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AI versus the brain and the race for general intelligence

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Intelligence, ±artificial

We already have an example of general intelligence, and it doesn’t look like AI.

There’s no question that AI systems have accomplished some impressive feats, mastering games, writing text, and generating convincing images and video. That’s gotten some people talking about the possibility that we’re on the cusp of AGI, or artificial general intelligence. While some of this is marketing fanfare, enough people in the field are taking the idea seriously that it warrants a closer look.

Many arguments come down to the question of how AGI is defined, which people in the field can’t seem to agree upon. This contributes to estimates of its advent that range from “it’s practically here” to “we’ll never achieve it.” Given that range, it’s impossible to provide any sort of informed perspective on how close we are.

But we do have an existing example of AGI without the “A”—the intelligence provided by the animal brain, particularly the human one. And one thing is clear: The systems being touted as evidence that AGI is just around the corner do not work at all like the brain does. That may not be a fatal flaw, or even a flaw at all. It’s entirely possible that there’s more than one way to reach intelligence, depending on how it’s defined. But at least some of the differences are likely to be functionally significant, and the fact that AI is taking a very different route from the one working example we have is likely to be meaningful.

With all that in mind, let’s look at some of the things the brain does that current AI systems can’t.

Defining AGI might help

Artificial general intelligence hasn’t really been defined. Those who argue that it’s imminent are either vague about what they expect the first AGI systems to be capable of or simply define it as the ability to dramatically exceed human performance at a limited number of tasks. Predictions of AGI’s arrival in the intermediate term tend to focus on AI systems demonstrating specific behaviors that seem human-like. The further one goes out on the timeline, the greater the emphasis on the “G” of AGI and its implication of systems that are far less specialized.

But most of these predictions are coming from people working in companies with a commercial interest in AI. It was notable that none of the researchers we talked to for this article were willing to offer a definition of AGI. They were, however, willing to point out how current systems fall short.

“I think that AGI would be something that is going to be more robust, more stable—not necessarily smarter in general but more coherent in its abilities,” said Ariel Goldstein, a researcher at Hebrew University of Jerusalem. “You’d expect a system that can do X and Y to also be able to do Z and T. Somehow, these systems seem to be more fragmented in a way. To be surprisingly good at one thing and then surprisingly bad at another thing that seems related.”

“I think that’s a big distinction, this idea of generalizability,” echoed neuroscientist Christa Baker of NC State University. “You can learn how to analyze logic in one sphere, but if you come to a new circumstance, it’s not like now you’re an idiot.”

Mariano Schain, a Google engineer who has collaborated with Goldstein, focused on the abilities that underlie this generalizability. He mentioned both long-term and task-specific memory and the ability to deploy skills developed in one task in different contexts. These are limited-to-nonexistent in existing AI systems.

Beyond those specific limits, Baker noted that “there’s long been this very human-centric idea of intelligence that only humans are intelligent.” That’s fallen away within the scientific community as we’ve studied more about animal behavior. But there’s still a bias to privilege human-like behaviors, such as the human-sounding responses generated by large language models

The fruit flies that Baker studies can integrate multiple types of sensory information, control four sets of limbs, navigate complex environments, satisfy their own energy needs, produce new generations of brains, and more. And they do that all with brains that contain under 150,000 neurons, far fewer than current large language models.

These capabilities are complicated enough that it’s not entirely clear how the brain enables them. (If we knew how, it might be possible to engineer artificial systems with similar capacities.) But we do know a fair bit about how brains operate, and there are some very obvious ways that they differ from the artificial systems we’ve created so far.

Neurons vs. artificial neurons

Most current AI systems, including all large language models, are based on what are called neural networks. These were intentionally designed to mimic how some areas of the brain operate, with large numbers of artificial neurons taking an input, modifying it, and then passing the modified information on to another layer of artificial neurons. Each of these artificial neurons can pass the information on to multiple instances in the next layer, with different weights applied to each connection. In turn, each of the artificial neurons in the next layer can receive input from multiple sources in the previous one.

After passing through enough layers, the final layer is read and transformed into an output, such as the pixels in an image that correspond to a cat.

While that system is modeled on the behavior of some structures within the brain, it’s a very limited approximation. For one, all artificial neurons are functionally equivalent—there’s no specialization. In contrast, real neurons are highly specialized; they use a variety of neurotransmitters and take input from a range of extra-neural inputs like hormones. Some specialize in sending inhibitory signals while others activate the neurons they interact with. Different physical structures allow them to make different numbers and connections.

In addition, rather than simply forwarding a single value to the next layer, real neurons communicate through an analog series of activity spikes, sending trains of pulses that vary in timing and intensity. This allows for a degree of non-deterministic noise in communications.

Finally, while organized layers are a feature of a few structures in brains, they’re far from the rule. “What we found is it’s—at least in the fly—much more interconnected,” Baker told Ars. “You can’t really identify this strictly hierarchical network.”

With near-complete connection maps of the fly brain becoming available, she told Ars that researchers are “finding lateral connections or feedback projections, or what we call recurrent loops, where we’ve got neurons that are making a little circle and connectivity patterns. I think those things are probably going to be a lot more widespread than we currently appreciate.”

While we’re only beginning to understand the functional consequences of all this complexity, it’s safe to say that it allows networks composed of actual neurons far more flexibility in how they process information—a flexibility that may underly how these neurons get re-deployed in a way that these researchers identified as crucial for some form of generalized intelligence.

But the differences between neural networks and the real-world brains they were modeled on go well beyond the functional differences we’ve talked about so far. They extend to significant differences in how these functional units are organized.

The brain isn’t monolithic

The neural networks we’ve generated so far are largely specialized systems meant to handle a single task. Even the most complicated tasks, like the prediction of protein structures, have typically relied on the interaction of only two or three specialized systems. In contrast, the typical brain has a lot of functional units. Some of these operate by sequentially processing a single set of inputs in something resembling a pipeline. But many others can operate in parallel, in some cases without any input activity going on elsewhere in the brain.

To give a sense of what this looks like, let’s think about what’s going on as you read this article. Doing so requires systems that handle motor control, which keep your head and eyes focused on the screen. Part of this system operates via feedback from the neurons that are processing the read material, causing small eye movements that help your eyes move across individual sentences and between lines.

Separately, there’s part of your brain devoted to telling the visual system what not to pay attention to, like the icon showing an ever-growing number of unread emails. Those of us who can read a webpage without even noticing the ads on it presumably have a very well-developed system in place for ignoring things. Reading this article may also mean you’re engaging the systems that handle other senses, getting you to ignore things like the noise of your heating system coming on while remaining alert for things that might signify threats, like an unexplained sound in the next room.

The input generated by the visual system then needs to be processed, from individual character recognition up to the identification of words and sentences, processes that involve systems in areas of the brain involved in both visual processing and language. Again, this is an iterative process, where building meaning from a sentence may require many eye movements to scan back and forth across a sentence, improving reading comprehension—and requiring many of these systems to communicate among themselves.

As meaning gets extracted from a sentence, other parts of the brain integrate it with information obtained in earlier sentences, which tends to engage yet another area of the brain, one that handles a short-term memory system called working memory. Meanwhile, other systems will be searching long-term memory, finding related material that can help the brain place the new information within the context of what it already knows. Still other specialized brain areas are checking for things like whether there’s any emotional content to the material you’re reading.

All of these different areas are engaged without you being consciously aware of the need for them.

In contrast, something like ChatGPT, despite having a lot of artificial neurons, is monolithic: No specialized structures are allocated before training starts. That’s in sharp contrast to a brain. “The brain does not start out as a bag of neurons and then as a baby it needs to make sense of the world and then determine what connections to make,” Baker noted. “There already a lot of constraints and specifics that are already set up.”

Even in cases where it’s not possible to see any physical distinction between cells specialized for different functions, Baker noted that we can often find differences in what genes are active.

In contrast, pre-planned modularity is relatively new to the AI world. In software development, “This concept of modularity is well established, so we have the whole methodology around it, how to manage it,” Schain said, “it’s really an aspect that is important for maybe achieving AI systems that can then operate similarly to the human brain.” There are a few cases where developers have enforced modularity on systems, but Goldstein said these systems need to be trained with all the modules in place to see any gain in performance.

None of this is saying that a modular system can’t arise within a neural network as a result of its training. But so far, we have very limited evidence that they do. And since we mostly deploy each system for a very limited number of tasks, there’s no reason to think modularity will be valuable.

There is some reason to believe that this modularity is key to the brain’s incredible flexibility. The region that recognizes emotion-evoking content in written text can also recognize it in music and images, for example. But the evidence here is mixed. There are some clear instances where a single brain region handles related tasks, but that’s not consistently the case; Baker noted that, “When you’re talking humans, there are parts of the brain that are dedicated to understanding speech, and there are different areas that are involved in producing speech.”

