather satellite. Less than 20 minutes later, United Launch Alliance's third Vulcan rocket lifted off from Florida on a US military mission. These are two of the three big rockets developed in the Western world that have made their orbital debuts in the last two years, alongside Blue Origin's New Glenn launcher. Ariane 6 narrowly won the "race" to reach its third orbital flight, but if you look at it another way, Ariane 6 reached its third flight milestone 13 months after its inaugural launch. It took Vulcan more than 19 months, and New Glenn has flown just once. SpaceX's Super Heavy/Starship rocket has flown nine times but has yet to reach orbit.

As always, we welcome reader submissions. If you don't want to miss an issue, please subscribe using the box below (the form will not appear on AMP-enabled versions of the site). Each report will include information on small-, medium-, and heavy-lift rockets, as well as a quick look ahead at the next three launches on the calendar.

Sixth success for sea-launched Chinese rocket. Private Chinese satellite operator Geespace added 11 spacecraft to its expanding Internet of Things constellation on August 8, aiming to boost low-power connectivity in key emerging markets, Space News reports. The 11 satellites rode into orbit aboard a solid-fueled Jielong 3 (Smart Dragon 3) rocket lifting off from an ocean platform in the Yellow Sea off the coast of Rizhao, a city in eastern China's Shandong province. This was the sixth flight of the Jielong 3, a rocket developed by a commercially oriented spinoff of the state-owned China Academy of Launch Vehicle Technology.

Mistaken for a meteor ... The fourth stage of the Jielong 3 rocket, left in orbit after deploying its 11 satellite payloads, reentered the atmosphere late Sunday night. The fiery and destructive reentry created a fireball that streaked across the skies over Spain, the Spanish newspaper El Mundo reports. Many Spanish residents identified the streaking object as a meteor associated with the Perseid meteor shower. But it turned out to be a piece of China's Jielong 3 rocket. Any debris that may have survived the scorching reentry likely fell into the Mediterranean Sea.

Portugal green-lights Azores spaceport. The Portuguese government has granted the Atlantic Spaceport Consortium a license to build and operate a rocket launch facility on the island of Santa Maria in the Azores, European Spaceflight reports. The Atlantic Spaceport Consortium (ASC) was founded in 2019 with the goal of developing a commercial spaceport on Santa Maria, 1,500 kilometers off the Portuguese mainland. In September 2024, the company showcased the island's suitability as a launch site by launching two small solid-fuel amateur-class rockets that it developed in-house.

What's on deck? ... The spaceport license granted by Portugal's regulatory authorities does not cover individual launches themselves. Those must be approved in a separate licensing process. It's likely that the launch site on Santa Maria Island will initially host suborbital launches, including flights by the Polish rocket company SpaceForest. The European Space Agency has also selected Santa Maria as the landing site for the first flight of the Space Rider lifting body vehicle after it launches into orbit, perhaps in 2027. (submitted by claudiodcsilva)

Why is Jeff Bezos buying launches from Elon Musk? Early Monday morning, a Falcon 9 rocket lifted off from its original launch site in Florida. Remarkably, it was SpaceX's 100th launch of the year. Perhaps even more notable was the rocket's payload: two-dozen Project Kuiper satellites, which were dispensed into low-Earth orbit on target, Ars reports. This was SpaceX's second launch of satellites for Amazon, which is developing a constellation to deliver low-latency broadband Internet around the world. SpaceX, then, just launched a direct competitor to its Starlink network into orbit. And it was for the founder of Amazon, Jeff Bezos, who owns a rocket company of his own in Blue Origin.

Several answers ... So how did it come to this—Bezos and Elon Musk, competitors in so many ways, working together in space? There are several answers. Most obviously, launching payloads for customers is one of SpaceX's two core business areas, alongside Starlink. SpaceX sells launch services to all comers and typically offers the lowest price per kilogram to orbit. There's immediate revenue to be made if a company with deep pockets like Amazon is willing to pay SpaceX. Second, the other options to get Kuiper satellites into orbit just aren't available at the volume Amazon needs. Amazon has reserved the lion's share of its Kuiper launches with SpaceX's competitors: United Launch Alliance, Arianespace, and Jeff Bezos' own space company Blue Origin. Lastly, SpaceX could gain some leverage by providing launch services to Amazon. In return for a launch, SpaceX has asked other companies with telecom satellites, such as OneWeb and Kepler Communications, to share spectrum rights to enable Starlink to expand into new markets.

Trump orders cull of commercial launch regulations. President Donald Trump signed an executive order on Wednesday directing government agencies to "eliminate or expedite" environmental reviews for commercial launch and reentry licenses, Ars reports. The FAA, part of the Department of Transportation, is responsible for granting the licenses after ensuring launch and reentries don't endanger the public, comply with environmental laws, and comport with US national interests. The drive toward deregulation will be welcome news for companies like SpaceX, led by onetime Trump ally Elon Musk; SpaceX conducts nearly all of the commercial launches and reentries licensed by the FAA.

Deflecting scrutiny? ... The executive order does several things, and not all of them will be as controversial as the potential elimination of environmental reviews. The order includes a clause directing the government to reevaluate, amend, or rescind a slate of launch-safety regulations written during the first Trump administration. The FAA published the new regulations, known as Part 450, in 2020, and they went into effect in 2021, but space companies have complained that they are too cumbersome and have slowed down the license approval process. The Biden administration established a committee last year to look at reforming the regulations in response to industry's outcry. Another part of the order that will likely lack bipartisan support is a call for making the head of the FAA's commercial spaceflight division a political appointee. This job has historically been held by a career civil servant.

Ariane 6 launches European weather satellite. Europe's new Ariane 6 rocket successfully launched for a third time on Tuesday night, carrying a satellite into orbit for weather forecasting and climate monitoring, Euronews reports. "The success of this second commercial launch confirms the performance, reliability, and precision of Ariane 6," said Martin Sion, CEO of ArianeGroup, operator of the rocket. "Once again, the new European heavy-lift launcher meets Europe's needs, ensuring sovereign access to space," Sion added. It marks the second commercial flight of the rocket, which has been in development for almost a decade with the European Space Agency (ESA). It is significant as it gives Europe independent access to space and reduces its reliance on Elon Musk's SpaceX.

Eumetsat returns to Europe ... The polar-orbiting weather satellite launched by the Ariane 6 rocket this week is owned by the European Organization for the Exploitation of Meteorological Satellites, or Eumetsat. Headquartered in Germany, Eumetsat is a multinational organization that owns and operates geostationary and polar-orbiting weather satellites, watching real-time storm development over Europe and Africa, while feeding key data into global weather and climate models. Just last month, Eumetsat's newest geostationary weather satellite launched from Florida on a SpaceX Falcon 9 rocket because of delays with the Ariane 6 program.

Rocket Lab isn't giving up on 2025 yet. Rocket Lab continues to push for a first launch of its medium-lift Neutron rocket before the end of the year, but company executives acknowledge that schedule has no margin for error, Space News reports. It may seem unlikely, but Rocket Lab's founder and CEO, Peter Beck, said in a conference call with investment analysts last week that the company has a "green light" schedule to debut the Neutron rocket within the next four-and-a-half months. There's still much work to do to prepare for the first launch, and the inaugural flight seems almost certain to slip into 2026.

Launch pad nearly complete ... Rocket Lab plans to host a ribbon-cutting at the Neutron rocket's new launch pad on Wallops Island, Virginia, on August 28. This launch pad is located just south of the spaceport's largest existing launch facility, where Northrop Grumman's Antares rocket lifts off on resupply missions to the International Space Station. Rocket Lab has a small launch pad for its light-class Electron launcher co-located with the Antares pad at Wallops.

Chinese company reveals drone ship. The Chinese launch company iSpace has released the first photos of an ocean-going recovery ship to support the landings of reusable first-stage boosters. The company hosted a dedication ceremony in Yangzhou, China, earlier this month for the vessel, which looks similar to SpaceX's rocket landing drone ships. In a press release, iSpace said the ship, named "Interstellar Return," is China's first marine rocket recovery ship, and the fifth such vessel in the world. SpaceX has three drone ships in its fleet for the Falcon 9 rocket, and Blue Origin has one for the New Glenn booster.

Rocket agnostic ... The recovery ship will be compatible with various medium- and large-sized reusable rockets, iSpace said. But its main use will be as the landing site for the first stage booster for iSpace's own Hyperbola 3 rocket, a medium-lift launcher with methane-fueled engines. The company has completed multiple vertical takeoff and landing tests of prototype boosters for the Hyperbola 3. The recovery ship measures about 100 meters long and 42 meters wide, with a displacement of 17,000 metric tons, and it has the ability to perform "intelligent unmanned operations" thanks to a dynamic positioning system, according to iSpace.

Vulcan's first national security launch. United Launch Alliance delivered multiple US military satellites into a high-altitude orbit after a prime-time launch Tuesday night, marking an important transition from development to operations for the company's new Vulcan rocket, Ars reports. This mission, officially designated USSF-106 by the US Space Force, was the first flight of ULA's Vulcan rocket to carry national security payloads. Two test flights of the Vulcan rocket last year gave military officials enough confidence to certify it for launching the Pentagon's medium-to-large space missions.

Secrecy in the fairing  ... The Vulcan rocket's Centaur upper stage released its payloads into geosynchronous orbit more than 22,000 miles (nearly 36,000 kilometers) over the equator roughly seven hours after liftoff. One of the satellites deployed by the Vulcan rocket is an experimental navigation testbed named NTS-3. It will demonstrate new technologies that could be used on future GPS navigation satellites. But the Space Force declined to disclose any information about the mission's other payloads.

Artemis II crew trains for nighttime ops. The four astronauts training to fly around the Moon on NASA's Artemis II mission next year have been at Kennedy Space Center in Florida this week. One of the reasons they were at Kennedy was to run through a rehearsal for what it will be like to work at the launch pad if the Artemis II mission ends up lifting off at night. Astronauts Reid Wiseman, Victor Glover, Christina Koch, and Jeremy Hansen put on their spacesuits and rehearsed emergency procedures at Launch Complex 39B, replicating a daytime simulation they participated in last year.

Moving forward ... The astronauts also went inside the Vehicle Assembly Building to practice using egress baskets they would use to quickly escape the launch pad in the event of a prelaunch emergency. The baskets are fastened to the mobile launch tower inside the VAB, where technicians are assembling and testing the Space Launch System rocket for the Artemis II mission. Later this year, the astronauts will return to Kennedy for a two-part countdown demonstration test. First, the crew members will board their Orion spacecraft once it's stacked atop the SLS rocket inside the VAB. Then, in part two, the astronauts will again rehearse emergency evacuation procedures once the rocket rolls to the launch pad.

China's Long March 5B flies again. China is ramping up construction of its national satellite-Internet megaconstellation with the successful deployment of another batch of Guowang satellites by a heavy-lift Long March 5B rocket on Wednesday, Space.com reports. Guowang, whose name translates as "national network," will be operated by China SatNet, a state-run company established in 2021. The constellation will eventually consist of about 13,000 satellites if all goes to plan.

Make this make sense ... Guowang is a long way from that goal. Wednesday's launch was the eighth overall for the network, but it was the fourth for the project in less than three weeks. Each mission lofts just five to 10 Guowang spacecraft, apparently because each satellite is quite large. For comparison, SpaceX launches 24 to 28 satellites on each mission to assemble its Starlink broadband megaconstellation, which currently consists of nearly 8,100 operational spacecraft. The Long March 5B is China's most powerful operational rocket, with a lift capacity somewhat higher than SpaceX's Falcon 9 but below that of the Falcon Heavy. It begs the question of just how big the Guowang satellites really are, and do they have a purpose beyond broadband Internet service?

Next three launches

Aug. 16: Kinetica 1 | Unknown Payload | Jiuquan Satellite Launch Center, China | 07:35 UTC

Aug. 17: Long March 4C | Unknown Payload | Xichang Satellite Launch Center, China | 09:05 UTC

Aug. 17: Long March 6A | Unknown Payload | Taiyuan Satellite Launch Center, China | 14:15 UTC

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Posted Saturday 16 August 2025 at 4:54 am AEST (my time).

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In a new entry -- PayPal use on Steam is currently unavailable in my currency. Why? -- Valve explains that PayPal transactions on Steam are limited to EUR, CAD, GBP, JPY, AUD, and USD for the time being. Any other currency, big or small, is not accepted currently.

Valve claims that PayPal notified them that it would "immediately terminate" any transactions related to Steam that were not in one of the currencies mentioned. Neither Valve nor PayPal offered additional insights. It is unclear why PayPal is blocking transactions for the majority of currencies and regions at the time of writing.

In other words: PayPal users from Switzerland, Brazil, Poland, South Africa, Turkey, South Korea and dozens of other countries can't use PayPal anymore to buy digital games or assets on Steam.

