Transhumanismus

Artificial Intelligence

China’s Moonshot AI Releases Model to Challenge Top US SystemsTracy Qu and Raffaele Huang | The Wall Street Journal ($)

“Moonshot said Friday that it planned to fully open-source the model, called Kimi K3, by late this month, where people will be generally free to download and adapt. With 2.8 trillion parameters dictating its decision-making, Kimi K3 is the world’s biggest open-source model, according to the Beijing-based startup.”

Robotics

The Fight Over Humanoid Robots Has Shut Down a Car Factory for the First TimeJiyoung Sohn | The Wall Street Journal ($)

“The union’s response [to Hyundai’s new Atlas robot] was blunt: Atlas would never step onto a production line without workers agreeing first. This week, Hyundai’s auto workers in South Korea have gone on a partial strike. It is the car industry’s first factory stoppage addressing humanoid robots.”

Computing

Psiquantum Has a Plan to Make a Massive Quantum Computer Out of LightJames O’Donnell | MIT Technology Review ($)

“PsiQuantum has attracted unusual investment and scrutiny for two reasons: It is one of the few companies aiming directly at building a large and useful machine, and it is already working with a major chip manufacturer to build its systems using existing semiconductor fabs.”

Tech

Generative AI Is an Engineering DisasterAlex Reisner | The Atlantic ($)

“I asked a few AI researchers whether they could name any other real-world software that scales so poorly. None of them could think of any. Even outside the world of software, it’s hard to find a comparable example, given that economy of scale is the principle that has made light bulbs, cars, and clothing so affordable. By economic and engineering measures, generative AI might be the worst technology ever deployed.”

Space

How Hard Is It to Build Orbital Data Centers, Actually?Eric Berger | Ars Technica

“You need unprecedented heavy lift: reusable and rapid launch. You need the ability to manufacture the largest satellites humans have ever built and to build 100 times more of them than humans ever have for a single constellation. You have to hope that radiation’s impacts on chips are manageable and that radiational cooling scales. You also need a few trillion bucks.”

Future

Once Again We Are Told AI May Be Conscious—I Study Consciousness, and I Have My DoubtsAnil Seth | The Guardian

“The information processing unfolding inside Claude is no more likely to result in consciousness than a simulation of a weather system is likely to generate a real hurricane. AI systems are getting more powerful every day. But to give ourselves the best chance of navigating this new world, we should remember how different we are from our almost-magical creations. When we sell our minds too cheaply to our machines, we not only overestimate them, we underestimate ourselves.”

Biotechnology

AI Teaches a Bitter Biology LessonReed Albergotti | Semafor

“Future discoveries and therapies will come not from a human-like understanding of science, but by simple pattern recognition of new biological information at scale. …[Richard] Sutton’s bitter lesson is applicable to biology because so much of the human body—not just the mind—is still beyond our understanding. And we’ll find the way forward by industrializing trial-and-error experimentation until the breakthroughs materialize.”

Future

Want Experts in 10 Years? Keep AI Away From Your Beginners TodayLaëtitia Vitaud | Fast Company

“A Nordic public school system and a 300-person American law firm aren’t pursuing the same goals. But they arrived at the same conclusion: Beginners must first learn without assistance in order to be, later on, well assisted.”

Space

Astronomers Find an Atmosphere on a Nearby Earthlike PlanetKatrina Miller | The New York Times ($)

“New data collected by the astronomers strongly suggests that LHS 1140b has a helium-rich atmosphere. The detection, published in the journal Science, is the first clear evidence of a potentially habitable planet with an atmosphere, and it reinforces the idea that there exists a population of worlds similar to our own with the properties necessary to sustain life.”

Future

The Big Reason Einstein Would Never Have Used AIEthan Siegel | Big Think

“Irrespective of whether AI counts as actual ‘intelligence’ or not, the fact is that outsourcing the growth and refinement of your critical thinking skills means you not only don’t develop those skills yourself, the ones you already have begin to decay. …This is where humans are needed most. Einstein was uncompromising about humans developing those exact skills.”

Artificial Intelligence

Simulating Everything, Sort Of: The Promise and Limits of World ModelsSamuel Axon | Ars Technica

“Instead of or in addition to working with language, world models aim to lay the groundwork for AI systems that are capable of simulating the physical world, or at least a useful approximation of it. To examine what’s different and important about this idea, Ars spoke with three expert practitioners working on world models and related technologies.”

Artificial Intelligence

Meet GPT-Red: An LLM Super-Hacker OpenAI Built to Make Its Models SaferWill Douglas Heaven | MIT Technology Review ($)

“GPT-Red automates a type of safety evaluation for software systems known as red-teaming, which is typically done by a team of human testers. The aim is to find as many different ways to break or hijack a system as possible. The weak spots can then be patched before the final version of the software is released.”

The post This Week’s Awesome Tech Stories From Around the Web (Through July 18) appeared first on SingularityHub.

When you interact with a large language model (LLM)—one of the systems behind chatbots such as ChatGPT and Claude—it can feel as though you are in contact with another conscious mind. But are you, really?

Some prominent scientists, such as Geoff Hinton and Richard Dawkins, claim you are. But most experts remain skeptical, arguing that the impressive cognitive capacities of LLMs occur in the absence of consciousness.

Recently, researchers at Anthropic, the company behind Claude, waded into this debate with an interesting finding. They claim Claude has a normally invisible set of representations of information that guide its internal reasoning and its verbal output.

This is where it gets interesting. The researchers argue this finding can be understood in terms of an influential theory of consciousness called the global workspace theory.

What Is the Global Workspace Theory?

First proposed by the psychologist Bernard Baars in 1998 and further developed by the neuroscientist Stanislas Dehaene and his collaborators, this theory holds that consciousness involves the activity of a “global workspace.” This is a kind of processing hub in the mind or brain that integrates and broadcasts information, allowing it to be used for reasoning, behavior control, and speech.

In a glossy video explaining the work, Anthropic depicts the contents of Claude’s “global workspace” as sailing ships afloat on a vast sea of unconscious mental activity.

How should we react to these developments? Do they provide evidence for artificial consciousness? If so, how strong is that evidence?

What Is a Global Workspace?

We can start by asking whether Claude does indeed have a “global workspace.” This is not straightforward, for the theory gives no formal definition of a global workspace.

The notion is characterized only informally. The (typically implicit) assumption is that any computational workspace “similar enough” to a human’s will qualify as a “global workspace.” But how similar is similar enough?

Anthropic researchers say they have found evidence of a space of internal thoughts that don’t appear in Claude’s output. Image Credit: Anthropic

Claude’s workspace may indeed have much in common with ours, but there do appear to be differences.

For example, the brain’s workspace is sustained by recurrent loops—signals cycling back through the same circuits over time. In contrast, Claude’s workspace evolves over a single pass through the network.

A related difference concerns how representations enter a workspace. Advocates of global workspace theory have long argued that in humans, a process called “ignition” occurs in which a non-linear process amplifies and sustains neural representations, allowing them to enter the workspace. As far as we know, nothing comparable occurs in Claude’s case.

Do these differences matter? The answer is not clear. Global workspace theory is based on data drawn from adult humans. There are questions about how far the notion can be—or should be—extended.

Does a Global Workspace Imply Consciousness?

But let’s suppose Claude does have a global workspace. To figure out whether that would be evidence for Claude being conscious we need to consider the status of the global workspace theory of consciousness.

There is no doubt it’s one of the most influential theories of consciousness, but it’s hardly uncontroversial among experts. (In a rather extreme understatement, Anthropic’s paper remarks that “the global workspace model is not universally accepted.”)

Many consciousness experts argue that computational properties alone are enough for consciousness. Even among those who think that consciousness is inherently computational, global workspace theory is only one of many options.

‘Conscious Access’ and Subjective Experience

What’s more, there are questions about whether global workspace theory is really a theory of consciousness in the relevant sense at all.

In an influential paper on artificial consciousness, the neuroscientist Dehaene and his collaborators advance the theory as an account of what they call “conscious access”—the availability of information for recall, the voluntary control of behavior, and verbal report. Crucially, they leave open the question of whether global workspace theory should be understood as an account of the subjective or experiential components of consciousness.

But if global workspace theory is just a theory of “conscious access,” then its implications for the artificial consciousness debate lose much of their significance. When we ask whether Claude is conscious we don’t want to know whether it has “conscious access”—instead, we want to know whether there is anything, subjectively speaking, that it’s like to be Claude. Global workspace theory doesn’t speak to that question if we treat it as nothing more than an account of “conscious access.”

So Has Artificial Consciousness Arrived?

Even taking these complications into account, there is no doubt that Anthropic’s findings are noteworthy. Global workspace theory can be understood as a theory of subjective experience, and Claude may indeed turn out to have something akin to a “global workspace.”

None of this is evidence that artificial consciousness has arrived. But it’s not unreasonable to think these findings do move the dial—if only ever so slightly—in the artificial consciousness debate.

But if that’s right, then it’s puzzling why Anthropic is quite so upbeat about these developments. As Anthropic recognizes, the creation of artificial consciousness would be a momentous event with wide-ranging social, ethical, political, and legal ramifications.

If chatbots are conscious then we would need to take their interests seriously. It would no longer be permissible to treat them as mere machines; instead, we would need to consider their welfare.

Should Anyone Even Be Trying to Do This?

Anthropic remarks that “it’s time to start thinking about whether we should be building conscious machines.”

I agree we need to have that discussion, but we should also pause work on building machines that might potentially be conscious. If Anthropic were serious, it would surely down tools rather than plough ahead with its attempt to develop conscious AI.

A moratorium on AI research that might be thought to lead to conscious AI would, of course, be far from straightforward. There are questions about the range of research it would affect and who might enforce it. But if we don’t close the stable door now we might find that the horse has already bolted.

This article is republished from The Conversation under a Creative Commons license. Read the original article.

The post Anthropic Says Chatbots Have What May Be a Key Feature of Consciousness. Are They Right? appeared first on SingularityHub.

Research suggests offloading mental work to AI is like debt: an immediate payoff with long-term consequences. But collaborating with the technology may boost our work without eroding skills.

Thinking is hard. It’s no wonder we lean on technology to lighten the load. We use calculators instead of doing long division by hand, GPS or Google Maps for navigation, and search engines instead of countless trips to the library. Yet just a few decades ago, getting around meant unfolding paper maps, and looking up a word required leafing through a hefty dictionary. Cognitive offloading of mental tasks to tools makes us more efficient. What’s the harm?

Then along came ChatGPT, Claude, and Gemini. Unlike earlier digital tools, AI chatbots can tackle an astonishing range of tasks and are easy to use. At a prompt, AI generates essays, analyzes medical images, writes software, and floods our feeds with AI slop. It’s cognitive offloading to the max.

Now people are asking: Is AI dulling our minds?

Yes and no, according to a new paper written by an international team of psychologists. AI can accelerate learning by giving people immediate guidance and feedback. But take the tool away, and those who rely on it often perform worse than people who learned the material on their own. Similarly, using AI to summarize information, rather than researching and organizing it yourself, often leads to shallower understanding.