This sort of re-use of would also provide an advantage in terms of learning since behaviors developed in one context could potentially be deployed in others. But as we’ll see, the differences between brains and AI when it comes to learning are far more comprehensive than that.

The brain is constantly training

Current AIs generally have two states: training and deployment. Training is where the AI learns its behavior; deployment is where that behavior is put to use. This isn’t absolute, as the behavior can be tweaked in response to things learned during deployment, like finding out it recommends eating a rock daily. But for the most part, once the weights among the connections of a neural network are determined through training, they’re retained.

That may be starting to change a bit, Schain said. “There is now maybe a shift in similarity where AI systems are using more and more what they call the test time compute, where at inference time you do much more than before, kind of a parallel to how the human brain operates,” he told Ars. But it’s still the case that neural networks are essentially useless without an extended training period.

In contrast, a brain doesn’t have distinct learning and active states; it’s constantly in both modes. In many cases, the brain learns while doing. Baker described that in terms of learning to take jumpshots: “Once you have made your movement, the ball has left your hand, it’s going to land somewhere. So that visual signal—that comparison of where it landed versus where you wanted it to go—is what we call an error signal. That’s detected by the cerebellum, and its goal is to minimize that error signal. So the next time you do it, the brain is trying to compensate for what you did last time.”

It makes for very different learning curves. An AI is typically not very useful until it has had a substantial amount of training. In contrast, a human can often pick up basic competence in a very short amount of time (and without massive energy use). “Even if you’re put into a situation where you’ve never been before, you can still figure it out,” Baker said. “If you see a new object, you don’t have to be trained on that a thousand times to know how to use it. A lot of the time, [if] you see it one time, you can make predictions.”

As a result, while an AI system with sufficient training may ultimately outperform the human, the human will typically reach a high level of performance faster. And unlike an AI, a human’s performance doesn’t remain static. Incremental improvements and innovative approaches are both still possible. This also allows humans to adjust to changed circumstances more readily. An AI trained on the body of written material up until 2020 might struggle to comprehend teen-speak in 2030; humans could at least potentially adjust to the shifts in language. (Though maybe an AI trained to respond to confusing phrasing with “get off my lawn” would be indistinguishable.)

Finally, since the brain is a flexible learning device, the lessons learned from one skill can be applied to related skills. So the ability to recognize tones and read sheet music can help with the mastery of multiple musical instruments. Chemistry and cooking share overlapping skillsets. And when it comes to schooling, learning how to learn can be used to master a wide range of topics.

In contrast, it’s essentially impossible to use an AI model trained on one topic for much else. The biggest exceptions are large language models, which seem to be able to solve problems on a wide variety of topics if they’re presented as text. But here, there’s still a dependence on sufficient examples of similar problems appearing in the body of text the system was trained on. To give an example, something like ChatGPT can seem to be able to solve math problems, but it’s best at solving things that were discussed in its training materials; giving it something new will generally cause it to stumble.

Déjà vu

For Schain, however, the biggest difference between AI and biology is in terms of memory. For many AIs, “memory” is indistinguishable from the computational resources that allow it to perform a task and was formed during training. For the large language models, it includes both the weights of connections learned then and a narrow “context window” that encompasses any recent exchanges with a single user. In contrast, biological systems have a lifetime of memories to rely on.

“For AI, it’s very basic: It’s like the memory is in the weights [of connections] or in the context. But with a human brain, it’s a much more sophisticated mechanism, still to be uncovered. It’s more distributed. There is the short term and long term, and it has to do a lot with different timescales. Memory for the last second, a minute and a day or a year or years, and they all may be relevant.”

This lifetime of memories can be key to making intelligence general. It helps us recognize the possibilities and limits of drawing analogies between different circumstances or applying things learned in one context versus another. It provides us with insights that let us solve problems that we’ve never confronted before. And, of course, it also ensures that the horrible bit of pop music you were exposed to in your teens remains an earworm well into your 80s.

The differences between how brains and AIs handle memory, however, are very hard to describe. AIs don’t really have distinct memory, while the use of memory as the brain handles a task more sophisticated than navigating a maze is generally so poorly understood that it’s difficult to discuss at all. All we can really say is that there are clear differences there.

Facing limits

It’s difficult to think about AI without recognizing the enormous energy and computational resources involved in training one. And in this case, it’s potentially relevant. Brains have evolved under enormous energy constraints and continue to operate using well under the energy that a daily diet can provide. That has forced biology to figure out ways to optimize its resources and get the most out of the resources it does commit to.

In contrast, the story of recent developments in AI is largely one of throwing more resources at them. And plans for the future seem to (so far at least) involve more of this, including larger training data sets and ever more artificial neurons and connections among them. All of this comes at a time when the best current AIs are already using three orders of magnitude more neurons than we’d find in a fly’s brain and have nowhere near the fly’s general capabilities.

It remains possible that there is more than one route to those general capabilities and that some offshoot of today’s AI systems will eventually find a different route. But if it turns out that we have to bring our computerized systems closer to biology to get there, we’ll run into a serious roadblock: We don’t fully understand the biology yet.

“I guess I am not optimistic that any kind of artificial neural network will ever be able to achieve the same plasticity, the same generalizability, the same flexibility that a human brain has,” Baker said. “That’s just because we don’t even know how it gets it; we don’t know how that arises. So how do you build that into a system?”

Photo of John Timmer

John is Ars Technica’s science editor. He has a Bachelor of Arts in Biochemistry from Columbia University, and a Ph.D. in Molecular and Cell Biology from the University of California, Berkeley. When physically separated from his keyboard, he tends to seek out a bicycle, or a scenic location for communing with his hiking boots.

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The ISS is nearly as microbe-free as an isolation ward

Biology, Ecology, international space station, microbiome, Science / /

“One of the more similar environments to the ISS was in the isolation dorms on the UCSD campus during the COVID-19 pandemic. All surfaces were continuously sterilized, so that microbial signatures would be erased by the time another person would show up,” Benitez said. So, one of the first solutions to the ISS microbial diversity problem he and his colleagues suggested was that they perhaps should ease up on sterilizing the station so much.

“The extensive use of disinfection chemicals might not be the best approach to maintaining a healthy microbial environment, although there is certainly plenty of research to be conducted,” Benitez said.

Space-faring gardens

He suggested that introducing microbes that are beneficial to human health might be better than constantly struggling to wipe out all microbial life on the station. And while some modules up there do need to be sterilized, keeping some beneficial microbes alive could be achieved by designing future spacecraft in a way that accounts for how the microbes spread.

“We found that microbes in modules with little human activity tend to stay in those modules without spreading. When human activity is high in a module, then the microbes spread to adjacent modules,”  Zhao said. She said spacecraft could be designed to put modules with high human activity at one end and the modules with little to no human activity at the opposite end, so the busy modules don’t contaminate the ones that need to remain sterile. “We are of course talking as microbiologists and chemists—perhaps spacecraft engineers have more pressing reasons to put certain modules at certain spots,” Zhao said. “These are just preliminary ideas.”

But what about crewed deep space missions to Mars and other destinations in the Solar System? Should we carefully design the microbial composition beforehand, plant the microbes on the spacecraft and hope this artificial, closed ecosystem will work for years without any interventions from Earth?

“I’d take a more holistic ecosystem approach,” Benitez said. He imagines in the future we could build spacecraft and space stations hosting entire gardens with microbes that would interact with plants, pollinators, and animals to create balanced, self-sustaining ecosystems. “We’d not only need to think about sending the astronauts and the machines they need to function, but also about all other lifeforms we will need to send along with them,” Benitez said

Cell, 2025. DOI: 10.1016/j.cell.2025.01.039

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We’ve figured out the basics of a shape-shifting, T-1000-style material

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Campàs and his colleagues decided to design cell-like robots that could do all those things.

T-1000 building blocks

Each robot had motorized gears around its perimeter that could interlock with gears on other robots. The gears allowed the robots to move within the collective without breaking their bonds with each other, just like cells do in a living organism.

Linking the robots was a job of magnets that could rotate to maintain adhesion regardless of their orientation. Each robot also had a photodetector that could sense the polarity of light, allowing basic commands to be sent using a simple flashlight with a polarization filter. “The switch between solid and liquid states was driven by fluctuations of the force the motors applied, and we encoded the intensity of those fluctuations in the intensity of light,” says Matthew Devlin, a researcher at the Department of Mechanical Engineering at the University of California Santa Barbara and lead author of the study.

In response to light signals, two robotic collectives, 20 robots total, could elongate toward each other, touch in the middle, and form a bridge that could hold a load of just under 5 kilograms. After forming a cube, they could support an adult human weighing around 70 kilograms. They could also flow around an object, assume a complementary shape, and stiffen up to act as a wrench. “This was the Terminator idea of shapeshifting. This was exactly what we had in mind,” Campàs claims.

The only problem was, the robots were a bit above 5 centimeters in diameter. To get robotic collectives closer to Terminator’s mimetic polyalloy, the team wants to make the robots smaller. Much smaller.