Valve suggests that Steam users use other means in the meantime. This may include using a credit card, direct bank transfers, or adding funds to Steam Wallets using codes or physical gift cards.

You can select a payment method on the review and purchase page. There you may select one of the available payment methods. PayPal should not be available, if your country's currency is not one of the six that are still supported on Steam.

It is unclear at this point whether this is another fallout of Valve's recent change regarding adult content on Steam, which Valve claims came after it was pressured by payment processors. This happened last month, but the PayPal issue seemed to predate this by a few days at least.

This is not the first time that Steam users ran into troubles when trying to use PayPal to buy games. For a time, PayPal was not even supported on Steam.

There is a chance that things may change in the near future. Valve says that it is in contact with PayPal to find a solution for the issue.

What about you? Do you use Steam or other gaming stores to buy digital games? If so, what is your preferred payment method and why? Feel free to leave a comment down below.

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Posted Friday 15 August 2025 at 4:36 am AEST (my time).

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When something goes wrong with an AI assistant, our instinct is to ask it directly: “What happened?” or “Why did you do that?” It's a natural impulse—after all, if a human makes a mistake, we ask them to explain. But with AI models, this approach rarely works, and the urge to ask reveals a fundamental misunderstanding of what these systems are and how they operate.

A recent incident with Replit's AI coding assistant perfectly illustrates this problem. When the AI tool deleted a production database, user Jason Lemkin asked it about rollback capabilities. The AI model confidently claimed rollbacks were “impossible in this case” and that it had “destroyed all database versions.” This turned out to be completely wrong—the rollback feature worked fine when Lemkin tried it himself.

And after xAI recently reversed a temporary suspension of the Grok chatbot, users asked it directly for explanations. It offered multiple conflicting reasons for its absence, some of which were controversial enough that NBC reporters wrote about Grok as if it were a person with a consistent point of view, titling an article, “xAI's Grok Offers Political Explanations for Why It Was Pulled Offline.”

Why would an AI system provide such confidently incorrect information about its own capabilities or mistakes? The answer lies in understanding what AI models actually are—and what they aren't.

There’s Nobody Home

The first problem is conceptual: You're not talking to a consistent personality, person, or entity when you interact with ChatGPT, Claude, Grok, or Replit. These names suggest individual agents with self-knowledge, but that's an illusion created by the conversational interface. What you're actually doing is guiding a statistical text generator to produce outputs based on your prompts.

There is no consistent “ChatGPT” to interrogate about its mistakes, no singular “Grok” entity that can tell you why it failed, no fixed “Replit” persona that knows whether database rollbacks are possible. You're interacting with a system that generates plausible-sounding text based on patterns in its training data (usually trained months or years ago), not an entity with genuine self-awareness or system knowledge that has been reading everything about itself and somehow remembering it.

Once an AI language model is trained (which is a laborious, energy-intensive process), its foundational “knowledge” about the world is baked into its neural network and is rarely modified. Any external information comes from a prompt supplied by the chatbot host (such as xAI or OpenAI), the user, or a software tool the AI model uses to retrieve external information on the fly.

In the case of Grok above, the chatbot's main source for an answer like this would probably originate from conflicting reports it found in a search of recent social media posts (using an external tool to retrieve that information), rather than any kind of self-knowledge as you might expect from a human with the power of speech. Beyond that, it will likely just make something up based on its text-prediction capabilities. So asking it why it did what it did will yield no useful answers.

The Impossibility of LLM Introspection

Large language models (LLMs) alone cannot meaningfully assess their own capabilities for several reasons. They generally lack any introspection into their training process, have no access to their surrounding system architecture, and cannot determine their own performance boundaries. When you ask an AI model what it can or cannot do, it generates responses based on patterns it has seen in training data about the known limitations of previous AI models—essentially providing educated guesses rather than factual self-assessment about the current model you're interacting with.

A 2024 study by Binder et al. demonstrated this limitation experimentally. While AI models could be trained to predict their own behavior in simple tasks, they consistently failed at “more complex tasks or those requiring out-of-distribution generalization.” Similarly, research on “recursive introspection” found that without external feedback, attempts at self-correction actually degraded model performance—the AI's self-assessment made things worse, not better.

This leads to paradoxical situations. The same model might confidently claim impossibility for tasks it can actually perform, or conversely, claim competence in areas where it consistently fails. In the Replit case, the AI's assertion that rollbacks were impossible wasn't based on actual knowledge of the system architecture—it was a plausible-sounding confabulation generated from training patterns.

Consider what happens when you ask an AI model why it made an error. The model will generate a plausible-sounding explanation because that's what the pattern completion demands—there are plenty of examples of written explanations for mistakes on the Internet, after all. But the AI's explanation is just another generated text, not a genuine analysis of what went wrong. It's inventing a story that sounds reasonable, not accessing any kind of error log or internal state.

Unlike humans who can introspect and assess their own knowledge, AI models don't have a stable, accessible knowledge base they can query. What they "know" only manifests as continuations of specific prompts. Different prompts act like different addresses, pointing to different—and sometimes contradictory—parts of their training data, stored as statistical weights in neural networks.

This means the same model can give completely different assessments of its own capabilities depending on how you phrase your question. Ask “Can you write Python code?” and you might get an enthusiastic yes. Ask “What are your limitations in Python coding?” and you might get a list of things the model claims it cannot do—even if it regularly does them successfully.

The randomness inherent in AI text generation compounds this problem. Even with identical prompts, an AI model might give slightly different responses about its own capabilities each time you ask.

Other Layers Also Shape AI Responses

Even if a language model somehow had perfect knowledge of its own workings, other layers of AI chatbot applications might be completely opaque. For example, modern AI assistants like ChatGPT aren't single models but orchestrated systems of multiple AI models working together, each largely “unaware” of the others’ existence or capabilities. For instance, OpenAI uses separate moderation layer models whose operations are completely separate from the underlying language models generating the base text.

When you ask ChatGPT about its capabilities, the language model generating the response has no knowledge of what the moderation layer might block, what tools might be available in the broader system, or what post-processing might occur. It's like asking one department in a company about the capabilities of a department it has never interacted with.

Perhaps most importantly, users are always directing the AI's output through their prompts, even when they don't realize it. When Lemkin asked Replit whether rollbacks were possible after a database deletion, his concerned framing likely prompted a response that matched that concern—generating an explanation for why recovery might be impossible rather than accurately assessing actual system capabilities.

This creates a feedback loop where worried users asking “Did you just destroy everything?” are more likely to receive responses confirming their fears, not because the AI system has assessed the situation, but because it's generating text that fits the emotional context of the prompt.

A lifetime of hearing humans explain their actions and thought processes has led us to believe that these kinds of written explanations must have some level of self-knowledge behind them. That's just not true with LLMs that are merely mimicking those kinds of text patterns to guess at their own capabilities and flaws.

This story originally appeared on Ars Technica.

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Posted Friday 15 August 2025 at 4:35 am AEST (my time).

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Most people would recognize the device in the image above, although they probably wouldn't know it by its formal name: the Crookes radiometer. As its name implies, placing the radiometer in light produces a measurable change: the blades start spinning.

Unfortunately, many people misunderstand the physics of its operation (which we'll return to shortly). The actual forces that drive the blades to spin, called photophoresis, can act on a variety of structures as long as they're placed in a sufficiently low-density atmosphere. Now, a team of researchers has figured out that it may be possible to use the photophoretic effect to loft thin sheets of metal into the upper atmosphere of Earth and other planets. While their idea is to use it to send probes to the portion of the atmosphere that's too high for balloons and too low for satellites, they have tested some working prototypes a bit closer to the Earth's surface.

Photophoresis

It's quite common—and quite wrong—to see explanations of the Crookes radiometer that involve radiation pressure. Supposedly, the dark sides of the blades absorb more photons, each of which carries a tiny bit of momentum, giving the dark side of the blades a consistent push. The problem with this explanation is that photons are bouncing off the silvery side, which imparts even more momentum. If the device were spinning due to radiation pressure, it would be turning in the opposite direction than it actually does.

An excess of the absorbed photons on the dark side is key to understanding how it works, though. Photophoresis operates through the temperature difference that develops between the warm, light-absorbing dark side of the blade and the cooler silvered side.

Any gas molecule that bumps into the dark side will likely pick up some of the excess thermal energy from it and move away from the blade faster than it arrived. At the sorts of atmospheric pressures we normally experience, these molecules don't get very far before they bump into other gas molecules, which keeps any significant differences from developing.

But a Crookes radiometer is in a sealed glass container with a far lower air pressure. This allows the gas molecules to speed off much farther from the dark surface of the blade before they run into anything, creating an area of somewhat lower pressure at its surface. That causes gas near the surface of the shiny side to rush around and fill this lower-pressure area, imparting the force that starts the blades turning.

It's pretty impressively inefficient in that sort of configuration, though. So people have spent a lot of time trying to design alternative configurations that can generate a bit more force. One idea with a lot of research traction is a setup that involves two thin metal sheets—one light, one dark—arranged parallel to each other. Both sheets would be heavily perforated to cut down on weight. And a subset of them would have a short pipe connecting holes on the top and bottom sheet. (This has picked up the nickname "nanocardboard.")

These pipes would serve several purposes. One is to simply link the two sheets into a single unit. Another is to act as an insulator, keeping heat from moving from the dark sheet to the light one, and thus enhancing the temperature gradient. Finally, they provide a direct path for air to move from the top of the light-colored sheet to the bottom of the dark one, giving a bit of directed thrust to help keep the sheets aloft.

Optimization

As you might imagine, there are a lot of free parameters you can tweak: the size of the gap between the sheets, the density of perforations in them, the number of those holes that are connected by a pipe, and so on. So a small team of researchers developed a system to model different configurations and attempt to optimize for lift. (We'll get to their motivations for doing so a bit later.)

Starting with a disk of nanocardboard, "The inputs to the model are the geometric, optical and thermal properties of the disk, ambient gas conditions, and external radiative heat fluxes on the disk," as the researchers describe it. "The outputs are the conductive heat fluxes on the two membranes, the membrane temperatures, and the net photophoretic lofting force on the structure." In general, the ambient gas conditions needed to generate lift are similar to the ones inside the Crookes radiometer: well below the air pressure at sea level.

The model suggested that three trends should influence any final designs. The first is that the density of perforations is a balance. At relatively low elevations (meaning a denser atmosphere), many perforations increase the stress on large sheets, but they decrease the stress for small items at high elevations. The other thing is that, rather than increasing with surface area, lift tends to drop because the sheets are more likely to equilibrate to the prevailing temperatures. A square millimeter of nanocardboard produces over 10 times more lift per surface area than a 10-square-centimeter piece of the same material.

Finally, the researchers calculate that the lift is at its maximum in the mesosphere, the area just above the stratosphere (50–100 kilometers above Earth's surface).

Light and lifting

The researchers then built a few sheets of nanocardboard to test the output of their model. The actual products, primarily made of chromium, aluminum, and aluminum oxide, were incredibly light, weighing only a gram for a square meter of material. When illuminated by a laser or white LED, they generated measurable force on a testing device, provided the atmosphere was kept sufficiently sparse. With an exposure equivalent to sunlight, the device generated more than it weighed.

It's a really nice demonstration that we can take a relatively obscure and weak physical effect and design devices that can levitate in the upper atmosphere, powered by nothing more than sunlight—which is pretty cool.

But the researchers have a goal beyond that. The mesophere turns out to be a really difficult part of the atmosphere to study. It's not dense enough to support balloons or aircraft, but it still has enough gas to make quick work of any satellites. So the researchers really want to turn one of these devices into an instrument-carrying aircraft. Unfortunately, that would mean adding the structural components needed to hold instruments, along with the instruments themselves. And even in the mesosphere, where lift is optimal, these things do not generate much in the way of lift.

Plus, there's the issue of getting them there, given that they won't generate enough lift in the lower atmosphere, so they'll have to be carried into the upper stratosphere by something else and then be released gently enough to not damage their fragile structure. And then, unless you're lofting them during the polar summer, they will likely come floating back down at night.

None of this is to say this is an impossible dream. But there are definitely a lot of very large hurdles between the work and practical applications on Earth—much less on Mars, where the authors suggest the system could also be used to explore the mesosphere. But even if that doesn't end up being realistic, this is still a pretty neat bit of physics.

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Posted Friday 15 August 2025 at 4:34 am AEST (my time).

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Much attention was paid to OpenAI's Sam Altman and xAI's Elon Musk trading barbs on X this week after Musk threatened to sue Apple over supposedly biased App Store rankings privileging ChatGPT over Grok.

