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Scientists Simulated Microgravity in Human Cells and Found Something Unexpected About DNA
Simulated microgravity changed the nucleus but left the genome surprisingly intact.
Quantum teleportation breakthrough: Scientists crack a 25-year entanglement challenge
Scientists have developed and experimentally demonstrated a long-sought method for identifying W states, an important form of multi-photon quantum entanglement. The technique could make complex entangled systems much easier to measure, opening new possibilities for quantum teleportation, communication, and computing.
Bucket List Provides an Experiential Introduction into a World of Electronic Musical Entertainment
Bucket List, an experimental music band conceived at Stanford University, performed in Ring Family Performing Arts Hall a little over a week ago. The band consists of Mark Applebaum on keyboard and guitar, Andy Meyerson on percussion, and Travis Andrews on guitar. All members perform vocals. Their performance was titled “Achievement: Presented by the Achievement […]
How FIBA 3x3 Basketball Went From A Business Case To An Olympic Sport
FIBA 3x3 basketball evolved from a Youth Olympic experiment into a global sport, driven by gender equity, digital engagement and a spectator-first approach ahead of LA28.
BTS Superstar V Named Global Brand Ambassador for Nothing Headphones
Praised Nothing co-founder and CEO Carl Pei: "V has an instinct for fearless experimentation. He's always pushing into different sounds and styles."
Scientists Observe Enzymes Breaking Down DNA in Real Time
The study directly visualizes nuclease-DNA interactions and DNA fragmentation in a purified experimental system.
Kodiak Sciences Stock Surges 125% After Late-Stage Drug Trial Success
The trial tested two experimental eye drugs, Zenkuda and tabirafusp-ted, for treating wet age-related macular degeneration.
In 1879 a scientist buried bottles filled with seeds. Every 20 years, one is dug up and studied.
A botanist buried 20 bottles of seeds in 1879 to test how long they'd survive, and the experiment is still running today.
Experimental Emulator Brings Nintendo Switch Games to Jailbroken PS5 Consoles
An unofficial port of the Eden Nintendo Switch emulator is now running natively on jailbroken PlayStation 5 consoles. Developer BlackBearReloaded released ProsperoEden, which adapts Eden, itself a fork of the now-defunct Yuzu project, to run directly on Sony's hardware as homebrew rather than...
Nintendo Switch emulator now runs natively on jailbroken PS5, Cuphead reaches 60 FPS
ProsperoEden is an experimental native PS5 port of the Eden Nintendo Switch emulator, with several games already reaching gameplay on jailbroken consoles.
Glucosamine, a popular joint supplement, linked to faster Alzheimer’s progression
A large health-record analysis found that glucosamine use was associated with a 25% higher likelihood of mild cognitive impairment progressing to dementia. Lab experiments suggest the popular joint supplement may intensify an abnormal sugar-tagging process in the Alzheimer’s brain, although researchers say clinical trials are needed to determine whether it actually causes harm.
Glucosamine, a popular joint supplement, linked to faster Alzheimer’s progression
A large health-record analysis found that glucosamine use was associated with a 25% higher likelihood of mild cognitive impairment progressing to dementia. Lab experiments suggest the popular joint supplement may intensify an abnormal sugar-tagging process in the Alzheimer’s brain, although researchers say clinical trials are needed to determine whether it actually causes harm.
Femme in STEM event brings hands-on science to Wilmington mall
Exhibitors from UNCW, local colleges and WECT’s First Alert Weather Team offered interactive experiments to spark curiosity.
Why Smithsonian scientists flood an Anne Arundel forest every summer
On a large campus in Edgewater, scientists at the Smithsonian Environmental Research Center flood a forest every summer to learn about climate change. It's just one of the large-scale experiments conducted at the institution which has, so far, escaped some of the scrutiny and critique that Donald Trump has lobbied at the rest of the Smithsonian.
2026 Maker Faire in Vallejo intersects art, science and all things inquisitive
Now in its 20th year, Maker Faire returned Friday to Mare Island’s historic Naval Shipyard, bringing together artists, engineers, scientists, students and curious minds from across the region for a weekend of experimentation and creativity.
Florida Department of Education launches B.E.S.T. science standards listening tour
This review of the B.E.S.T. Science Standards gives Floridians an opportunity to help shape the future of science and health education in Florida and establish a strong foundation built on knowledge, observation, inquiry, experimentation, evidence, and reason.
Earth microbes survive simulated conditions of Saturn moon’s ocean
Experiment suggests organisms could live in harsh environment under Enceladus’s icy crust, strengthening possibility moon could support life
A 60-beam ultraviolet laser flash-vaporized the surface of tiny diamonds so the blast would kick a shock wave through them, melting the hardest material on Earth at 12,680 degrees and 145 million psi, and solid diamond turned out to float on its own melt like ice on water
The experiments ran on the OMEGA laser at the University of Rochester's Laboratory for Laser Energetics, which fires 60 ultraviolet beams into a target
CERN has begun disconnecting the Large Hadron Collider
CERN has started replacing some of the Large Hadron Collider’s most important magnets as part of its High-Luminosity upgrade. The new superconducting magnets will produce fields about 40% stronger, allowing particle beams to be squeezed more tightly before they collide. That should create far more collisions for the ATLAS and CMS experiments to analyze, giving physicists a much larger window into the fundamental workings of the universe.
Trump admin using AI to deny medical care for seniors in disastrous experiment
Vendors rolling out AI have an "incentive to deny as many claims as possible."
Scattering neutrinos to probe the fundamental laws of the universe
As part of Ricochet, an international collaboration that studies neutrinos, MIT PhD student Faith Reyes progressed from learning the basics of the experiment to helping guide the work of other scientists.
Debating Just How Disappointing Phoenix Suns' Last Era Was
From championship favorites to a first-round sweep, Phoenix’s star-studded experiment backfired spectacularly. High costs and chemistry issues now cement this era as a historic cautionary tale.
Insurance Coverage Lags as Cancer Science, Treatment Move Forward
Health insurance may not cover experimental targeted therapies for rare cancers, which do not have an established standard of care.
Blue Light Doesn’t Actually Fry Your Eyes. The Real Problem Is Much Stranger.
A dark-room experiment reveals why blue blurs the world, and why darker eyes handle it better.
Is metascience being co-opted?
In July, the White House released a report that argued academia is deeply dysfunctional and in need of radical reform.Science: A New Golden Age sets out a litany of problems many academics will recognise: interminable waits for grants; short-term funding rather than support for longer, more ambitious projects; ballooning administrative requirements; pressure to publish, and many more. “The scientific machine is getting bogged down,” it says. At least on the face of it, Science: A New Golden Age is a triumph for the metascience movement, a loose-knit, global group of academics, philanthropists and think tankers that want far more testing and experimentation in how we fund public research and innovation. The report tells US research funders to set up internal metascience units to do just this. But it has also set alarm bells ringing that metascience is being conveniently deployed to help justify the defunding of US universities, which US vice president JD Vance has openly labelled “the enemy.” “Just because you have an issue with your plumbing in your house doesn't mean you light the entire house on fire and burn it to the ground,” said Colette Delawalla, chief executive of Stand Up for Science, a group campaigning against what it says are attacks on scientists by the Trump administration. No one is arguing that academia doesn’t need reform, but there’s debate over how far and how fast the system should be shaken up. Does public R&D need slow and steady evidence-based adjustment, or radical new experiments?One of the key arguments in Science: A New Golden Age is that there’s not enough funding for what it calls “mid-level” science: engineering-heavy projects that require tens of millions of dollars, involve ten to a hundred people, and last around five years. Such a project might develop a brain-computer interface for people with Alzheimer's disease, for example. As such, the US National Science Foundation (NSF) has already announced $1.5 billion to set up so-called X-Labs, effectively new research organisations to pursue breakthroughs in areas such as quantum sensing and new scientific instruments. Funding divertedBut there’s a catch: this money has squeezed NSF budgets for more traditional, fundamental research grants, Science reported in June, likely meaning less cash for university-based scientists. Science: A New Golden Age also makes various swipes at universities, accusing them of extracting overheads from scientists to fund administrative bloat. “We have become dependent on a narrow set of legacy institutions,” it says. The report doesn’t mention it, but the US government is simultaneously seeking greater powers over federal funding, which would allow political appointees at funding agencies to screen or cancel research grants mid-project. The White House is also seeking to slash the NSF’s budget by more than half in 2027, although similar cuts proposed for 2026 were blocked by Congress. Convenient hookThis has worried some that the metascience agenda could be misused as a kind of smokescreen to further weaken universities. James Wilsdon, executive director of the Research on Research Institute at University College London, said that the report contains lots of “interesting ideas” and agrees that in places, academia is a “pretty broken system.” But the risk is that metascience is being deployed as a “convenient hook” to support cuts and a “political land grab” to transfer grant power from scientists to political appointees in US funding agencies.So far, the metascience agenda hasn’t been seized on by radical right parties in Europe. But Wilsdon worries it will cross the Atlantic, politicising research reform efforts and making them more difficult to carry out. The report is already making some in Europe sceptical of the entire idea. “The system is not without flaws, but the metascience discussion is not likely to improve the system but rather to generate munition to undermine it,” said Claes de Vreese, a professor of AI and society at the University of Amsterdam. Peter Thiel protégéOfficially, Science: A New Golden Age has just one named author: Michael Kratsios, the director of the Office of Science and Technology Policy and a former chief of staff to Silicon Valley mogul Peter Thiel. He also served as chief financial officer of Thiel’s Clarium Capital Management. Since the 1990s, Thiel has criticised US universities for moving away from teaching what he views as the classic works of western civilisation, and drifting towards “anti-Western zealotry.” And since 2011, he has offered two-year fellowships of $250,000 to young people to skip or drop out of university, and instead start companies or pursue scientific research. “College can be good for learning about what’s been done before, but it can also discourage you from doing something new,” according to the Thiel Fellowships website. In other areas, the Trump administration has promoted academics with a longstanding interest in metascience. For example, the head of the National Institutes of Health, Jay Bhattacharya, in 2020 co-authored a study arguing the funder backs overly conservative proposals, although he achieved wider prominence as a critic of pandemic lockdowns. Careless talk costs fundingEven before the Trump administration embraced the metascience agenda, some metascientists privately wondered whether they should be careful not to overstate dysfunctions in academia, in case this gets used as ammunition against universities. But others think being cautious with criticism is pointless. After all, last year, the Trump administration sought to cut funding from US universities on an entirely different premise: supposed antisemitism on campus. “I don't think these governments need a technical metascientific excuse to attack the universities, they will want to do so anyway,” said Will Stone, a researcher at Science Works, a new think tank advocating for a “metascience revolution” in the UK. “I think researchers should report what they find, even when the findings may be used to advance policies they disagree with,” echoed Russell Funk, a researcher at the University of Minnesota, who in 2023 co-authored a highly influential paper that argued scientific papers were becoming less disruptive over time. No justificationThat said, Funk thinks that metascientific research certainly doesn’t justify a weakening of universities. Instead, scientists