Terminator nanobots?

“The good news is, you don’t have to go down with scale to what you see in living systems,” Campàs says. “Cells are roughly 10 microns. But anything around 100 microns—even up to 1 millimeter—robots would already be really impressive.” Unfortunately, we are rather far from making machines that small.

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Federal firings could wreak havoc on Great Lakes fishery

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Her performance reviews for the last year had been glowing, so the letter made no sense. “It’s not a real explanation,” she said.

The USFWS layoffs will not affect the sea lamprey control program in Canada, McClinchey said. “The Canadian government has assured us that the money from Canada will continue to be there and we’re on track to deliver a full program in Canadian waters,” he said. “That’s great, but this program works because it’s border blind.”

In other words: Cuts to lamprey control in US waters are a threat to fish and fishermen everywhere on the Great Lakes.

Just a week ago, the Great Lakes Fishery Commission faced a more dire staffing situation, as the USFWS informed directors they’d also be unable to hire seasonal workers to spread lampricide come April. Within a few days, that hiring freeze was reversed, said McClinchey.

This reversal gives him a bit of hope. “That at least tells us no one is rooting for the lamprey,” he said.

McClinchey is currently in DC for appropriation season, presenting the commission’s work to members of Congress and defending the agency’s budget. It’s an annual trip, but this year he’s also advocating for the reinstatement of laid-off lamprey control employees.

He is optimistic. “It seems clear to me that it’s important we preserve this program, and so far everyone we’ve encountered thinks that way and are working to that end,” he said.

Cutting back the program isn’t really on the table for the commission. Even minor cuts to scope would be devastating for the fishery, he said.

Even the former USFWS employee from Marquette is remaining hopeful. “I still think that they’re going to scramble to make it happen,” she said. “Because it’s not really an option to just stop treating for a whole season.”

This story originally appeared on Inside Climate News.

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SpaceX readies a redo of last month’s ill-fated Starship test flight

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The FAA has cleared SpaceX to launch Starship’s eighth test flight as soon as Monday.

Ship 34, destined to launch on the next Starship test flight, test-fired its engines in South Texas on February 12. Credit: SpaceX

SpaceX plans to launch the eighth full-scale test flight of its enormous Starship rocket as soon as Monday after receiving regulatory approval from the Federal Aviation Administration.

The test flight will be a repeat of what SpaceX hoped to achieve on the previous Starship launch in January, when the rocket broke apart and showered debris over the Atlantic Ocean and Turks and Caicos Islands. The accident prevented SpaceX from completing many of the flight’s goals, such as testing Starship’s satellite deployment mechanism and new types of heat shield material.

Those things are high on the to-do list for Flight 8, set to lift off at 5: 30 pm CST (6: 30 pm EST; 23: 30 UTC) Monday from SpaceX’s Starbase launch facility on the Texas Gulf Coast. Over the weekend, SpaceX plans to mount the rocket’s Starship upper stage atop the Super Heavy booster already in position on the launch pad.

The fully stacked rocket will tower 404 feet (123.1 meters) tall. Like the test flight on January 16, this launch will use a second-generation, Block 2, version of Starship with larger propellant tanks with 25 percent more volume than previous vehicle iterations. The payload compartment near the ship’s top is somewhat smaller than the payload bay on Block 1 Starships.

This block upgrade moves SpaceX closer to attempting more challenging things with Starship, such as returning the ship, or upper stage, back to the launch site from orbit. It will be caught with the launch tower at Starbase, just like SpaceX accomplished last year with the Super Heavy booster. Officials also want to bring Starship into service to launch Starlink Internet satellites and demonstrate in-orbit refueling, an enabling capability for future Starship flights to the Moon and Mars.

NASA has contracts with SpaceX worth more than $4 billion to develop a Starship spinoff as a human-rated Moon lander for the Artemis lunar program. The mega-rocket is central to Elon Musk’s ambition to create a human settlement on Mars.

Another shot at glory

Other changes introduced on Starship Version 2 include redesigned forward flaps, which are smaller and closer to the tip of the ship’s nose to better protect them from the scorching heat of reentry. Technicians also removed some of the ship’s thermal protection tiles to “stress-test vulnerable areas” of the vehicle during descent. SpaceX is experimenting with metallic tile designs, including one with active cooling, that might be less brittle than the ceramic tiles used elsewhere on the ship.

Engineers also installed rudimentary catch fittings on the ship to evaluate how they respond to the heat of reentry, when temperatures outside the vehicle climb to 2,600° Fahrenheit (1,430° Celsius). Read more about Starship Version in this previous story from Ars.

It will take about 1 hour and 6 minutes for Starship to fly from the launch pad in South Texas to a splashdown zone in the Indian Ocean northwest of Australia. The rocket’s Super Heavy booster will fire 33 methane-fueled Raptor engines for two-and-a-half minutes as it climbs east from the Texas coastline, then jettison from the Starship upper stage and reverse course to return to Starbase for another catch with mechanical arms on the launch tower.

Meanwhile, Starship will ignite six Raptor engines and accelerate to a speed just shy of orbital velocity, putting the ship on a trajectory to reenter the atmosphere after soaring about halfway around the world.

Booster 15 perched on the launch mount at Starbase, Texas. Credit: SpaceX

If you’ve watched the last few Starship flights, this profile probably sounds familiar. SpaceX achieved successful splashdowns after three Starship test flights last year, and hoped to do it again before the premature end of Flight 7 in January. Instead, the accident was the most significant technical setback for the Starship program since the first full-scale test flight in 2023, which damaged the launch pad before the rocket spun out of control in the upper atmosphere.

Now, SpaceX hopes to get back on track. At the end of last year, company officials said they targeted as many as 25 Starship flights in 2025. Two months in, SpaceX is about to launch its second Starship of the year.

The breakup of Starship last month prevented SpaceX from evaluating the performance of the ship’s Pez-like satellite deployer and upgraded heat shield. Engineers are eager to see how those perform on Monday’s flight. Once in space, the ship will release four simulators replicating the approximate size and mass of SpaceX’s next-generation Starlink Internet satellites. They will follow the same suborbital trajectory as Starship and reenter the atmosphere over the Indian Ocean.

That will be followed by a restart of a Raptor engine on Starship in space, repeating a feat first achieved on Flight 6 in November. Officials want to ensure Raptor engines can reignite reliably in space before actually launching Starship into a stable orbit, where the ship must burn an engine to guide itself back into the atmosphere for a controlled reentry. With another suborbital flight on tap Monday, the engine relight is purely a confidence-building demonstration and not critical for a safe return to Earth.

The flight plan for Starship’s next launch includes another attempt to catch the Super Heavy booster with the launch tower, a satellite deployment demonstration, and an important test of its heat shield. Credit: SpaceX

Then, about 47 minutes into the mission, Starship will plunge back into the atmosphere. If this flight is like the previous few, expect to see live high-definition video streaming back from Starship as super-heated plasma envelops the vehicle in a cloak of pink and orange. Finally, air resistance will slow the ship below the speed of sound, and just 20 seconds before reaching the ocean, the rocket will flip to a vertical orientation and reignite its Raptor engines again to brake for splashdown.

This is where SpaceX hopes Starship Version 2 will shine. Although three Starships have made it to the ocean intact, the scorching temperatures of reentry damaged parts of their heat shields and flaps. That won’t do for SpaceX’s vision of rapidly reusing Starship with minimal or no refurbishment. Heat shield repairs slowed down the turnaround time between NASA’s space shuttle missions, and officials hope the upgraded heat shield on Starship Version 2 will decrease the downtime.

FAA’s green light

The FAA confirmed Friday it issued a launch license earlier this week for Starship Flight 8.

“The FAA determined SpaceX met all safety, environmental and other licensing requirements for the suborbital test flight,” an FAA spokesperson said in a statement.

The federal regulator oversaw a SpaceX-led investigation into the failure of Flight 7. SpaceX said NASA, the National Transportation Safety Board, and the US Space Force also participated in the investigation, which determined that propellant leaks and fires in an aft compartment, or attic, of Starship led to the shutdown of its engines and eventual breakup.

Engineers concluded the leaks were most likely caused by a harmonic response several times stronger than predicted, suggesting the vibrations during the ship’s climb into space were in resonance with the vehicle’s natural frequency. This would have intensified the vibrations beyond the levels engineers expected from ground testing.

Earlier this month, SpaceX completed an extended-duration static fire of the next Starship upper stage to test hardware modifications at multiple engine thrust levels. According to SpaceX, findings from the static fire informed changes to the fuel feed lines to Starship’s Raptor engines, adjustments to propellant temperatures, and a new operating thrust for the next test flight.

“To address flammability potential in the attic section on Starship, additional vents and a new purge system utilizing gaseous nitrogen are being added to the current generation of ships to make the area more robust to propellant leakage,” SpaceX said. “Future upgrades to Starship will introduce the Raptor 3 engine, reducing the attic volume and eliminating the majority of joints that can leak into this volume.”