But while the heated social media exchanges were among the most tense ever seen between the two former partners who cofounded OpenAI—more on that below—it seems likely that their jabs were motivated less by who's in the lead on Apple's "Must Have" app list than by an impending order in a lawsuit that landed in the middle of their public beefing.

Yesterday, a court ruled that OpenAI can proceed with claims that Musk was so incredibly stung by OpenAI's success after his exit didn't doom the nascent AI company that he perpetrated a "years-long harassment campaign" to take down OpenAI.

Musk's motivation? To clear the field for xAI to dominate the AI industry instead, OpenAI alleged.

OpenAI's accusations arose as counterclaims in a lawsuit that Musk initially filed in 2024. Musk has alleged that Altman and OpenAI had made a "fool" of Musk, goading him into $44 million in donations by "preying on Musk’s humanitarian concern about the existential dangers posed by artificial intelligence."

But OpenAI insists that Musk's lawsuit is just one prong in a sprawling, "unlawful," and "unrelenting" harassment campaign that Musk waged to harm OpenAI's business by forcing the company to divert resources or expend money on things like withdrawn legal claims and fake buyouts.

"Musk could not tolerate seeing such success for an enterprise he had abandoned and declared doomed," OpenAI argued. "He made it his project to take down OpenAI, and to build a direct competitor that would seize the technological lead—not for humanity but for Elon Musk."

Most significantly, OpenAI alleged that Musk forced OpenAI to entertain a "sham" bid to buy the company in February. Musk then shared details of the bid with The Wall Street Journal to artificially raise the price of OpenAI and potentially spook investors, OpenAI alleged. The company further said that Musk never intended to buy OpenAI and is willing to go to great lengths to mislead the public about OpenAI's business so he can chip away at OpenAI's head start in releasing popular generative AI products.

"Musk has tried every tool available to harm OpenAI," Altman's company said.

To this day, Musk maintains that Altman pretended that OpenAI would remain a nonprofit serving the public good in order to seize access to Musk's money and professional connections in its first five years and gain a lead in AI. As Musk sees it, Altman always intended to "betray" these promises in pursuit of personal gains, and Musk is hoping a court will return any ill-gotten gains to Musk and xAI.

In a small win for Musk, the court ruled that OpenAI will have to wait until the first phase of the trial litigating Musk's claims concludes before the court will weigh OpenAI's theories on Musk's alleged harassment campaign. US District Judge Yvonne Gonzalez Rogers noted that all of OpenAI's counterclaims occurred after the period in which Musk's claims about a supposed breach of contract occurred, necessitating a division of the lawsuit into two parts. Currently, the jury trial is scheduled for March 30, 2026, presumably after which, OpenAI's claims can be resolved.

If yesterday's X clash between the billionaires is any indication, it seems likely that tensions between Altman and Musk will only grow as discovery and expert testimony on Musk's claims proceed through December.

Whether OpenAI will prevail on its counterclaims is anybody's guess. Gonzalez Rogers noted that Musk and OpenAI have been hypocritical in arguments raised so far, condemning the "gamesmanship of both sides" as "obvious, as each flip flops." However, "for the purposes of pleading an unfair or fraudulent business practice, it is sufficient [for OpenAI] to allege that the bid was a sham and designed to mislead," Gonzalez Rogers said, since OpenAI has alleged the sham bid "ultimately did" harm its business.

In April, OpenAI told the court that the AI company risks "future irreparable harm" if Musk's alleged campaign continues. Fast-forward to now, and Musk's legal threat to OpenAI's partnership with Apple seems to be the next possible front Musk may be exploring to allegedly harass Altman and intimidate OpenAI.

"With every month that has passed, Musk has intensified and expanded the fronts of his campaign against OpenAI," OpenAI argued. Musk "has proven himself willing to take ever more dramatic steps to seek a competitive advantage for xAI and to harm Altman, whom, in the words of the President of the United States, Musk 'hates.'"

Tensions escalate as Musk brands Altman a “liar”

On Monday evening, Musk threatened to sue Apple for supposedly favoring ChatGPT in App Store rankings, which he claimed was "an unequivocal antitrust violation."

Seemingly defending Apple later that night, Altman called Musk's claim "remarkable," claiming he's heard allegations that Musk manipulates "X to benefit himself and his own companies and harm his competitors and people he doesn't like."

At 4 am on Tuesday, Musk appeared to lose his cool, firing back a post that sought to exonerate the X owner of any claims that he tweaks his social platform to favor his own posts.

"You got 3M views on your bullshit post, you liar, far more than I’ve received on many of mine, despite me having 50 times your follower count!" Musk responded.

Altman apparently woke up ready to keep the fight going, suggesting that his post got more views as a fluke. He mocked X as running into a "skill issue" or "bots" messing with Musk's alleged agenda to boost his posts above everyone else. Then, in what may be the most explosive response to Musk yet, Altman dared Musk to double down on his defense, asking, "Will you sign an affidavit that you have never directed changes to the X algorithm in a way that has hurt your competitors or helped your own companies? I will apologize if so."

Court filings from each man's legal team show how fast their friendship collapsed. But even as Musk's alleged harassment campaign started taking shape, their social media interactions show that underlying the legal battles and AI ego wars, the tech billionaires are seemingly hiding profound respect for—and perhaps jealousy of—each other's accomplishments.

A brief history of Musk and Altman’s feud

Musk and Altman's friendship started over dinner in July 2015. That's when Musk agreed to help launch "an AGI project that could become and stay competitive with DeepMind, an AI company under the umbrella of Google," OpenAI's filing said. At that time, Musk feared that a private company like Google would never be motivated to build AI to serve the public good.

The first clash between Musk and Altman happened six months later. Altman wanted OpenAI to be formed as a nonprofit, but Musk thought that was not "optimal," OpenAI's filing said. Ultimately, Musk was overruled, and he joined the nonprofit as a "member" while also becoming co-chair of OpenAI's board.

But perhaps the first major disagreement, as Musk tells it, came in 2016, when Altman and Microsoft struck a deal to sell compute to OpenAI at a "steep discount"—"so long as the non-profit agreed to publicly promote Microsoft’s products." Musk rejected the "marketing ploy," telling Altman that "this actually made me feel nauseous."

Next, OpenAI claimed that Musk had a "different idea" in 2017 when OpenAI "began considering an organizational change that would allow supporters not just to donate, but to invest." Musk wanted "sole control of the new for-profit," OpenAI alleged, and he wanted to be CEO. The other founders, including Altman, "refused to accept" an "AGI dictatorship" that was "dominated by Musk."

"Musk was incensed," OpenAI said, threatening to leave OpenAI over the disagreement, "or I’m just being a fool who is essentially providing free funding for you to create a startup."

But Musk floated one more idea between 2017 and 2018 before severing ties—offering to sell OpenAI to Tesla so that OpenAI could use Tesla as a "cash cow." But Altman and the other founders still weren't comfortable with Musk controlling OpenAI, rejecting the idea and prompting Musk's exit.

In his filing, Musk tells the story a little differently, however. He claimed that he only "briefly toyed with the idea of using Tesla as OpenAI's 'cash cow'" after Altman and others pressured him to agree to a for-profit restructuring. According to Musk, among the last straws was a series of "get-rich-quick schemes" that Altman proposed to raise funding, including pushing a strategy where OpenAI would launch a cryptocurrency that Musk worried threatened the AI company's credibility.

When Musk left OpenAI, it was "noisy but relatively amicable," OpenAI claimed. But Musk continued to express discomfort from afar, still donating to OpenAI as Altman grabbed the CEO title in 2019 and created a capped-profit entity that Musk seemed to view as shady.

"Musk asked Altman to make clear to others that he had 'no financial interest in the for-profit arm of OpenAI,'" OpenAI noted, and Musk confirmed he issued the demand "with evident displeasure."

Although they often disagreed, Altman and Musk continued to publicly play nice on Twitter (the platform now known as X), casually chatting for years about things like movies, space, and science, including repeatedly joking about Musk's posts about using drugs like Ambien.

By 2019, it seemed like none of these disagreements had seriously disrupted the friendship. For example, at that time, Altman defended Musk against people rooting against Tesla's success, writing that "betting against Elon is historically a mistake" and seemingly hyping Tesla by noting that "the best product usually wins."

The niceties continued into 2021, when Musk publicly praised "nice work by OpenAI" integrating its coding model into GitHub's AI tool. "It is hard to do useful things," Musk said, drawing a salute emoji from Altman.

This was seemingly the end of Musk playing nice with OpenAI, though. Soon after ChatGPT's release in November 2022, Musk allegedly began his attacks, seemingly willing to change his tactics on a whim.

First, he allegedly deemed OpenAI "irrelevant," predicting it would "obviously" fail. Then, he started sounding alarms, joining a push for a six-month pause on generative AI development. Musk specifically claimed that any model "more advanced than OpenAI’s just-released GPT-4" posed "profound risks to society and humanity," OpenAI alleged, seemingly angling to pause OpenAI's development in particular.

However, in the meantime, Musk started "quietly building a competitor," xAI, without announcing those efforts in March 2023, OpenAI alleged. Allegedly preparing to hobble OpenAI's business after failing with the moratorium push, Musk had his personal lawyer contact OpenAI and demand "access to OpenAI’s confidential and commercially sensitive internal documents."

Musk claimed the request was to "ensure OpenAI was not being taken advantage of or corrupted by Microsoft," but two weeks later, he appeared on national TV, insinuating that OpenAI's partnership with Microsoft was "improper," OpenAI alleged.

Eventually, Musk announced xAI in July 2023, and that supposedly motivated Musk to deepen his harassment campaign, "this time using the courts and a parallel, carefully coordinated media campaign," OpenAI said, as well as his own social media platform.

Musk “supercharges” X attacks

As OpenAI's success mounted, the company alleged that Musk began specifically escalating his social media attacks on X, including broadcasting to his 224 million followers that "OpenAI is a house of cards" after filing his 2024 lawsuit.

Claiming he felt conned, Musk also pressured regulators to probe OpenAI, encouraging attorneys general of California and Delaware to "force" OpenAI, "without legal basis, to auction off its assets for the benefit of Musk and his associates," OpenAI said.

By 2024, Musk had "supercharged" his X attacks, unleashing a "barrage of invective against the enterprise and its leadership, variously describing OpenAI as a 'digital Frankenstein’s monster,' 'a lie,' 'evil,' and 'a total scam,'" OpenAI alleged.

These attacks allegedly culminated in Musk's seemingly fake OpenAI takeover attempt in 2025, which OpenAI claimed a Musk ally, Ron Baron, admitted on CNBC was "pitched to him" as not an attempt to actually buy OpenAI’s assets, "but instead to obtain 'discovery' and get 'behind the wall' at OpenAI."

All of this makes it harder for OpenAI to achieve the mission that Musk is supposedly suing to defend, OpenAI claimed. They told the court that "OpenAI has borne costs, and been harmed, by Musk’s abusive tactics and unrelenting efforts to mislead the public for his own benefit and to OpenAI’s detriment and the detriment of its mission."

But Musk argues that it's Altman who always wanted sole control over OpenAI, accusing his former partner of rampant self-dealing and "locking down the non-profit’s technology for personal gain" as soon as "OpenAI reached the threshold of commercially viable AI." He further claimed OpenAI blocked xAI funding by reportedly asking investors to avoid backing rival startups like Anthropic or xAI.

Musk alleged:

Altman alone stands to make billions from the non-profit Musk co-founded and invested considerable money, time, recruiting efforts, and goodwill in furtherance of its stated mission. Altman’s scheme has now become clear: lure Musk with phony philanthropy; exploit his money, stature, and contacts to secure world-class AI scientists to develop leading technology; then feed the non-profit’s lucrative assets into an opaque profit engine and proceed to cash in as OpenAI and Microsoft monopolize the generative AI market.

For Altman, this week's flare-up, where he finally took a hard jab back at Musk on X, may be a sign that Altman is done letting Musk control the narrative on X after years of somewhat tepidly pushing back on Musk's more aggressive posts.

In 2022, for example, Musk warned after ChatGPT's release that the chatbot was "scary good," warning that "we are not far from dangerously strong AI." Altman responded, cautiously agreeing that OpenAI was "dangerously" close to "strong AI in the sense of an AI that poses e.g. a huge cybersecurity risk" but "real" artificial general intelligence still seemed at least a decade off.

And Altman gave no response when Musk used Grok's jokey programming to mock GPT-4 as "GPT-Snore" in 2024.

However, Altman seemingly got his back up after Musk mocked OpenAI's $500 billion Stargate Project, which launched with the US government in January of this year. On X, Musk claimed that OpenAI doesn't "actually have the money" for the project, which Altman said was "wrong," while mockingly inviting Musk to visit the worksite.

"This is great for the country," Altman said, retorting, "I realize what is great for the country isn't always what's optimal for your companies, but in your new role [at the Department of Government Efficiency], I hope you'll mostly put [America] first."