need “time, resources and stability to pursue unfamiliar ideas,” he said. “Taking away those conditions works against the very goal the reforms are supposed to achieve.”The Institute for Progress, a Washington DC-based innovation policy think tank that has championed X-Labs and metascience units, also says that reforms should complement, not supplant, universities. “Unpredictable, unreliable, and reduced federal funding to researchers is destabilising to the very foundations of research and development and is bad,” said Jenn Gustetic, the institute’s director of metascience and R&D policy.Evolution or revolution?This points to a much bigger divide in the metascience community: how far and how fast should public R&D be shaken up? Does it need evolution or revolution? For example, Science: A New Golden Age says the science system relies too heavily on traditional “workhorse” project grants, the type that pay out around $250,000 a year to fund “hypothesis-driven science by small teams on tractable questions.” However, in criticising project grants, the report “decisively picks one side of a debate that is far from settled,” David Hilmer Rex, a metascientist based in Denmark, has written. In June, Pierre Azoulay, a metascientist at the Massachusetts Institute of Technology, defended project grants, saying that the alternative of X-Labs “merits scepticism.”A-B testingOne challenge in metascience is that it’s easier to generate evidence for some types of change than others. Most straightforwardly, research funders can run A-B tests on different ways of awarding money. For example, Germany’s Volkswagen Foundation recently trialled distributed peer review, where applicants rate each other’s proposals, and measured its results against traditional review panels. Distributed peer review made quicker decisions, although awarded money to largely different ideas. However, much of the focus of the metascience movement has been on founding fast-moving and free-acting new research organisations and funders, in contrast to the alleged stodginess of mainstream academia or public innovation grants. A culture of speed and freedom are the animating principles behind Germany’s Sprind or the UK’s Advanced Research and Invention Agency (Aria).Related articlesViewpoint: it's time to experiment with how Europe funds science European researchers sound the alarm that Trump rule changes will hit cooperationHowever, while it’s possible to closely study previously successful bodies, such as the US Defense Advanced Research Projects Agency (Darpa), for historical clues to their secret sauce, it’s impossible to guarantee in advance that the likes of Sprind or Aria will actually work as hoped. But advocates of new organisations say this inherent uncertainly shouldn’t stop us trying. “If we wait for definitive proof that something will work before we try it, I don't know where your proof is coming from,” said Stone. Trade-offsUp until now, experiments in metascience haven’t generally come with hard trade-offs over money. In the US, new ideas such as focused research organisations have often been funded by billionaire philanthropists. In Europe, new innovation agencies such as Sprind and Aria, or the Netherland’s new National Agency for Disruptive Innovation, haven’t needed explicit cuts elsewhere in the research system. But with the $1.5 billion establishment of X-Labs by the NSF, the trade-offs are becoming clearer. Some metascientists privately wonder whether a smaller pilot would have been more appropriate, given that the idea is untested. The Institute for Progress counters that the $1.5 billion X-Labs budget is spread out over a decade, so will account for less than 2% of the NSF’s annual budget. “It’s important to remember that [Darpa] was once an institutional experiment as well. Now it’s one of the most cited innovative funding models in the world,” said Gustetic.As for Europe?The US isn’t the only country placing metascience at the heart of its research strategy. Science: A New Golden Age looks admiringly at the UK, which in 2024 set up a Metascience Unit to scrutinise how it funds research. In Brussels, it’s more of a mixed picture. In 2018, the EU set up the European Innovation Council to funnel grants and equity to start-ups, although it’s sometimes criticised for awarding money too slowly. Recently, the council has started experimenting with challenges, where teams of inventors compete to overcome a technological challenge. The European Commission also wants to experiment with partially randomising grant winners, to cut down on bureaucracy. However, the Commission’s own advisers have said the EU’s own research schemes are too conventional. They want the Commission to establish a new dedicated unit to scrutinise and experiment with funding. But there’s no sign of a such unit emerging in Brussels’ plans for the next Horizon Europe programme, which from 2028 is set to distribute more than €160 billion over seven years. Sam Bogerd, director of breakthrough innovation at the Brussels-based Arq Foundation, an AI-focused think tank that also looks at metascience, says that Europe might have the opposite problem to the US: universities and basic research funding are still reasonably well supported, but there’s not enough experimentation. “We're not taking a close enough look at where this money can achieve the most, and I am worried that the good ideas around metascience will be tainted politically by their association with the Trump administration,” he said. He’s still lobbying for the Commission to set up an experimental unit. But in the meantime, the Arq Foundation plans to do its own research, and is currently hiring two metascience researchers to run the rule over how Brussels spends research funding.
Hands-on science can be cool
After spending many long days conducting experiments to find a new way to combat bacterial infections in crops, Misha Hegde and Mia Soleil Maurer have been rewarded with international recognition and access to top research facilities. But these are not typical scientists. They are 16-year-old German high school students.“Our supervisor told us that in order to start a project, you need to begin with either a question or a problem,” says Misha, adding that she and Mia had read about antibiotic resistance in certain plants being treated for bacterial infections. “We found out that antibiotics overuse is very common in agriculture,” explains Mia. “Our aim was to create an alternative to antibiotics and to try to raise awareness of the problem of overusing antibiotics.”Their subsequent research has focused on harnessing bacteriophages, the natural predators of bacteria, to eliminate pathogens threatening food crops treated with antibiotics. At the Schuldorf Bergstraße Jugend forscht MakerLab in Seeheim-Jugenheim, located in the German state of Hesse, they discovered a novel phage that infects the Rhizobium rhizogenes bacterium, which causes the hairy root disease that can reduce yields of tomatoes, carrots, soya beans and other food staples.The students believe their method could curb antibiotic use, while protecting plants from infections without disturbing the natural soil microbiome. “The application of phages is host-specific, so they would only kill the targeted pathogen or disease-causing bacteria,” explains Mia. It may also offer environmental benefits, since applying antibiotics can contaminate groundwater.Getting to this point has not been easy. The childhood friends admit to feeling frustrated when their trials did not yield the expected results. “We spent six months on our first experiment, just doing the same thing over and over and over again, to the point where we thought, is it even worth it? Why are we doing this?” Misha says. “You just need to be brave enough to take that first step and keep going.”The benefits of inquiry-based learningTheir determination has paid off. In 2025, the pair won first prize in biology at Jugend forscht, Germany’s national competition for young people interested in science, technology, engineering and mathematics. They were also among the winners of the German Research Foundation Europa-Preis, which is awarded to selected national winners at Jugend forscht, and took third place in the 2025 European Union Contest for Young Scientists.The Jugend forscht Foundation opens doors for young people to connect with scientists as well as industry professionals. Jessica Bönsch, executive director of the Foundation, sees Misha and Mia as prime examples of how young people can develop a deeper understanding of science through their own research projects. “The experience of working on your own research question is very important,” she explains, adding that “inquiry-based learning engages with real-life problems in a way that can be more motivating than traditional classroom teaching.”The Jugend forscht Foundation offers financial support through sponsor pools in Germany’s federal states. Some projects are developed in cooperation with student research centres, university labs or informal collaborative learning areas called makerspaces. Other activities start as hands-on “garage projects” and can grow within the Jugend forscht network and infrastructure.The Jugend forscht Foundation is also a partner of Science Comes to Town, an EU initiative to strengthen public awareness about science and create bridges between researchers and communities. The EU-financed project involves universities, research institutions and other stakeholders in three host cities — Brest (France), Kiel (Germany) and Split (Croatia).“It's so important for people not to live in a bubble, because I think science can be very scary if you misunderstand it,” Mia says of SCTT. The initiative’s aim of raising awareness about science is “absolutely amazing,” Misha adds. “I think it's the best way to kind of make science digestible for the public. In a world where misinformation in science is getting more radical, more dangerous, becoming more of a threat to the trust in scientific infrastructure and foundations, we need such programmes.”Misha and Mia also believe that SCTT can help break down gender stereotypes in science by encouraging young women to study and pursue careers in scientific fields. Both students have benefited from female mentors and encouragement they had when they were much younger. Mia’s love of science began with a class trip to a lab, while Misha — with a smile on her face — says she wanted to study history until “a teacher kind of coerced me into joining a school science club.”Recognition beyond EuropeIn May, Misha and Mia were among the finalists at the Regeneron International Science and Engineering Fair held in Phoenix, Arizona, and involving nearly 1,700 pre-university students from over 60 countries. “It was very crazy because there were so many people and so many teenagers interested in science,” Mia recalls. The event was also challenging. “It was eight hours of continuously presenting your project,” adds Misha.Attending the fair was a chance for the young women to see first-hand the value of international collaboration as well as how research cultures differ. “America is a bit more willing to take risks, and I think that's something we can learn about here in Europe,” Misha explains. However, she continues, “I think Europe has the talent, has the innovation and has the resources” to be competitive.Misha and Mia plan to continue their phage experiments in the new school year, inspired by the project’s hands-on nature and the support they receive from their supervisors. They have also attracted the interest of professional scientists and received invitations to leading research facilities, including the Centre for Synthetic Microbiology, jointly run by the University of Marburg and the Max Planck Institute for Terrestrial Microbiology in Germany. “It is so cool that we can do something to try to move the world in our school and at this age,” Mia says.After completing secondary school, Mia plans to study microbiology and pursue a career in medical research, focusing on Ebola and other infectious diseases. “This has been my dream for so long,” she says. Her friend Misha is interested in biological research with a focus on medicine. “I've gotten addicted to the process of going to the lab, planning out experiments, then failing, trying again,” Misha says. “I think there's just so much to be discovered, so much to be done.”The students' names and photos were published with the permission of their parents.Science|Business, which connects policymakers, academics and industry through its news reporting, analysis and events, is an SCTT partner.
Biophysical Therapeutics brings longevity science to skincare with its new IF1 brand
From equations and experiments in the laboratory to exclusive skincare for skin longevityWILMINGTON, Del., Sep. 23,
Rep. Pocan joins bipartisan bill to end cat and dog testing funding
Wisconsin Rep. Mark Pocan is pushing a bill to end federal funding for cat and dog experiments after Ridglan Farms’ closure.
Aiming at number 9: CASPAR targets fluorine in new science run
The Compact Accelerator System for Performing Astrophysical Research (CASPAR) recreates conditions inside stars to study how elements are made. The experiment recently restarted with a new target—the ...
Can a living fossil learn new tricks? Meet the nautilus!
With poor eyesight, the chambered nautilus hunts by smell. Explore how a blue-light experiment revealed mysteries of the cephalopod’s memory.