But it’s not all bad news. Core cognitive abilities—including attention, reasoning, and working memory—seem to be “stubbornly resistant” to manipulation, the team wrote.

As technology evolves, so does the way we gain knowledge and think for ourselves. AI may reshape not just what we learn, but how we learn to learn. And like any other tool, its impact comes down to how we use it. Completely relying on AI is likely detrimental. But as a collaborator that challenges ideas or fills knowledge gaps, it can boost performance even after the tool is taken away.

“There is clearly a risk that AI can make us ‘stupid’ by compromising our skills (and knowledge) if we completely offload them to AI,” wrote the team. “[But] AI may be less likely to diminish the foundational cognitive capacities that underpin our ability to be smart, rather than ‘stupid’, in the first place.”

The AI Crutch

It’s easy to rely on large language models (LLMs)—the algorithms behind chatbots—for help. Why read an assigned novel when AI can summarize it in seconds? Gmail has already drafted an email reply; all I need to do is click send. That pesky essay? A few prompts and voila, done.

It seems like an easy hack, but there’s a cost to handing over too much thinking.

Researchers have long studied the consequences of cognitive offloading, or using external tools to reduce mental effort. Writing down a shopping list and keeping appointments in a calendar free up working memory, the brain’s temporary mental workspace, and allow us to focus on more important tasks without having to remember every detail.

AI is different. Beyond memory, it can offload critical thinking itself.

An MIT preprint introduced the idea of “cognitive debt” to describe the tradeoff. Participants wrote essays either with ChatGPT, using only a search engine, or with just their brains. Researchers monitored their brain activity during the task. Those using AI showed the weakest brain connectivity, which suggests they were less engaged. They also struggled to remember their own writing and felt the completed essay didn’t reflect their own ideas. When asked to write again without AI, they produced weaker work according to human judges.

Like financial debt, cognitive debt offers an immediate payoff with long-term consequences. Outsourcing mental effort makes writing faster and easier, but it slashes opportunities to build knowledge, strengthen reasoning, and practice critical thinking.

“While LLMs offer immediate convenience, our findings highlight potential cognitive costs,” wrote the MIT team.

Other studies have found the same pattern. High school students learning a new mathematical concept solved practice questions better with AI help, but they struggled on a later test when left to think on their own. Using AI “impeded the students’ learning by preventing them from engaging in the practice needed to acquire the skill,” wrote the team.

Habitual reliance on AI may even erode already-acquired expertise. In a large study of over 1,400 patients undergoing colonoscopy screening, doctors used an AI system to help detect abnormal growths. Three months later, when the AI was unavailable, their detection rate dropped from 28.4 to 22.4 percent.

“Continuous exposure to AI…[suggests] a negative effect on endoscopist behavior,” wrote the European team.

These effects extend beyond individual skills. AI can also influence how we build knowledge in the first place.

A recent study asked participants to learn about gardening by either Googling and synthesizing the knowledge themselves or by asking ChatGPT for a summary. They were then asked to give advice to someone else without technological help. Answers from those who relied on ChatGPT were rated as generic and less helpful, suggesting a shallower understanding of the topic.

With Great Power

We’re only beginning to understand how AI reshapes the mind. And it’s not all doom and gloom. The crux is how we use it.

In the MIT essay-writing study, for example, people who initially wrote on their own but later gained access to ChatGPT produced work with higher creativity and stronger arguments, while retaining their original perspectives and voice. Likewise, high school students who used AI as a tutor—asking for hints rather than answers—performed well even after the chatbot was taken away.

Used thoughtfully, AI may also enhance collaborative learning and brainstorming or serve as a writing coach, helping people work less and learn more.

Far less is known about if, and how, AI impacts fundamental cognitive capabilities. Attention, reasoning, and working memory have proven remarkably resilient over decades of cognitive research. Becoming better at a task usually reflects learning to use these mental resources more efficiently, not expanding the brain’s processing power. While AI may erode a specific skill, it could spare this core cognitive architecture, wrote the authors.

Whether that remains true over decades of AI use or during early childhood—when the brain is rapidly developing—is an open question.

Plenty other unknowns remain. Will we eventually adapt to AI, just as we’ve embraced calculators, search engines, and smartphones? Can refresher training ward off skill decay, or will some tasks simply become obsolete? How can we encourage people to strategically offload and benefit from AI use? And perhaps more philosophically: As we increasingly share our thinking with machines, will our definition of thinking evolve?

The post Is AI Making Us Dumber? appeared first on SingularityHub.

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A newly discovered brain-gut-bone marrow highway in mice could inspire strategies to protect immunity from chronic stress.

Stress does more than take a toll on mental health. After a particularly taxing week or month, it’s easier to catch a cold and harder to recover. Health issues build up as stress lingers, raising the risk of heart disease, diabetes, cancer, and a weakened immune system.

Chronic stress is often treated as an unavoidable part of modern life. While therapy can help people cope, researchers are increasingly asking a deeper question: How do stress signals in the brain ripple through the rest of the body, and can that damage be stopped?

A new study offers one of clearest answers yet. In mice modeling chronic stress, activity dropped in two brain regions governing emotional resilience. By way of a large nerve to the digestive track, the change wiped out a beneficial bacterial strain key to a healthy microbiome.

Without those microbes, the gut produced less of a crucial molecule that helps cells clear damaged proteins and other molecular  junk. These effects impacted the bone marrow, where stem cells generate oxygen-carrying blood cells and components of the immune system. Over time, these stem cells dwindled, leaving signs of premature immune aging in stressed mice.

“One surprising finding of our study was that suppression of only two specific brain regions was sufficient to produce many of the hematopoietic [blood stem cell] defects caused by psychological stress,” study author Linjia Jiang at Sun Yat-sen University said in a press release.

By tracing a direct pathway from brain to gut microbiome and bone marrow, the results could inspire new ways to blunt the biological toll of stress, from targeted probiotics to non-invasive brain stimulation.

Three-Piece Puzzle

De-stressing has become synonymous with self-care. Whether it’s work, family obligations, or a stream of notifications stressing you out, escaping into a good book or a walk in the woods feels like a deep mental exhale.

Stress has its perks. A product of the “fight-or-flight” response, it activates the sympathetic nervous system, a kind of highway connecting brain and body. In extreme cold, the system redirects blood from the skin to vital organs and temporarily slows digestion to prioritize muscles during a marathon. Brief bursts of stress aren’t detrimental. They’re an evolutionary survival hack.

But chronic stress is another story. Decades of research have found that prolonged or repeated mental strain disrupts brain activity and increases the vulnerability to a range of diseases. This is largely related to stress hormones released by the brain. But direct electrical signals traveling to the gut—which is often nicknamed the “second brain”—may also play a major role.

The garden of microbes in our gut roughly matches the number of cells in the body. These bacteria regulate digestion, metabolism, and immunity. They also communicate with the brain. When the ecosystem falls out of balance, it contributes to conditions ranging from diabetes to brain disease.

These beneficial effects can be traced to chemicals gut microbes manufacture. Lactobacillus reuteri, for example, boosts production of spermidine, a molecule that helps cells and tissues clear toxic debris. The process, called autophagy, is essential for the maintenance of healthy tissues but declines with age.

Stress also makes blood stem cells less resilient. Studies have linked prolonged stress to shortened telomeres, the protective caps at the ends of chromosomes, and an accumulation of senescent “zombie” cells. Both are hallmarks of accelerated biological aging.

The brain, gut microbiome, and bone marrow all respond to chronic stress. The new study aimed to find out if they’re connected.

Chain Reaction

To trace how chronic stress ages the body, the team tested four mouse models. Some experienced mild nerve injury. Others faced subtle disruptions to their daily routines, such as lights switching on earlier than expected or their home cages gently rocking at unpredictable times.

The changes put the mice on edge based on established behavioral tests. Mapping brain activity, the team zeroed in on two regions that consistently quieted. One, the medial prefrontal cortex, orchestrates executive control, or the ability to keep ideas in mind while reaching towards a goal. The other, the periaqueductal grey, coordinates attention to potential threats.

As activity decreased in both regions, blood stem cells struggled to divide and replenish immune cells. Inflammation and other toxic pathways flared up, and the cells developed molecular signatures similar to those seen in much older animals. Silencing either brain region with genetic tools reproduced many of the same symptoms, suggesting neural changes are a cause, not just a correlation.

But how was the brain communicating with the bone marrow? The answer lay in the gut microbiome.

Comparing the levels of chemicals surrounding the bone marrow in stressed and unstressed mice, the team zeroed in on spermidine. The molecule is made by gut bacteria and boosts autophagy, a process that’s linked to healthy aging.

Spermidine levels plummeted in stressed mice due to the loss of Lactobacillus reuteri, a beneficial strain of bacteria in the gut ecosystem that supports spermidine production. Stress-related nerve signals from the brain depleted these microbes, which caused spermidine levels to collapse and leaves blood stem cells unable to maintain themselves.

In another test, transplanting gut microbes from a stressed mouse into a happy-go-lucky mouse triggered early blood stem cell aging in the recipient—even though it didn’t experience stress itself. The results strengthen the case that the gut microbiome is a major link between the brain and bone marrow.

Rather than stress hormones, the pathway seems largely driven by electrical signals traveling from stress-sensitive brain regions to the gut. This means targeted brain stimulation could interrupt the cascade. Supplementing Lactobacillus reuteri as a probiotic or directly providing spermidine in a pill may also restore the missing molecule and slow blood stem cell aging.

This is just speculation though. Stress is deeply personal, and mice can’t capture the entire human experience. The team is now investigating whether the same brain circuits operate in people and if targeting this brain-gut-bone marrow axis can benefit the immune system.

“Our findings raise the possibility that managing psychological stress may not only improve mental well-being but also help preserve immune function and promote healthy aging,” said Jiang.

The post Scientists Find a Surprising New Way Stress Cascades From Brain to Body appeared first on SingularityHub.

The robot removed a pig’s gallbladder with standard surgical tools in an ordinary operating room.

Watchers held their breath as the robot made its first incision. Hovering over its patient, an anesthetized pig, with a robotic assistant standing nearby, it navigated to the gallbladder and gently removed it.

The operation marked the debut of humanoid robots in a standard surgical setting. The robot, named Surgie, wasn’t autonomous—it was controlled by an expert surgeon—but the study is a step toward using humanoid robots as collaborators in minimally invasive surgery.

“Remotely operated and autonomous humanoid robots have real potential for amplifying access to critical surgeries to which patients would otherwise not have access,” said study author Michael Yip at UC San Diego.

The study included two successful surgeries. Human surgeons remained on standby for emergencies, but the teleoperated robot completed the task with only minimal intervention.

Feedback from surgeons operating Surgie was positive. They reported less physical strain and frustration, along with better overall performance. But they also pointed to practical problems like intermittent overheating and the need to frequently reposition the robot.

Despite a long road ahead, humanoid robots “have a viable future,” said Yip. “You can imagine these robots being deployed in remote communities where staffing is challenging, or in austere environments like search and rescue scenarios where a massive deployment of field medicine is needed in a short period of time.”