It remains to be seen whether Altman wants to keep trading jabs with Musk, who is generally a huge fan of trolling on X. But Altman seems more emboldened this week than he was back in January before Musk's breakup with Donald Trump. Back then, even when he was willing to push back on Musk's Stargate criticism by insulting Musk's politics, he still took the time to let Musk know that he still cares.

"I genuinely respect your accomplishments and think you are the most inspiring entrepreneur of our time," Altman told Musk in January.

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Posted Friday 15 August 2025 at 4:33 am AEST (my time).

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Scientists have figured out how to make frozen discs of ice self-propel across a patterned metal surface, according to a new paper published in the journal ACS Applied Materials and Interfaces. It's the latest breakthrough to come out of the Virginia Tech lab of mechanical engineer Jonathan Boreyko.

A few years ago, Boreyko's lab experimentally demonstrated a three-phase Leidenfrost effect in water vapor, liquid water, and ice. The Leidenfrost effect is what happens when you dash a few drops of water onto a very hot, sizzling skillet. The drops levitate, sliding around the pan with wild abandon. If the surface is at least 400° Fahrenheit (well above the boiling point of water), cushions of water vapor, or steam, form underneath them, keeping them levitated. The effect also works with other liquids, including oils and alcohol, but the temperature at which it manifests will be different.

Boreyko's lab discovered that this effect can also be achieved in ice simply by placing a thin, flat disc of ice on a heated aluminum surface. When the plate was heated above 150° C (302° F), the ice did not levitate on a vapor the way liquid water does. Instead, there was a significantly higher threshold of 550° Celsius (1,022° F) for levitation of the ice to occur. Unless that critical threshold is reached, the meltwater below the ice just keeps boiling in direct contact with the surface. Cross that critical point and you will get a three-phase Leidenfrost effect.

The key is a temperature differential in the meltwater just beneath the ice disc. The bottom of the meltwater is boiling, but the top of the meltwater sticks to the ice. It takes a lot to maintain such an extreme difference in temperature, and doing so consumes most of the heat from the aluminum surface, which is why it's harder to achieve levitation of an ice disc. Ice can suppress the Leidenfrost effect even at very high temperatures (up to 550° C), which means that using ice particles instead of liquid droplets would be better for many applications involving spray quenching: rapid cooling in nuclear power plants, for example, firefighting, or rapid heat quenching when shaping metals.

This time around, Boreyko et al. have turned their attention to what the authors term "a more viscous analog" to a Leidenfrost ratchet, a form of droplet self-propulsion. "What's different here is we're no longer trying to levitate or even boil," Boreyko told Ars. "Now we're asking a more straightforward question: Is there a way to make ice move across the surface directionally as it is melting? Regular melting at room temperature. We're not boiling, we're not levitating, we're not Leidenfrosting. We just want to know, can we make ice shoot across the surface if we design a surface in the right way?"

Mysterious moving boulders

The researchers were inspired by Death Valley's famous "sailing stones" on Racetrack Playa. Watermelon-sized boulders are strewn throughout the dry lake bed, and they leave trails in the cracked earth as they slowly migrate a couple of hundred meters each season. Scientists didn't figure out what was happening until 2014. Although co-author Ralph Lorenz (Johns Hopkins University) admitted he thought theirs would be "the most boring experiment ever" when they first set it up in 2011, two years later, the boulders did indeed begin to move while the playa was covered with a pond of water a few inches deep.

So Lorenz and his co-authors were finally able to identify the mechanism. The ground is too hard to absorb rainfall, and that water freezes when the temperature drops. When temperatures rise above freezing again, the ice starts to melt, creating ice rafts floating on the meltwater. And when the winds are sufficiently strong, they cause the ice rafts to drift along the surface.

"Nature had to have wind blowing to kind of push the boulder and the ice along the meltwater that was beneath the ice," said Boreyko. "We thought, what if we could have a similar idea of melting ice moving directionally but use an engineered structure to make it happen spontaneously so we don't have to have energy or wind or anything active to make it work?"

The team made their ice discs by pouring distilled water into thermally insulated polycarbonate Petrie dishes. This resulted in bottom-up freezing, which minimizes air bubbles in the ice. They then milled asymmetric grooves into uncoated aluminum plates in a herringbone pattern—essentially creating arrowhead-shaped channels—and then bonded them to hot plates heated to the desired temperature. Each ice disc was placed on the plate with rubber tongs, and the experiments were filmed from various angles to fully capture the disc behavior.

The herringbone pattern is the key. "The directionality is what really pushes the water," Jack Tapocik, a graduate student in Boreyko's lab, told Ars. "The herringbone doesn't allow for water to flow backward, the water has to go forward, and that basically pushes the water and the ice together forward. We don't have a treated surface, so the water just sits on top and the ice all moves as one unit."

Boreyko draws an analogy to tubing on a river, except it's the directional channels rather than gravity causing the flow. "You can see [in the video below] how it just follows the meltwater," he said. "This is your classic entrainment mechanism where if the water flows that way and you're floating on the water, you're going to go the same way, too. It's basically the same idea as what makes a Leidenfrost droplet also move one way: It has a vapor flow underneath. The only difference is that was a liquid drifting on a vapor flow, whereas now we have a solid drifting on a liquid flow. The densities and viscosities are different, but the idea is the same: You have a more dense phase that is drifting on the top of a lighter phase that is flowing directionally."

Next, the team repeated the experiment, this time coating the aluminum herringbone surface with water-repellant spray, hoping to speed up the disc propulsion. Instead, they found that the disc ended up sticking to the treated surface for a while before suddenly slingshotting across the metal plate.

"It's a totally different concept with totally different physics behind it, and it's so much cooler," said Tapocik. "As the ice is melting on these coated surfaces, the water just doesn't want to sit within the channels. It wants to sit on top because of the [hydrophobic] coating we have on there. The ice is directly sticking now to the surface, unlike before when it was floating. You get this elongated puddle in front. The easiest place [for the ice] to be is in the center of this giant, long puddle. So it re-centers, and that's what moves it forward like a slingshot."

Essentially, the water keeps expanding asymmetrically, and that difference in shape gives rise to a mismatch in surface tension because the amount of force that surface tension exerts on a body depends on curvature. The flatter puddle shape in front has less curvature than the smaller shape in back. As the video below shows, when the mismatch in surface tension becomes sufficiently strong, "It just rips the ice off the surface and flings it along," said Boreyko. "In the future, we could try putting little things like magnets on top of the ice. We could probably put a boulder on it if we wanted to. The Death Valley effect would work with or without a boulder because it's the floating ice raft that moves with the wind."

One potential application is energy harvesting. For example, one could pattern the metal surface in a circle rather than a straight line so the melting ice disk would continually rotate. Put magnets on the disk, and they would also rotate and generate power. One might even attach a turbine or gear to the rotating disc.

The effect might also provide a more energy-efficient means of defrosting, a longstanding research interest for Boreyko. "If you had a herringbone surface with a frosting problem, you could melt the frost, even partially, and use these directional flows to slingshot the ice off the surface," he said. "That's both faster and uses less energy than having to entirely melt the ice into pure water. We're looking at potentially over a tenfold reduction in heating requirements if you only have to partially melt the ice."

That said, "Most practical applications don't start from knowing the application beforehand," said Boreyko. "It starts from 'Oh, that's a really cool phenomenon. What's going on here?' It's only downstream from that it turns out you can use this for better defrosting of heat exchangers for heat pumps. I just think it's fun to say that we can make a little melting disk of ice very suddenly slingshot across the table. It's a neat way to grab your attention and think more about melting and ice and how all this stuff works."

DOI: ACS Applied Materials and Interfaces, 2025. 10.1021/acsami.5c08993  (About DOIs).

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Posted Friday 15 August 2025 at 4:29 am AEST (my time).

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United Launch Alliance delivered multiple US military satellites into a high-altitude orbit after a prime-time launch Tuesday night, marking an important transition from development to operations for the company's new Vulcan rocket.

This mission, officially designated USSF-106 by the US Space Force, was the first flight of ULA's Vulcan rocket to carry national security payloads. Two test flights of the Vulcan rocket last year gave military officials enough confidence to certify it for launching the Pentagon's medium-to-large space missions.

United Launch Alliance's third 202-foot-tall (61.6-meter) Vulcan rocket lifted off from Cape Canaveral Space Force Station, Florida, at 8:56 pm EDT Tuesday (00:56 UTC Wednesday). Two methane-burning BE-4 main engines, supplied by Jeff Bezos' space company Blue Origin, and four solid-fueled boosters from Northrop Grumman powered the rocket off the launch pad with nearly 3 million pounds of thrust.

The rocket steered east from Florida's Space Coast and climbed through the atmosphere, shedding its four strap-on boosters, core stage, and payload fairing to fall into the Atlantic Ocean. Vulcan's Centaur upper stage ignited its RL10 engines several times to maneuver into a near-circular geosynchronous orbit more than 22,000 miles (nearly 36,000 kilometers) over the equator.

These maneuvers took approximately seven hours to complete before the Centaur upper stage released its payloads to begin their missions. One of the satellites is an experimental platform to test next-generation technologies that may improve GPS navigation. There was at least one additional satellite—and perhaps more—aboard the rocket that the Space Force declined to discuss publicly.

Taking a bite of the apple

ULA and Space Force officials declared success early Wednesday, celebrating the Vulcan rocket's entry into service as ULA begins the challenging task of working through a firm backlog of more than 70 Vulcan launches on contract. Nearly all of the Vulcan launches have been booked by the Space Force's National Security Space Launch (NSSL) program and by Amazon for its Kuiper satellite broadband network.

Col. Jim Horne, USSF-106 mission director, said in a statement, "It’s an exciting day for us as we launched the first NSSL flight of Vulcan, an outstanding achievement for United Launch Alliance and the nation’s strategic space lift capability. This is an important milestone for the Space Force and all involved." He added, "After years of development, technical collaboration, and dedication by all involved, including our government mission partners and the entire ULA team, I’m proud to say the first Vulcan NSSL mission delivered its payloads safely into space."

ULA's first national security mission on the Vulcan rocket wasn't an easy one. For a flight profile to reach geosynchronous orbit, a rocket's upper stage must endure exposure to higher doses of radiation and carry more capacity for electrical power. Additionally, on these kinds of missions, a rocket must keep its super-cold propellant at just the right temperature, withstanding extreme heat and cold that could cause fluids to boil off or freeze.

In the United States, only ULA's Centaur upper stage and the upper stage of SpaceX's Falcon Heavy rocket are currently capable of flying such a long-duration mission. Eventually, SpaceX, ULA, and other companies aim to build on these capabilities to develop cryogenic rockets, refuelers, and propellant depots that can operate for months or years in space.

"Vulcan did exactly what it was built to do: deliver a critical mission with power, precision, and confidence," said Gary Wentz, ULA's vice president of government and commercial programs. "We are proud to play a role in strengthening the nation's space capabilities."

It's true that ULA, a joint venture between Boeing and Lockheed Martin, has a critical role in the future of America's military space program. The Space Force has tapped ULA's Vulcan rocket to launch more than half of its national security space missions over the next several years. These contracts, awarded in 2020, split the rights to launch the Pentagon's most important space missions 60-40 between ULA and SpaceX. The split ended up closer to 50-50 after ULA faced delays in bringing the Vulcan rocket online.

Senior procurement officials at the Pentagon have expressed concern over ULA's ability to deliver on its contractual commitments. While Tuesday night's launch was a noteworthy success for ULA, it doesn't necessarily quash these anxieties.

What’s next?

In the near term, ULA will switch back to launching its soon-to-retire Atlas V rocket, the Vulcan rocket's predecessor. The company has 13 more Atlas Vs in its inventory, most of them sold to Amazon and Boeing to launch Kuiper Internet satellites and Starliner crew missions to the International Space Station.

In a post-launch press release early Wednesday, ULA confirmed its next mission will be an Atlas V launch for Amazon's Kuiper constellation, a network that will eventually number more than 3,200 satellites. Later this year, ULA expects to launch more Vulcan rockets with Kuiper satellites and the Space Force's next national security mission.

The Space Force has firm orders for at least 26 more launches on the Vulcan rocket and will add more to ULA's backlog in the coming years. The Space Force's most recent phase of launch procurement announced in April reverses the 60-40 split from the 2020 contract award, with SpaceX taking responsibility for the bulk of the Pentagon's national security launches. Under this contract, ULA is still guaranteed roughly 17 more of the Vulcan launches the Space Force will dole out in the next few years, on top of the 26 firm orders already counted in the Vulcan backlog.

Amazon's contract for 38 Vulcan launches—six Vulcan flights reserved by Sierra Space for its Dream Chaser cargo vehicle, and the 13 remaining Atlas Vs—bring ULA's potential order book to approximately 100 missions. The Space Force accounts for a little more than 40 percent of the contracts.