Scientific Papers Can Now Become AI Agents
There are millions of scientific research papers that include tons of information. Of course, not all that information is valuable, but buried across those papers are experiments, datasets, methods and software that could help researchers answer new questions. The problem is that no scientist can possibly read and make use of more than a small […]
Showcase your research at Science is Wonderful! 2027
Science is Wonderful! is the annual science fair organised by the Marie Skłodowska-Curie Actions (MSCA). It invites EU-funded researchers from around the world to come to Brussels and explain their work to children and youngsters. MSCA is calling on its fellows and alumni to apply and present their research project to over 4,000 pupils coming from all corners of Belgium to see science come alive. The 2027 edition will take place in Brussels, from 17 to 19 March 2027. Teams of researchers will showcase their work at booths through live experiments, interactive presentations, floor games, physical challenges, and many other
SAGE III/ISS Science Team Meeting Highlights Advancements in Aerosol Products and Strong Global Partnerships in Atmospheric Research
The Stratospheric Aerosol and Gas Experiment (SAGE) III on the International Space Station (ISS) ninth annual science team meeting was held August 19–20, 2026
How lip-syncing to AI let Forced Entertainment ‘play the game of theatre’
Today we have a fascinating piece by long-time Forced Entertainment fan Ben Kulvichit, speaking to Tim Etchells about their latest show Cold Sweat, how they are integrating lip-sync and AI voices into their work, the question of ‘authenticity’ on stage, and how lip-sync has even opened the door for them to make “something a little bit like drama”. This piece is a paid partnership with the Southbank Centre, where you can see Cold Sweat next month – we’re very grateful to the Southbank Centre for their ongoing support for Exeunt. Holly Williams ‘It was immediately interesting and uncanny’ **By Ben Kulvichit** “Is the microphone on?” So goes one of the opening lines of Signal to Noise, delivered by a human performer lip-syncing to an AI-generated voice. The voice is American, cheery but sluggish, slowed down into a gelatinous drawl. It repeats ad infinitum in a farce of stuckness; an answer never materialises. I find myself asking the same question as I hop on a Google Meet call with Tim Etchells, the artistic director of Forced Entertainment. We spend five or ten minutes frowning at each other, muting and unmuting, me gesticulating in semaphore into my webcam, checking if I am coming through now, restarting the laptop. To Etchells, I appear exaggeratedly mouthing words, my voice missing. In this gloopy purgatory of broken communication, life imitates art imitates life imitates art. We try a Zoom instead. Forced Entertainment, the pioneering British theatre company who have been at the avant-garde of performance since the 1980s, turned an interesting artistic corner with Signal to Noise, created on the occasion of their 40th anniversary. The whole performance employed this lip-sync technique to AI voices; on the face of it a left-field move from a company whose identity has long been grounded in the earthy, immediate presences of its performers and its unassuming, low-tech approach to theatricality. The technique, however, turned out to provide the company with a “rich new seam” of artistic enquiry, and has now spawned a trilogy of works. The second instalment, Cold Sweat, plays at Sheffield Theatres, Southbank Centre, and Lancaster Arts in October, while the third part, Everything Must Go, has been touring in Europe and is slated to come to the UK in 2027. As is often the case with Forced Entertainment shows, the main conceit for this work didn’t arrive until quite late. They were “four or five weeks into rehearsals for Signal to Noise,” Etchells recalls, and getting nowhere. Away from rehearsals, he had been playing around with feeding “weird texts” to AI voices to see how they would cope with them – “basically for my own amusement” – and was compelled by the uniformly “serviceable, benign, good-natured” tone they would read in, no matter how poetic, fractured or experimental the writing. On a hunch, he brought some examples into rehearsals and the performers gave lip-syncing a go. “It was immediately interesting and uncanny,” he recalls, with the performers having to deal in the moment with the problem of mapping themselves onto another artificial ‘performer,’ which itself was dealing with the problem of a very human text. “Almost all the writing for these projects would be useless to us unless it was done in this way,” says Etchells. “We wouldn’t know what to do with it. It’s too poetic. It’s too fictional. It’s too tangled.” But exploring lip-syncing along to the text has opened “an enormous reservoir of ways of thinking about writing and performing.” Subscribe to Exeunt, and get two in-depth pieces on theatre a week, direct to your inbox Subscribe Forced Entertainment have long been sifting through the detritus of popular culture, from daytime TV to end-of-the-pier vaudeville, magic acts and clown shows, to find frameworks for their own unusual entertainments. Lip-syncing, then, makes sense for them to experiment with. As a mode of performance, it’s wired into popular consciousness through pop stars trying to convince stadium audiences of their liveness, or those same voices as channeled through the made-up lips of contestants on RuPaul’s Drag Race, or movie dialogue spreading virally through the host bodies of TikTok users. For Etchells, lip-syncing is often about “approaching real voices and trying to take on their aura,” subsuming that original human presence into yours. “There’s a very basic, elemental sort of theatre magic to it, produced in this very easy way.” This broad approach resonates with instances of lip-syncing within contemporary performance, too. In works like Re-Member Me and Showmanism, performance artist Dickie Beau acts as a kind of spirit medium for archival recordings (this process of re-membering – as in, giving corporeal form to voices – relies on his masterfully precise actor’s technique), while Frankie Thompson is similarly possessed by a host of characters ranging from a nine-year-old Jacob Rees-Mogg to Cliff Richards, all of whom she finds compellingly nauseating, in the exorcism ritual that is her latest show, Horrible Things. What’s different about Forced Entertainment’s use of lip-syncing is that here, there is no original presence to be channeled. The performers are instead taking on what Etchells describes as “the voices of nobody,” or rather the “phantasmic, aggregated echoes” of the many many voices on whose data the AI has been trained, and which are now conjuring into existence words they never actually said. There is a sort of mournful, empty quality to these voices, having “washed up” far away from the people they originally belonged to, to find themselves in stranger’s mouths listing objects, wondering if anyone can hear them and glitching in interminable loops. There is a cold, sad anonymity to it all. Etchells remarks that occasionally the software company he used has notified him that particular people are withdrawing their voices from the platform, instructing him to cease use of those voices. Using these technologies in performance certainly brings up ethical questions around digital rights, consent, identity and ownership, although in the grand scheme of things, Etchells is fairly blasé about it: of all the purposes someone’s voice might be put to without their knowledge, “an avant-garde performance is probably the least of their worries.” [ ](https://exeuntmagazine.substack.com/p/frankie-thompson-horrible-things-essay-mental-health-compulsive-behaviours-pleasance-courtyard-soho-theatre) [ Frankie Thompson: How I manage my own ‘horrible things’ at the Edinburgh Fringe ](https://exeuntmagazine.substack.com/p/frankie-thompson-horrible-things-essay-mental-health-compulsive-behaviours-pleasance-courtyard-soho-theatre) Exeunt · Aug 25 [ Read full story ](https://exeuntmagazine.substack.com/p/frankie-thompson-horrible-things-essay-mental-health-compulsive-behaviours-pleasance-courtyard-soho-theatre) For the performers, though, lip-syncing to these strange, artificial voices is an odd task, requiring them to bend their live, human presence into the shapes produced by machines. Politically, it mirrors processes that are already at play in the continued computational automation of human life. Etchells brings up James Bridle’s writings on new technologies as a reference point: one example Bridle gives is of “chaotic storage”, a logistics technique employed by Amazon fulfilment centres whereby items are stored not according to traditional methods of categorisation or alphabetisation, but in a way that an algorithm determines to produce the most efficient routes for ‘picking’ based on customer purchase patterns. This appears completely random and incomprehensible to humans, with paddling pools sitting next to USB sticks sitting next to blowtorches, and so for the warehouse workers, the process of picking items becomes completely reliant on technology which tells them where to go. Our world is increasingly being designed not with humans in mind, but rather machines. As Etchells puts it, “technology malforms the space, and then you end up having to live in it.” Initially, Forced Entertainment tried their best to live in the world of machines: “I was in the it’s-got-to-be-perfect school of lip-sync,” says Etchells. But with their aesthetic being so tied to the failing act, the slipping mask, the shoddy costume, “it’s no surprise really that that didn’t last.” Instead, the performers got to enjoy being late for a line, or playing games with each other, “stealing” each other’s voices. Etchells compares it to the principles of ventriloquism, in which a free-floating voice unattached to a body is fundamentally discomforting and “sort of traumatic”. That discomfort is equally as alluring to Forced Entertainment as the satisfaction of precision, the pretence of authenticity only interesting if shown to be a pretence. Lip-sync has also opened up new avenues for the company. Having been allergic all their lives to Plays-with-a-capital-P, with Cold Sweat Forced Entertainment find themselves approaching something a little bit like drama. Rather than the presentational arena of Signal to Noise’s open white stage, Cold Sweat places us more decisively in a “fictional locale”: what appears to be “the aftermath of some disastrous party or backyard drinking binge” where three figures – family members, or neighbours, perhaps – are the last ones standing. “It’s all quite acrimonious and accusatory, everyone’s talking over each other.” For Etchells, this more fictional mode is “a door that we’ve never been able to open. We’ve just never really gone there.” Perhaps it is the technique of lip-syncing, an extra buffer of mediation, that allows them to venture away from the here-and-now without feeling that they have to commit to the “psychological claptrap” that comes along with acting; to be able to “play the game of theatre, without getting one’s hands too dirty.” As I wonder how else the impulses behind Forced Entertainment’s work have changed over time, it occurs to me that over the last ten years of new creations, with the exception of If All Else Fails, the company’s performers haven’t ever spoken on stage: there were two shows without any language at all, Out of Order and Under Bright Light, and then this trilogy of lip-sync works. Etchells agrees it’s a shift away from earlier productions, that were so often about “the actual voices of the performers and their actual presences. We had a lot of money, in some ways, on an authentic approach to what it might mean to speak on the stage.” But this sense of authentic presence itself had a fakeness to it; these days, Etchells can’t stand that mode of being onstage where performers “are here to be cheeky and witty versions of themselves. I don’t want to be charmed.” Pulling back into a more anonymous space has resulted in works that feel slightly sharper-edged, more brutal in a way. “All of these shows are post-Brexit, post-Trump, post-truth, post-everything,” Etchells notes. Speech, charisma, authenticity – these things feel politically loaded, and perhaps warmth and openness just don’t feel like the right tools to reflect the world we’re living in. “It feels like the space is closing down, and we’re trying to deal with the fact that the system, the structure that you’re in, is more oppressive and more powerful. It probably always was, but I think we’re just more tuned to it now.” Yet even without their voices, the performers’ distinctive presences – ones that many audiences have followed around for years, if not decades – still, inevitably, shine through as they physically navigate whatever unending task the system of the piece has set for them. They’re still trying to keep up with the onslaught of text, still running about, changing costumes, moving stuff around. The human is always stuck in the teeth of the machine, jamming the smooth, frictionless cheeriness of the not-real, gesticulating silently, trying desperately to communicate. Cold Sweat is at Sheffield Theatres, 2 to 3 October; Southbank Centre, London, 9 to 10 October; Lancaster Arts, 14 October [ ](https://exeuntmagazine.substack.com/p/exeunt-recommends-the-best-autumn-theatre-2026-lives-of-others-standard-of-living-our-friends-in-the-north-lanny-) [ Exeunt recommends... the best autumn theatre ](https://exeuntmagazine.substack.com/p/exeunt-recommends-the-best-autumn-theatre-2026-lives-of-others-standard-of-living-our-friends-in-the-north-lanny-) Exeunt · Sep 16 [ Read full story ](https://exeuntmagazine.substack.com/p/exeunt-recommends-the-best-autumn-theatre-2026-lives-of-others-standard-of-living-our-friends-in-the-north-lanny-) This piece was paid for by the Southbank Centre. Such support helps Exeunt to keep publishing the most interesting writing, about the most exciting theatre. Interested in partnering with Exeunt? Visit our Advertise with Exeunt page, where you can get more information, download an advertising pack, and find our contact details.
China’s bet on AI-driven science
Beijing is making its research system an experiment in whether AI can compensate for central planning.
I tried to upgrade myself to business class without my kids. I knew it would never work
Chalk it up to a failed experiment.