FAA officials were apparently satisfied with all of this. The agency’s commercial spaceflight division completed a “comprehensive safety review” and determined Starship can return to flight operations while the investigation into the Flight 7 failure remains open. This isn’t new. The FAA also used this safety determination to expedite SpaceX launch license approvals last year as officials investigated mishaps on Starship and Falcon 9 rocket flights.

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Stephen Clark is a space reporter at Ars Technica, covering private space companies and the world’s space agencies. Stephen writes about the nexus of technology, science, policy, and business on and off the planet.

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Mars’ polar ice cap is slowly pushing its north pole inward

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The orbiters that carried the radar hardware, along with one or two others, have been orbiting long enough that any major changes in Mars’ gravity caused by ice accumulation or crustal displacement would have shown up in their orbital behavior. The orbital changes they do see, “indicates that the increase in the gravitational potential associated with long-term ice accumulation is higher than the decrease in gravitational potential from downward deflection.” They calculate that the deformation has to be less than 0.13 millimeters per year to be consistent with the gravitational signal.

Finally, the model had to have realistic conditions at the polar ice cap, with a density consistent with a mixture of ice and dust.

Out of those 84 models, only three were consistent with all of these constraints. All three had a very viscous Martian interior, consistent with a relatively cold interior. That’s not a surprise, given what we’ve already inferred about Mars’ history. But it also suggests that most of the radioactive elements that provide heat to the red planet are in the crust, rather than deeper in the interior. That’s something we might have been able to check, had InSight’s temperature measurement experiment deployed correctly. But as it is, we’ll have to wait until some unidentified future mission to get a picture of Mars’ heat dynamics.

In any case, the models also suggest that Mars’ polar ice cap is less than 10 million years old, consistent with the orbitally driven climate models.

In a lot of ways, the new information is an update of earlier attempts to model the Martian interior, given a few more years of orbital data and the information gained from the InSight lander, which also determined the thickness of Mars’ crust and size of its core. But it’s also a good way of understanding how scientists can take bits and pieces of information from seemingly unrelated sources and build them into a coherent picture.

Nature, 2025. DOI: 10.1038/s41586-024-08565-9  (About DOIs).

Mars’ polar ice cap is slowly pushing its north pole inward Read More »

research-roundup:-7-cool-science-stories-from-february

Research roundup: 7 cool science stories from February

ancient egypt, fluid dynamics, Herculaneum scrolls, Physics, research roundup, Science / /

Dancing sea turtles, the discovery of an Egyptian pharaoh’s tomb, perfectly boiled eggs, and more.

X-ray image of the PHerc.172 scroll Credit: Vesuvius Challenge

It’s a regrettable reality that there is never time to cover all the interesting scientific stories we come across each month. In the past, we’ve featured year-end roundups of cool science stories we (almost) missed. This year, we’re experimenting with a monthly collection. February’s list includes dancing sea turtles, the secret to a perfectly boiled egg, the latest breakthrough in deciphering the Herculaneum scrolls, the discovery of an Egyptian pharaoh’s tomb, and more.

Dancing sea turtles

There is growing evidence that certain migratory animal species (turtles, birds, some species of fish) are able to exploit the Earth’s magnetic field for navigation, using it both as a compass to determine direction and as a kind of “map” to track their geographical position while migrating. A paper published in the journal Nature offers evidence of a possible mechanism for this unusual ability, at least in loggerhead sea turtles, who perform an energetic “dance” when they follow magnetic fields to a tasty snack.

Sea turtles make impressive 8,000-mile migrations across oceans and tend to return to the same feeding and nesting sites. The authors believe they achieve this through their ability to remember the magnetic signature of those areas and store them in a mental map. To test that hypothesis, the scientists placed juvenile sea turtles into two large tanks of water outfitted with large coils to create magnetic signatures at specific locations within the tanks. One tank features such a location that had food; the other had a similar location without food.

They found that the sea turtles in the first tank performed distinctive “dancing” moves when they arrived at the area associated with food: tilting their bodies, dog-paddling, spinning in place, or raising their head near or above the surface of the water. When they ran a second experiment using different radio frequencies, they found that the change interfered with the turtles’ internal compass, and they could not orient themselves while swimming. The authors concluded that this is compelling evidence that the sea turtles can distinguish between magnetic fields, possibly relying on complex chemical reactions, i.e., “magnetoreception.” The map sense, however, likely relies on a different mechanism.

Nature, 2025. DOI: 10.1038/s41586-024-08554-y  (About DOIs).

Long-lost tomb of Thutmose II

Archaeologists found a simple tomb near Luxor and identified it as the 3,500-year-old burial site of King Thutmose II.

Archaeologists found a simple tomb near Luxor and identified it as the 3,500-year-old burial site of King Thutmose II. Credit: Egypt’s Ministry of Tourism and Antiquities

Thutmose II was the fourth pharaoh of the Tutankhamun (18th) dynasty. He reigned only about 13 years and married his half-sister Hatshepsut (who went on to become the sixth pharaoh in the dynasty). Archaeologists have now confirmed that a tomb built underneath a waterfall in the mountains in Luxor and discovered in 2022 is the final resting place of Thutmose II. It’s the last of the 18th dynasty royal tombs to be found, more than a century after Tutankhamun’s tomb was found in 1922.

When it was first found, archaeologists thought the tomb might be that of a king’s wife, given its close proximity to Hatshepsut’s tomb and those of the wives of Thutmose III. But they found fragments of alabaster vases inscribed with Thutmose II’s name, along with scraps of religious burial texts and plaster fragments on the partially intact ceiling with traces of blue paint and yellow stars—typically only found in kings’ tombs. Something crucial was missing, however: the actual mummy and grave goods of Thutmose II.

It’s long been assumed that the king’s mummy was discovered in the 19th century at another site called Deir el-Bahari. But archaeologist Piers Litherland, who headed the British team that discovered the tomb, thinks that identification was in error. An inscription stated that Hatshepsut had the tomb’s contents relocated due to flooding. Litherland believes the pharaoh’s actual mummy is buried in a second tomb. Confirmation (or not) of his hypothesis won’t come until after archaeologists finish excavating what he thinks is the site of that second tomb, which is currently buried under multiple layers of rock and plaster.

Hidden images in Pollock paintings

“Troubled Queen” reveals a “hidden” figure, possibly a soldier. Credit: D.A. Morrissette et al., CNS Spectrums 2025

Physicists have long been fascinated by the drip paintings of “splatter master” Jackson Pollock, pondering the presence of fractal patterns (or lack thereof), as well as the presence of curls and coils in his work and whether the artist deliberately exploited a well-known fluid dynamics effect to achieve them—or deliberately avoided them. Now psychiatrists are getting into the game, arguing in a paper published in CNS Spectrums that Pollock—known to incorporate images into his early pre-drip paintings—also used many of the same images repeatedly in his later abstract drip paintings.

People have long claimed to see images in those drip paintings, but the phenomenon is usually dismissed by art critics as a trick of human perception, much like the fractal edges of Rorschach ink blots can fool the eye and mind. The authors of this latest paper analyzed Pollock’s early painting “Troubled Queen” and found multiple images incorporated into the painting, which they believe establishes a basis for their argument that Pollock also incorporated such images into his later drip painting, albeit possibly subconsciously.

“Seeing an image once in a drip painting could be random,” said co-author Stephen M. Stahl of the University of California, San Diego. “Seeing the same image twice in different paintings could be a coincidence. Seeing it three or more times—as is the case for booze bottles, monkeys and gorillas, elephants, and many other subjects and objects in Pollock’s paintings—makes those images very unlikely to be randomly provoked perceptions without any basis in reality.”

CNS Spectrums, 2025. DOI: 10.1017/S1092852924001470

Solving a fluid dynamics mystery

Soap opera in the maze: Geometry matters in Marangoni flows.

Every fall, the American Physical Society exhibits a Gallery of Fluid Motion, which recognizes the innate artistry of images and videos derived from fluid dynamics research. Several years ago, physicists at the University of California, Santa Barbara (UCSB) submitted an entry featuring a pool of red dye, propelled by a few drops of soap acting as a surfactant, that seemed to “know” how to solve a maze whose corridors were filled with milk. This is unusual since one would expect the dye to diffuse more uniformly. The team has now solved that puzzle, according to a paper published in Physical Review Letters.

The key factor is surface tension, specifically a phenomenon known as the Marangoni effect, which also drives the “coffee ring effect” and the “tears of wine” phenomenon. If you spread a thin film of water on your kitchen counter and place a single drop of alcohol in the center, you’ll see the water flow outward, away from the alcohol. The difference in their alcohol concentrations creates a surface tension gradient, driving the flow.