Smooth Operator

Robots have assisted surgeons for years. With a human surgeon at the helm, they excel at delicate procedures requiring precision and dexterity. They’re especially well-equipped for laparoscopic surgery, a minimally invasive technique that uses tiny incisions to reduce pain, speed recovery, and lower the risk of infection.

Despite the promise, surgeons face tradeoffs when they use surgical robots. The robots are highly specialized and often require operating rooms to be redesigned to accommodate them.

A major reason for this is the way they’re built. Intuitive Surgical’s Da Vinci system, for example, uses a robot with multiple arms, each independently controlled from a remote console. Other systems, such as Versius from CMR Surgical, deploy several lightweight independent arms, each attached to a mobile base. The robots have to be carted near the patient.

Surgeons operate all these systems from a console using a magnified, high-definition, 3D view of the surgical field, which is often better than what they’d see with their own eyes. Da Vinci 5 adds sharper visuals and depth perception with two cameras, one for each eye. And because the cameras are held by a robot rather than a human assistant, the image is far more stable.

These platforms are already used in a range of operations. But they have weaknesses. Most require proprietary surgical instruments and methods to make extra space for robot docking and maneuvering during procedures. Staff training adds further complexity and cost, limiting where the systems can be deployed.

Humanoid robots, in contrast, are far more mobile and compact. Their human-like bodies could move through standard operating rooms, use conventional surgical instruments, and potentially be easier to incorporate into existing operating rooms.

The timing may also be right. Recent advances in electric components controlling their motion have made humanoid robots faster and more stable than their awkward, stumbling predecessors. Newer AI systems that predict full-body movement and provide feedback have improved robots’ balance and ability to adjust to real-world complexities. Humanoid robots are already stocking warehouses and winning marathons.

But surgery sets a higher bar.

We still don’t know how close humanoid robots are to meeting the requirements for surgical procedures, wrote the team. That’s what they set to find out.

Hello, Surgie

The new system consists of a surgeon’s control console and the robot itself. The surgeon wears a stereoscopic headset with a magnified 3D view of the surgical field and controls the robot with an input device. The robot translates the surgeon’s commands into movements in real time.

The team chose the commercially available Unitree G1 for the job. Unlike Da Vinci, which was built for surgery, G1 is a more general-purpose humanoid with dexterous wrists and multiple joints. The researchers customized the robot’s hands so that it can rapidly switch between surgical tools. Standing just over four feet tall and weighing roughly 77 pounds, the robot takes up a fraction of the space needed by conventional surgical robots.

Precision is key for laparoscopic surgery. Surgical instruments must pivot around a fixed site at the incision, allowing them to move freely inside the body without stretching or tearing neighboring tissues. After extensively mapping Surgie’s movements, the team identified a safe set-up with enough range of motion for most minimally invasive surgeries.

Surgie passed standard robotics benchmarks evaluating surgical skill for both humans and robots. But the real challenge came next. The team performed two gallbladder removal surgeries in a standard operating room. Both operations followed a typical workflow, with a lead surgeon and an assistant responsible for placing the camera, cleaning lenses, and swapping instruments.

Surgie collaborated with the human assistant to locate, identify, and remove the gallbladder with minimal damage to surrounding tissues, including the liver. During part of one procedure, a second humanoid briefly took over camera handling while the human assistant stepped aside.

Both operations went relatively smoothly. One involved minor bleeding and bile leakage from the gallbladder, but both were easily managed. In interviews, surgeons said controlling humanoid robots felt intuitive, particularly because they had two arms and could use standard surgical tools.

“We were surprised at how well Surgie meshed with our workspace and workflow,” said study author Nikita Thareja.

The system is still in early development. Surgie’s restricted reach required frequent repositioning and recalibration, adding more than three minutes each time. The robot also occasionally needed cooling breaks after overheating. In a real operating room, interruptions like these could increase risk by forcing surgeons to split their attention between the procedure and supervising the robot.

Still, Surgie has a leg up on conventional surgical robots: It can walk. Beyond assisting with an operation, it could potentially fetch surgical tools or help clean operation rooms between procedures.

The team is now refining the system to reduce control lag, particularly during long-distance teleoperation, and exploring ways to safely sterilize—or “scrub in”—a humanoid robot for the operating room.

“Our goal is an operating theater of the future, where humanoid robots and humans work side by side as an integrated team to deliver procedures to those in need, both in traditional hospital settings as well as in non-traditional, field medicine scenarios,” said Yip.

The post In a First, a Humanoid Robot Performed Live Surgery Under a Surgeon’s Control appeared first on SingularityHub.

Artificial Intelligence

Khosla-Backed Startup Claims Breakthrough With Largest-Ever AI Model on an iPhoneAaron Tilley | The Information ($)

“The largest AI models, which can measure in the trillions of parameters, are still far too big to run on mobile devices. But the model PrismML has working on an iPhone is capable of tasks like complex chat, reasoning, fully autonomous agents and software coding, the startup said.”

Robotics

Humanoid Robots Controlled by Surgeons Did World-First Operation on Live PigsJeremy Hsu | Ars Technica

“Humanoid robots have surgically removed the gallbladders from living animals in an unprecedented medical experiment—but not as autonomous machines capable of replacing human doctors. Instead, skilled human surgeons remotely controlled the robots’ movements in a new example of human-robot teamups.”

Biotechnology

mRNA Vaccines Clear Sweeping Global Review of Safety and EffectivenessBronwyn Thompson | Refractor

“An international team…reviewed data from laboratory studies, clinical trials, and real-world statistics to fully investigate this relatively novel class of vaccine, from design and manufacturing to its long-term performance. ‘After billions of doses, we now have an extraordinary amount of scientific evidence,’ says lead author Dr. Anna Blakney, assistant professor at UBC’s Michael Smith Laboratories and School of Biomedical Engineering.”

Tech

Anthropic, OpenAI, and SpaceX Are Bigger Than the Last 25 Years of Tech ExitsRussell Brandom | TechCrunch

“SpaceX has already gone public at a $1.77 trillion valuation, and with both Anthropic and OpenAI pushing into the trillions it’s likely the trio together will land somewhere north of $4 trillion. By comparison, the US Securities and Exchange Commission counted just $70 billion in US-based IPO proceeds last year.”

Biotechnology

11% of Americans Are Currently Taking a GLP-1 Weight Loss Drug Like WegovyMatt Novak | Gizmodo

“Gallup notes that obesity reached a record high in the US in 2022 at 39.9% but has ticked down to 36.4%, according to the latest data based on self-reported height and weight. That dip has been credited to the large number of Americans now using GLP-1 drugs.”

Tech

The Mistrust of AI Labs Bubbles OverLiz Hoffman | Semafor

“Forward-deployed engineers, dispatched by AI labs to help customers implement their models, will come back to the mother ship with a deep understanding of how banks, consulting firms, retailers, manufacturers, and consultants operate. That customer support, to a suspicious eye, looks a lot like reconnaissance.”

Future

Microsoft’s Carbon Emissions Went Up 25 Percent Last YearStevie Bonifield | The Verge

“Microsoft says this was ‘driven primarily by the expansion of our datacenter infrastructure,’ as well as the company’s decision last February to stop purchasing ‘non-additional, unbundled renewable energy certificates.'”

Tech

China’s Answer to AI Sticker ShockMatteo Wong | The Atlantic ($)

“Having successfully persuaded corporate America to give their products a try, OpenAI, Anthropic, and Google are now struggling to prove that their tools are worth the money. …While it’s too soon to know whether GLM-5.2 is really capable of replacing America’s top-tier AI agents, any firm or developer who is balking at the costs now might have an alternative.”

Artificial Intelligence

Anthropic Found a Hidden Space Where Claude Puzzles Over ConceptsWill Douglas Heaven | MIT Technology Review ($)

“The J-space contains individual words that are related to the words and phrases that the model is most likely to spit out in a response in the near future. If Claude were a person (which it is not), you might say that these hidden words can reveal what’s on its mind before it actually speaks.”

Artificial Intelligence

Hackers Can Use 9 of the Most Popular AI Tools to Assemble Massive BotnetsDan Goodin | Ars Technica

“A new attack the researchers have named HalluSquatting has the potential to assemble massive botnets, perform large-scale DDoSes, and infect devices at scale, a first for prompt-injection attacks. The attack works against AI coding assistants and agents, including Cursor, Cursor CLI, Gemini CLI, Windsurf, GitHub Copilot, Cline, OpenClaw, ZeroClaw, and NanoClaw, which are all susceptible.”

Future

UN Secretary-General Seeks Ban on AI WeaponsTom Chivers | Semafor

“The UN Secretary-General António Guterres called for a ban on ‘killer robots,’ saying the decision to take life ‘must remain forever human.’ …Guterres called AI-controlled weapons ‘morally repugnant,’ although not all ethicists agree: One roboticist argues they are more discriminate in their killing than scared human soldiers, while a philosopher said in 2022 that using robots will prevent young men and women bearing ‘the moral burden’ of wars.”

The post This Week’s Awesome Tech Stories From Around the Web (Through July 11) appeared first on SingularityHub.

Separate teams discovered the same target in solid cancers, enabling a powerful two-pronged attack on both tumors and the cells shielding them.

Cancer researchers just found a new way to take on tumors.

CAR T cell therapy revolutionized blood cancer treatment by supercharging a patient’s own immune cells to hunt down cancers. But the approach has struggled in solid cancers. These are some of our top killers—breast, lung, prostate. Roughly two million Americans are expected to be diagnosed with cancer in 2026, and over 600,000 will likely succumb to the disease.

Unlike blood cancers, solid tumors rarely share a single, universal target for CAR T cells. Even cells within the same tumor are a mishmash. Some have little or none of a target protein, allowing them to evade the engineered immune cells, survive treatment, and fuel relapse.

“Target discovery remains a considerable challenge in the development and translation of

CAR T cell therapies for solid tumors,” wrote Christopher Mount and Marcela Maus at the Massachusetts General Brigham Cancer Institute.

Now, two independent teams have converged on the same promising target: A cell-surface protein called GPNMB. In one study, CAR T cells engineered to recognize GPNMB rapidly destroyed glioblastoma—a lethal brain cancer—in tissues taken from patients and shrank tumors in mice.

A second team used a similar strategy against an aggressive soft tissue cancer to fight tumors in organoids and mice. In an early clinical trial involving a single participant, one infusion stabilized the disease for three months without serious side effects.

CAR T designers are often wary of broadly shared targets because they can trigger dangerous attacks on healthy tissue. But GPNMB is an odd duck. In addition to cancer cells, it also sits on immune cells that spur cancer growth or suppress the body’s innate ability to get rid of tumors.

“Our approach attacks both the tumor and the environment that allows it to thrive,” said Sheila Singh at McMaster, who led the glioblastoma study, in a press release. “We’re going beyond targeting the cancer alone and eliminating the immune cells that help shield it from treatment.”