RKL Webinar to Help Business Leaders Move From AI Experimentation to AI Strategy
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Chimpanzees once used for vaccine research get health checks as part of long-term care
Chimpanzees once used in hepatitis B vaccine experiments are getting health checks at their new home in Liberia. The West African chimpanzees receive care such as teeth cleanings and X-rays
Proteus Labs Partners with Avantis Education to Add Mixed Reality Science Experiments to ClassVR Xcelerate
Avantis Education has added Proteus Labs’ virtual science labs to ClassVR Xcelerate and its EduverseSTEM education platform | XR News from Auganix.com
Nuggets preseason begs for mad science from David Adelman
The Nuggets don't know what they have behind their top eight in the rotation. The preseason is the place to experiment for David Adelman.
Minecraft Takes Science to a New Level: A Fly’s Brain Was Transplanted Into the Video Game
The experiment demonstrated the potential of gaming as a tool for testing consciousness in a virtual environment.
I tried to upgrade myself to business class without my kids. I never thought it would work
Chalk it up to a failed experiment.
7-Year-Old Boy Burned in Fire After ‘Science Experiment’ with Household Items Goes Wrong
“Every single day asks an unbelievable amount of strength from him,” a family member wrote on GoFundMe
Laying Science: Exploring density with liquids
In Mr. Bullock’s eighth-grade science class, students recently put their analytical skills to work through a hands- on density laboratory experiment. Using a variety of common liquids, including oil, rubbing
The Big Holes in Wearable Heart Rate Variability And Readiness Scores
On September 9th, Apple announced it was revamping its Apple Watch Health Sensing System, rolling out a Readiness score (0 to 10), and increasing the frequency of heart rate variability (HRV) outputs 24-fold. This can be viewed as upping its competition with various other consumer wearable sensors. These “readiness scores” as a composite of multiple metrics, with heart rate variability (HRV) being front and center for most. The majority of Americans are now using wearable sensors, which equates to well over 100 million adults. HRV and Readiness scores are increasingly being marketed as a measurement of autonomic nervous system health, a digital marker for future disease, a clock for biological age, and a holistic metric to promote healthspan and even longevity. (Apple also introduced a new longevity tab and “Health Age”.) None of this has been proven. In this edition of Ground Truths I am going to review what we know about heart rate variability and readiness scores. Heart Rate Variability HRV is the variation in normal heart cycle timing. The variability of the heart rate, the barely perceptible millisecond changes in time between consecutive heart beats (see R-R intervals in the Figure below, left panel), is due to interplay between the sympathetic and parasympathetic (vagal nerve) inputs. Distinct from heart rate, individuals with the same heart rate can have very different HRVs. It is a rough reflection of the autonomic nervous system (ANS) activity, inadequate to say whether a person’s ANS function is abnormal. For more than three decades, heart rate variability (HRV) has been measured and several studies have found an association of low HRV and clinical outcomes, particularly a link with higher all-cause and cardiovascular mortality. There have also been less well established links of low HRV to risk of early cognitive impairment, dementia, mental illness, Type 2 diabetes and substance abuse. An important reminder is that HRV is a surrogate marker without any established cause-and-effect relationship. If you increase your HRV, that doesn’t mean it will improve health outcomes. In fact, there is no hard evidence for that. All that work linking to health outcomes was done with electrocardiogram (ECG) derived HRV. Now, in the era of consumer wearables, this is getting assessed differently, by optical pulse (yes, the lights you see) plethysmography (PPG) or what is called pulse rate variability (PRV). They are not the same, as shown below (right panel) and only concordant when the delay between the ECG and pulse is kept constant, which basically means at rest. I should mention there’s also what I will call MPV, a mattress mechanical movement sensor, a derived heart rate variability, that companies like Eight Sleep use, even further away from directly measuring HRV. HRV has not one uniform measurement but many different types of quantification, such as RMSSD, the magnitude of difference between successive R-R intervals of normal sinus beats (N-N) or SDNN, the standard deviation of NN intervals, both in milliseconds. SDNN is one of the so-called frequency domain HRVs (others are LF, HF, LF/HF). Different wearable sensors use different metics; Apple has relied on SDNN and nearly all of the others use RMSSD, which is generally considered the more accurate metric. There’s also the different length of time measured, such as for a matter of minutes, all day, or an overnight’s sleep. Short measurements are especially problematic since they don’t capture enough of respiratory modulation and other factors that influence HRV. Share Ground Truths How well does HRV correlate with PRV? There are very limited studies, especially independently done. One that is commonly cited was conducted by Air Force researchers in only 13 healthy adults assessing Oura ring 3 and 4, Whoop 4.0, and Garmin Fenix 6 and showed a correlation coefficient of 0.88 to 0.97 and a mean absolute percentage error from 6 to 10%. The correlation is not a perfect 1.0, but there’s at least a fairly high level of correlation. HRV is supposed to increase during the night due to takeover of the parasympathetic nervous system, and higher during deep sleep. A recent example of my 1 week, all day “HRV,” and one during sleep is shown below. As you can see, the N of 1 data are inconsistent for the same days from different sensors (Oura, AppleWatch, Fitbit Air, and Eight Sleep) by patterns, absolute numbers, and comparison with prior days and weeks. The largest study in over 8 million Fitbit users (the old version, not Google Fitbit Air, introduced in May 2026) gives you a sense of the effect of age, sex, and the 2 different main HRV (here PRV) metrics, with RMSSD on the left and SDRR (=SDNN) on the right below. That study, from data collected in 2018, is a major outlier, since all the more recent ones are tiny with respect to sample size. Many of the companies have not had independent evaluation of their HRV, such as Eight Sleep, but have published a low standard error on their website. There are some other published studies on the correlation between HRV and PRV, but they are all small and only in healthy adults. A scoping review emphasized the lack of study in underrepresented individuals, including the aged, people of color (which affects the PPG signal), and individuals who are underweight or obese. Add the typical adult age 60 plus with one or more chronic diseases. For example, one study in over 900 adults found poor correlation of HRV and PRV, non-uniformly underestimated across many chronic diseases (cardiovascular, endocrine, neurological, respiratory, and others), concluding PRV is “an invalid surrogate for HRV.” A recent systematic review of 43 studies comparing HRV and PRV found reasonable pooled absolute standardized error (HRV as gold standard) but only 10 of the studies provided quantitative synthesis in ideal conditions. Their main conclusion was similarly cautious: “PPG-derived HRV [PRV] should not be regarded as universally interchangeable with ECG-derived HRV across all devices, populations, and recording contexts.” Factors Affecting HRV and PRV That gets me to the long list of factors that affect HRV (and PRV) besides the device, the type of measurement (RMSSD, SDNN or others), the person’s signal, the sensor site, the duration of data capture, if weighting by sleep stage is used, how artifact is processed and corrected. And this list is not complete!: Oura puts out data from their community of users (who input data) on what affects their overnight HRV. The factors currently provided are: no alcohol (increase 8%), melatonin (increase 2%, float tank (increase 2%), wine (decrease 4%), and party (decrease 14%) in overnight HRV. Must be some big parties! Subscribe What is a PRV measurement good for? It has been falsely characterized as an index of “autonomic balance” and a specific indicator of stress. A 2018 review of the studies available for HRV and its relationship to stress, not using any of the current wearables, found that stress can lower HRV. But so can many other factors. The non-specificity of the signal, indexed to the table above, is striking. Evidence from a UK Biobank study of over 46,000 participants with actual HRV looked at genetically predicted HRV, a genetic risk score, that failed to show the expected HRV-mortality link, indicating that _HRV is likely not causa_l, but rather a reflection of person’s physiologic state. A review of consumer wearable HRV data from 5 longitudinal studies showed that nighttime PRV was not associated with perceived stress, and surprisingly higher HRV, in the largest cohort (N=717 participants), was correlated with higher stress. An Oura ring cohort of 525 first-year college students found a link between overnight PRV and perceived stress, but that was also seen with resting heart rate, sleep, and respiratory rate. Several very small studies have examined the relationship of HRV and athletic injuries or guiding training with mixed, and predominantly negative results. HRV biofeedback training with paced breathing had no significant effect on reducing stress or raising HRV, as demonstrated with sham controlled trials. When HRV for multiple days showed a decline in conjunction with body temperature, the Oura ring published data for prediction of Covid. The WHOOP company sponsored an observational study, published in 2026, of 30,000 users for 72 weeks, without a control group, that reported reduced alcohol intake (5.8 % points) by self-report. That doesn’t tell us much, and particularly about the merits of HRV for behavioral change. If you use the same device and conditions as longitudinal trends for multiple (at least 2-3) weeks that may be the one way to get something useful from the measurements. Data for overnight sleep with minimal motion and using RMSSD is the best proxy for real HRV. The reason to look at trends rather than any given night is that it more likely represents something, even though you won’t know with certainty what the “it” is. Keep in mind there are no data, no peer-reviewed evidence, to show that HRV fluctuation in-person has any correlation with health outcomes. Share Readiness Scores These are proprietary scores that integrate different metrics for each of the wearables: no algorithms have been disclosed. They are unvalidated against health outcomes. In a review of 14 composite health scores of readiness and recovery, HRV contributed 86% to the scores, followed by reading heart rate (79%), physical activity and sleep duration (both at 71%). That review noted the substantial variability in measurement protools and lack of standardization. Sleep staging is notoriously inconsistent and inaccurate by these sensors, which adds further to the HRV uncertainties for what the scores, which use sleep stage data, mean. Only resting heart rate has been shown consistently across devices to be extremely accurate. I’ve made a Table to summarize what we know about which metrics are included, the scores, any peer-reviewed studies that compared the readiness score with health outcomes, and the corresponding (if any, NA-not available) citation. You will note that some companies do not use the term “readiness," such as WHOOP for recovery, and Garmin, which has 2 different scores, one of which is Body Battery. Eight Sleep uses the term “Fitness Score.” They all include HRV; Apple includes a new metric they call “Recovery HRV” which among other components uses 7-days of sleep, but it is unclear what this means or how it is differentiated from other scores (there are clearly no data for outcomes). We have no knowledge of how the different components are weighted or whether any of these scores are better than resting heart rate, HRV alone, physical activity, or any other single metric. Since none of these are standardized, they are not interchangeable, so if you get a 90 for Oura that has no relationship to a 90 on a Google Fitbit Air. Notably, the company can update its algorithm for readiness score at any point without notification to device users. Without any useful evidence of actionability for these scores or established relationship with health outcomes, it is hard to make a case for their value. At the Apple recent announcement they showed their Readiness score (0-10) on the watch (Figure below) but there are no published data on this score, not even on their website. It’s available only on their new Watch Series 12 or Ultra 4 [of course, ;-)]. That exemplifies the problems with these scores, lack of data and evidence for being meaningful to promote health. Perhaps the best study (which isn’t saying much) is the WHOOP Recovery for golfer performance, because it did correlate with an objective outcome, even though there was no control group and the authors were all from the company. Among the 389 pro golfers, an absolute 10-per cent point increase in Recovery score was associated with about 0.5 fewer strokes per round. But that’s hardly a health outcome! WHOOP is also conducting a study in over 