In the case of the UCSB experiment, the soap reduces local surface tension around the red dye to set the dye in motion. There are also already surfactants in the milk that work in combination with the soapy surfactant to “solve” the maze. The milk surfactants create varying points of resistance as the dye makes its way through the maze. A dead end or a small space will have more resistance, redirecting the dye toward routes with less resistance—and ultimately to the maze’s exit. “That means the added surfactant instantly knows the layout of the maze,” said co-author Paolo Luzzatto-Fegiz.

Physical Review Letters, 2025. DOI: 10.1073/pnas.1802831115

How to cook a perfectly boiled egg

Credit: YouTube/Epicurious

There’s more than one way to boil an egg, whether one likes it hard-boiled, soft-boiled, or somewhere in between. The challenge is that eggs have what physicists call a “two-phase” structure: The yolk cooks at 65° Celsius, while the white (albumen) cooks at 85° Celsius. This often results in overcooked yolks or undercooked whites when conventional methods are used. Physicists at the Italian National Research Council think they’ve cracked the case: The perfectly cooked egg is best achieved via a painstaking process called “periodic cooking,” according to a paper in the journal Communications Engineering.

They started with a few fluid dynamics simulations to develop a method and then tested that method in the laboratory. The process involves transferring a cooking egg every two minutes—for 32 minutes—between a pot of boiling water (100° Celsius) and a bowl of cold water (30° Celsius). They compared their periodically cooked eggs with traditionally prepared hard-boiled and soft-boiled eggs, as well as eggs prepared using sous vide. The periodically cooked eggs ended up with soft yolks (typical of sous vide eggs) and a solidified egg white with a consistency between sous vide and soft-boiled eggs. Chemical analysis showed the periodically cooked eggs also contained more healthy polyphenols. “Periodic cooking clearly stood out as the most advantageous cooking method in terms of egg nutritional content,” the authors concluded.

Communications Engineering, 2025. DOI: 10.1038/s44172-024-00334-w

More progress on deciphering Herculaneum scrolls

X-ray scans and AI reveal the inside of ancient scroll

X-ray scans and AI reveal the inside of an ancient scroll. Credit: Vesuvius Challenge

The Vesuvius Challenge is an ongoing project that employs “digital unwrapping” and crowd-sourced machine learning to decipher the first letters from previously unreadable ancient scrolls found in an ancient Roman villa at Herculaneum. The 660-plus scrolls stayed buried under volcanic mud until they were excavated in the 1700s from a single room that archaeologists believe held the personal working library of an Epicurean philosopher named Philodemus. The badly singed, rolled-up scrolls were so fragile that it was long believed they would never be readable, as even touching them could cause them to crumble.

In 2023, the Vesuvius Challenge made its first award for deciphering the first letters, and last year, the project awarded the grand prize of $700,000 for producing the first readable text. The latest breakthrough is the successful generation of the first X-ray image of the inside of a scroll (PHerc. 172) housed in Oxford University’s Bodleian Libraries—a collaboration with the Vesuvius Challenge. The scroll’s ink has a unique chemical composition, possibly containing lead, which means it shows up more clearly in X-ray scans than other Herculaneum scrolls that have been scanned.

The machine learning aspect of this latest breakthrough focused primarily on detecting the presence of ink, not deciphering the characters or text. Oxford scholars are currently working to interpret the text. The first word to be translated was the Greek word for “disgust,” which appears twice in nearby columns of text. Meanwhile, the Vesuvius Challenge collaborators continue to work to further refine the image to make the characters even more legible and hope to digitally “unroll” the scroll all the way to the end, where the text likely indicates the title of the work.

What ancient Egyptian mummies smell like

mummified bodies in the exhibition area of the Egyptian museum in Cairo.

Mummified bodies in the exhibition area of the Egyptian Museum in Cairo. Credit: Emma Paolin

Much of what we know about ancient Egyptian embalming methods for mummification comes from ancient texts, but there are very few details about the specific spices, oils, resins, and other ingredients used. Science can help tease out the secret ingredients. For instance, a 2018 study analyzed organic residues from a mummy’s wrappings with gas chromatography-mass spectrometry and found that the wrappings were saturated with a mixture of plant oil, an aromatic plant extract, a gum or sugar, and heated conifer resin. Researchers at University College London have now identified the distinctive smells associated with Egyptian mummies—predominantly”woody,” “spicy,” and “sweet,” according to a paper published in the Journal of the American Chemical Society.

The team coupled gas chromatography with mass spectrometry to measure chemical molecules emitted by nine mummified bodies on display at the Egyptian Museum in Cairo and then asked a panel of trained human “sniffers” to describe the samples smells, rating them by quality, intensity, and pleasantness. This enabled them to identify whether a given odor molecule came from the mummy itself, conservation products, pesticides, or the body’s natural deterioration. The work offers additional clues into the materials used in mummification, as well as making it possible for the museum to create interactive “smellscapes” in future displays so visitors can experience the scents as well as the sights of ancient Egyptian mummies.

Journal of the American Chemical Society, 2025. DOI: 10.1021/jacs.4c15769

Photo of Jennifer Ouellette

Jennifer is a senior writer at Ars Technica with a particular focus on where science meets culture, covering everything from physics and related interdisciplinary topics to her favorite films and TV series. Jennifer lives in Baltimore with her spouse, physicist Sean M. Carroll, and their two cats, Ariel and Caliban.

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Rocket Report: Starship will soon fly again; Gilmour has a launch date

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One Falcon 9 launched an Intuitive Machines lunar lander, an asteroid prospector, and a NASA science probe.

Peter Beck, Rocket Lab’s founder and CEO, stands inside a test version of the “Hungry Hippo,” a nickname used to describe the clamshell-like nose cone of the Neutron rocket’s first stage booster. The fairing will open in flight to release Neutron’s second and payloads to continue into orbit, then close as the booster comes back to Earth for recovery. Credit: Rocket Lab

Welcome to Edition 7.33 of the Rocket Report! Phew, what a week for Rocket Lab! The company released a bevy of announcements in conjunction with its quarterly earnings report Thursday. Rocket Lab is spending a lot of money to develop the medium-lift rocket Neutron rocket, and as we’ll discuss below, a rocket landing platform and a new satellite design. For now, the company is sticking by its public statements that the Neutron rocket will launch this year—the official line is it will debut in the second half of 2025—but this schedule assumes near-perfect execution on the program. “We’ve always been clear that we run aggressive schedules,” said Peter Beck, Rocket Lab’s founder and CEO. The official schedule doesn’t quite allow me to invoke a strict interpretation of Berger’s Law, which states that if a rocket’s debut is predicted to happen in the fourth quarter of a year, and that quarter is six or more months away, the launch will be delayed. However, the spirit of the law seems valid here. This time last year, Rocket Lab targeted a first launch by the end of 2024, an aggressive target that has come and gone.

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.

Australian startup sets a launch date. The first attempt to send an Australian-made rocket into orbit is set to take place no sooner than March 15, the Australian Broadcasting Corporation reports. Gilmour Space Technologies’ launch window announcement marks a major development for the company, which has been working towards a test launch for a decade. Gilmour previously hoped to launch its test rocket, Eris, in May 2024, but had to wait for the Australian government to issue a launch license and airspace approvals for the flight to go forward. Those are now in hand, clearing the last regulatory hurdle before liftoff.

Setting expectations … Gilmour’s Eris rocket is made of three stages powered by hybrid engines consuming a solid fuel and a liquid oxidizer. Eris is designed to haul payloads of up to 672 pounds (305 kilograms) to low-Earth orbit, and will launch from Bowen Orbital Spaceport in Queensland on Australia’s northeastern coast. Gilmour said it would be “very lucky” if the rocket reached orbit on first attempt. “Success means different things for different people, but ignition and liftoff will be huge,” said James Gilmour, the company’s co-founder. (submitted by ZygP)

Blue Origin is keeping a secret. Blue Origin conducted the tenth crewed flight of its New Shepard suborbital vehicle Tuesday, carrying six people, one of whom remained at least semi-anonymous, Space News reports. The five passengers Blue Origin identified come from business and entertainment backgrounds, but in a break from past missions, the company did not disclose the identity of the sixth person, with hosts of the company webcast saying that individual “requested we not share his name today.” Photos released by the company before the launch, and footage from the webcast, showed that person to be a man wearing a flight suit with an “R. Wilson” nametag, and the NS-30 mission patch also included “Wilson” with the names of the other members of the crew. Not disclosing the name of someone who has been to space has little precedent.

Big names on NS-31 … Some of the passengers Blue Origin will fly on the next New Shepard crew mission lack the anonymity of R. Wilson. The next flight, designated NS-31, will carry an all-female crew, including music star Katy Perry, CBS host Gayle King, and Lauren Sánchez, a former journalist who is engaged to Blue Origin’s founder, Jeff Bezos. Blue Origin identified the other three passengers as Aisha Bowe, Amanda Ngyuen, and Kerianne Flynn. (submitted by EllPeaTea)

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Virgin Galactic is still blowing through cash. Virgin Galactic reported a net loss of $347 million in 2024, compared to a $502 million net loss in 2023, with the improvement primarily driven by lower operating expenses, the company said this week in a quarterly earnings release. These lower operating expenses are tied to Virgin Galactic’s decision to suspend operations of its VSS Unity suborbital rocket plane last year to focus investment into a new series of suborbital spacecraft known as Delta-class ships. Virgin Galactic said cash and cash equivalents fell 18 percent from the same period a year ago to $178.6 million. Investors have been eager for details on when it would resume—and then ramp up—flights to increase sales and cash in on a backlog of around 700 ticket holders, Bloomberg reports.