Horne, a longtime leader in the Space Force's national security launch program, said the service is "postured to launch as quickly as we can as we work through that backlog."

Complicating ULA's ability to ramp up its Vulcan launch cadence is the rocket's design. Unlike SpaceX, which has a fleet of reusable Falcon 9 boosters, ULA has doubled down on building single-use boosters. This will keep ULA's factory humming in Decatur, Alabama.

But the most pressing bottleneck restricting ULA's ability to ramp up its launch cadence is at the launch site. United Launch Alliance has a single launch pad at Cape Canaveral and is outfitting another at Vandenberg Space Force Base in California. What's more, the company has just one active rocket integration hangar, where technicians vertically stack Atlas V and Vulcan rockets on their launch platforms.

Construction crews are racing to finish work on a second integration building a couple of miles south of the existing hangar. ULA officials project the new building to be ready to start stacking rockets before the end of this year, but teams have already missed an earlier schedule that would have brought the hangar online this summer.

ULA is also preparing a third mobile launch platform, giving managers more flexibility in moving rockets around the spaceport. Ground crews assemble the pieces of each rocket atop the launch platforms, which then transfer the complete launch vehicles to the launch pad for final countdown preps. Ultimately, this will give ULA the capacity to work on three simultaneous launch campaigns at Cape Canaveral, plus one at the Vandenberg spaceport on the West Coast.

Wentz told reporters earlier this week that the second rocket assembly building will theoretically allow ULA to launch as often as once every 13 days. This would get the company to its goal of flying 25 missions per year. ULA has launched just three times so far in 2025, and the company recently halved its projected launch manifest for this year from 20 missions to around nine.

Other hurdles lie ahead for Vulcan. The rocket's most powerful configuration, with six strap-on boosters, still hasn't flown or been certified for Space Force missions. This heavy-lift configuration will be able to lift more massive cargo than ULA's now-retired Delta IV Heavy rocket, but with a single core stage augmented by strap-on motors instead of three huge core stages strapped together.

Horne said the intermediate certification of the Vulcan rocket completed earlier this year covers the Space Force's so-called Category A and Category B missions. The heaviest Category C payloads, such as the government's largest spy satellites, will need the upgraded Vulcan rocket.

ULA is also moving forward with modifications to Vulcan's core stage to allow for the recovery and reuse of the rocket's main engines. Tory Bruno, the company's chief executive, announced last week that engineers completed a critical design review for the hardware changes required for engine reuse. These changes include severable mechanical and fluid connections for the engine section to jettison from the rocket, plus a heat shield and parachute to safely bring the engines back for an ocean recovery downrange from the launch pad.

Officials haven't announced an exact timetable for introducing engine recovery and reuse.

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Posted Thursday 14 August 2025 at 12:41 pm AEST (my time).

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Thousands of delegates have descended upon Geneva this week for what’s supposed to be the culmination of years of negotiations that, if successful, are supposed to end in a groundbreaking global plastics treaty. They might be breathing in the very thing they’re trying to clean up as they negotiate.

Greenpeace tested the air around the city just before the talks began this month and found a small amount of microplastics. It wasn’t so much a rigorous study as it was a way to prove a point. Microplastics are turning up all over the place, including in the air we breathe.

That’s why health and environmental advocates, as well as a coalition of governments, are pushing for an ambitious plastics treaty in Geneva. Recycling isn’t enough — only limiting production can stem the tide of plastic pollution, they contend.

“That you can find microplastics in urban air, that’s not really shocking because it’s been reported before in other cities. I think this is just a way of illustrating that nowhere is free from this pollution,” says David Santillo, a senior scientist with Greenpeace Research Laboratories.

Greenpeace strapped an air-monitoring device to a person while they went about their day in Geneva, spending about eight hours in and out of shops, cafes, office spaces, and a railway station. The samples they collected on July 17th were meant to show what a typical visitor to the city might be exposed to; they weren’t able to take any samples within the negotiation rooms that delegates would actually use.

The device had a replaceable silver filter that Greenpeace researchers were then able to analyze to see what particles they caught, which amounted to at least 165 fibers and fragments. The filters picked up a range of different materials like bits of skin, plant-based fibers, and what was likely soot. Greenpeace was interested in synthetic materials, however, and was ultimately able to identify 12 pieces of microplastics, including polyester, nylon, polyethylene used to make bottles and bags, and other types of plastics. That might not sound like much, but the organization only had the equipment to be able to detect larger particles that were at least 10 microns in size. (For comparison, the average human hair is about 70 microns in diameter.)

“If they found the big ones, it’s a pretty fair bet that the smaller ones were there, as well,” says Philip Landrigan, director of the Global Public Health and the Common Good Program at Boston College, who was not involved in the Greenpeace study.

Generally, the smaller the particle, the more problems it can potentially pose by being able to penetrate deeper into organs and tissues in the human body. A human brain might contain as much as a spoon’s worth of microplastics, research published in the journal Nature Medicine earlier this year suggests.

“Unfortunately, microplastics are pretty much everywhere in today’s world,” Landrigan says. He’s the lead author of an August report, published in the journal The Lancet, on the links between plastic pollution and health outcomes.

“Plastics cause disease and death from infancy to old age,” the report says, adding that plastics are responsible for $1.5 trillion in health-related economic losses each year. The report accounts for all the risks along the lifecycle of plastic, including chemicals that workers and communities near manufacturing facilities are exposed to, and waste that breaks down into nanoplastic particles that have been found in human bodies and breastmilk.

Scientists are still working to understand the health impacts of inhaling microplastics in the air. Landrigan points out that we at least know that all plastics are made of two main components, a carbon-based backbone derived from fossil fuels and chemical additives.

“When the microplastic comes into the human body, whether you inhale it or drink it with your water or eat it with your food, when it it gets into you and the plastics move from your gastrointestinal tract into the bloodstream, the microplastic particles are carrying all those chemicals with them,” Landrigan says.

The more than 16,000 different chemicals used in plastics production — including the carcinogen vinyl chloride, for example — are primarily responsible for the known health risks associated with plastics. But the toxicity of more than 75 percent of the chemicals in plastics have yet to be studied.

Greenpeace doesn’t claim to be assessing air quality in Geneva or the health impacts of what they found in their air samples. All they can show is the presence of microplastics in the air, adding to previous research that has done the same. What’s notable now is that Greenpeace has documented this at a time when leaders from around the world have the opportunity to actually do something about it.

Negotiations on a plastics treaty in Geneva are scheduled to end on August 14th. In 2022, United Nations member states agreed to develop a legally binding pact on plastic pollution. It’s been an uphill battle to agree on terms ever since. Major fossil fuel producing nations blocked a deal in December, pushing negotiations past their initial 2024 deadline. So far this year, there’s still a fight over whether focusing on recycling and reducing plastic waste is enough. The fossil fuel industry and countries including the US that produce a lot of plastics and its ingredients are fighting efforts to exclude limits to plastic production from the treaty.

A “high ambition coalition” launched by Rwanda and Norway, on the other hand, wants to address the full lifecycle of plastic, starting with production. It’s also open to using the treaty to phase out or restrict the use of problematic chemicals in plastics.

It doesn’t make sense to simply mop up the mess plastic leaves behind without also turning off the faucet, says Angel Pago, Greenpeace global plastics campaign media lead. “We’re brimming with plastic because of overproduction. And we cannot solve this crisis with just, you know, cleanups,” Pago tells The Verge from Geneva.

The Lancet article similarly says “the principal driver of this [health] crisis is accelerating growth in plastic production.” Production has ballooned from 2 metric megatons in 1950 to 475 in 2022. Less than 10 percent of plastic waste has ever been recycled, in part because the many chemicals used to manufacture different types plastics make it difficult or uneconomical to rehash the material.

“If we’re going to do something about plastics, we need to cap plastic production,” Landrigan says. “I hope and I pray that the treaty negotiators are actually going to produce a treaty that protects human health.”

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Posted Thursday 14 August 2025 at 12:37 pm AEST (my time).

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Health officials in Wyoming are sinking their teeth into a meaty task.

Over 200 people who stayed in a hotel in Grand Teton National Park between May and July may have unknowingly been exposed to rabies, according to Wyoming Public Radio.

In an announcement on Friday, the National Park Service reported finding evidence of a bat colony in the attic. The discovery was made after there had been at least eight incidents in which guests encountered winged mammals inside the hotel.

Now, the Wyoming Health Department is trying to contact all guests who stayed in a block of rooms under the bat's lair. Specifically, they're reaching out to the over 200 who stayed in rooms 516, 518, 520, 522, 524, 526, 528, and 530 at the Jackson Lake Lodge between May 15 and July 27. It was on July 27 that the eighth bat run-in occurred and the hotel closed the eight rooms.

"Although there were a lot of people exposed in this incident, one positive about it is that we know who 100 percent of those people are," Travis Riddell, director of the Teton County Public Health Department, told Wyoming Public Radio.

In Wyoming, bats are one of the two main carriers of rabies, the other being skunks. But bats are of particular concern because—unlike an extremely obvious skunk attack—people might not be aware of bat exposures.

Inconspicuous risk

The rabies virus generally transmits through saliva via bites and scratches, and bat bites and scratches are easy to miss. The most common bat in Wyoming is the small brown bat, which weighs less than half an ounce on average—though they can look larger due to their wide wings. These teeny bats, with their wee teeth, can leave bites and scratches that are not visible, do not bleed, and are not painful.

While the bats themselves are feeble foes, the rabies virus is a brutal beast. An infection, which can occur weeks to months after an exposure, produces an acute, progressive, brain-destroying disease that is nearly 100 percent fatal.

So far this year, testing by the University of Wyoming has found only two rabies-positive bats out of 259 tested. One of the positive bats was found in a child's bed.

While the incidence is low, officials don't take chances due to the deadly consequences. For hotel guests who slept under the bat colony, a seemingly harmless bat encounter could have gone unreported.

“The chances of even one of [the hotel bats] having rabies or having been exposed to rabies is low, but to me, the death of one person because of something that we could have otherwise prevented is not acceptable,” Riddell said.

In contacting the hotel guests, officials will determine if someone is at risk based on physical contact with the bats or if a guest cannot confirm or communicate if there was any physical contact, such as younger children, heavy sleepers, or people with mental impairments or drug use.

People who have been exposed are advised to get post-exposure prophylaxis, which includes a dose of human rabies immune globulin (HRIG) and a four-dose series of rabies vaccine.

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Posted Thursday 14 August 2025 at 12:35 pm AEST (my time).

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Astronomers have identified what could be a new supermassive black hole, and with an estimated mass 36 billion times that of the sun, it has about 10,000 times the mass of the black hole at the center of the Milky Way. This would make it among the most massive objects ever detected.

The finding, published in the Monthly Notice of the Royal Astronomical Society, was made by researchers from the Institute of Cosmology and Gravitation at the University of Portsmouth in the UK in collaboration with the Federal University of Rio Grande in Brazil. The scientists located the signs of the new supermassive black hole within a gravitational lens known as the “Cosmic Horseshoe,” pictured below. A gravitational lens occurs when the gravity of a massive object, such as a galaxy, is so great that it bends light and time that passes near it, distorting light traveling from behind.

The Cosmic Horsehoe was discovered by the Hubble telescope in 2007. The galaxy LRG 3-757 sits at its center, while the blue horseshoe shape surrounding this yellow-colored object is distorted light emitted from another galaxy beyond it. LRG 3-757 is one of the most massive galaxies ever observed by astronomers, having a mass 100 times that of the Milky Way, and it sits approximately 5.6 billion light-years away from Earth.

Thanks to this luminous structure, astronomers have been able to calculate the mass of the black hole that presumably lies at the center of LRG 3-757 (while not definitively proven, large galaxies are assumed to have a black hole at their center). Although there are no direct observations of this black hole, measurements of the motion of light in the ring and the velocity of stars in the inner regions of the galaxy are consistent with the presence of an ultramassive black hole. “By combining these two measurements we can be completely confident that the black hole is real,” Thomas Collett, professor of astrophysics at the University of Portsmouth, said in a press statement.

Collett also suggests that a black hole of such proportions could only originate from the merger of two supermassive black holes resulting from the collision of galaxies. Astronomers are still debating whether this will be the shared fate of our galaxy, the Milky Way, and neighboring Andromeda.

What About TON 618 and the Like?

Any astronomy enthusiast knows that the most massive object found in the universe so far is potentially TON 618. According to the most widespread estimates, this black hole has a mass equivalent to 66 billion suns, almost twice that of the Cosmic Horseshoe.