2,700 runners to see if their recovery score will be linked to less injuries and improved performance, but that is not yet published and has no control group or randomization. Putting This in Context For two decades I’ve been enthusiastic about the potential for digital health and particularly wearable biosensors. Over the years, we’ve seen some great progress for their ability to promote physical activity and accurately detect atrial fibrillation (the first FDA cleared deep learning AI for consumers). That work was the subject of rigorous research. But there are holes in the data and evidence for other metrics. One notable one is the “VO2 max” story that I wrote about earlier this year. At that time many subscribers asked me to cover heart rate variability, which I finally got to here. When I dived into the research and publication for HRV and readiness scores, I expected to find at least some that were of high quality and demonstrated their utility by linkage to health outcomes. To my surprise, I found none. The wearable sensor measurements for HRV (PRV) are, for the most part, accurate, but that validation work has only been done in small studies of healthy adults and does not take into account the long list of factors, from the device, software side, and the user side, that affect HRV measurements. Moreover, this metric chiefly relies on optical sensing and, as we have learned for heart rate PPG sensing, may be less accurate in people of color. Keep in mind that all of the health outcome association evidence comes from ECG-derived HRV; none are from wearable sensor data. I will repeat the key point: there's no peer-reviewed evidence to show that in-person HRV fluctuation—or efforts to raise your HRV— has any correlation with health outcomes. For those of you who look at your HRV on awakening, or even 2+ week trends of it being low, I hope this context helps to relieve any anxiety. Yes, low HRV (not PRV) has been shown to increase risk of some diseases as summarized above. But efforts to raise your HRV—a surrogate metric— has not been established for improving any health outcomes. HRV does not have any evidence of causality (the genetic evidence actually goes against this possibility). In this summary, I have not included data for other wearable sensors such as Polar, Samsung, Withings, Suunto, Amazfit, Coros, Ultrahuman, or additional mattress sensors. These are beyond my first-hand experience, and as far as I know from my in-depth review none have any peer-reviewed published data that differ from the 6 sensors I’ve reviewed here. From the points I’ve gone over above, we’re not ready for readiness scores. Besides being proprietary, they are predominantly based on metrics that have their own issues. It’s compounding the problem, like building a house without a solid foundation that has never undergone a rigorous inspection, and then selling it. Like I mentioned for PRV, you can look at trends over weeks rather than any single day, to get a handle, but even that may not be helpful. There’s simply no evidence that these scores meaningfully relate to health outcomes. I’d emphasize they might, but that requires doing prospective or randomized studies to prove it. None exist. There’s great promise for HRV/PRV utility_. For example**,**_ Prof Maiken Nedergaard, who discovered the brain glymphatics that are essential in eliminating metabolic waste products from the brain during sleep, has posited that HRV could be a non-invasive marker for neuromodulator oscillations, brain-body regulatory circuits, and brain clearance. That would be extremely useful, but like everything else on HRV and readiness scores it requires solid research and validation. The lay media isn’t helping much to get the story straight. Earlier this year The Economist published a piece entitled “The most useful indicator of your overall health” which ordained HRV as an “accumulated stress score.” That’s akin to the false assertion about VO2max: “V02 max is the singular most powerful marker for longevity.” As I’ve summarized here, that is not established. The fact is that so many things can lower HRV, including physical exercise (especially an intense workout), reduced sleep quality, stress, the list above, no less the device, signal, and software. Whatever fluctuations observed have not been correlated with any health outcome. Sadly, “datamaxxers” are widely using HRV and readiness scores that have never been validated to mean anything. We already know that for some people using the sensors for sleep metrics, it can induce “orthosomnia,” an obsession to get high sleep quality, with associated high levels of anxiety. In an experiment done by a company to promote sleep quality for its employees, “For those employees who did use the trackers, many reported feeling perfectly rested until their tracker told them they had had a terrible night. Others were told that they had slept like a baby when they had actually been lying awake worrying about the quality of their sleep. “ The same problem can result from preoccupation with HRV or readiness scores, with anxiety that would lead to further reduction in both. It you are using a wearable like >100 million American adults, it’s OK to look at these data, but contextualized with the major caveats reviewed here. If you are one to require evidence that HRV or readiness scores are linked to health outcomes, you may not even want to look. The companies make it hard to turn them off! Let me end with the companies that make and sell wearables. Apple’s doubling down on HRV (24-fold more reporting and heart rate very 5 seconds) and introduction of a Readiness score tells us that consumers have bought into these metrics and they are joining the club. However, all of this is occurring with a backdrop of tens millions of users, claims about the data that are not backed up by adequate evidence, marketing way out in front of whatever limited data exists, and not being transparent about their readiness score algorithms. The companies can well afford to do the research that is needed to connect these metrics with health outcomes show, once and for all, that increasing HRV or using readiness scores promotes our health. If they believed and invested in the products they are selling, we’d not be in this position of not knowing. That’s essentially where we are with HRV and readiness scores. Perhaps someday this will change and we’ll have good reason to embrace them. NB: I wrote this post. No AI. I have no conflicts of interest with any of its content. Loading... Ground Truths has 215,000 subscribers from every US state and 214 countries. There are over 300,000 followers of Ground Truths so more than 90,000 folks who can easily convert to be free subscribers. Your subscription to these free essays and podcasts makes my work in putting them together worthwhile. If you’re not a subscriber, please join! If you found this interesting PLEASE share it! Share Ground Truths The proceeds from all voluntary paid subscriptions go to support our summer internship program. It enabled us to accept and support a record number of 62 summer interns that joined us in 2026! These are high school, college and medical students selected from thousands of applicants. We couldn’t do this expanded program without the funds coming in through Ground Truths. Thank you!
Your Cat Knows Exactly Who You Are And Scientists Just Proved It
Scientists in Japan designed a deceptively simple experiment to probe what goes on behind a cat's quiet stare, and the results are forcing a serious rethink of everything we assumed about feline intelligence.
7-year-old boy burned in fire after science experiment with household items goes wrong
A family is speaking for the first time after a science experiment sent a 7-year-old boy to the hospital with serious burns in Lake Worth.
7-year-old boy burned in fire after science experiment with household items goes wrong
7-year-old boy burned in fire after science experiment with household items goes wrong
Why AI is speeding up scientific research but not lab experiments
A new report by Google, Google DeepMind and MIT finds that researchers are using AI…a lot. It’s just not helping as much in the lab
Engrams Embedding Entendre: Codesign for Efficient DRAM/SSD Offloading
Engram extends standard token embeddings with learned multi-token lookups. Recurring local patterns retrieve vectors directly, reducing the need to reconstruct them through attention and feed-forward layers. With Engram model architecture optimization, it allows for lower HBM capacity to be needed for models at the same quality. This does not mean there won’t be an insane demand for HBM but it just means that model architecture will continue to innovate around constraints. This model architecture design is naturally codesigned for parameter offloading: each token accesses a few embedding rows whose addresses depend on token IDs, not hidden states. The runtime can prefetch those rows from host DRAM while earlier layers compute, keeping the table outside HBM without transferring entire weight matrices. Our Memory model contains our latest estimates of quarter by quarter HBM, DRAM, & NAND supply and demand. Offloading frees HBM for model weights and KV cache, potentially supporting larger batches or more concurrent sessions. When DRAM becomes the next constraint, NVMe offers another tier. Recommendation systems already cache frequently or recently accessed embedding rows in faster memory while backing colder rows with SSDs. After NVIDIA roadmap had to change due to massively despec’ing Rubin Ultra from 1024GB to now ~200GB of HBM per chip, model architecture optimizations like emgram maybe helpful. Our DeepSeek-V4.1-Flash configuration uses roughly 189 GiB of memory for Engram. We replace it with a memory-mapped (mmap) file and measure serving performance with offload to SSD. Later on in our report, we will show our Engram offloading experiments along with the official InferenceX agentic inference serving results on Engram models like DeepSeekv4.1 Flash across all 6 NVIDIA GPU SKUs along with MI355X. Unsurprisingly, the CUDA Moat is still mogging MI355X on the ultra popular DeepSeekV4.1 Flash model. We also show how even on high capacity HBM SKUs, offloading emgrams to DRAM could result in even better performance for most of the pareto than keeping the emgram in HBM. Our benchmark has been widely reproduced, validated and/or supported by almost every major buyer of compute from Google Cloud to Microsoft Azure to Oracle, to Meta and many more. Furthermore, it has the support of the ML community including from vLLM, LMCache, SGLang, PyTorch, Huggingface and the support of major labs like OpenAI, MiniMax, ZAI, Qwen, Moonshot Kimi, etc. Star the InferenceX GitHub repository if you find the open-source benchmark and data useful!. InferenceX is the only inference benchmark in the world to have TPUv7, Jalapeño, Nvidia Rubin NVL72, AMD, and soon, SambaNova and Trainium. Due to how realistic AgentX scenario is to real world agentic inference workloads, AMD has committed to collaborating on MI455X UALoE72 too. DeepSeek did not release the original paper’s two trained Engram models. We replicated its setup on fineweb-edu using the released code and training hyperparameters, at an estimated 6E18 FLOPs per run. We observed the same U-shape scaling: Engram improved performance over pure MoE baselines. We also reproduced DeepSeek’s results, where earlier-layer representations with Engram resembled those of later layers. Like the original Engram paper, it is possible to probe Engram’s gate scores to see what n-grams DeepSeek-V4.1-Flash makes the most use of. Our gate scan finds names, code fragments, relational phrasing, and boilerplate. These examples prioritize interesting-ness over gate strength. One unexpected result was Wright : Ace Attorney. These examples suggest learned memory optimizes the training objective, not a judgment of which facts deserve storage. Licenses, bibliography fragments, API scaffolding, and website furniture can provide prediction shortcuts, so the value of additional Engram capacity may depend on what survives data preparation. This does not show that table capacity is “wasted”: the evaluation-corpus scan establishes neither training exposure nor the capacity occupied by each category. For offloading, strong gates do not identify cache-hot rows. Low gates do not automatically save reads either: computing the gate requires the retrieved key and undoes the performance gain of a fused kernel. Skipping reads would require a separate usefulness predictor before retrieval. In the original paper’s inference-time ablation, factual-knowledge benchmarks retained just 29–44% of their original performance, while reading comprehension retained 81–93%. This is due to the training–inference mismatch. The resulting degradation therefore measures this trained model’s dependence on Engram, not the performance difference between models trained with and without it. In our ablations, suppressing Engram worsens token likelihood across all evaluated domains, especially encyclopedia text and several code corpora. Surprisingly, GSM8K accuracy stays within measured run-to-run variation and removing Engram has no effect. Engram is not a detachable dictionary beside an unchanged MoE. Removing it changes downstream features and expert selection. We tested whether rerouting hurts or compensates by holding tokens fixed in a teacher-forced experiment on CRUXEval, a code-reasoning benchmark of small Python functions where the model predicts a function’s output from its code and an input, and scoring the reference answer. Removing Engram raised answer loss from 0.2848 