March toward manufacturing … Virgin Galactic said it plans to start assembling its first Delta-class ship in March, with a first flight targeted for the summer of 2026, two years after it stopped flying VSS Unity. The Delta ships will be easier to recycle between flights, and will carry six paying passengers, rather than the four VSS Unity carried on each flight. Company officials believe a higher flight rate with more passengers will bring in significantly more revenue, which was reported at just $430,000 in the fourth quarter of 2024. (submitted by EllPeaTea)

Japanese customers seem to love Rocket Lab. While Rocket Lab is developing the larger Neutron rocket, the company’s operational Electron launch vehicle continues to dominate the market for dedicated launches of small satellites. Rocket Lab announced Thursday it signed a new multi-launch deal with iQPS, a Japan-based Earth imaging company. The new deal follows an earlier multi-launch contract signed with iQPS in 2024 and brings the total number of booked dedicated Electron launches for iQPS to eight.

Radar is all the rage … These eight Electron launches in 2025 and 2026 will help iQPS build out its planned constellation of 36 radar remote sensing satellites capable of imaging the Earth day and night, and through any weather. The new deal is one of the largest Electron launch agreements to date, second only to Rocket Lab’s ten launch deal with another Japanese radar constellation operator, Synspective, signed last year. (submitted by zapman987)

Falcon 9 launch targets Moon and asteroid. With two commercial Moon landers already on their way, Houston-based Intuitive Machines launched its second robotic lander atop a SpaceX Falcon 9 rocket Wednesday, CBS News reports. Given the on-time launch and assuming no major problems, the Athena lander is expected to descend to touchdown on a flat mesa-like structure known as Mons Mouton on March 6, setting down just 100 miles from the Moon’s south pole—closer than any other spacecraft has attempted. Intuitive Machines became the first company to successfully land a spacecraft on the Moon last year, but the Athena lander will pursue more complex goals. It will test a NASA-provided drill designed to search for subsurface ice, deploy a small “micro-rover,” and dispatch a rocket-powered drone to explore a permanently shadowed crater.

Hitching a ride … The Athena lander didn’t take up all the capacity of the Falcon 9 rocket. Three other spacecraft also rocketed into space Wednesday night. These rideshare payloads were AstroForge’s commercially developed Odin asteroid prospector to search for potentially valuable mineral deposits, NASA’s Lunar Trailblazer satellite to characterize lunar ice from a perch in lunar orbit, and a compact space tug from Epic Aerospace. (submitted by EllPeaTea)

This rocket got a visitor for the first time since 2009. Astroscale’s ADRAS-J mission became the first spacecraft (at least in the unclassified world) to approach a piece of space junk in low-Earth orbit, Ars reports. This particular object, a derelict upper stage from a Japanese H-IIA rocket, has been in orbit since 2009. It’s one of about 2,000 spent rocket bodies circling the Earth and one of more than 45,000 objects in orbit tracked by US Space Command. Astroscale, based in Tokyo, built and launched the ADRAS-J mission in partnership with the Japanese space agency as a demonstration to show how a commercial satellite could rendezvous with an object in orbit that was never designed to receive visitors.

Next steps … ADRAS-J worked like a champ, closing in to a distance of less than 50 feet (15 meters) from the H-IIA rocket as it orbited several hundred miles above the Earth. The rocket is a “non-cooperative” object representative of other large pieces of space junk, which Astroscale wants to remove from orbit with a series of trash collecting satellites like ADRAS-J. But this demo only validated part of the technology required for space debris removal. Japan’s space agency and Astroscale are partnering on another mission, ADRAS-J2, for launch in 2027 to go up and latch on to the same H-IIA rocket and steer it out of orbit toward a controlled reentry over the ocean.

An update on Falcon 9’s upper stage. SpaceX said that a Falcon 9 upper stage that reentered over Europe earlier this month suffered a propellant leak that prevented it from doing a controlled reentry, Space News reports. The upper stage was placed in orbit on a February 1 launch from Vandenberg Space Force Base in California. After deploying its payload of 22 Starlink satellites, the upper stage was expected to perform a burn to enable a controlled reentry over the ocean, a standard procedure on most Falcon 9 launches to low-Earth orbit. The stage, though, did not appear to perform the burn and remained in orbit. Its orbit decayed from atmospheric drag and the stage reentered over Europe on February 19. Debris from the Falcon 9 second stage, including composite overwrapped pressure vessels, fell in Poland, landing near the city of Poznań.

Higher than expected body rates … In an update posted to its website this week, SpaceX blamed the upper stage anomaly on a liquid oxygen leak. “During the coast phase of this Starlink mission, a small liquid oxygen leak developed, which ultimately drove higher than expected vehicle body rates,” SpaceX said. SpaceX aborted the deorbit burn and instead passivated the upper stage, a process where the rocket discharges energy from its batteries and vents leftover propellant from its tanks to minimize the risk of a break-up in orbit. This was the third incident involving a Falcon 9 upper stage in a little more than six months. (submitted by EllPeaTea)

Rocket Lab’s reveals “Return On Investment.” Rocket Lab’s Neutron rocket is designed for partial reusability, and the company unveiled Thursday an important piece of infrastructure to make this a reality. Neutron’s first stage booster will land on a modified barge named “Return On Investment” measuring around 400 feet (122 meters) wide, somewhat bigger than SpaceX’s drone ships used for Falcon 9 landings at sea. In order to prep the barge for rocket duty, the company is adding autonomous ground support equipment to capture and secure the landed Neutron, blast shielding to protect equipment during Neutron landings, and station-keeping thrusters for precise positioning. It should be ready to enter service in 2026. Rocket Lab also has the option to return the Neutron first stage back to the launch site when mission parameters allow the rocket to reserve enough propellant to make the return journey.

More news from Rocket Lab … Continuing the firehose of news from Rocket Lab this week, the company announced a new satellite design called “Flatellite” that looks remarkably similar to SpaceX’s Starlink satellites. The satellite is flat in shape, hence its name, and stackable to fit as many spacecraft as possible into the envelope of a rocket’s payload fairing. Rocket Lab said the new satellite “can be produced in high volumes and (is) tailored for large constellations, targeting high value applications and national security missions.” (submitted by zapman987)

The writing is on the wall for SLS. The lights may be starting to go out for NASA’s Space Launch System program. On Wednesday, one of the Republican space policy leaders most consistently opposed to commercial heavy lift rockets over the last decade—as an alternative to NASA’s large SLS rocket—has changed his mind, Ars reports. “We need an off-ramp for reliance on the SLS,” said Scott Pace, director of the Space Policy Institute at George Washington University, in written testimony before a congressional hearing about US space policy.

Not keeping Pace … A physicist and influential policy expert, Pace has decades of experience researching and writing space policy. He has served in multiple Republican administrations, most recently as executive secretary of the National Space Council from 2017 to 2020. He strongly advocated for the SLS rocket after Congress directed NASA to develop it in 2011. As part of his policy recommendations, Pace said NASA should seek to use commercial providers of heavy lift launch so that NASA can send “multiple” crew and cargo missions to the Moon each year. He notes that the SLS rocket is not reusable and is incapable of a high flight rate. Commercial options from SpaceX, Blue Origin, and United Launch Alliance are now available, Pace wrote.

The verdict is in for Starship Flight 7. SpaceX believes the spectacular break-up of Starship’s upper stage during its most recent test flight was caused by a harmonic response that stressed onboard hardware, leading to a fire and loss of the vehicle, Aviation Week reports. Higher-than-expected vibrations stressed hardware in the ship’s propulsion system, triggering propellant leaks and sustained fires until the test flight ended prematurely. The rocket broke apart and deposited debris over the Turks and Caicos Islands and the Atlantic Ocean, and forced dozens of commercial and private aircraft to delay their flights or steer into safer airspace.

Whole lotta shaking … SpaceX’s description of the problem as a harmonic response suggests vibrations during Starship’s climb into space were in resonance with the vehicle’s natural frequency. This would have intensified the vibrations beyond the levels engineers expected from ground testing. SpaceX completed an extended duration static fire of the next Starship upper stage to test hardware modifications at multiple engine thrust levels. According to SpaceX, findings from the static fire informed changes to the fuel feed lines to Starship’s Raptor engines, adjustments to propellant temperatures, and a new operating thrust for the next test flight, which could launch from South Texas as soon as Monday.