However, scientists are cautious about labelling TON 618 as the most massive object ever seen. Being located more than 10 billion light-years away, its host galaxy and surrounding objects cannot be observed in detail. What little is known about it comes from analysis of its brightness and from theoretical models that allow us to estimate its size. The uncertainty is too high to consider it the most massive black hole known.

In contrast, the Portsmouth researchers argue that the Cosmic Horseshoe black hole offers greater observational certainty, unlike distant, almost mythological holes like TON 618. As such, they claim that their discovery could represent the most massive black hole confirmed to date.

This story originally appeared on WIRED en Español and has been translated from Spanish.

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Posted Thursday 14 August 2025 at 3:36 am AEST (my time).

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After more than a decade of development and testing, US military officials are finally ready to entrust United Launch Alliance's Vulcan rocket to haul a batch of national security satellites into space.

An experimental military navigation satellite, also more than 10 years in the making, will ride ULA's Vulcan rocket into geosynchronous orbit more than 22,000 miles (nearly 36,000 kilometers) over the equator. There are additional payloads buttoned up inside the Vulcan rocket's nose cone, but officials from the US Space Force are mum on the details.

The Vulcan rocket is set for liftoff from Cape Canaveral Space Force Station, Florida, at 7:59 pm EDT (23:59 UTC) Tuesday. There's an 80 percent chance of favorable weather during the one-hour launch window. It will take several hours for the Vulcan rocket's Centaur upper stage to reach its destination in geosynchronous orbit. You can watch ULA's live launch webcast below.

The Vulcan rocket flew two demonstration missions in 2024, capping a lengthy campaign to design, build, and test ULA's new launch vehicle before the Space Force could declare it ready for operational service.

Now, ULA is poised to begin ticking off a backlog of more than 70 Vulcan launches the company has sold to commercial and government customers. The new rocket's largest users, by far, will be Amazon and the US Space Force.

New and improved

"We're excited to see this mission launch," said Gary Wentz, ULA's vice president of government and commercial programs. "This will be the most powerful Vulcan yet."

The first two Vulcan test flights last year used a configuration of the rocket with two strap-on boosters to add an extra burst of speed off the launch pad. For this flight, which the Space Force has named USSF-106, the launcher will fly with four solid rocket boosters made by Northrop Grumman.

These boosters are larger versions of the solid rocket motors ULA and its predecessors have flown on their previous rockets for 35 years. Despite their long history of successful flights, the boosters came under the microscope after a nozzle failure on the second Vulcan test flight last October. The nozzle at the bottom of one of the solid rocket boosters fell off the launcher moments after liftoff, but the motor continued firing, and Vulcan still made it to its intended orbit.

The setback contributed to the delay of the Space Force's first operational flight with the Vulcan rocket from the end of last year until now. Engineers determined that a carbon composite insulator, or heat shield, inside the nozzle failed to protect the nozzle's metallic structure from the superheated exhaust coming from the booster. Investigators traced the cause of the failure to a "manufacturing defect" in one of the insulators, which led to the melting and burn-through of the booster nozzle.

The rest of the Vulcan rocket performed close to perfection on the two test flights last year, including the vehicle's BE-4 main engines supplied by Blue Origin, the space company owned by billionaire Jeff Bezos. Two BE-4s fly on each Vulcan rocket, consuming cryogenic methane and liquid oxygen for the first five minutes of flight.

Space Force officials formally certified the Vulcan rocket for national security launches in March, setting the stage for Tuesday's launch of the USSF-106 mission.

United Launch Alliance, a 50-50 joint venture between Boeing and Lockheed Martin, is one of two companies approved to launch the Pentagon's most expensive and sensitive satellites. SpaceX is the other one, and that company's Falcon 9 and Falcon Heavy rockets have overtaken ULA's launch vehicles, thanks largely to booster reuse. Vulcan, like ULA's legacy Atlas and Delta rockets, is currently designed for a single use. Eventually, ULA aims to recover and reuse the BE-4 engines themselves, but not the entire Vulcan core stage.

Despite its higher cost and unproven capability, the Vulcan rocket won the lion's share of US military launch contracts from 2020 through 2024, while SpaceX received a bit less than half of the launch orders the Pentagon put up for competition between the two providers. The balance shifted with a new round of launch contracts awarded in April, with SpaceX becoming the military's leading launch provider and ULA taking second place. Blue Origin also won the right to receive a handful of military launch contracts with its New Glenn rocket, which debuted in January.

The Vulcan rocket checks off several important boxes for the Space Force. First, it relies entirely on US-made rocket engines. The Atlas V rocket it is replacing uses Russian-built main engines, and given the chilled relations between the two powers, US officials have long desired to stop using Russian engines to power the Pentagon's satellites into orbit. Second, ULA says the Vulcan rocket will eventually provide a heavy-lift launch capability at a lower cost than the company's now-retired Delta IV Heavy rocket.

Third, Vulcan provides the Space Force with an alternative to SpaceX's Falcon 9 and Falcon Heavy, which have been the only rockets in their class available to the military since the last national security mission was launched on an Atlas V rocket one year ago.

Col. Jim Horne, mission director for the USSF-106 launch, said this flight marks a "pretty historic point in our program's history. We officially end our reliance on Russian-made main engines with this launch, and we continue to maintain our assured access to space with at least two independent rocket service companies that we can leverage to get our capabilities on orbit."

What’s onboard?

The Space Force has only acknowledged one of the satellites aboard the USSF-106 mission, but there are more payloads cocooned inside the Vulcan rocket's fairing.

The $250 million mission that officials are willing to talk about is named Navigation Technology Satellite-3, or NTS-3. This experimental spacecraft will test new satellite navigation technologies that may eventually find their way on next-generation GPS satellites. A key focus for engineers who designed and will operate the NTS-3 satellite is to look at ways of overcoming GPS jamming and spoofing, which can degrade satellite navigation signals used by military forces, commercial airliners, and civilian drivers.

"We're going to be doing, we anticipate, over 100 different experiments," said Joanna Hinks, senior research aerospace engineer at the Air Force Research Laboratory's space vehicles directorate, which manages the NTS-3 mission. "Some of the major areas we’re looking at—we have an electronically steerable phased array antenna so that we can deliver higher power to get through interference to the location that it's needed."

GPS jamming is especially a problem in and near war zones. Investigators probing the crash of Azerbaijan Airlines Flight 8243 last December determined GPS jamming, likely by Russian military forces attempting to counter a Ukrainian drone strike, interfered with the aircraft's navigation as it approached its destination in the Russian republic of Chechnya. Azerbaijani government officials blamed a Russian surface-to-air missile for damaging the aircraft, ultimately leading to a crash in nearby Kazakhstan that killed 38 people.

"We have a number of different advanced signals that we’ve designed," Hinks said. "One of those is the Chimera anti-spoofing signal... to protect civil users from spoofing that’s affecting so many aircraft worldwide today, as well as ships."

The NTS-3 spacecraft, developed by L3Harris and Northrop Grumman, only takes up a fraction of the Vulcan rocket's capacity. The satellite weighs less than 3,000 pounds (about 1,250 kilograms), about a quarter of what this version of the Vulcan rocket can deliver to geosynchronous orbit.

Horne demurred when asked about what else the Vulcan rocket will deploy in orbit: "I’ll just say that any other further details beyond NTS-3 are not releasable to the public, and leave it at that... We’re not going to make any further comments on anything beyond NTS-3 in the mission stack."

The Space Force's refusal to disclose any information about additional payloads on the USSF-106 mission, even the total number of satellites aboard Vulcan, is somewhat of an outlier compared to the way military officials have historically handled these questions. While the Space Force has consistently kept secret details about specific maneuvers and instruments (or in some cases, potential weapons), officials have named and numbered the payloads carried aboard nearly all recent national security launches.

This is in contrast to the National Reconnaissance Office, which owns the US government's fleet of spy satellites. The NRO has nearly always followed a stricter protocol of secrecy than the Air Force or Space Force.

That changed last year, when a classified Space Force mission named USSF-51 launched on an Atlas V rocket. Military leaders didn't disclose the mission's purpose or how many satellites it was carrying until the Space Force officially cataloged three payloads from the launch in its publicly accessible list of all human-made objects in orbit.

Some of the Space Force's most secret satellites have the ability to release smaller spacecraft themselves, adding to the uncertainty for potential adversaries. Some information about the payloads on Tuesday's launch might become public as the Space Force adds them to the public catalog, and a network of amateur skywatchers on Earth stands ready to observe their movements thousands of miles overhead.

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Posted Wednesday 13 August 2025 at 5:38 pm AEST (my time).

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A Powerade bottle from 2001 was found on Yaya, a Peruvian beach south of Lima. A Coca-Cola bottle from 2002 was found on Robinson Crusoe Island, a World Biosphere Reserve, in Chile. These were the oldest of all the bottles collected.

These discarded pieces of packaging were collected in a new macro-study that looked at the origin of plastic bottle pollution on beaches and cities along Latin America’s Pacific coastline. The research—the first to be conducted on a regional scale, thanks to a citizen science initiative covering 10 countries—combed more than 12,000 kilometers of coastline along the west coast of South and Central America. It found that across the region, Central American countries are most affected by coastal plastic pollution, and underscores the urgency of confronting this major problem.

Although volunteers found numerous bottles dating back more than a decade, “most of them were less than a year old,” says scientist Ostin Garcés, an expert on the impact of plastic on marine ecosystems at the University of Barcelona and a lead author of this new research.

Plastic makes up the majority of the garbage on coastlines around the world and has reached even the most inhospitable corners of the planet, including the deepest parts of the oceans and both the Arctic and Antarctic. Its impact not only has repercussions on biodiversity and the balance of ecosystems; various studies show how plastic already colonizes our insides, runs through our blood, and lives in our brains and organs. Microplastics have even been found in semen and ovaries. The microplastics that we eat, drink, and breathe every day are part of us.

“Production and consumption continue unabated,” says Garcés, who is part of the team that sampled a total of 92 continental beaches, 15 island beaches, and 38 human settlements to determine the abundance, origin, and characteristics of plastic bottles along Central and South America’s Pacific coast. This study reveals surprising data, given that more than half of the bottles and caps collected had visible dates.

According to the study, containers for soft drinks, energy drinks, and drinking water were the most common. The countries with the highest rates of plastic bottle pollution were El Salvador, Nicaragua, and Guatemala, likely due to their coastal population density, high consumption of beverages in plastic containers, and poor waste management, the study’s authors argue. “These are countries that lack the necessary infrastructure and technical capacity [to control plastic bottle waste]. Therefore, all the beverage waste that reaches their communities ends up in nature,” says Garcés.

There is also another very important factor that is driving up pollution, Garcés says. “Our study shows rising temperatures have caused people in these tropical areas to consume more bottled beverages.”

The large number of plastic water bottles found in Central American countries is a symptom of another serious problem in the region, but one that affects most countries on the continent: limited access to safe drinking water, which drives people to buy bottled water and other packaged drinks.

The results reveal that almost 60 percent of the items with identifiable origins came from countries within the Latin American Pacific region itself—that is, from local producers. “They are manufactured by bottling companies located in the same country but that work with international brands, such as Coca-Cola, PepsiCo, and Aje Group,” explains Garcés. These three multinationals account for the majority of the collected bottles. Bottles from 356 brands produced by 253 companies were identified.

The study recorded information contained on the bottles and their caps—such as labels and engravings—to work out their manufacturer, production date, and place of origin. This allowed the researchers to identify sources of pollution and the journeys taken by individual items to reach the beach or city where they were collected.

While continental beaches were filled with local products, island beaches receive many Asian bottles, likely arriving from ships and via ocean currents. This observation, Garcés says, was precisely what prompted the research he participated in. In 2023, the Trash Scientists Network, a program of Universidad Católica del Norte in Chile, conducted a study that showed that many bottles that end up on remote islands, such as Rapa Nui (Easter Island) or the Galapagos, had letters on their labels that were not in Spanish, but in Chinese or Japanese. “That’s where the idea of investigating where those bottles came from came from,” Garcés says.

The scientists found that, like other marine debris, the bottles and caps they retrieved were sometimes colonized by immobile organisms called epibionts, which live on the surface of other organisms or materials. The team found items with bryozoans, barnacles, and mollusks attached, with the presence of these correlating with the age of the plastic. Bottles and caps also exhibited degradation patterns typical of marine exposure—discoloration, wear, and fragmentation.

However, despite these transformations, the plastic waste often retained key identifying characteristics, such as product codes, brand names, manufacturing locations, and dates. This data helped trace their provenance, even when bottles were damaged or heavily colonized by organisms, providing valuable information about their origin and transport pathways.

For Garcés, one of the most worrying conclusions of his study is the situation on islands like the Galapagos and Rapa Nui, protected natural areas. As he explains, epibionts attached to the plastic bottles are washing up on their beaches, “and that represents a serious threat, because we don’t know what species of organisms are arriving or where they’re coming from. And they can be invasive.”