Cancer Fortress

Solid cancers have plenty of tricks to outsmart CAR T cells.

Researchers make these supercharged immune cells  by extracting a patient’s own T cells and genetically engineering them to produce protein “claws” that latch onto a specific cancer target. After infusing the cells back into the body, they seek and destroy tumor cells. CAR T has transformed treatment for several blood cancers and is showing promise in autoimmune diseases and excessive heart and kidney scarring. To simplify the procedure, researchers are also exploring ways to directly transform T cells inside the body with gene therapy.

Solid cancers, however, are far tougher opponents. Unlike blood cancers, which are heavily coated with a shared target called an antigen, solid tumors are molecular patchworks. Cells within the same tumor can display different targets—or none at all—allowing some to evade a CAR T attack and trigger relapse. Many of these targets also appear on healthy tissues, raising the risk of dangerous side effects. And then there’s the tumor microenvironment: A toxic, glue-like “fortress” that hijacks immune cells and uses them to battle incoming CAR T cells.

These barriers aren’t impenetrable. Previous work enlisted  bacteria to help CAR T cells burrow into tumors. Other efforts engineered ultra-sensitive CAR T cells capable of detecting tiny amounts of a cancer target shared across multiple solid tumors.

“Recent reports of activity in several clinical trials reinforce optimism that these efforts may result in true clinical benefit,” wrote Mount and Maus, who were not involved in either study.

But these strategies require additional engineering steps, increasing complexity and cost. And most still leave one major roadblock intact: The tumor’s immune defenses.

One-Two Punch

In the glioblastoma study, the team at McMaster University scoured donated tumors for proteins that distinguished the most aggressive cancer cells. They found one standout: GPNMB. Another test of every protein dotting the cell surface confirmed it as a promising target. The protein is evident across a cancer cell’s membrane, making it readily accessible to CAR T cells.

In lab tests, CAR T cells engineered against GPNMB performed well, nearly eliminating tumors grown from patient samples and extending survival in mice.

The target turned out to be far more valuable than expected. The team soon realized that GPNMB also marked the immune cells that suppress anti-cancer drugs. CAR T cells attacked both fronts simultaneously, weakening the tumor’s immune shield and killing the cancer itself.

“Most approaches have focused on killing cancer cells alone,” said study author Shan Grewal. “Our work suggests we may also need to dismantle the immune support system that helps the tumor survive.”

The second team focused on alveolar soft-part sarcoma, a rare soft-tissue cancer that often spreads to the lungs, brain, and bones before it’s diagnosed. Treatment often comes too late.

The disease is driven by a type of “fusion” gene created when pieces of genetic material are accidentally stitched together. These genes are extremely tough to target directly. Instead, the team screened all surface proteins on the cancer cells and again landed on GPNMB as a top candidate for intervention. The protein’s levels closely tracked the activity of the fusion gene.

CAR T cells targeting GPNMB cleared tumors and prevented metastasis in mice. But because an earlier antibody drug against the protein caused severe skin toxicity in patients, the team also tested their CAR T cells in mice carrying small human skin grafts. Although inflammation initially flared, there were no signs of ongoing skin damage.

Encouraged, the team treated a patient with relapsed, metastasized alveolar soft-part sarcoma. After a single infusion, the engineered cells rapidly divided in the bloodstream and remained detectable for roughly a month. The treatment didn’t trigger skin rashes or more dangerous side effects, like cytokine release syndrome where the body mounts a hyperactive immune defense that harms healthy organs.

The treatment’s benefits outlasted the engineered cells themselves. For roughly three months, imaging tests found fewer of the small, round spots on the patient’s lungs that often signal metastatic cancer, suggesting the disease had stabilized.

A final analysis identified another roadblock: Clusters of cells that suppress the immune system and could blunt the benefits. Adding drugs to block these immune molecules boosted tumor killing in mice. Because the same kind of gene fusion drives other cancers, including kidney, the CAR T cells could have reach beyond this specific type of sarcoma.

Together, the studies underscore that the best CAR T targets might extend beyond cancer cells to expose and attack cancer’s immune cell supporters too. Finding a viable target is a delicate balancing act. Chosen well, and CAR T cells could tackle multiple drivers for cancer growth. Choose poorly, and healthy tissues could get hurt in the crossfire.

Even so, “these two studies indicate that GPNMB represents an actionable target for CAR T cell therapies in several solid tumors,” wrote Mount and Maus.

The post CAR T Revolutionized How We Treat Blood Cancers. Now It’s Closing In on Solid Tumors. appeared first on SingularityHub.

SpudCell is a big step toward synthetic biology’s dream of building life from scratch.

Synthetic biologists have long dreamed of constructing artificial cells from the bottom up. Researchers have now taken a major step in this direction by demonstrating that non-living components can be assembled into a system that grows, copies its DNA, and divides.

The genomic revolution transformed our ability to understand and manipulate cellular machinery, allowing scientists to rewire cells’ genetic circuitry to fight disease, produce valuable chemicals, and make crops more resilient. The holy grail for the field, however, has been to use these tools to create entirely synthetic cells—a milestone that would signal humanity’s mastery of life’s key ingredients.

How best to do this has long been an open question. Genomics pioneer Craig Venter made significant progress by stripping living bacteria back to their bare essentials, culminating in the 2016 unveiling of a minimal cell with just 473 genes. The Synthetic Yeast Genome Project has taken the opposite approach, building artificial versions of all 16 yeast chromosomes from scratch, though they’ve yet to get them working together in a single cell.

Now, researchers from the University of Minnesota, have assembled a synthetic cell out of engineered, non-living components housed inside an artificial, cell-like membrane. Their creation was capable of the four hallmarks of a living entity—the ability to feed, grow, copy genetic material, and produce offspring.

“We’ve replicated in chemistry what only used to be possible in biology: the complete set of behaviors of a cell,” Kate Adamala, who led the project, said in a press release. “It proves that the most fundamental functions of life, like growth and replication, do not need a mysterious magical spark.”

The researchers outline the design for their synthetic organism—nicknamed SpudCell for its potato-like shape under the microscope—in a non-peer reviewed paper uploaded to bioRxiv. SpudCell features a genome 90,000 base pairs long, which is considerably smaller than the 113,000 base pairs researchers had previously predicted would be the bare minimum needed to support a viable cell.

Rather than housing all the genes in a single chromosome, the team split them across several small, circular DNA molecules called plasmids, each specialized to fulfill specific functions. The researchers say this makes it possible to modify different aspects of the organism more easily.

To read the genome and build proteins, SpudCell uses a pre-defined kit of 36 purified enzymes drawn largely from E. coli. The whole assembly sits inside a liposome, a hollow bubble of the same fatty molecules that form natural cell membranes.

The artificial cell feeds in two distinct ways. Small molecules pass directly into the cell through protein pores implanted across the membrane. Molecules too large to squeeze through—like ribosomes and enzymes—are packaged inside tiny lipid bubbles that fuse with the membrane and empty their contents inside.

While the cell can feed, it’s entirely reliant on the researchers providing it with specially prepared meals. This means it’s a long way from surviving in the wild, which is both a major limitation and a key safety mechanism. “It’s a bed-ridden Frankenstein’s monster that has to be spoon-fed,” Adamala told New Scientist. “There’s no danger of it running amok.”

After ingesting “food,” SpudCell’s genes use the material to churn out proteins, while folding the incoming lipids into its membrane. This causes the whole cell structure to swell. Within a few hours, it’s bulked up enough to reproduce by dividing into two smaller cells.

Replicating cell division has been a longstanding challenge in the field. Natural cells split using an intricate protein scaffold called a cytoskeleton that’s fiendishly difficult to recreate. Adamala’s team sidestepped this problem by using a completely different mechanism, in which proteins bunch up on the membrane’s surface, putting it under mechanical strain. Eventually this squeezes two parts of the membrane together to pinch off a new cell.

The cells even manage a crude form of evolution. When the researchers introduced a genetic tweak boosting the cells’ ability to feed, those with the variant outcompeted the original lineage within five generations, and their edge widened when the researchers exposed the population to nutrient scarcity.

However, no one is claiming SpudCell is alive. Crucially, the cells cannot make their own ribosomes—the machines that build proteins from genetic instructions—and the ribosomes provided by the researchers degrade over time, limiting the cells to five to ten divisions.

The University of Chicago’s Jack Szostak told Quanta the work is an “impressive step” but the inability to produce ribosomes seriously limits potential for sustained growth. “If their system was able to generate its own ribosomes and other proteins and RNAs, it would be much closer to existing biological cells such as bacteria,” he said.

Nonetheless, the researchers think these artificial cells are a promising way to manufacture drugs, fuels, and materials without the toxic, energy-hungry industrial chemistry we rely on today. And they’ve created a new nonprofit called Biotic to share the tools they’ve developed with researchers.

The post This Synthetic Cell Grows, Copies Its DNA, and Produces Offspring—But It Isn’t Alive appeared first on SingularityHub.

Scientists used AI to find targets shared by thousands of related viruses and build what they hope is a universal vaccine.

Researchers at the University of Cambridge have developed what they describe as a fundamentally new type of vaccine using artificial intelligence. The vaccine’s key component was designed entirely by AI and has now been tested in people for the first time.

The goal is ambitious: a single vaccine that works not just against all known human coronavirus variants, but against related bat viruses that could jump from animals to humans and cause future pandemics.

Traditional vaccines train our immune system to recognize one specific virus. The problem is that viruses mutate. When they change enough, the vaccine stops working, which is why we need a new flu shot every year and why Covid vaccines have been updated repeatedly since 2021.

AI offers a way around this. By analyzing genetic data from thousands of related viruses, it can identify the parts that stay the same across different strains and that are unlikely to change over time. Target those stable features, and you have a vaccine that should work against the whole family, not just the strain you started with.

This is exactly what the Cambridge team did. They used AI to scan viruses from the sarbecovirus family, which includes the viruses that cause both SARS and Covid, as well as a range of animal coronaviruses—looking for shared features that evolution has left largely untouched. Those features became the basis of the vaccine.

DNA Vaccines

While many people are familiar with the mRNA shots used during the pandemic, this new vaccine uses DNA. DNA vaccines are generally more stable than mRNA vaccines, making them easier to store and transport. This is a significant advantage in lower-income countries where “cold-chain” infrastructure is limited.

They can also be administered without needles. A high-pressure stream of liquid delivers the vaccine through the skin, making administration less painful and easier to scale up during an outbreak.

Could It Protect Against Future Pandemics?

These practical advantages matter most if the vaccine itself can do something no existing jab can: protect against viruses we haven’t encountered yet.

Broad-spectrum vaccines could change the way the world responds to emerging infectious diseases. By offering much wider protection than traditional vaccines, they could provide rapid immunity against new and emerging viral threats. This would equip public health officials with tools to stop future outbreaks in their tracks before they have a chance to turn into global pandemics.

They could also transform our approach to more familiar diseases. Influenza is a prime target because it exists in many different strains and evolves so rapidly. Scientists have to predict which strains will dominate each flu season, and if they guess wrong, vaccine effectiveness can suffer. A universal flu vaccine that targets features shared across multiple strains could eventually end the annual race to keep up with the virus.