to 0.3093 bits/token. Forcing the ablated model to use the original Engram-on expert choices made it worse still, at 0.3375 bits/token. Rerouting partially compensates for the missing memory. Memory features and expert selection work together, rather than following a clean “memory stores facts; experts reason” division. On the same CRUXeval, removing Engram during either phase reduced accuracy and increased generated tokens; removing it throughout produced the largest changes. Keeping Engram for prefill leads to more correct answers than keeping for decode likely due to semantically richer KV cache transferred to decode workers, allowing it to mitigate some of the performance loss. Engram’s table is large, but each lookup is small. DeepSeek-V4.1-Flash requests 24 rows at each of two Engram layers, about 12.4 KiB per processed token position across the model, or 3.1 KiB per GPU when split across four GPUs. Currently as of Day 7 since Model Release, MI355X is still 2-4x worse performance per dollar compared to B200 even when normalized by Mi355X’s lower TCO. Our full total cost of ownership breakdown comes from our AI Cloud TCO Model along with monthly market surveys of over 100+ gpu clouds & gpu cloud customers. On the Day 0 release of DeepSeekv4.1 Flash, NVIDIA vLLM works out of the box with zero issues across all 6 SKUs: H100, H200, B200, B300, GB200, GB300! This was thanks to the amazing work by the NVIDIA & Interact teams! In comparison, AMD vLLM did not work on day 0 for DeepSeekv4.1 Flash.Source: SemiAnalysis InferenceX AMD’s vLLM documentation points to using vllm/vllm-openai-rocm:deepseekv41-flash-0909, but from hour 0 of the model release to hour 23, AMD has not publicly released the image. AMD claims, “SPEED IS THE MOAT,” yet it has still not released it by the 23rd hour. We wish that, going forward, the AMD team has a better process for hour 0 model releases. Eventually when they did publicly release for “day 0” image support, performance-wise, it is currently up to 14.8x worse perf per dollar than H200 and up to 42x worse perf per dollar than B200/B300. The power of the CUDA MOAT is NVIDIA’s collaboration with its massive 6 million-developer community ecosystem including most of the vLLM & SGLang & Tokenspeed maintainers which means that CUDA is optimized on day 0. Overall, AMD did make significant improvements but the performance per dollar is still currently 2-4x worse than B200. AgentX Engram DRAM Offloading Improving Performance The HBM and DRAM offload use the same GPU kernel to select and dequantize rows. With HBM, it reads GPU memory; with Unified Virtual Addressing (UVA), it reads pinned host memory directly. Both support full decode graphs. Moving the table into HBM accelerates only the sparse lookup, leaving decoder computation and communication unchanged, resulting in little overall benefit while consuming memory otherwise available to KV cache. Another benefit of Engram offloaded to DRAM which means you can reduce the communication overhead by using less HBM GPUs per replica. For example, when enabling Engram offloading on B300, we are able to switch from TP4 to now TP2 which improves the pareto curve by up to 1.6x. When iso-model quality, less HBM is required as the engrams could be offloaded to host DRAM. Thus HBM bandwidth matters way more than HBM capacity. For inference workloads where memory bandwidth matters the most, 4-hi HBM provides the best $/bandwidth and therefore lowest cost per token. If China continues to make more and more revolutionary model architecture innovations, soon it could potentially 0Hi HBM stacks. [ ](https://newsletter.semianalysis.com/p/long-live-the-short-king-why-4-hi) [ Long Live the Short King: Why 4-hi HBM Wins ](https://newsletter.semianalysis.com/p/long-live-the-short-king-why-4-hi) Myron Xie, Bryan Shan, and 3 others · Sep 13 [ Read full story ](https://newsletter.semianalysis.com/p/long-live-the-short-king-why-4-hi) Moreover, on B300 and week-0 stack, moving the Engram table back to HBM did not improve results and stay within run-to-run variance. This is a result of the work optimizing DRAM offload, such as async, and overlap. SSD Offloading On B200, we created a unoptimized vLLM fork and stored the Engram tables in memory-mapped files on local SSDs. File backing lets the OS reclaim table pages when other applications need RAM. Pages already cached in memory can be served without reading the SSD again. Furthermore, note that we were unable to turn on GDS The unoptimized SSD implementation changes how rows reach the GPU. It copies row IDs to the CPU, deduplicates them, gathers the requested rows into pinned buffers, copies those rows back to the GPU and dequantizes them. This work runs between segments of the GPU execution graph. Native UVA performs row selection and dequantization directly on the GPU, avoiding the CPU round trip. A warm filesystem cache removes physical SSD reads, but leaves the coordination, row gathering and transfers. This is why a file already cached in RAM can still perform worse than a pinned DRAM table. The comparison measures the whole serving path; it does not separate the time spent on each of these operations. B200 DRAM dominates both measured SSD serving curves in total tokens per dollar and P90 interactivity. Near 125 tokens/s/user, DRAM delivers 121 million total tokens per dollar versus 52 million for SSD. For production serving, SSD offloading is likely not worth the tradeoff. On the B200 configurations we measured, SSD offloading loses on both measures: every observed SSD point has a DRAM alternative that delivers higher P90 interactivity and more total tokens per dollar. The only points where Cheaper storage does not automatically produce a cheaper inference service. Moving Engram to SSD leaves the same four expensive GPUs and the rest of the server in place. Reclaiming RAM only creates an economic benefit if it enables a cheaper server configuration or additional useful capacity. The current unoptimized path provides neither benefit, and the filesystem cache still consumes RAM when table pages are resident. Next we will look at the mechanisms and specific implementation of ngrams from DeepSeekv4.1 Flash, LongCat, Qwen3.8 Flash Next.
Anthropic quietly sets up biology lab as it ramps AI drug program
At a time when fears of AI are gripping the public, the startup has built a wet lab — or place for physical experiments — in the San Francisco Bay Area, two people familiar with the matter said.
Cost-Saving Medicaid Meal Deliveries Threatened by Cuts, Policy Uncertainty
An experiment to provide meals to some Medicaid recipients shows food can be cost-effective medicine. But even as federal officials tout the power of nutrition, Medicaid budget cuts could lead states to think twice about covering healthy food for sick residents. One has already reconsidered.
LACCE
The Landslide Change Characterization Experiment (LACCE) will investigate landslides as they occur in real time across California and Alaska.
Google announces new experimental "CC" AI agent for families
Multiple family members can share data to help the agent make plans and complete tasks.
Microsoft’s AI playbook shows businesses how to turn experiments into results
Microsoft’s new Frontier Playbook outlines how businesses can move beyond AI experimentation and turn artificial intelligence deployments into measurable business results, including greater productivity and time savings, Inc. reports. The guide draws on more than 100 of Microsoft’s internal AI projects across its corporate functions, commercial organization and engineering teams. It comes as enterprise AI […]
Science in a Bag is Bringing Hands-On Experiments to Wisconsin Kids
Sometimes, all it takes to get a kid excited about science, the environment, or agriculture — is a drawstring bag.
Free mad science event Saturday in Apache Junction
Grab your lab coat because it’s going to get messy. There will be more than 30 different fun science experiments to watch, touch and experience at a free mad science event in Apache Junction in …
Pollard Lecture set for Oct. 8
Dorothee Kern, from Howard Hughes Medical Institute and Scripps Research, will present the 2026 Ernest C. Pollard Lecture in Biochemistry and Molecular Biology, titled “The Protein Dance: From Experiments to AI Predictions,” at 12:10 p.m. on Thursday, Oct. 8, in 008 Mueller Laboratory at Penn State University Park. This free public lecture is sponsored by the Penn State Eberly College of Science.
Robotic lab sets up and runs optics experiments on demand
The process of building and running an optics experiment to analyze a material’s properties could one day be fully automated, MIT scientists say. Taking a step toward such a future, they developed a reconfigurable, robotic optics laboratory.
Health Rounds: New dye for MRI exams detects lung cancer earlier
Hello Health Rounds readers! Today we highlight a potentially game-changing experimental contrast agent for MRI exams that may enable detection of lung cancer when tumors are small and more treatment options are available. We also report on a Johnson & Johnson antidepressant that appears to help improve sexual dysfunction in patients with major depressive disorder.
Use of untested 'Wolverine' peptide backed by US Health Secretary Kennedy on the rise, study finds
An experimental peptide backed by U.S. Health Secretary Robert F. Kennedy Jr. and marketed online for pain, healing and performance enhancement is being used for a wide range of ailments despite little safety and efficacy evidence from human studies, a new analysis found.
Use of Untested 'Wolverine' Peptide Backed by US Health Secretary Kennedy on the Rise, Study Finds
By Nancy Lapid Sept 15 (Reuters) - An experimental peptide backed by U.S. Health Secretary Robert F. Kennedy Jr. and marketed online for pain, healing and performance enhancement is being used for a wide range of ailments despite little safety and efficacy evidence from human studies, a new ...
Has dark matter been found? Bay Area scientists analyze signal deep underground
A single unexplained particle interaction has Bay Area scientists investigating a tantalizing possibility: a direct detection of dark matter, the mysterious substance thought to make up most of the universe’s matter.
Scientists hunt for dark matter deep underground
A SLAC-led experiment more than a mile beneath a Canadian mine has begun collecting early scientific data ahead
A 3-Year-Old's Metastatic Cancer Disappeared After Two Doses of Experimental Therapy
This could save lives.
Health Brief: Exclusive | States line up for Medicaid drug pilot
At least 19 have applied to the Trump administration’s drug-pricing experiment offering internationally benchmarked prices under Medicaid
Potential dark matter detection sparks hope in search for elusive substance
Finding dark matter would help to understand what the universe is made of. The LZ experiment may have made a breakthrough in detecting the invisible substance.
Science in a Bag, a popular part of the Wisconsin Science Festival, marks its sixth year
Three thousand drawstring bags filled with at-home science experiments will be distributed to public libraries across the state and bring a spark of curiosity to all corners of Wisconsin.
A Vinyl Bar in Shibuya is a startup from former Spotify employee offering fun music apps
Former Spotify exec's company releases experimental "singles" that involves users in music making.
A Vinyl Bar in Shibuya is a startup offering fun music apps without any AI prompting
Former Spotify exec's company releases experimental "singles" that involves users in music making.
Ian-credible Science: Amylase breakdown
Each week, we bring you a quick and easy experiment you can do at home to explore a concept in science. This week, we’re exploring one way our mouth breaks down the food we eat.
Stop Automating Old Processes. Design New Ones Instead.
Companies are pouring money into AI but often failing to generate enterprise-wide returns because they automate individual tasks rather than redesign the workflows that produce business value. This typically results in one or more of four failures: accelerating tasks rather than value, ignoring unhappy outcomes, overlooking the end-to-end flow of work, or optimizing the wrong metric. To capture AI’s potential, managers need to make three decisions. First, determine what to redesign by identifying the outcome customers value, the constraints AI can remove, and opportunities for learning that compounds over time. Second, decide where human authority should remain, choosing among four modes—Assist, Approve, Audit, and Automate—according to the stakes and reversibility of potential errors. Third, design for the “unhappy path”: specify how the system will recognize uncertainty, escalate exceptions, stop or reverse actions, and learn from corrections. Together, these choices turn isolated AI experiments into reliable, value-producing operating processes.
Bryan Johnson and Kate Tolo's very public experiment in love
Bryan Johnson and Kate Tolo are lovers, cofounders, and human experiments trying to engineer a future where people and AI evolve together.
Magic of science
Students take a fun science class in Wenling, East China’s Zhejiang Province, on September 13, 2026. Through intuitive and interesting experiments, abstract physical principles were turned into visible phenomena, allowing students to explore the mysteries of low-temperature science up close. Photo: VCG
Science experiments and fun for all at Oh Wow's Silly Science Sunday
Oh Wow is launching its 16th Silly Science Sunday, the free-to-attend interactive sceince exposition at Weamn Park in Youngstown. Here's more.