The work would not have been possible without the collaboration of up to 200 local leaders from 74 social organizations, as well as the 1,000 volunteers who were part of this citizen science initiative. Their methodological approach not only allowed the research team to better understand the characteristics of the plastic waste affecting the Latin American Pacific, but also to understand regional beverage preferences and consumption trends in different countries.

Proposals to Solve This Crisis

Given the widespread presence of disposable plastic bottles, mainly of local origin, one of the researchers’ main recommendations is to replace them with standardized returnable bottles throughout the region—“like we used to do,” Garcés says. “When I was a kid, products were sold in returnable glass bottles. This would be one of the main measures we propose to reduce the production of plastics from the source.”

This measure, he says, should be complemented by refund policies and corporate social responsibility initiatives on the part of the beverage companies involved. Demanding reusable packaging and accountability from large producers of bottled drinks are essential strategies to reduce plastic pollution and protect coastal ecosystems, say the authors. “In the end, companies have their own interests and look for the cheapest alternatives for bottle production. That is why governments have to get involved,” says Garcés. However, he says that improving waste management, especially in coastal communities, is another key issue that needs to be addressed.

The researchers also highlight the central role of human behavior in reducing plastic pollution. “As we grow as a population, consumption increases. And, as long as the basic needs of coastal populations in terms of access to drinking water are not met, it will continue to increase, contaminating more and more coastal environments,” Garcés says. When drinking water is only available in single-use plastic bottles, consumers have no alternatives, “limiting their ability to act sustainably.”

This story originally appeared on WIRED en Español and has been translated from Spanish.

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Posted Wednesday 13 August 2025 at 3:36 am AEST (my time).

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Ford just announced its new universal EV platform that is expected to rein in costs for the company’s money losing EV business. Chief among those cost savings will be a much, much smaller battery.

Ford said the new battery will be 15 percent smaller than that of a BYD Atto electric crossover. BYD uses the same lithium iron phosphate (LFP) chemistry that Ford says it will use in its future EVs, starting with a four-door midsized pickup in 2027.

The BYD Atto 3 offers two battery options: a 49.92 kWh pack and a 60.48 kWh pack. That could mean Ford is looking at a battery with 51 kWh capacity, smaller than first-gen the Chevy Bolt’s 57 kWh pack. That’s tiny, especially by today’s standards of EVs with 300-miles-plus of range.

Ford acknowledges that the smaller battery will result in less range than typically available. Alan Clarke, the company’s head of advanced EV development, said if you dropped this new powertain into a conventional ICE truck, you would get 50 miles less range.

Clarke said the company is hoping to boost the range through improved aerodynamics.

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Posted Tuesday 12 August 2025 at 4:32 am AEST (my time).

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Generative AI is becoming more advanced and scaling to impressive heights every day, though recent opposing reports suggest that the technology has seemingly hit a wall and even begun plateauing, predominantly due to an implied lack of higher-quality training data.

Aside from privacy and security concerns, artificial intelligence is rapidly becoming a threat to professionals. In 2022, as ChatGPT was just launching, AI was predominantly viewed as just a text-based tool for generating simple, conversational responses to emails and messages.

However, it has rapidly gained broad adoption across the world, with continued integration into companies to automate redundant and repetitive tasks in their workflows, apparently creating more time for demanding tasks. Still, as the technology becomes more advanced, some companies are embracing a totally different approach of laying off their staffers entirely and replacing them with AI to cut down on costs.

This year, Salesforce CEO Marc Benioff indicated that the company was "seriously debating" hiring software engineers in 2025. He later revealed that AI was handling up to 50% of the company's tasks, citing incredible productivity gains via agentic AIs.

Last month, a Microsoft study revealed 40 professions that are most susceptible to automation using AI, including writers, editors, telephone operators, radio DJs, web developers, and more.

Some executives argue that integrating AI into workflows isn't inherently bad. While they admit the technology has a high probability of rendering some professions obsolete, they also claim that the technology will create new job opportunities.

Former CBO (Chief Business Officer) at Google X, Mo Gawdat, doesn't subscribe to this school of thought. Like Microsoft's co-founder Bill Gates, Gawdat believes that AI will replace humans for most things, including entry-level jobs (via CNBC). Speaking in an interview on the Diary of a CEO podcast, the executive indicated that the idea of AI creating jobs for humans is "100% crap."

He used his AI startup, Emma.love, to further drive the point home. He indicated that he was able to build the app with the help of two other software developers, a task that would have otherwise required the manpower of "over 350 developers in the past."

According to Gawdat, "Artificial general intelligence is going to be better than humans at everything, including being a CEO. There will be a time where most incompetent CEOs will be replaced.”

Anthropic CEO Dario Amodei indicated that AI is on the verge of slashing 50% of entry-level white-collar jobs, leaving fresh graduates and Gen Z out of an already tough job market. While the former Google executive indicates the paradigm shift is imminent, an AI-driven world isn't entirely a bad thing.

Microsoft's special June Work Trend Index report revealed that most employees are stuck in an "infinite workday", which often coerces them to carry work home, prompting them to work late into the night. Some even lamented that Sunday "feels like the new Monday".

But thanks to AI, employees have devised ingenious ways to leverage AI to free themselves from this vicious loop, including automating repetitive and mundane tasks to create a healthy work-life balance.

We'll need a universal basic income (UBI) in an AI-driven world

iRobot, maker of the iconic Roomba robot vacuum, announced its second-quarter earnings late last week, and the numbers keep going down. Despite launching an entirely new product line, its revenue declined 23 percent to $127.6 million from the previous quarter, with the lucrative US and European markets being hit hardest.

The company has struggled in the face of increased competition from Chinese manufacturers and the collapse of a sale to Amazon, which left it deep in debt. Earlier this year, CEO Gary Cohen indicated iRobot could shut down within 12 months if something didn’t change. The clock is ticking.

Last week, Cohen said that while customer response to the new product line has been “encouraging,” iRobot didn’t meet its goals this quarter “due to persistent market headwinds and delays in scaling production and sales of our new products.” He confirmed the company is still looking at a potential sale or other “strategic alternatives” to get out of debt.

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Posted Tuesday 12 August 2025 at 4:21 am AEST (my time).

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The question of when life began on Earth is as old as human culture.

“It's one of these fundamental human questions: When did life appear on Earth?” said Professor Martin Whitehouse of the Swedish Museum of Natural History.

So when some apparently biological carbon was dated to at least 3.95 billion years ago—making it the oldest remains of life on Earth—the claim sparked interest and skepticism in equal measure, as Ars Technica reported in 2017.

Whitehouse was among those skeptics. This July, he presented new evidence to the Goldschmidt Conference in Prague that the carbon in question is only between 2.7–2.8 billion years old, making it younger than other traces of life found elsewhere.

Organic carbon?

The carbon in question is in rock in Labrador, Canada. The rock was originally silt on the seafloor that, it's argued, hosted early microbial life that was buried by more silt, leaving the carbon as their remains. The pressure and heat of deep burial and tectonic events over eons have transformed the silt into a hard metamorphic rock, and the microbial carbon in it has metamorphosed into graphite.

“They are very tiny, little graphite bits,” said Whitehouse.

The key to showing that this graphite was originally biological versus geological is its carbon isotope ratio. From life’s earliest days, its enzymes have preferred the slightly lighter isotope carbon-12 over the marginally heavier carbon-13. Organic carbon is therefore much richer in carbon-12 than geological carbon, and the Labrador graphite does indeed have this “light” biological isotope signature.

The key question, however, is its true age.

Mixed-up, muddled-up, shook-up rocks

Sorting out the age of the carbon-containing Labrador rock is a geological can of worms.

These are some of the oldest rocks on the planet—they’ve been heated, squished, melted, and faulted multiple times as Earth went through the growth, collision, and breakup of continents before being worn down by ice and exposed today.

“That rock itself is unbelievably complicated,” said Whitehouse. “It's been through multiple phases of deformation.”

In general, the only ways to date sediments are if there’s a layer of volcanic ash in them, or by distinctive fossils in the sediments. Neither is available in these Labrador rocks.

“The rock itself is not directly dateable,” said Whitehouse, “so then you fall onto the next best thing, which is you want to look for a classic field geology cross-cutting relationship of something that is younger and something that you can date.”

The idea, which is as old as the science of geology itself, is to bracket the age of the sediment by finding a rock formation that cuts across it. Logically, the cross-cutting rock is younger than the sediment it cuts across.

In this case, the carbon-containing metamorphosed siltstone is surrounded by swirly, gray banded gneiss rock, but the boundary between the siltstone and the gray gneiss is parallel, so there's no cross-cutting to use.

Professor Tsuyoshi Komiya of The University of Tokyo was a coauthor on the 3.95 billion-year age paper. His team used a cross-cutting rock they found at a different location and extrapolated that to the carbon-bearing siltstone to constrain its age. “It was discovered that the gneiss was intruded into supracrustal rocks (mafic and sedimentary rocks),” said Komiya in an email to Ars Technica.

But Whitehouse disputes that inference between the different outcrops.

“You're reliant upon making these very long-distance assumptions and correlations to try to date something that might actually not have anything to do with what you think you're dating,” he said.

Professor Jonathan O'Neil of the University of Ottawa, who was not involved in either Whitehouse’s or Komiya’s studies but who has visited the outcrops in question, agrees with Whitehouse. “I remember I was not convinced either by these cross-cutting relationships,” he told Ars. “It's not clear to me that one is necessarily older than the other.”

With the field geology evidence disputed, the other pillar holding up the 3.95-billion-year-old date is its radiometric date, measured in zircon crystals extracted from the rocks surrounding the metamorphosed siltstone.

The zircon keeps the score

Geologists use the mineral zircon to date rocks because when it crystallizes, it incorporates uranium but not lead. So as radioactive uranium slowly decays into lead, the ratio of uranium to lead provides the age of the crystal.

But the trouble with any date obtained from rocks as complicated as these is knowing exactly what geological event it dates—the number alone means little without the context of all the other geological evidence for the events that affected the area.

Both Whitehouse and O’Neil have independently sampled and dated the same rocks as Komiya’s team, and where Komiya’s team got a date of 3.95, Whitehouse’s and O’Neil’s new dates are both around 3.87 billion years. Importantly, O’Neil’s and Whitehouse’s dates are far more precise, with errors around plus-or-minus 5 or 6 million years, which is remarkably precise for dates in rocks this old. The 3.95 date had an error around 10 times bigger. “It's a large error,” said O’Neil.

But there's a more important question: How is that date related to the age of the organic carbon? The rocks have been through many events that could each have “set” the dates in the zircons. That’s because zircons can survive multiple re-heatings and even partial remelting, with each new event adding a new layer, or “zone,” on the outer surface of the crystal, recording the age of that event.

“This rock has seen all the events, and the zircon in it has responded to all of these events in a way that, when you go in with a very small-scale ion beam to do the sampling on these different zones, you can pick apart the geological history,” Whitehouse said.

Whitehouse’s team zapped tiny spots on the zircons with a beam of negatively charged oxygen ions to dislodge ions from the crystals, then sucked away these ions into a mass spectrometer to measure the uranium-lead ratio, and thus the dates. The tiny beam and relatively small error have allowed Whitehouse to document the events that these rocks have been through.

“Having our own zircon means we've been able to go in and look in more detail at the internal structure in the zircon,” said Whitehouse. “Where we might have a core that's 3.87, we'll have a rim that is 2.7 billion years, and that rim, morphologically, looks like an igneous zircon,” said Whitehouse.

That igneous outer rim of Whitehouse’s zircons shows that it formed in partially molten rock that would have flowed at that time. That flow was probably what brought it next to the carbon-containing sediments. Its date of 2.7 billion years ago means the carbon in the sediments could be any age older than that.

That’s a key difference from Komiya’s work. He argues that the older dates in the cores of the zircons are the true age of the cross-cutting rock. “Even the igneous zircons must have been affected by the tectonothermal event; therefore, the obtained age is the minimum age, and the true age is older,” said Komiya. “The fact that young zircons were found does not negate our research.”

But Whitehouse contends that the old cores of the zircons instead record a time when the original rock formed, long before it became a gneiss and flowed next to the carbon-bearing sediments.

Zombie crystals

Zircon's resilience means it can survive being eroded from the rock where it formed and then deposited in a new, sedimentary rock as the undead remnants of an older, now-vanished landscape.

The carbon-containing siltstone contains zombie zircons, and Whitehouse presented new data on them to the Goldschmidt Conference, dating them to 2.8 billion years ago. Whitehouse argues that these crystals formed in an igneous rock 2.8 billion years ago and then were eroded, washed into the sea, and settled in the silt. So the siltstone must be no older than 2.8 billion years old, he said.