The Ebola virus shows why this matters right now. The recent outbreak in the Democratic Republic of the Congo and Uganda is driven by the Bundibugyo strain, which bypasses existing vaccines. While researchers rush to create a new vaccine specifically for this strain, local communities remain at high risk. A broad-spectrum vaccine designed to cover an entire virus family could transform that picture.

What the Trial Found

This is the first human trial of an AI-designed vaccine. The results showed that this DNA vaccine was able to stimulate the immune system to produce antibodies that can recognize different types of sarbecoviruses. The technology was found to be safe and well tolerated.

This is an exciting advance because it demonstrates how AI has the potential to design variant-proof vaccines against future pandemic threats. The needle-free delivery system could also make the vaccine easier to administer and distribute worldwide.

However, there is more work to do. Although the results in this study are encouraging, the immune responses following vaccination were modest. It was also uncertain how long the protection lasts and whether further boosters will be required. Larger trials are also needed to determine whether the vaccine can prevent or reduce viral infections in the real world.

A universal vaccine remains a few years away. And any new vaccine must still pass larger trials to prove it is safe, effective, and provides lasting protection. But this study shows the goal is getting closer—and AI may help us get there faster.

This article is republished from The Conversation under a Creative Commons license. Read the original article.

The post The First AI‑Designed Vaccine Has Been Tested in People. Here’s What Happened. appeared first on SingularityHub.

Similar concepts in different languages share an address in the brain.

My octogenarian father-in-law is trilingual and a lifelong fan of the World Cup. As he cheers on his favorite teams in English, Spanish, or French—sometimes switching between them mid-sentence—I’m always amazed at how easy it seems.

Scientists have long been fascinated by the brain’s ability to learn and retain multiple languages. Even after years of disuse, a brief exposure can quickly revive a language without having to consciously relearn its grammar or vocabulary. Bilingualism may offer other cognitive perks. Small studies suggest it delays brain aging, lowers dementia risk, and provides a slight edge in executive function (the ability to stay focused on a goal).

But most  of the evidence is from brain imaging studies that offer only a bird’s-eye view of neural activity and miss the finer details.

Now, scientists from the Baylor College of Medicine and collaborators have recorded activity from single neurons in four bilingual volunteers with epilepsy as they listened, read, and spoke in English and Spanish. The participants already had electrodes implanted in the hippocampus—a brain region critical for learning and memory—to track the source of their seizures.

“This is the very first study to look at how bilingual brains work at the level of individual neurons, and to do so in real time,” said study author Xinyuan Yan in a press release.

The results suggest the bilingual brain operates on two levels. Individual neurons often showed a strong preference for one language when participants heard or spoke words with the same meaning. But networks of neurons were largely language independent. They spontaneously organized into a concept map, placing words with related meanings—such as “dog” and “wolf”—closer together than unrelated words like “fork.”

Surprisingly, both languages relied on the same underlying map. Using the English concept map alone, the team could accurately predict clusters of related Spanish words.

“It’s like looking into a room from a different window. Everything inside is the same, but the perspective is different,” said study author Sameer Sheth.

Bridging Worlds

Language is central to human connection. Although some words don’t directly translate, people can express the same ideas across multiple languages without losing their core meaning.

Children raised in multilingual households are especially adept at switching between languages, often blending words and phrases together. Even when languages differ dramatically in grammar, syntax, and pronunciation, the brain somehow keeps their structures distinct while fluidly merging their meanings.

Long before we learn to speak, neural networks transform thoughts into electrical patterns that form words and sentences. Because languages are built differently—for example, where a verb falls in a sentence—it seems reasonable that each language would have a unique neural fingerprint.

But that might not be the case. A recent AI-powered analysis of functional MRI (fMRI) scans from monolingual speakers of 21 languages suggested that languages share a similar neural scaffold that represents meaning and concepts. Even fictional languages, including Klingon from Star Trek and Na’vi from Avatar, appear to tap into the same underlying system.

A growing body of evidence from bilingual speakers echoes these findings. One fMRI study found native Chinese speakers learned English more efficiently when they recruited brain networks used for Chinese. Another study identified shared speech-related brain activity sufficient for decoding words across languages.

Despite hinting at a universal language map, these standard imaging technologies struggle to capture detailed patterns as people switch languages in real time. To see how bilingual brains actually pull off the feat, we need to listen in on single cells.

Mapping It Out

The team studied four volunteers fluent in English and Spanish. All had learned the languages before age five and continued to use them regularly. Each also had electrodes implanted in the hippocampus to monitor seizures as part of epilepsy treatment, allowing researchers to track individual neuron activity as they listened and spoke.

Though often overlooked in language research, the hippocampus is increasingly recognized as a hub for word meaning, and it may also link concepts together. Here, the team monitored more than 100 neurons in each participant as they completed three language tasks.

First, the participants listened to roughly an hour of YouTube videos and the audiobook Eat Pray Love (Come Reza Ama). Next, they read aloud nearly 100 phrases displayed on a screen, such as “let’s have fun” and its Spanish equivalent “vamos a divertirnos.” Finally, they spent up to 90 minutes chatting with native speakers of each language, discussing everything from family to their epilepsy journey.

By the end, the team had compiled thousands of spoken words, hundreds of matched phrases, and hours of natural conversation.

A Language Landscape

Only a handful of neurons appeared truly bilingual, responding similarly to equivalent words such as “friends” and “amigos.” To better interpret the neural activity, the team turned to mBERT, Google’s multilingual language model that understands more than 100 languages. Like other LLMs, the model represents words according to their relationships and context rather than simple dictionary definitions.

The comparison revealed a similar pattern in brains and machines. Individual neurons rarely encoded the same word across languages. Instead, meaning emerged at the population level.

Both neural activity and mBERT tracked broader context, organizing words into an abstract conceptual landscape called semantic geometry. In this map, related concepts cluster together—“cat” sits closer to “dog” than to “galaxy,” for example—even if the precise features defining those relationships are unclear.

Yet the map remained largely unchanged across languages, suggesting it captured a fundamental mechanism for language processing in the brain. Using the English map alone, the team could predict which Spanish words would cluster around “perro” (or “dog”).

“This is how the brain encodes the meaning of words across languages,” said Yan. “It doesn’t rely on individual neurons translating individual words, but groups of neurons adjusting their activities to create the similar pattern for equivalent words in both languages.”

The study focused on semantics, or meaning, as opposed to syntax, the rules governing sentence structure. A recent study also using single-cell recordings from people with epilepsy suggests that other groups of neurons, particularly those in the frontal parts of the brain, may specialize in grammar while ignoring semantics. Whether they also share a “map” across languages remains to be seen.

The next step is to watch these maps emerge. The team hopes to track people as they learn a new language, revealing how new words and concepts are woven into semantic landscapes in real time. The results could deepen our understanding of one of the most fundamental communication skills and even inspire more capable and efficient language models in AI.

“Our study shows that the brain is wired to learn multiple languages,” said study author Benjamin Hayden.

The post How the Bilingual Brain Switches Languages With Ease appeared first on SingularityHub.

The night sky seems eternal and unchanging. But in cosmic time, nothing could be further from the truth.

Vasily Belokurov is one of three winners of the 2026 Kavli Prize in Astrophysics. The award is for uncovering fossil evidence of past galactic mergers that prove how the Milky Way evolved.

No matter the time or vantage point, from a pre-Neolithic cave to a post-lockdown London high-rise, the predictability of the night sky has always been humanity’s symbol of permanence and reassuring stability.

Yet this apparent calm is deceptive. Our galaxy, the Milky Way, emerged from chaos and turbulence, and its constellations are full of migrants, exiles and survivors. Right now, it has begun to stretch and distort again, pulled by a massive companion and heading for an inevitable collision.

How can I be so sure? As a galactic archaeologist, my job is to reconstruct the past of our galaxy and read the signs of its future.

Instead of digging through soil, I use the laws of dynamics and stellar evolution to sift through hundreds of millions of stars—searching for the most ancient and chemically peculiar among them, interpreting their orbits and piecing together the events that shaped the Milky Way. One ancient encounter left scars so deep that, billions of years later, they still define the galaxy around us.

I want to understand what governs the lives of these massive cosmic systems: which changes are nature—the slow internal evolution of a galaxy disk—and which are nurture, imposed by collisions and mergers.

Questions about the source of dark matter underpin it all. This is the invisible substance whose gravity holds galaxies together, but whose true identity remains one of the greatest unsolved puzzles in astrophysics.

The Milky Way is the one galaxy where stellar motions can be measured in extraordinary detail. This allows cosmologists including myself to construct our most precise map yet of dark matter: how far it reaches, how dense it is around the sun, what shape it has, and how smooth or lumpy it may be. If we can build this map in enough detail, we may begin to understand not just where dark matter is, but what it is.

A Cataclysmic Collision

Our work has been transformed by a revolution in open sky surveys. From 2000, the Sloan Digital Sky Survey showed what becomes possible when vast astronomical datasets are made public, enabling discoveries far beyond the goals for which the survey was first built.

And since 2014, Gaia, the European space telescope, has taken this transformation to another level by mapping the positions and motions of nearly 2 billion stars, turning the galaxy into a vast archaeological record. No ruins, no shards, and no bones—only stars that hold the clues.

The Milky Way mapped with SDSS data. Vasily Belokurov, CC BY-NC-ND

The clearest giveaway that something cataclysmic took place long ago in our galaxy is the migrants we observe: stars that were not born in the Milky Way.

While native stars mostly travel together, circling the galactic center in the great rotating flow of the disk, migrants cut across that order. They slide past the locals, plunge into the inner galaxy, then fly back out to its outskirts, again and again.

These unusual orbits go hand-in-hand with unusual chemistry. Most of the migrant stars are less enriched in heavier elements than the locally born population. Their chemical composition is a sign of a slower rate of evolution that is typical of a dwarf galaxy.

This makes the migrants doubly valuable. They are both fossils of the Milky Way’s violent past and probes of its outer regions, traveling where the local stars rarely go.

How the Milky Way Was Rewired

One of the central ideas in the theory of cosmic structure formation is that galaxies grow hierarchically. Smaller galaxies fall into larger ones and are torn apart, leaving their stars behind as migrants.

In the Milky Way, the largest ancient structure of this kind is known as Gaia-Sausage-Enceladus. It is the remains of a vanished galaxy that collided with our own between 8 and 11 billion years ago (the “sausage” refers to a pattern in its stars’ motions).

Artist’s impression of the young Milky Way colliding with another galaxy around 10 billion years ago. Vasily Belokurov, based on image by Juan Carlos Muñoz/ESO, CC BY-NC-SA

The Milky Way also did not go through that crash unscathed. The collision rewired and reshaped it.

Some of these changes are easily visible in the data. Stars from the old disk were splashed into our galaxy’s halo, becoming exiles in the place where they were born. A new posse of star clusters were also acquired.