America's Health Care System Is So Screwed That Patients Are Flying to China for Cancer Treatment
An experimental cancer treatment developed in the US has become a standalone industry in China, attracting throngs of medical tourists.
Did Scientists Just Witness a Key Step in the Origin of Complex Life?
A recent headline suggests a breakthrough. Have researchers recently witnessed experimental support for the origin of complex life?
Chimpanzees once used for vaccine research get health checks as part of long-term care
Chimpanzees once used in hepatitis B vaccine experiments are getting health checks at their new home in Liberia. The West African chimpanzees receive care such as teeth cleanings and X-rays
Are fish farms the future of Gulf seafood? The stakes are high for Louisiana.
Aquaculture experiments are emerging in the Gulf and prompting intense debate. For Louisiana and its seafood industry and culture, the stakes are enormous.
In 1971, scientists moved just five pairs of Italian wall lizards onto a small Croatian island; 36 years later their descendants had larger heads, stronger bites and altered digestive tracts suited to eating far more vegetation than the original population
A forgotten experiment in island translocation became an accidental demonstration of evolution in real time, reshaping an entire species in just over three decades.
Physicists discover a hidden “curveball” in quantum light
Researchers have experimentally demonstrated the optical Magnus effect for the first time, revealing that a tightly focused laser interacts most strongly with an atom slightly away from the beam’s center. The unexpected shift is similar to the physics that makes a spinning table tennis ball curve through the air. Because lasers are used to control qubits, the effect could create errors in quantum computers, but it might also provide a new way to couple qubits together.
Scientists got diamond's melting point wrong by more than 1,000 degrees, crushing new laser experiment reveals
Scientists blasted diamonds with lasers to get the best measurement of the mineral's melting point yet. The new, more accurate numbers could help improve fusion experiments and studies of giant planets.
CERN finds gluons behaving strangely deep inside atomic nuclei
Physicists at CERN have found a new way to peer deep inside atomic nuclei and distinguish between two competing explanations for how gluons behave. Using the ALICE experiment at the Large Hadron Collider, researchers measured particle production at unprecedented spatial resolution, revealing structures as small as about one-quarter the size of a proton. At the smallest scales, they saw a surprising drop in J/ψ production that conventional “nuclear shadowing” struggles to explain.
How scientists achieve simulated outer space conditions on earth: The tower in Germany where gravity takes a break
Conducting experiments in space is costly, but on Earth there are facilities where they can be done more economically. The most outstanding is in Bremen.
The politics and possibilities of ‘AI could kill us all’
I found myself fielding a lot of questions from folks who don’t usually talk much about AI this week. They were mostly along the lines of “do you think AI is going to kill us all?” or “how worried should I be about this human extinction stuff?” Motivating this wave of existential anxiety was the highly dramatic resignation of now-former Anthropic employee Jacob Coxon, who quit his job while publicly sharing his concerns about safety practices at the leading AI companies. More specifically, he declared that almost everyone at OpenAI and Anthropic, the leading AI labs, believes that there’s a decent chance the AI systems they’re producing could “kill us all” by the end of the decade, and the companies aren’t “acting responsibly.” Other AI safety researchers, including those still employed at Anthropic and OpenAI, all confirmed that yes, Coxon is correct, they’re all worried that their company’s products might prove fatal for the entire human race as well. Two more AI employees quit and joined the chorus. Now, the warning shot has been covered everywhere from the Wall Street Journal to Fox News to WIRED to the Guardian. I understand why all this sounds scary, but my response to those who have asked, has generally been: No, you don’t need to worry that AI will kill go rogue and kill us all. But that does not mean we shouldn’t worry, period. Far from it. The companies building AI products are now among the wealthiest and most powerful entities in the world. And they very much are building enormous engines of mass surveillance, extraction, and automation. They can and have allowed their AI systems to carry out felony hacks of other companies, provided the government with autonomously generated kill lists, and sold enterprise technology to firms around the world that is explicitly intended to replace jobs. But “AI” has done these things not because they have all-powerful minds of their own but, ultimately, because people have programmed, calibrated, and directed them to. In other words, it’s not AI we need to worry the most about. It’s the people and corporations working to profit from and gain power by deploying it. The technology is sophisticated, sure, and, especially in cybersecurity contexts, potentially disruptive to plenty of existing systems. But if we want to stop this predatory, profiteering, and extractive form of AI—and it’s worth noting that at this point, most people do—we absolutely can. A quick note/plea: I can only do all of this with the support of readers like you, so if you find value in independent, critical tech journalism and analysis, please consider becoming a paid subscriber. I want to keep as much of this un-paywalled as absolutely possible, and I need your support to do so. Many thanks to all who continue to chip in, it’s very much appreciated. Onward. Subscribe First, some context: AI industry folks like Coxon have been discussing the prospect that AI will destroy humanity for years. Even before the beginning of the AI boom, many working in the industry, from the executive staff to the rank and file researchers, have obsessed over ‘x-risk’, or the possibility that AI will become sentient or semi-sentient and move one way or another to exterminate humanity. This is ostensibly why Elon Musk bankrolled OpenAI in the first place, and is the grounds for his lawsuit alleging OpenAI betrayed its charter by abandoning its nonprofit status to become a commercial enterprise. Many AI engineers and startup founders have calculated their own personal p(doom), or the probability that the tech product they are working on will initiate an actual humanity-extinguishing apocalypse. 10-25% p(doom)s are pretty common. (I wrote about a long weekend I spent among these folks at one of their top conferences here, to give you an idea of their ideas and belief systems.) Sam Altman himself drove the narrative of the imminent rise of a super-powerful AI, or artificial general intelligence, to prominence by declaring that the technology he was building posed an existential risk to humanity. This idea is in other words baked into the DNA of modern AI companies and into the products they engineer. It’s also why the industry is routinely accused, by myself and others, of “doom marketing,” ie, using such proclamations and framings to impart the sheer power of the technology behind your product onto investors, partners, consumers, and the state. Some ambient understanding of this tendency may have helped prevent the press from repeating the claim every time one of the x-risk folks made it over the years, including when they quit their jobs at AI companies while doing so. Yet Coxon’s AI x-risk alarm has broken containment, as they say, and has exposed the idea to the mainstream media once again. This has happened, I think, for a number of reasons. First, when AI CEOs were going around saying AI might kill everyone in 2023, their companies were well-capitalized, but not nearly to the extent they are today. They were more easily dismissed as eccentric geeks of the sort that Silicon Valley is supposed to produce. Now, not only do their products have much greater market saturation, but people are more aware of a) the often unethical ways the executives and companies comport themselves b) the other adverse impacts of AI that have already arrived, and c) the physical cost of building these systems, particularly when it comes to data centers. Finally, toss in the constant stream of headlines in 2026 about AI models going rogue or potentially upending the world’s infrastructure. [ ](https://www.bloodinthemachine.com/p/with-the-backlash-to-data-centers) [ With the backlash to data centers, Flock and AI glasses, a mass opposition to big tech is underway. Silicon Valley is in denial. ](https://www.bloodinthemachine.com/p/with-the-backlash-to-data-centers) Brian Merchant · Aug 27 [ Read full story ](https://www.bloodinthemachine.com/p/with-the-backlash-to-data-centers) As a result, general sentiment was already overwhelmingly skeptical of AI and its overlords, so the table was pretty well set for someone to come along and say ‘just a reminder, the companies that are building the product that promises to take your job and leave a data center in your neighborhood also think that it might exterminate the human race’ and get a strong reaction from the media and the public. The question is: Should we understand this stuff as hype, strategically fanned to feed already swelling valuations? Is it doom marketing? Genuine cause for alarm that the infrastructure that undergirds modern life is facing a novel threat vector? Or reason to be sincerely worried that AI companies are amassing too much power, and that their products are genuinely dangerous? The answer, I’m afraid, is “yes.” Let me try to untangle all of this a bit, because arguments over how to navigate this moment are extremely heated right now, as they are essentially arguments over how to approach the politics of AI at a moment where there may be a unique opening for action. Those sympathetic to AI alignment concerns and x risk arguments—which increasingly includes a faction on the left who want to shut down AI over safety concerns—argue that people who dismiss AI as all hype have their heads in the sand. Meanwhile, critics of the x-risk narrative—which I might note includes a cadre of investors and tech folks on the right, too—argue that it is hype and can be used to further inflate valuations or for pursuing regulatory capture. The challenge is that many feel that dismissing AI as just hype or purely marketing also diminishes the urgency of taking on the AI industry as the novel and threat to labor, civil society, and the public sphere it is; others that by accepting the industry’s own terms, we imbue it with undue power and enable it. But let’s be clear: Declarations that AI is so powerful it might end the world are a kind of marketing, and anyone who says otherwise is just as off base as those who say that’s all that it is. If you don’t think that these sub-trillion dollar companies have higher-ups who noticed that when their founders talked about super-powerful dangerous AI they got spikes in media interest and phone calls from investors, or that those founders didn’t notice that themselves, and lean into certain narratives to advantage their products, then I don’t know what to tell you. Not all marketing is a Pepsi ad campaign with a celebrity spokesperson. Yet confronting the AI industry should certainly be considered an urgent project. Do I share the x-riskers’ fear that out-of-control, super-intelligent AI agents might end the world? I do not. I’ve read a good deal of AI extinction literature over the last couple of years and I have not come across a credible, step-by-step documentation of how exactly AI might move from self-recursively improving AI to killing every single human on the planet. Most of what I’ve read seems predicated on a sort of reverse Ian Malcolmian logic: Eventually, it becomes smart enough and AI, uh, finds a way (to exterminate humanity). Are the AI companies also overstating and dramatizing what their products can do? Yes, pretty much all the time. They’re in a knife fight for market share and are trying to win customers and government contracts before their investors come knocking. And yet. They have concentrated enormous amounts of compute, have extensive data collection and surveillance capacities, have inserted themselves into the state in numerous capacities, including military kill chains, and they are being run by egomaniacal billionaires who are rushing to monopolize an entire new market. The way I think about their most recent frightening-seeming exploits is not as a “swarm of rogue AI agents building a new civilization” or whatever, but as corporations with a hitherto-unimaginable amount of compute at their disposal recklessly experimenting with automation programs, completely unafraid of any repercussions because we have been unwilling or unable to impose any on them. So I think we should welcome any newfound imperative to hold them accountable. I also think that ultimately, the AI critics, Pause AI folks, leftists, doomers, effective altruists, and, honestly, most of the public, want a lot of the same things: legitimate checks and limits on AI companies’ power, actual transparency into what the companies are doing, and for more of AI to be under public control. (Ultimately, a lot of what animates the x-risk fears are rooted in just that: a fear of losing control.) How we move towards all this, exactly, is the question of the day, and while there’s much to be argued over in terms of building a viable political platform to challenge the AI industry’s power, I do want to cast a vote against one particular approach. Not to pick on Chris here, as there are a lot of folks out there proposing stuff like this, and the policy ideas actually stem from AI safety groups. But not only would this be challenging to land politically (I can already hear the ‘China will beat us to AGI’ calls) and all but unworkable in practice, this approach is a) far too limiting, b) fails to address the current harms caused by AI and c) would likely only wind up serving Anthropic and OpenAI; it’s what regulatory capture looks like in action. Full model transparency is the floor for what should be on offer here. If these companies believe their products will kill us, the very least we deserve is to know how. It’s in the public interest. I would also argue we might get a lot of the way to stopping any currently envisioned robot apocalypse simply by forcing AI companies to assume liability, and to submit to the full brunt of the law. If Sam Altman were liable to be charged with a felony for approving the hack on Hugging Face1, if Google was forced to pay defamation fines each time it published a false and injurious AI Overviews, these companies might suddenly find cause to restrain their models’ output, and we might hear less about rogue AI. We would need to introduce new frameworks and available tools for tracking automated lawbreaking, to be sure, but I’d wager that little would frighten the AI companies more than actually being held accountable for what their products enable. To that end, Illinois has passed an AI liability law, which the industry fought tooth and nail, and Florida is considering one. The next steps would be towards moving AI under public control; again, it’s only reasonable, since everyone, not just AI insiders, should get a say over how a technology whose developers say might kill us is developed and deployed. Dismantling the whole industrial project as currently structured should be on the table, too, pending democratic input. But that’s for another post. For now, suffice to say that while I won’t be losing any sleep about an AI-enabled extinction event, Mr. Coxon and co. have given us an opportunity to underscore the urgency of the clear and present damage AI companies are doing, the extreme power they wield and the extent to which they hold themselves unaccountable, and the abundance of political capital there is out there for taking them on. Subscribe 1 Purely speculative! I do not know if he did or not.