Next three launches

March 1: Kuaizhou 1A | Unknown Payload | Jiuquan Satellite Launch Center, China | 10: 00 UTC

March 2: Ceres 1 | Unknown Payload | Jiuquan Satellite Launch Center, China | 08: 10 UTC

March 2: Soyuz-2.1b | Glonass-K2 No. 14L | Plesetsk Cosmodrome, Russia | 22: 22 UTC

Photo of Stephen Clark

Stephen Clark is a space reporter at Ars Technica, covering private space companies and the world’s space agencies. Stephen writes about the nexus of technology, science, policy, and business on and off the planet.

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Astroscale aced the world’s first rendezvous with a piece of space junk

Astroscale, Japan, JAXA, satellite servicing, Science, Space, space debris, space junk / /

Astroscale’s US subsidiary won a $25.5 million contract from the US Space Force in 2023 to build a satellite refueler that can hop around geostationary orbit. Like the ADRAS-J mission, this project is a public-private partnership, with Astroscale committing $12 million of its own money. In January, the Japanese government selected Astroscale for a contract worth up to $80 million to demonstrate chemical refueling in low-Earth orbit.

The latest win for Astroscale came Thursday, when the Japanese Ministry of Defense awarded the company a contract to develop a prototype satellite that could fly in geostationary orbit and collect information on other objects in the domain for Japan’s military and intelligence agencies.

“We are very bullish on the prospects for defense-related business,” said Nobu Matsuyama, Astroscale’s chief financial officer.

Astroscale’s other projects include a life extension mission for an unidentified customer in geostationary orbit, providing a similar service as Northrop Grumman’s Mission Extension Vehicle (MEV).

So, can Astroscale really do all of this? In an era of a militarized final frontier, it’s easy to see the usefulness of sidling up next to a “non-cooperative” satellite—whether it’s to refuel it, repair it, de-orbit it, inspect it, or (gasp!) disable it. Astroscale’s demonstration with ADRAS-J showed it can safely operate near another object in space without navigation aids, which is foundational to any of these applications.

So far, governments are driving demand for this kind of work.

Astroscale raised nearly $400 million in venture capital funding before going public on the Tokyo Stock Exchange last June. After quickly spiking to nearly $1 billion, the company’s market valuation has dropped to about $540 million as of Thursday. Astroscale has around 590 full-time employees across all its operating locations.

Matsuyama said Astroscale’s total backlog is valued at about 38.9 billion yen, or $260 million. The company is still in a ramp-up phase, reporting operating losses on its balance sheet and steep research and development spending that Matsuyama said should max out this year.

“We are the only company that has proved RPO technology for non-cooperative objects, like debris, in space,” Okada said last month.

“In simple terms, this means approach and capture of objects,” Okada continued. “This capability did not exist before us, but one’s mastering of this technology enables you to provide not only debris removal service, but also orbit correction, refueling, inspection, observation, and eventually repair and reuse services.”

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Brewing tea removes lead from water

chemistry, food chemistry, lead contamination, Science, tea / /

Testing the teas

Scanning electron microscope image of black tea leaves, magnified by 500 times. Black tea, which is wilted and fully oxidized, exhibits a wrinkled surface, potentially increasing the available surface area for adsorption. Credit: Vinayak P. Dravid Group/Northwestern University

To test their hypothesis, the authors purchased Lipton and Infusions commercial tea bags, as well as a variety of loose-leaf teas and herbal alternatives: black tea, green tea, white peony tea, oolong tea, rooibos tea, and chamomile tea. The tea bags were of different types (cotton, cellulose, and nylon). They brewed the tea the same way daily tea drinkers do, steeping the tea for various time intervals (mere seconds to 24 hours) in water spiked with elevated known levels of lead, chromium, copper zinc, and cadmium. Tea leaves were removed after steeping by pouring the tea through a cellulose filter into a separate tube. The team then measured how much of the toxic metals remained in the water and how much the leaves had adsorbed.

It turns out that the type of tea bag matters. The team found that cellulose tea bags work the best at adsorbing toxic metals from the water while cotton and nylon tea bags barely adsorbed any contaminants at all—and nylon bags also release contaminating microplastics to boot. Tea type and the grind level also played a part in adsorbing toxic metals, with finely ground black tea leaves performing the best on that score. This is because when those leaves are processed, they get wrinkled, which opens the pores, thereby adding more surface area. Grinding the tea further increases that surface area, with even more capacity for binding toxic metals.

But the most significant factor was steeping time: the longer the steeping time, the more toxic metals were adsorbed. Based on their experiments, the authors estimate that brewing tea—using a tea bag that steeps for three to five minutes in a mug—can remove about 15 percent of lead from drinking water, even water with concentrations as high as 10 parts per million.

Brewing tea removes lead from water Read More »

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COVID shots protect kids from long COVID—and don’t cause sudden death

COVID-19, health, kids, long COVID, Science, sudden cardiac arrest, sudden cardiac death / /

Benefits and a non-existent risk

Using an adjusted odds ratio, the researchers found that vaccination reduced the likelihood of developing long COVID with one or more symptoms by 57 percent, and reduced the likelihood of developing long COVID with two or more symptoms by 73 percent. Vaccination prior to infection was also linked to a 75 percent reduction in risk of developing long COVID that impacted day-to-day functioning. The authors note that the estimates of protection are likely underestimates because the calculations do not account for the fact that vaccination prevented some children from getting infected in the first place.

“Our findings suggest that children should stay up to date with current COVID-19 vaccination recommendations as vaccination not only protects against severe COVID-19 illness but also protects against [long Covid],” the authors conclude.

In a second short report in JAMA Network Open, researchers helped dispel concern that the vaccines could cause sudden cardiac arrest or sudden cardiac death in young athletes. This is an unproven claim that was fueled by anti-vaccine advocates amid the pandemic, including the new US Health Secretary and long-time anti-vaccine advocate Robert F. Kennedy Jr.

While previous analyses have failed to find a link between COVID-19 vaccines and sudden cardiac deaths, the new study took a broader approach. The study, led by researchers at the University of Washington, looked at whether the number of sudden cardiac arrests (SCA) and sudden cardiac deaths (SCD) among young athletes changed at all during the pandemic (2020–2022) compared with prior years (2017–2019). The researchers drew records from the National Center for Catastrophic Sports Injury Research. They also collected medical records and autopsy reports on cases among competitive athletes from the youth, middle school, high school, club, college, or professional levels who experienced sudden cardiac arrest or death at any time.

In all, there were 387 cases, with no statistically significant difference in the number of cases in the years prior to the pandemic (203) compared with those during the pandemic (184).

“This cohort study found no increase in SCA/SCD in young competitive athletes in the US during the COVID-19 pandemic, suggesting that reports asserting otherwise were overestimating the cardiovascular risk of COVID-19 infection, vaccination, and myocarditis,” the authors conclude.

COVID shots protect kids from long COVID—and don’t cause sudden death Read More »

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In war against DEI in science, researchers see collateral damage

dei, Policy, Science, syndication, trump administration / /

Senate Republicans flagged thousands of grants as “woke DEI” research. What does that really mean?

Senate Commerce Committee Chairman Ted Cruz (R-Texas) at a hearing on Tuesday, January 28, 2025. Credit: Getty Images | Tom Williams

When he realized that Senate Republicans were characterizing his federally funded research project as one of many they considered ideological and of questionable scientific value, Darren Lipomi, chair of the chemical engineering department at the University of Rochester, was incensed. The work, he complained on social media, was aimed at helping “throat cancer patients recover from radiation therapy faster.” And yet, he noted on Bluesky, LinkedIn, and X, his project was among nearly 3,500 National Science Foundation grants recently described by the likes of Ted Cruz, the Texas Republican and chair of the powerful Senate Committee on Commerce, Science, and Transportation, as “woke DEI” research. These projects, Cruz argued, were driven by “Neo-Marxist class warfare propaganda,” and “far-left ideologies.”

“Needless to say,” Lipomi wrote of his research, “this project is not espousing class warfare.”

The list of grants was compiled by a group of Senate Republicans last fall and released to the public earlier this month, and while the NSF does not appear to have taken any action in response to the complaints, the list’s existence is adding to an atmosphere of confusion and worry among researchers in the early days of President Donald J. Trump’s second administration. Lipomi, for his part, described the situation as absurd. Others described it as chilling.

“Am I going to be somehow identified as an immigrant that’s exploiting federal funding streams and so I would just get deported? I have no idea,” said cell biologist Shumpei Maruyama, an early-career scientist and Japanese immigrant with permanent residency in the US, upon seeing his research on the government watch list. “That’s a fear.”

Just being on that list, he added, “is scary.”

The NSF, an independent government agency, accounts for around one-quarter of federal funding for science and engineering research at American colleges and universities. The 3,483 flagged projects total more than $2 billion and represent more than 10 percent of all NSF grants awarded between January 2021 and April 2024. The list encompasses research in all 50 states, including 257 grants totaling more than $150 million to institutions in Cruz’s home state of Texas.