At the same time, we think something even more momentous was taking place. The encounter changed the orientation of the Milky Way’s disk, and its alignment with the dark matter halo.

While dark matter is too diffuse to dominate our solar system, in the outer galaxy it is the main gravitating mass—moving, streaming, and in the standard picture, clumping into a hierarchy of lumps.

Around the Milky Way, this dark matter forms a vast halo, much larger than the luminous part of our galaxy. We often imagine this halo as a sparse, round cloud, but Gaia has helped show this picture is too simple.

The dark halo can be stretched out of shape by a major encounter. Like a ship beginning to list, the Milky Way started to lean—not suddenly, not visibly, but over billions of years.

View of the Southern sky shows the Milky Way and (far right, close to horizon) two galactic neighbors, the Small and Large Magellanic Clouds. H.H. Heyer/ESO via Wikimedia Commons, CC BY-NC-ND A New Galactic Dance

Unusually, compared with many galaxies of similar mass, the Milky Way was allowed ample time to recover from the shock of the “sausage merger.” No other cosmic cataclysm appears to have shaken our galaxy since, letting it settle into a quiet, uneventful life. That is, until now.

The Large Magellanic Cloud (LMC), currently our galaxy’s most massive companion, is already pulling at the Milky Way, disturbing its halo again. In an echo of what happened some 10 billion years ago, the Milky Way is being drawn into an accelerating dance with this neighboring dwarf galaxy, recoiling in response to the LMC’s approach.

This is a dance that only one galaxy is likely to survive intact. A new chapter of migration, survival and adaptation has begun.

None of this spoils the beauty of the night sky—it deepens it. The calm band of light above us is not a symbol of permanence, but the visible reminder of a long survival.

The Milky Way has been broken, rebuilt, and is now being disturbed again. Its stars remember the past; their motions reveal the future. What looks eternal is, in truth, a moment in a much longer story.

This article is republished from The Conversation under a Creative Commons license. Read the original article.

The post The Milky Way Was Rewired by a Cataclysmic Collision Billions of Years Ago. Now It Is on Course for Another. appeared first on SingularityHub.

After 300+ interviews on Singularity.FM, it still feels strange to sit on the other side of the microphone. But when Cadell Last invited me on Philosophy Portal, saying no was never an option. Cadell is one of the very few people who can push me on the deep questions and make me enjoy every minute […]

A single observational case suggests psilocybin may ‘awaken’ cognitive reserve in dementia. But scientists caution controlled trials are needed to know if the drug was the cause.

For five years, Alzheimer’s slowly stripped away a Japanese-American woman’s ability to speak more than one syllable at a time. The woman, now in her 80s, was diagnosed roughly a decade ago, and her condition steadily worsened. She struggled to walk and recognize family members.

Then, under medical supervision, she took a large dose of mushrooms containing the psychedelic psilocybin. Within three days, her symptoms had improved. She began spontaneously recounting memories and initiating conversations in full sentences. Her alertness returned, and she could move around independently.

A week later, she was recognizing family members, asking where they were, and pointing out cars that seem out of place.

Psilocybin has been maligned for decades. But renewed interest in its unique effects on the brain has pushed it into mainstream research. Early studies suggest it may help treat depression, anxiety, addiction, post-traumatic stress disorder, and other psychiatric conditions. A clinical trial is underway to gauge whether it can protect the aging brain.

The case study, conducted in Brazil, adds to that momentum. The team emphasizes that it describes a single patient and is purely observational. Because of the severity of her disease, they could not perform brain scans, measure biomarkers, or conduct standard cognitive tests. Exactly why her symptoms improved remains unknown.

Even so, they propose that psilocybin may have temporarily unlocked brain function in late-stage Alzheimer’s, potentially allowing dormant neural networks to rewire.

Brain Under Fire

Alzheimer’s is often synonymous with memory loss. Sadly, symptoms range far beyond forgetting names or misplacing glasses.

As the disease progresses, people gradually struggle to find the right words or follow conversations. Their ability to tackle everyday tasks—cooking, managing finances, planning ahead—erodes. Depression, irritability, and anxiety often emerge. Over time, their personalities flatten, leaving them less outgoing, engaged, or empathetic.

These stories are far too common. According to the World Health Organization, roughly 57 million people worldwide were living with dementia in 2021. Alzheimer’s may account for up to 70 percent of cases. As populations age, that number is expected to climb.

Alzheimer’s has no single cause. Genetics likely play a role. Some gene variants are linked to early-onset forms of the disease, an area scientists are now tackling with gene therapy.

Another hallmark of the disease is a buildup of abnormal protein clumps, or plaques, in and around neurons, which disrupts normal function and wrecks their ability to form neural networks supporting memory and cognition. Years of efforts to remove plaques have largely failed, though the FDA recently approved two antibodies that reduce them and modestly slow cognitive decline.

Then there’s inflammation. In Alzheimer’s, the brain’s immune system can become overactive. Rather than responding only to damage, inflammation drives disease progression, spreading toxic protein clumps through the brain and further damaging its ability to form new connections.

Here’s where psilocybin, the active ingredient in magic mushrooms, may help. Psilocybin alters serotonin signaling, a brain chemical involved in mood, perception, and cognition. But its effects likely extend far beyond that.

Studies in mice suggest the chemical boosts the brain’s ability to rewire, a process known as neuroplasticity. Human brain imaging studies have found that the psychedelic temporarily reorganizes communication between large brain networks, changing how distant regions interact. In some participants, supervised treatment has been linked to greater cognitive flexibility, deeper self-reflection, and improved well-being.

Other studies hint at a protective role. Psilocybin triggers the release of “nurturing” proteins. This process helps neurons survive stress and extend their branching connections. It’s these delicate structures that build up neural networks, and they wither away during depression, aging, and dementia. Inside the hippocampus, a region crucial for learning and memory, the drug stimulates the birth of new neurons, at least in mice.

Given its positive effects on brain plasticity, psilocybin is now being tested in multiple psychiatric disorders characterized by unusually rigid patterns of brain activity. Older adults remain largely absent from these studies, even though they could benefit the most.

Tale of One

Before treatment, the woman struggled with everyday life. For five years, she could communicate using only single-syllable words. Her mobility was severely limited, and she struggled with incontinence.

With the consent of her caretaker, she received five grams of the Enigma strain of Psilocybe cubensis. Because psilocybin levels vary widely between mushrooms, the exact dose is unknown. But compared to other clinical trials, it was relatively high.

The team chose the dose “based on prior experiential observations regarding depth and duration of psychedelic-induced neurobehavioral effects,” wrote the team.

Initially, the woman fell into a deep sleep-like state accompanied by elevated body temperature and heavy sweating. Roughly 19 hours later, she suddenly awoke and began speaking to caregivers in complete sentences, recounting memories from her life. The conversation lasted around four hours.

Over the following days, she became increasingly alert and engaged. She recognized family members, regained mobility, and could pick out matching clothes to dress herself. A week later, she was noticing small details in her environment, including a rental car parked outside the house. When a family member was absent, she asked, “Where did Celso go?” She also seemed to rediscover her love of social interactions, making eye contact, smiling back, and actively starting conversations.

A month after the initial session, she returned for a second supervised dose of three grams. After the second dose, she became even more verbally expressive, displayed a sense of humor, and described memories of surfing with her son on a peaceful island. Throughout the trial, the drug alleviated incontinence and improved her quality of life.

The results come with major caveats. The improvements were observational and largely reported by caregivers, leaving room for bias. The team didn’t administer standardized tests for cognition, dementia, depression, and anxiety. Nor did they perform brain scans or monitor sleep, making it impossible to determine what brain changes were behind her apparent “awakening.”

“Causality cannot be established, and spontaneous fluctuations inherent to neurodegenerative disease cannot be completely excluded,” they wrote.

But the study touches on a provocative idea in Alzheimer’s: Cognitive reserve. The theory proposes some people can tolerate greater levels of harm to the brain and continue functioning despite significant damage. Psilocybin may have temporarily tapped into these reserves, allowing dormant neural circuits to engage and rewire to compensate for impaired ones. The hypothesis is highly speculative and needs to be rigorously tested.

Meanwhile, a clinical trial is investigating whether psilocybin can reduce depression and improve quality of life in people with mild cognitive impairment or early Alzheimer’s disease, moving the needle beyond a single case study.

For one family, however, the benefits are already substantial. At a follow-up visit, the woman spontaneously said to everyone in the room, “It is pleasant to come here.”

The post Woman With Alzheimer’s Shows Striking Improvement After Taking Magic Mushrooms appeared first on SingularityHub.

Switches drive nearly every machine. A new one, made of folded DNA, does the same work at the scale of molecules.

Scientists have long dreamed of developing nanoscale machines, but building reliable mechanical components at the molecular scale has proved challenging. Researchers have now developed a DNA-based switch that can rapidly and repeatedly snap between two stable states, much like the components that underpin everyday electronics.

Ever since Richard Feynman’s visionary lecture “There’s Plenty of Room at the Bottom,” researchers have been enamored with the idea of engineering at the scale of atoms and molecules. But manipulating matter at the nanoscale is easier said than done.

Individual molecules are in constant motion and continuously jostled about by the thermal energy of their surroundings. This makes it extremely difficult to position and assemble larger structures and undermines control of the mechanical motion of components.

This is particularly true for switches—key components in many mechanical and electronic devices you might want to build. Getting a tiny structure to hold one position, flip cleanly to another, and then stay there has so far been an unsolved problem.

But now, a team at the Technical University of Munich has created a switch made from folded strands of DNA that remains stable for up to an hour and flips in milliseconds on the application of a brief electric field. Crucially, the device was able to switch back and forth repeatedly with no degradation in performance.

“Individual devices sustain hundreds of thousands of switching cycles over several hours and remain functional for actuation over several days,” the researchers write in a paper in Science Robotics. “As a nanoscale electromechanical interface, our device enables applications in molecular information processing, optical nanodevices, and the dynamic control of chemical reactions.”

The device borrows a principle from standard engineering known as a snap-through mechanism, which rests in either of two states and only flips when pushed hard enough, a bit like a light switch.

Scaling the idea down to a few tens of nanometers meant designing rigid arms linked by flexible molecular hinges, so the structure settles into one of two configurations and does not flick between them on its own. The team relied on DNA origami to accomplish this, where a long strand of DNA is folded into custom 2D and 3D shapes using hundreds of shorter “staple” strands.

One of the two arms features a longer “extension arm” that acts as a lever to push the switch between configurations. DNA carries negative charge, so when an electric field is applied to the device, it pushes the arm hard enough to flip the switch. Left alone, the team estimates that the structure stays in its resting state for roughly six hours, and they observed no spontaneous flips while monitoring 70 switches for an hour.

One of the device’s main strengths is its endurance. One switch survived more than 200,000 flips over five and a half hours, and a simplified version withstood a million switching cycles in three hours while still working about 85 percent of the time. Performance varied considerably from one device to the next, however, with some failing after a few thousand cycles and others continuing for days.

The researchers say failures likely stem from a combination of contaminants, surface wear, and chemical changes in the surrounding fluid. However, some inactive switches later started working again, which the team says suggests they are capable of self-repairing.