Experiment Tested Out-of-Body Experiences. Two Reported Seeing Things Scientists Can't Explain.
This is actually weird.
How AI is helping many small businesses hire, not fire
AI is often linked to job losses, but new research suggests it may actually help small businesses expand their workforces, Inc. reports. A Gusto survey of roughly 2,000 small businesses finds that 64% are experimenting with AI, and nearly two-thirds of those businesses say the technology is making it easier to launch or operate their […]
Mystery Science Redux at the Majestic This Weekend
The noble art of cracking wise at bad movies is one of the last of our culture's great oral traditions to be co-opted by professionals. But co-opted it was, in the late ’80s, by Mystery Science Theatre 3000, which at its best was humblingly brilliant TV.
Wilmington health tech founder launches new venture
Several years after launching his health tech startup Artemis Immersive, founder Adam Isley is setting his sights on new horizons. Co-founded in 2023 by husband-and-wife Adam Isley and Kaylan Barbrey, along with Matthew Raffa and Bill Blakesley, Artemis Immersive began as a spatial medtech company that created digital renderings of medical scans for viewing in augmented reality (AR). Isley said the firm, which won an NC Tech award in the Biotech + HealthTech Innovation category last year, has raised $1.2 million in total in seed funding since launching. Isley has since created a new venture, Research and Me, building on the Artemis platform. Like Artemis Immersive’s core software, VoxScan, Research and Me combines health data with artificial intelligence in a 3D interactive environment to help patients better understand health outcomes and provide integrative wellness support. While the Artemis product is no longer Isley’s primary focus, he said the company’s technology and ambitions have evolved into different ventures, like Research and Me. "It's a different venture building on the Artemis platform, and there'll probably be more,” Isley said. He added, "I was very disappointed in the quality of the information available to general patients about their healthcare... I wanted to give patients more and a better plate of choices." Research and Me is still in its beta phase, Isley said, with usability testing ongoing in partnership with the firm’s partner, Medicap Pharmacy and Wellness Center, owned by Barbrey. "As someone who's kind of dedicated their life to working in healthcare, I've tried to bring this spirit and passion to it,” he said, “and a lot of the resources that we'll be providing are free — like a base level of free care for any patients, or medical education if they've got specific conditions." Isley describes Research and Me as a “patient-first” platform designed to securely store and pseudonymize health data and use AI and medical literature to generate insights. The insights are presented in an interactive 3D environment for patients and providers to explore conditions, treatments and wellness plans together. "It's almost like a democratization of understanding medical information," Isley said. "We take a whole bunch of clinical data, we take a whole bunch of peer‑reviewed, published studies on PubMed, and we try to turn them into chunks of information that normal humans can understand." Like VoxScan, the Research and Me platform lets users interact with 3D anatomical models for visualization. The platform provides a space for tracking, notes and insights. The platform also supports video conferencing, Isley said, allowing providers or coaches to examine models and data together. "We wanted to create a safe environment where you can start to learn and experiment with new features about your health, using agents to do that,” Isley said. While Research and Me is in beta-phase testing with Medicap Pharmacy, Isley said he envisions the platform serving a wellness-oriented community, working with sports performance clinics and hormone optimization. Isley, who is working towards a wellness-coach board certification, also plans to offer functional wellness consults through the platform. Long‑term, Isley says he wants the platform to embody an “integrative health practitioner” approach, “connecting experts of different fields and specializations in a way that they can make a greater impact in people's lives.” “For people in the state of North Carolina, it's already a win,” Isley said of the Medicap rollout, noting that partner clinics get “immediate resources for learning about their health and wellness conditions… out of the box.” Isley plans to launch Research and Me’s provider portal in 2028 and begin pursuing integrations with larger systems, he said.
Awards for mad scientists
The Ig Nobel Prizes were handed out last week for silly, absurd, outlandish science experiments. Or, as Robert F. Kennedy Jr. calls it, science.
Why Science and Education Videos Are Thriving on YouTube
From deep-dive science explainers to optimistic experiments, creators are proving there’s an audience for STEM content beyond the classroom
Humans experimented with drugs 23,000 years earlier than we thought
Betel nut use among hunter-gatherers may turn back the clock.
Viewpoint: Unlocking Europe’s wildfire data
Europe is already investing in the science, technology and infrastructure needed to understand, prevent and fight wildfires. Copernicus provides satellite-based Earth observation and environmental information, while the European Forest Fire Information System provides information on fire danger and forest fires across Europe. Weather and climate systems add forecasts of heat, drought, wind and humidity; historical fire databases show where fires have occurred; and researchers generate increasingly detailed knowledge about fuels, fire behaviour, forecasting, modelling and risk management. Meanwhile, new European research projects are adding digital twins and other tools to this growing ecosystem.However, these data do not necessarily sit together, nor are they necessarily described, structured or governed in ways that allow them to be used together. Much of the information is public, but some is commercially held. Some is sensitive. Some is subject to legal, security or operational restrictions. Even when data can be legally accessed, different systems may use different formats, terminology and rules.Europe therefore faces an unusual paradox: we have vast amounts of relevant information to respond to the wildfire challenge, but not the means to bring it together. For example, a wildfire researcher or emergency service might need to ask whether a particular combination of vegetation, drought, wind and topography has historically been associated with rapid fire spread. The relevant information may exist in several institutions, using different systems and subject to different conditions of access.The challenge is to conduct an authorised analysis that interacts with these sources, combines the results and respects the rules imposed by each data custodian.An important part of the answer can be found in the Fair principles, the idea that data should be findable, accessible, interoperable and reusable. Developed more than a decade ago, these principles have become a central reference point for modern data stewardship, making it easier for people and machines to find data, understand what it means and determine whether it can be reused.Readability by machines is essential, since AI systems will be key to meeting the data challenge. Bring analysis to the dataThe proposition is not to give an AI system unrestricted access to sensitive databases. Quite the opposite. The goal is to make it possible for approved algorithms to go to the data, rather than requiring sensitive data or large datasets to be copied to wherever the analysis happens.Imagine an analysis asking a series of questions of different data stations. At one station it might examine weather and climate data; at another, historical fire records; at another, experimental measurements of fire behaviour. The algorithm does not need to download everything. It can operate within the environment permitted by each data custodian and return only the results that the rules allow to leave.This is sometimes described as data visiting, and related approaches already exist in areas such as federated analysis and federated learning.Sensitive data should therefore not be treated as a free-for-all for machines. This requires appropriate governance at multiple levels. Access needs to be authenticated and authorised. The purpose of an analysis should be defined. The code or model being run should be controlled. Data custodians should be able to specify what can be queried and what results can leave their environment. Activities should be auditable and human oversight should remain where the consequences require it.In other words, the objective is not to trust AI with the data. It is to design systems in which AI never has more access than it needs.As open as possible, as closed as necessaryFair data should also not be confused with open data. Some wildfire data should be openly available. Other information may legitimately need to remain restricted because it concerns critical infrastructure, security, commercial interests, privacy or operational capabilities. The principle should be: as open as possible, as closed as necessary.The important point is that restricted data should not automatically become unusable data. If machines can discover what information exists, understand its meaning, establish where it came from and determine the conditions under which it can be used, authorised analyses can potentially be carried out without the underlying data ever leaving the environment in which it is protected.Restricted data can still be Fair and machine-actionable.This is also an important question of data sovereignty. European institutions should not have to surrender control of their data to a handful of technology platforms in order to benefit from AI. Nor does Europe need to start again by building one giant repository for every piece of wildfire information. The better approach is to connect what already exists.This is the principle behind emerging approaches such as Tryangle, developed through the Leiden Initiative for Fair and Equitable Science. Rather than creating another centralised data warehouse, the approach seeks to provide an interoperable layer through which approved algorithms can visit distributed data sources while respecting the rules of their custodians.In this way, a data station can remain where it is. Its custodians can retain control. Existing databases and applications do not have to be abandoned. What changes is their ability to communicate with other systems through common, machine-readable descriptions, access rules and interoperability mechanisms.But approaches like this need data that meets the Fair principles. Only then can an interoperable ecosystem safely begin to turn fragmented information into collective intelligence.Data infrastructure is wildfire infrastructureThe implications of this approach are entirely practical. Firefighters could gain better intelligence about local and evolving risks. Land managers could test prevention strategies using more comprehensive information about fuels, weather and past fires. Researchers could compare evidence across ecosystems without repeatedly moving huge datasets between institutions. Smaller regions and resource-constrained teams could access analytical capabilities without having to build large data infrastructures themselves.Europe is already investing heavily in satellites, databases, research programmes, forecasting systems and scientific expertise. The question is whether we will connect those investments well enough to turn them into actionable intelligence.That requires policymakers and funders to treat data infrastructure as seriously as physical infrastructure. Data generated or supported through European public funding should be Fair, verifiable and machine actionable by design, wherever legally and ethically possible.Related articlesData Corner: Europe’s burning need for wildfire mitigation researchClimate monitoring must remain a global enterprise, experts sayIn practice, that means funding not only the production of data, but also the infrastructure that makes data usable across systems: metadata, provenance, interoperability, access mechanisms and governance. Where data must remain restricted, we should ensure that it can still be securely discovered, verified and used for authorised analysis.Initiatives such as the European Open Science Cloud offer an existing framework through which these principles can be put into practice. What is needed now is to accelerate implementation and make them a standard part of how Europe funds and builds research and innovation systems.We do not need another generation of disconnected databases. The data is already there. The opportunity is to make it work together, securely, responsibly and quickly enough to help prevent the next fire, rather than simply document the last one.Jean-Claude Burgelman is professor emeritus at the Free University of Brussels (VUB) and editor-in-chief at Frontiers Policy Lab. For more than 20 years he held leading roles in research and innovation policy at the European Commission.
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