The flagged grants, according to the committee report, “went to questionable projects that promoted diversity, equity, and inclusion (DEI) tenets or pushed onto science neo-Marxist perspectives about enduring class struggle.” The committee cast a wide net, using a programming tool to trawl more than 32,000 project descriptions for 699 keywords and phrases that they identified as linked to diversity, equity, and inclusion.

Cruz has characterized the list as a response to a scientific grantmaking process that had become mired in political considerations, rather than focused on core research goals. “The Biden administration politicized everything it touched,” Cruz told Undark and NOTUS. “Science research is important, but we should want researchers spending time trying to figure out how to cure cancer, how to cure deadly diseases, not bean counting to satisfy the political agenda of Washington Democrats.”

“The ubiquity of these DEI requirements that the Biden administration engrafted on virtually everything,” Cruz added, “pulls a lot of good research money away from needed research to satisfy the political pet projects of Democrats.”

Others described the list—and other moves against DEI initiatives in research—as reversing decades-old bipartisan policies intended to strengthen US science. For past Congresses and administrations, including the first Trump term, DEI concepts were not controversial, said Neal F. Lane, who served as NSF director in the 1990s and as a science adviser to former President Bill Clinton. “Budget after budget was appropriated funds specifically to address these issues, to make sure all Americans have an opportunity to contribute to advancement of science and technology in the country,” he said. “And that the country then, in turn, benefits from their participation.”

At the same time, he added: “Politics can be ugly.”

Efforts to promote diversity in research predate the Biden administration. A half a century ago, the NSF established a goal of increasing the number of women and underrepresented groups in science. The agency began targeting programs for minority-serving institutions as well as minority faculty and students.

In the 1990s, Lane, as NSF director, ushered in the requirement that, in addition to intellectual merit, reviewers should consider a grant proposal’s “broader impacts.” In general, he said, the aim was to encourage science that would benefit society.

The broader impacts requirement remains today. Among other options, researchers can fulfill it by including a project component that increases the participation of women, underrepresented minorities in STEM, and people with disabilities. They can also meet the requirement by promoting science education or educator development, or by demonstrating that a project will build a more diverse workforce.

The Senate committee turned up thousands of “DEI” grants because the broad search not only snagged projects with a primary goal of increasing diversity—such as a $1.2 million grant to the Colorado School of Mines for a center to train engineering students to promote equity among their peers—but also research that referenced diversity in describing its broader impact or in describing study populations. Lipomi’s project, for example, was likely flagged because it mentions recruiting a diverse group of participants, analyzing results according to socioeconomic status, and posits that patients with disabilities might benefit from wearable devices for rehabilitation.

According to the committee report, concepts related to race, gender, societal status, as well as social and environmental justice undermine hard science. They singled out projects that identified groups of people as underrepresented, underserved, socioeconomically disadvantaged, or excluded; recognized inequities; or referenced climate research.

Red flags also included words like “gender,” “ethnicity,” and “sexuality,” along with scores of associated terms — “female,” “women,” “interracial,” “heterosexual,” “LGBTQ,” as well as “Black,” “White,” “Hispanic,” or “Indigenous” when referring to groups of people. “Status” also made the list along with words such as “biased,” “disability,” “minority,” and “socioeconomic.”

In addition, the committee flagged “environmental justice” and terms that they placed in that category such as “climate change,” “climate research,” and “clean energy.”

The committee individually reviewed grants for more than $1 million, according to the report.

The largest grant on the list awarded more than $29 million to the National Center for Supercomputing Applications (NCSA) at the University of Illinois at Urbana-Champaign, which contributes to the vast computing resources needed for artificial intelligence research. “I don’t know exactly why we were flagged, because we’re an AI resource for the nation,” said NCSA Director William Gropp.

One possible reason for the flag, Gropp theorized, is that one of the project’s aims is to provide computing power to states that have historically received less funding for research and development—including many Republican-leaning states—as well as minority-serving institutions. The proposal also states that a lack of diversity contributes to “embedded biases and other systemic inequalities found in AI systems today.”

The committee also flagged a grant with a total intended award amount of $26 million to a consortium of five institutions in North Carolina to establish an NSF Engineering Research Center to engineer microbial life in indoor spaces, promoting beneficial microbes while preventing the spread of pathogens. One example of such work would be thinking about how to minimize the risk that pathogens caught in a hospital sink would get aerosolized and spread to patients, said Joseph Graves, Jr., an evolutionary biologist and geneticist at North Carolina A&T State University and a leader of the project.

Graves was not surprised that his project made the committee’s list, as NSF policy has required research centers to include work on diversity and a culture of inclusion, he said.

The report, Graves said, seems intended to strip science of diversity, which he views as essential to the scientific endeavor. “We want to make the scientific community look more like the community of Americans,” said Graves. That’s not discriminating against White or Asian people, he said: “It’s a positive set of initiatives to give people who have been historically underrepresented and underserved in the scientific community and the products it produces to be at the table to participate in scientific research.”

“We argue that makes science better, not worse,” he added.

The political environment has seemingly left many scientists nervous to speak about their experiences. Three of the major science organizations Undark contacted—the Institute of Electrical and Electronics Engineers, the National Academy of Sciences, and the American Institute of Physics—either did not respond or were not willing to comment. Many researchers appearing on Cruz’s list expressed hesitation to speak, and only men agreed to interviews: Undark contacted eight women leading NSF-funded projects on the list. Most did not respond to requests for comment, while others declined to talk on the record.

Darren Lipomi, the chemical engineer, drew a parallel between the committee report and US Sen. Joseph McCarthy’s anti-communist campaign in the early 1950s. “It’s inescapable,” said Lipomi, whose project focused on developing a medical device that provides feedback on swallowing to patients undergoing radiation for head and neck cancer. “I know what Marxism is, and this was not that.”

According to Joanne Padrón Carney, chief government relations officer at the American Association for the Advancement of Science, Republican interest in scrutinizing purportedly ideological research dovetails with a sweeping executive order, issued immediately after Trump’s inauguration, aimed at purging the government of anything related to diversity, equity, and inclusion. Whether and how the Senate committee report will wind up affecting future funding, however, remains to be seen. “Between the executive order on DEI and now the list of terms that was used in the Cruz report, NSF is now in the process of reviewing their grants,” Carney said. One immediate impact is that scientists may become more cautious in preparing their proposals, said Carney.

Emails to the National Science Foundation went unanswered. In response to a question about grant proposals that, like Lipomi’s, only have a small component devoted to diversity, Cruz said their status should be determined by the executive branch.

“I would think it would be reasonable that if the DEI components can reasonably be severed from the project, and the remaining parts of the project are meritorious on their own, then the project should continue,” Cruz said. “It may be that nothing of value remains once DEI is removed. It would depend on the particular project.”

Physicist and former NSF head Neal F. Lane said he suspects that “DEI” has simply become a politically expedient target—as well as an excuse to slash spending. Threats to science funding are already causing huge uncertainty and distraction from what researchers and universities are supposed to be doing, he said. “But if there’s a follow-through on many of these efforts made by the administration, any damage would be enormous.”

That damage might well include discouraging young researchers from pursuing scientific careers at all, Carney said—particularly if the administration is perceived as being uninterested in a STEM workforce that is representative of the US population. “For us to be able to compete at the global arena in innovation,” she said, “we need to create as many pathways as we can for all young students—from urban and rural areas, of all races and genders—to see science and technology as a worthwhile career.”

These questions are not just academic for cell biologist and postdoctoral researcher Shumpei Maruyama, who is thinking about becoming a research professor. He’s now concerned that the Trump administration’s proposed cuts to funding from the National Institutes of Health, which supports research infrastructure at many institutions, will sour the academic job market as schools are forced to shutter whole sections or departments. He’s also worried that his research, which looks at the effects of climate change on coral reefs, won’t be fundable under the current administration—not least because his work, too, is on the committee’s list.

“Corals are important just for the inherent value of biodiversity,” Maruyama said.

Although he remains worried about what happens next, Maruyama said he is also “weirdly proud” to have his research flagged for its expressed connection to social and environmental justice. “That’s exactly what my research is focusing on,” he said, adding that the existence of coral has immeasurable environmental and social benefits. While coral reefs cover less than 1 percent of the world’s oceans in terms of surface area, they house nearly one-quarter of all marine species. They also protect coastal areas from surges and hurricanes, noted Maruyama, provide food and tourism for local communities, and are a potential source of new medications such as cancer drugs.

While he also studies corals because he finds them “breathtakingly beautiful,” Maruyama, suggested that everyone—regardless of ideology—has a stake in their survival. “I want them to be around,” he said.

This story was co-reported by Teresa Carr for Undark and Margaret Manto for NOTUS. This article was originally published on Undark. Read the original article.

In war against DEI in science, researchers see collateral damage Read More »