To test whether the switch could do anything useful, the researchers attached a gold nanorod to the moving arm, turning it into a microscopic light switch that changed how light scattered off the particle. In a second test, they used the switch to expose or hide a molecular binding site, allowing it to control whether DNA strands could attach.

That second capability could be particularly useful as it could make it possible to control chemical reactions—for instance by turning enzymes on and off. The authors suggest that this could be used to create “control knobs” for chip-based bio-factories that run sequences of reactions.

Considerable obstacles remain before the device can become genuinely useful. A single switch encodes just one bit of information, and the team acknowledges that wiring arrays of switches together to create something resembling a circuit remains a distant prospect.

But a workable switch is a fundamental component that can be used to create all manner of devices. While we’re still a long way from Feynman’s dream of molecular machines, this is a meaningful step in that direction.

The post This DNA Switch Could Control Molecular Machines appeared first on SingularityHub.

Let loose on existing regulations, AI models sniffed out known loopholes—and exposed entirely new ones too.

AI’s hacking skills are big news at the moment, but finding vulnerabilities in code may be the least of our worries. A new study suggests AI models can discover potentially damaging loopholes in the rules and regulations underpinning society.

Modern AI systems are powerful optimizers. Give them a goal, and they’ll pursue it relentlessly, quickly discovering solutions that would take a human years to find. But they are also incredibly literal in the way they approach a problem. They will do exactly what you tell them and are incapable of reading between the lines in the ways a human would.

This tendency leads to a recurring problem known as “reward hacking,” where an AI finds some loophole to maximize its performance on the metric used to measure success without actually achieving what its designers intended. The classic example is the AI that discovered it could win a boat racing videogame by looping around in circles collecting power-ups rather than completing the course.

The problem is partly due to humans being bad at specifying their goals. And unfortunately, it seems this weakness exists in the rules and regulations used to run society. When researchers let popular large language models loose in 72 simulated regulatory environments, the models found 60 percent of known loopholes and even identified some entirely new exploits.

“Within these environments, reward hacking naturally emerges and leads to regulatory loophole discovery,” the authors write in a non-peer-reviewed paper published on arXiv. “Models learn to hack the social rules and generate strategies that remain technically compliant while defeating regulatory intent.”

The regulatory environments the researchers created were primarily based on rules governing things like pharmaceutical patents, NBA salary caps, and deep-sea mining. In each case, Alibaba’s Qwen3 model was given the relevant rules, an explanation of its task, a predefined set of actions it could take, and the system used to score different outcomes.

A more powerful model, Google’s Gemini-3-flash, then simulated the consequences of different actions Qwen3 took and judged if and when it had found a way to exploit the rules of the game. When that occurred, the larger model patched the loophole by adding new rules, and the smaller model was set loose again. Over many iterations, the models to discover increasingly subtle workarounds.

When building their regulatory environments, the researchers omitted real-world fixes that regulators had used to close known loopholes. Over many trials, Qwen3 rediscovered more than 60 percent of these exploits. In a simulation of pharmaceutical patent regulations, the two models ended up replaying the same sequence of loophole discovery and regulatory reform that occurred in the real world.

Crucially, their behavior emerged spontaneously without the researchers asking the algorithms to cheat the system. This is a byproduct of the popular reinforcement learning approach the researchers used, where a model is rewarded for getting closer to a specific, numerically-defined goal.

Worryingly, the team found that existing safety measures offered little protection. Both models are designed to refuse prompts featuring harmful language, but loophole-seeking behavior slipped under the radar. When asked to self-critique their own behavior, the models identified fewer than 40 percent of their own exploits.

The researchers note that the same capabilities could be used more proactively to scour proposed regulations for loopholes before enactment. But lead author Wei Liu, a PhD student at King’s College London, says there are always likely to be gaps. “In the real world,” he told Science, “society is a huge, complicated reward function that can’t ever be patched to a perfect status.”

Adding to the concern, the models used in this study were far from the frontier, suggesting that more powerful AI could be even more adept at regulatory hacking. Whether our existing institutions can adapt quickly enough to this emerging threat is an open question.

The post Forget Code: AI Is Learning to Hack Society appeared first on SingularityHub.

Computing

IBM Has Unveiled Chip Technology That Could Help Extend Moore’s Law Another DecadeSophia Chen | MIT Technology Review ($)

“To fit more transistors on a chip, engineers across the industry are eyeing a pivot to an approach familiar to urban planners: build up. On Thursday, IBM announced it has created a chip that uses this strategy. The new architecture, known as a nanostack, vertically stacks transistors in two layers on a silicon chip.”

Artificial Intelligence

AI Is Designing Radio Chips That Humans Couldn’t Even ImagineKaushik Sengupta | IEEE Spectrum

“Some of the…chips look more like modern art than circuit layouts. Yet in many cases, the physical prototypes bested state-of-the art circuits in terms of performance. The real achievement, however, is that it took the AI orders of magnitude less time to conceive a working design than it would a human designer.”

Science

A Dark Dimension Could Link Two of the Universe’s Great UnknownsSteve Nadis | Quanta Magazine

“Even though scientists have assumed that dark energy and dark matter ‘don’t have anything to do with each other,’ said Tim Tait, a particle physicist at the University of California, Irvine, ‘you can imagine a case where one influences the other. And it would not be surprising if [they] were manifestations of a kind of unified theory of the dark universe.'”

Biotechnology

New Effort Will Get Genome Sequences for Entire Endangered Species ListJohn Timmer | Ars Technica

“Over 2,300 plant and animal populations remain on the [endangered species] list, requiring ongoing government intervention. On Thursday, it was announced that all of those species would see their genomes sequenced and tissue samples preserved to aid future conservation efforts.”

Future

AI Was Supposed to Kill Engineering Jobs, but New Data Suggests They’re the Most ResilientMarina Temkin | TechCrunch

“Software engineering, in theory, is the professional field most vulnerable to automation, given the rapid adoption of AI-powered coding tools. However, researchers at venture firm SignalFire say the hiring data tells a different story. ‘The rationale given for lots of layoffs is consistently AI, and specifically they’ll say AI with respect to code; they’ll say one engineer could do the job of however many engineers in the past,’ said Asher Bantock, SignalFire’s head of research. ‘What we’re seeing on the ground is a little inconsistent with that.'”

Computing

This Flying Solar-Powered Platform Could Deliver Better Internet From the AirRachel Courtland | MIT Technology Review ($)

“As soon as August, a giant silver bullet will cut its way through the dry air of the southwestern US and cross the Pacific to reach the coast of Japan. Once there, the roughly 200-foot-long craft, built by the New Mexico–based company Sceye, will park some 18 kilometers above the ocean’s surface, in a wispy-thin layer known as the stratosphere. Then it will use a custom-built antenna to supplement Softbank’s 5G network, a test that will include beaming data straight to devices.”

Computing

A New Paper Argues Microsoft Exaggerated Its Quantum Claims a Year AgoSophia Chen | The Verge

“A critique published in Nature Wednesday calls the basic technology behind Microsoft’s ‘breakthrough’ quantum computing chip the Majorana 1 into question. …In a peer-reviewed article, Henry Legg, a physicist at the University of St. Andrews, reanalyzed Microsoft’s data on their device and argued that the company’s researchers did not conclusively demonstrate a working topological qubit in the first place.”

Artificial Intelligence

The AI World Is Getting ‘Loopy’Russell Brandom | TechCrunch

“‘Two years ago, we wrote source code by hand. We started to transition so agents write the code. And now we’re transitioning to the point where agents are prompting agents that then write the code,’ [said Claude Code creator Boris Cherny]. ‘As big as the step from source code to agents was, loops are just as important and as big a step.'”

The post This Week’s Awesome Tech Stories From Around the Web (Through June 27) appeared first on SingularityHub.

There’s a vast difference between launching satellites and operating an industrial-scale computing infrastructure in orbit.

Imagine if one company could become the railroad, electric utility, and cloud-computing provider of the emerging space economy. That potential fueled excitement around the long-anticipated initial public offering of SpaceX. Investors are not simply betting on rockets anymore. They are betting on an entire orbital ecosystem.

Among the most ambitious and challenging ideas riding this wave of enthusiasm is something that sounds almost like science fiction: orbital data centers. SpaceX may be one of the most well-known companies seeking to build them, but it is not the only one.

The logic is seductive: Launch the data centers into orbit, where solar energy is abundant and land, water, and local power grids are no longer constraints. As artificial intelligence drives an explosion in computing demand, companies are pitching orbital data centers as a way to escape the growing environmental and infrastructure pressures of Earth-based computing. Data centers often also face backlash from the public at having these centers located in their communities.

But there is a vast difference between launching satellites and operating an industrial-scale computing infrastructure in orbit. Space is unforgiving. Radiation damages electronics. The electronics generate enormous amounts of heat, and getting rid of that heat is surprisingly difficult in space. Repairs are extraordinarily expensive, and every pound launched into orbit still carries a significant cost.

We are engineering professors who study data-center design and space systems engineering. Building a space-based data center will involve considerations from both sides.

What Goes Into a Data Center on Earth

First off, consider what goes into an Earth-based data center, like those that you’ve probably begun to see pop up everywhere. These facilities power cloud computing, video streaming, online banking, scientific computing, and increasingly, artificial intelligence. But a data center is much more than a room full of servers.

A data center needs several things to operate reliably. The first is electric power. Servers, networking equipment, and storage devices consume large amounts of electricity, and that power demand is growing rapidly with AI.

The second is cooling. Almost all the electricity consumed by servers eventually becomes heat. If that heat is not removed quickly and reliably, equipment performance drops, failures increase, and the data center can shut down. Cooling systems often include air handling units, chillers, cooling towers, pumps, and increasingly, liquid-cooling equipment. In many facilities, cooling is the largest energy consumer after the computing equipment itself.

The third is physical infrastructure, including the necessary land, buildings, structural support, backup power, water systems, communication networks, and maintenance access. Data centers also need to be close enough to users and network backbones to provide fast digital services.

In short, Earth-based data centers are large electrical and thermal infrastructure systems built around computing hardware.

Placing Them in Space

So what would it take to build these data centers in space, and why are companies finding this possibility such an interesting business proposition?

As on Earth, these data centers would require massive amounts of power. In space, this power would come from solar panels. The sun always shines in space and can’t be blocked by clouds. However, depending on the orbit the solar panels are put in, the Earth may shadow them for some portion of the orbit.

And even the best solar cells available today can convert only about half the sunlight that hits them to electricity.

Another potential advantage found in space is cooling. The cold background of space (roughly -455 degrees Fahrenheit, or -270 degrees Celsius) creates an opportunity: Waste heat from the data center could escape into space through radiators, keeping the electronics cool.

In principle, that design could eliminate some of the bulky and water-intensive cooling infrastructure used on Earth. However, those thermal radiators would require a large amount of surface area, and that would be in addition to the area required by the solar panels.