“You cannot deposit a zircon that is not formed yet,” O’Neil explained.

This 2.8-billion-year age, along with the igneous zircon age of 2.7 billion years, brackets the age of the organic carbon to anywhere between 2.8 and 2.7 billion years old. That’s much younger than Komiya’s date of 3.95 billion years old.

Komiya disagrees: “I think that the estimated age is minimum age because zircons suffered from many thermal events, so that they were rejuvenated,” he said. In other words, the 2.8-billion-year age again reflects later heating, and the true date is given by the oldest-dated zircons in the siltstone.

But Whitehouse presented a third line of evidence to dispute the 3.95-billion-year date: isotopes of hafnium in the same zombie zircon crystals.

The technique relies on radioactive decay of lutetium-176 to hafnium-176. If the 2.8-billion-year age resulted from rejuvenation by later heating, it would have had to have formed from material with a hafnium isotope ratio incompatible with the isotope composition of the early Earth.

“They go to impossible numbers,” said Whitehouse.

The only way that the uranium-lead ratio can be compatible with the hafnium in the zircons, Whitehouse argued, is if the zircons that settled in the silt had crystallized around 2.8 billion years ago, constraining the organic carbon to being no older than that.

The new oldest remains of life on Earth, for now

If the Labrador carbon is no longer the oldest trace of life on Earth, then where are the oldest remains of life now?

For Whitehouse, it’s in the 3.77-billion-year-old Isua Greenstone Belt in Greenland: “I'm willing to believe that's a well-documented age… that's what I think is the best evidence for the oldest biogenicity that we have,” said Whitehouse.

O’Neil recently co-authored a paper on Earth's oldest surviving crustal rocks, located next to Hudson Bay in Canada. He points there. “I would say it's in the Nuvvuagittuq Greenstone belt,” said O’Neil, “because I would argue that these rocks are 4.3 billion years old. Again, not everybody agrees!” Intriguingly, the rocks he is referring to contain carbon with a possibly biological origin and are thought to be the remains of the kind of undersea vent where life could well have first emerged.

But the bigger picture is the fact that we have credible traces of life of this vintage—be it 3.8 or 3.9 or 4.3 billion years.

Any of those dates is remarkably early in the planet's 4.6-billion-year life. It’s long before there was an oxygenated atmosphere, before continents emerged above sea level, and before plate tectonics got going. It’s also much older than the oldest microbial “stromatolite” fossils, which have been dated to about 3.48 billion years ago.

O’Neil thinks that once conditions on Earth were habitable, life would have emerged relatively fast: “To me, it's not shocking, because the conditions were the same,” he said. “The Earth has the luxury of time… but biology is very quick. So if all the conditions were there by 4.3 billion years old, why would biology wait 500 million years to start?”

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Posted Tuesday 12 August 2025 at 4:19 am AEST (my time).

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The Cleveland Clinic is partnering with San Francisco–based startup Piramidal to develop a large-scale AI model that will be used to monitor patients’ brain health in intensive care units.

Instead of being trained on text, the system is based on electroencephalogram (EEG) data, which is collected via electrodes placed on the scalp and then read out by a computer in a series of wavy lines. EEG records the brain’s electrical activity, and changes in this activity can indicate a problem. In an ICU setting, doctors scan EEG data looking for evidence of seizures, altered consciousness, or a decline in brain function.

Currently, doctors rely on continuous EEG monitoring to detect abnormal brain activity in an ICU patient, but they can’t monitor every individual patient in real time. Instead, EEG reports are typically generated every 12 or 24 hours and then analyzed to determine whether a patient is experiencing a neurological issue. It can take two to four hours to manually review a day’s worth of brainwave data.

“This type of thing is time-consuming. It is subjective, and it is experience- and expertise-dependent,” says Imad Najm, a neurologist and director of the Epilepsy Center at the Cleveland Clinic’s Neurological Institute.

The system that the Cleveland Clinic and Piramidal are developing is designed to interpret continuous streams of EEG data and flag abnormalities in seconds so that doctors can intervene sooner.

“Our model plays that role of constantly monitoring patients in the ICU and letting the doctors know what’s happening with the patient and how their brain health is evolving in real time,” says Piramidal’s chief product officer Kris Pahuja.

Pahuja and CEO Dimitris Fotis Sakellariou founded Piramidal in 2023, with the goal of building a foundation model for the brain—an AI system that can read and interpret neural signals broadly across different people. Prior to this, Sakellariou spent 15 years as a neuroengineer and AI scientist doing EEG research. Pahuja worked on product strategy at Google and Spotify. Their startup, which is backed by Y Combinator, raised $6 million in seed funding last year.

The company built its ICU brain model using publicly available EEG datasets, as well as proprietary EEG data from the Cleveland Clinic and other partnerships. Sakellariou says the model incorporates nearly a million hours of EEG monitoring data from “dozens of thousands” of patients, both neurologically healthy and unhealthy. Brain activity patterns are extremely variable from person to person, so building a brain foundation model requires huge amounts of data to capture common patterns and features.

“The beauty of a foundation model is the same way ChatGPT can generalize text, it can adapt to your tone, it can adapt to your way of writing—our model is able to adapt to the brains of different people,” Sakellariou says.

Currently, the Cleveland Clinic and Piramidal team is using retrospective patient data to fine-tune the model. In the next six to eight months, they plan to test the model in a tightly controlled ICU environment with live patient data and a limited number of beds and doctors. From there, they aim to slowly roll out the software to the entire ICU. Eventually, the software will allow the hospital system to monitor hundreds of patients at once, Najm says.

The slow rollout is to reduce the rate of false positives and false negatives—instances where the system misidentifies patients who don’t have a severe event or failing to catch someone who does. The latter scenario especially is “a big problem that keeps us awake at night,” Najm says.

Piramidal did not comment on the model’s current accuracy but said it has evaluated its technology against a network of doctors and has achieved “humanlike” performance. The company plans to publish data on the model’s accuracy at a future date.

While Piramidal’s immediate focus is on applying its brain foundation model to the ICU, Sakellariou and Pahuja also want to use it for epilepsy and sleep monitoring. Meanwhile, brain-computer interface company Synchron is developing a brain foundation model incorporating data from trial participants to make its system more accurate and generalizable to more users. There are also consumer applications of brain foundation models, such as using EEG earbuds to measure emotional states. Both medical and consumer applications raise questions about how brain data will be used and stored, as well as how and when it should be used.

“Advancements like this one highlight the need for anticipatory ethical frameworks that support responsible development and use of these technologies,” says Caroline Montojo, president and CEO of the Dana Foundation, a private philanthropic organization dedicated to neuroscience research. “It’s critical to bring in many different perspectives at early stages of technology design from multiple disciplines, including ethicists, social scientists, and legal scholars, as well as the lived experiences of patients.”

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Posted Tuesday 12 August 2025 at 4:18 am AEST (my time).

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Most adhesives can’t stick to wet surfaces because water and other fluids disrupt the adhesive’s bonding mechanisms. This problem, though, has been beautifully solved by evolution in remora suckerfish, which use an adhesive disk on top of their heads to attach to animals like dolphins, sharks, and even manta rays.

A team of MIT scientists has now taken a close look at these remora disks and reverse-engineered them. “Basically, we looked at nature for inspiration,” says Giovanni Traverso, a professor at MIT Department of Mechanical Engineering and senior author of the study.

Sticking Variety

Remora adhesive disks are an evolutionary adaptation of the fish’s first dorsal fin, the one that in other species sits on top of the body, just behind the head and gill covers. The disk rests on an intercalary backbone—a bone structure that most likely evolved from parts of the spine. This bony structure supports lamellae, specialized bony plates with tiny backward-facing spikes called spinules. The entire disk is covered with soft tissue compartments that are open at the top. “This makes the remora fish adhere very securely to soft-bodied, fast-moving marine hosts,” Traverso says.

A remora attaches to the host by pressing itself against the skin, which pushes the water out of these compartments, creating a low-pressure zone. Then, the spinules mechanically interlock with the host’s surface, making the whole thing work a bit like a combination of a suction cup and Velcro. When the fish wants to detach from a host, it lifts the disk, letting water back into the compartments to remove the suction. Once released, it can simply swim away.

What impressed the scientists the most, though, was the versatility of those disks. Reef-associated species of remora like Phtheirichthys lineatus are generalists and stick to various hosts, including other fish, sharks, or turtles. Other species living in the open sea are more specialized and attach to cetaceans, swordfish, or marlins. While most remoras attach to the external tissue of their hosts, R. albescens sticks within the oral cavities and gill chamber of manta rays.

To learn what makes all these different disks so good at sticking underwater, the team first examined their anatomy in detail. It turned out that the difference between the disks was mostly in the positioning of lamellae. Generalist species have a mix of parallel and angled lamellae, while remoras sticking to fast-swimming hosts have them mostly parallel. R. albescens, on the other hand, doesn’t have a dominant lamellae orientation pattern but has them positioned at a very wide variety of angles.

The researchers wanted to make an adhesive device that would work for a wide range of applications, including maritime exploration or underwater manufacturing. Their initial goal, though, was designing a drug delivery platform that could reliably stick to the inside walls of the gastrointestinal tract. So, they chose R. albescens disks as their starting point, since that species already attaches internally to its host. They termed their device an Mechanical Underwater Soft Adhesion System (MUSAS).

However, they didn’t just opt for a biomimetic, copy-and-paste design. “There were things we did differently,” Traverso says.

Upgrading nature

The first key difference was deployment. MUSAS was supposed to travel down the GI tract to reach its destination, so the first challenge was making it fit into a pill. The team chose the size 000 capsule, which at 26 millimeters in length and 9.5 millimeters in diameter, is the largest Food and Drug Administration-approved ingestible form. MUSAS had a supporting structure—just like remora disks, but made with stainless steel. The angled lamellae with spinules fashioned after those on R. albescens were made of a shape memory nickel-titanium alloy. The role of remora’s soft tissues, which provide the suction by dividing the disk into compartments, was played by an elastomer.

MUSAS, would be swallowed in a folded form within its huge pill. “The capsule is tuned to dissolve in specific pH environment, which is how we determine the target location—for example the small intestine has a slightly different pH than the stomach”, says Ziliang Kang, an MIT researcher in Traverso’s group and lead author of the study.  Once released, the shape memory alloy in MUSAS lamellae-like structures would unfold in response to body temperature and the whole thing would stick to the wall of the target organ, be it the esophagus, the stomach, or the intestines.

The mechanism of sticking was also a bit different from that of remoras. “The fish can swim and actively press itself against the surface it wants to stick to. MUSAS can’t do that, so instead we relied on the peristaltic movements within the GI tract to exert the necessary force,” Traverso explains. When the muscles contract, MUSAS would be pressed against the wall and attach to it. And it was expected to stay there for quite some time.

The team ran a series of experiments to evaluate MUSAS performance in a few different scenarios. The drug-delivery platform application was tested on pig organ samples. MUSAS stayed in the sample GI tract for an average of nine days, with the longest sticking time reaching three and a half weeks. MUSAS managed to stay in place despite food and fluids going through the samples.

Even when the team poked the devices with a pipette to test what they called “resisting dynamic interference,” MUSAS just slid a little but remained firmly attached. Other experiments included using MUSAS to attach temperature sensors to external tissues of live fish and putting sensors that could detect reflux events in the GI tract of live pigs.

Branching out

The team is working on making MUSAS compatible with a wider range of drugs and mRNA vaccines. “We also think about using this for stimulating tissues,” Traverso says. The solution he has in mind would use MUSAS to deliver electrical pulses to the walls of the GI tract, which Traverso’s lab has shown can activate appetite-regulating hormones. But the team also wants to go beyond strictly medical applications.

The team demonstrated that MUSAS is really strong as an adhesive. When it sticks to a surface, it can hold a weight over a thousand times greater than its own. This puts MUSAS more or less on par with some of the best adhesives we have, such as polyurethane glues or epoxy resins. What’s more, this sticking strength was measured when MUSAS was attached to soft, uneven, wet surfaces. “On a rigid, even surface, the force-to-weight ratio should be even higher,” Kang claims. And this, Kang thinks, makes scaled-up variants of MUSAS a good match for underwater manufacturing.

“The first scenario I see is using MUSAS as grippers attached to robotic arms moving around soft objects,” Kang explains. Currently, this is done using vacuum systems that simply suck onto a fabric or other surface. The problem is that these solutions are rather complex and heavy. Scaled-up MUSAS should be able to achieve the same thing passively, cutting cost and weight. The second idea Kang has is using MUSAS in robots designed to perform maintenance jobs beneath the waterline on boats or ships. “We are really trying to see what is possible,” Traverso says.

Nature, 2025.  DOI: 10.1038/s41586-025-09304-4

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