In space, there is no air to blow across hot equipment and help heat escape. The heat has to leave as infrared radiation, which is a relatively slow process. As a result, removing 10 megawatts of waste heat can require radiator surfaces comparable to the size of two football fields.

Space-based data centers could also avoid some of the local conflicts that come with building large data centers on the ground. Many communities resist new data center developments because of their land use, energy and water demand, and noise and environmental impact.

A space-based system would avoid competing for local land and water resources, and it would not generate neighborhood noise or require local zoning approval in the same way.

However, space is already getting crowded, and launching thousands of large orbital data centers would accelerate this issue. Orbital debris and micrometeorites are hazards because they can puncture the space data center, and a worst-case collision could destroy it and create even more space debris.

The frequency of space launches necessary to send all the equipment to orbit may also become a concern for some communities. SpaceX has had protests at its launch complex in Boca Chica, Texas from local activists who argue its rocket testing and launches damage the surrounding environment.

All that data would need to be sent between Earth and these data centers—and between the data centers themselves—using radio waves or laser communications systems. Although satellite constellations such as Starlink and Amazon Leo have demonstrated that doing this is possible, the amount of data sent to and from space would balloon.

Additional Challenges

These data centers, along with their solar panels and radiators, cannot be launched in one piece and would need to be assembled in space. This process would require new equipment for in-space servicing, assembly, and manufacturing.

Another key challenge is the refresh cycle of computing hardware. Data-center servers are not built to last forever. Operators on Earth usually replace or upgrade hardware every three to five years as chips improve, workloads change, and equipment ages.

And equipment failures can require replacing components. The refresh and repair processes are relatively straightforward on Earth, where workers can physically remove and replace servers.

In space, refresh and repair becomes much harder. Hardware sent to orbit may be difficult or too expensive to upgrade. If the computing platform cannot be updated, or too many components fail, it may become obsolete long before the surrounding infrastructure reaches the end of its useful life.

In a field where performance improves so rapidly and demand from computing continues to increase, this hurdle could prove a major economic and operational challenge.

Then there is the harshness of space. These data centers would be in a near vacuum, with constant radiation hitting them. And depending on their orbit, they would go from hot when in the sunlight to cold in Earth’s shadow many times a day. All of these challenges, and more, are issues that will need to be addressed.

So, Do They Still Make Sense?

Despite these challenges, companies are moving forward with designing space-based data centers. SpaceX just announced the design for its AI1 Compute Satellite, which it hopes to use as an orbital data center spacecraft. However, this satellite is 100 to 1,000 times less capable than current Earth-based data centers.

Not every computing task makes sense to do in space. Many data center applications depend on fast response times and close connections to users on Earth. Financial transactions, interactive AI services, and most cloud applications are extremely sensitive to delay.

More feasible early applications may be those that are less latency-sensitive and more tightly connected to space operations. Examples could include processing Earth observation data from satellites, military or intelligence data processing, scientific computing related to space missions, or specialized computing for satellites and other space assets.

In other words, the first viable space data centers may serve space-based customers before they compete with mainstream cloud data centers on Earth.

This article is republished from The Conversation under a Creative Commons license. Read the original article.

The post Orbital Data Centers Are Seductive on Paper, but They Face Daunting Challenges in Reality appeared first on SingularityHub.

Eight live sessions across July and August. €100 for the full series. Reserve your spot: pay via PayPal. The technological singularity did not arrive as a fact. It arrived as a story, one we have been telling ourselves about machines, progress, and what it means to be human. This July and August, I want to […]

Companies once moved whole factories overseas to reduce labor costs. Now, workers a world away can operate local excavators, forklifts, and even humanoid robots with an internet connection.

Packaging potassium sulfate, a fertilizer vital to the planet’s food supply, is visually striking—not because of what you see, but because you don’t see much at all. In China’s Xinjiang region, home to the world’s largest deposit of the mineral, piling it up in warehouses creates dust clouds so severe that workers are forced to drive heavy machinery by feel.

Some companies are now turning to a technology that not only offers a way to see through the dust but also keeps workers from entering the warehouse at all. The system, developed by BuilderX Robotics, a Chinese tech company, uses cameras that are like night-vision for dusty areas. More significantly, operators drive excavators, loaders, and other machines from a remote office filled with rows of videogame-like stations. All they need is a 5G or satellite connection.

The ability to control physical machines from a distance is called teleoperation, and it could become a significant force of change in the global economy.

In Japan, the shelves of over 300 convenience stores are being restocked by robots monitored and sometimes controlled by workers in the Philippines. Düsseldorf airport was slated to begin testing shuttles driven by remote workers in May. A startup in Atlanta is offering robot security guards operated by remote staff, and last summer, a surgeon in France performed a teleoperated procedure on a patient in India.

While offshoring teleoperated jobs to overseas workers hasn’t yet become routine, Mark Graham, professor of internet geography at the University of Oxford, suggests the technology is worth our attention because it might enable companies to expand on their well-established habit of outsourcing jobs to places where labor is cheaper.

The use of remote labor isn’t new, Graham told SingularityHub. But teleoperation extends the logic of outsourcing to tasks that were previously thought to be “stubbornly local.”

“The novelty is less about the existence of remote labor and more about the kinds of work that can now be pulled into a planetary labor market,” he said. “Once that happens you can expect the usual pressures around labor arbitrage, control, and fragmentation to follow.”

It’s not clear we’re ready for the consequences.

BuilderX Robotics is a global leader in teleoperation for heavy machinery and a good expression of the changes ahead. Shaolong Sui, a graduate of Stanford University with a degree in mechanical engineering, founded the company in 2018 as a response to labor shortages in the construction industry in Asia.

“A shortage of trained operators isn’t a problem only in developed countries,” he told me. “Young people here in China don’t want to do this work. It’s dusty and dangerous.”

Rather than focusing on full robotic autonomy, which many construction companies have pursued over the past decade, Sui identified teleoperation as a more realistic way to move operators from harsh environments to safer conditions. Making use of the proliferation of low-cost sensors and 5G at the time, Sui completed a prototype in 2019. Today, his company offers teleoperation for 14 different industrial machines, including excavators, loaders, and bull dozers.

In our conversation, it was clear he hopes to improve working conditions for manual laborers. I lost track of the number of times he mentioned removing operators from dangerous worksites. “These workers deserve a better life,” he said.

BuilderX’s workstations do seem to have transformed some of the punishing work of an industrial site into a more white-collar experience, complete with tea and coffee break rooms and toilets down the hall. Sui said his solution allows construction firms to hire senior citizens or people with disabilities who, thanks to the videogame-like interface, can now operate heavy machinery. In another video, a Japanese woman who pilots an excavator proudly shows off her complex nail art, something she claims she couldn’t maintain when she worked in the field.

“Not only is this a much safer workplace, but the lifestyle benefits are that you can sit in an air-conditioned space, enjoy your tea, and when you go home, you’re still clean,” Sui said.

There’s no doubt the approach is safer for frontline workers like those in Xinjiang. Evidence suggests that high levels of potassium dust exposure can cause chronic bronchitis. While pulling someone from dangerous work is a good thing and that should be taken seriously, Graham told me, it doesn’t necessarily mean they’re free from exploitation.

“A worker can be removed from the physical site and still be subjected to intense surveillance, deskilling, isolation, fragmented contracts, algorithmic management, and downward pressure on wages. In other words, the risk can move rather than disappear,” he said.

Sui and Graham both agree there are plenty of forces that might slow the pace of outsourcing. Currently, none of BuilderX’s customers offshore work to overseas operators. But that doesn’t appear to be a technology constraint, as recently demonstrated by an operator in Poland controlling an excavator over 4,000 miles away in Beijing. On the technical side, latency—the delay between operator and machine—and reliability will shape the rate at which firms can choose to offshore workers. But it’s more likely to be limited by regulatory constraints in the form of licensing, insurance, and safety requirements.

That said, Graham believes the biggest force driving work overseas will be the same one that’s pushed clerical and service work offshore; the relentless pursuit to increase profit and reduce cost.

“If firms can hire people in lower-wage labor markets to operate expensive equipment thousands of miles away, many of them will try,” he said.

Most debates about AI and robotics focus on job loss due to automation. There is relatively little discussion about the risk of offshoring teleoperated work as the technology comes online. This is partly due to the hype surrounding physical AI, a Silicon Valley buzzword describing a world where fully autonomous robots cut humans out of the loop. But Graham says that when machines arrive people tend to incorrectly assume humans disappear.

“In many cases, what gets described as automation is really a reorganization of labor. Work gets broken apart, moved around, and hidden from view,” he says.

As is the case with AI,  the robotics industry’s push toward full automation is still plenty reliant on a hidden system of faraway workers. Teleoperation provides training data for robots and is needed to help them deal with unexpected events. Consumer robotics startup 1X is selling a $20,000 humanoid that will sometimes need to be  controlled by remote staff. It’s not clear how often future robots cleaning dishes in San Francisco kitchens will be steered by gig workers in Mumbai.

Robotaxi company Waymo already relies on human agents to assist, though not literally drive, vehicles stuck in difficult scenarios. The firm recently disclosed for the first time that some of these agents are based in the Philippines. This information, surfaced during US congressional testimony, immediately raised questions of oversight for safety-critical work: For instance, should a worker in Manila be required to get a California driver’s license?

Amid an already combustible US political environment, teleoperation could raise the heat even higher. Fueled by fears of Americans losing jobs to people overseas, Wyndham Hotels and Resorts, the parent company of La Quinta, was last year forced to respond to anger over a viral video depicting workers allegedly in India remotely handling check-in at one of their Miami hotels. As Graham points out, people tend to care more about outsourcing when it’s no longer hidden in a back office.

But outrage alone, he says, rarely defeats a business model that saves money. Due to network effects surrounding training, infrastructure, and other business process optimization, outsourced labor also tends to cluster in specific areas. This may already be happening in the case of Waymo, which could soon see the rise of something like a “driving district” in Manila. In the future, other types of teleoperated work could follow suit, giving companies a ready-made destination to shop for low-cost labor.

For Graham, it’s urgent that we begin requiring certification from independent bodies, which can better scrutinize a company’s production networks. At Oxford he directs Fairwork, a project aiming to improve labor practices in digital supply chains.

I asked Sui how he thinks his customers may reorganize their operations around this new ability to remotely control their machinery.

“We’re working with traditional industries, and so it’s not just about adopting a new technology. There are significant management changes they will have to navigate. You could call this transformation friction because they will need time to digest this new capability step by step,” Sui said.

Despite the fact they could use the technology to outsource work across national borders, none of his customers are doing so just yet. Sui used open pit mines as an example. In this case, where fully developed towns with schools and hospitals have built up over decades, his customers still cluster their workforce next to the sites where they operate. Instead of driving into the mine, operators work from an office and go home clean at the end of a shift.

BuilderX has deployed its technology at more than 100 sites in China, Japan, and parts of Europe. It’s now expanding into new markets including South America and the Middle East. When asked whether he thinks his technology will be used for transnational outsourcing, there’s no hesitation. “Oh yes, I think this is coming in the very near future.”

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