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Bruins’ Scoring Depth Reveals Remarkable Early-Season Stat
The Boston Bruins have one of the NHL’s most explosive scoring units. They showed off their scoring prowess again on Thursday night.Boston blew out the Pittsburgh Penguins 6-2. But the bigger story was their scoring outburst. The Bruins had five different players score against Pittsburgh — Pavel Zacha (two goals), Mark Kastelic, Elias Lindholm, Morgan […] The post Bruins’ Scoring Depth Reveals Remarkable Early-Season Stat appeared first on HEAVY.
Luka Doncic's remarkable scoring streak gives Lakers a new challenge
Luka Doncic has scored at least 40 points in three straight games, but another extraordinary statistical streak makes his recent Lakers performances even more impressive.
Oregon was once a Republican stronghold. This politician started shifting the balance in 1954
For much of the first half of the 20th century, Oregon was effectively a one-party Republican state. Democrats had not won a U.S. Senate seat in 40 years, had not won a U.S. House seat in 18 years, and had controlled the state legislature for only four of 74 years since 1880. Into this landscape emerged Richard Neuberger, a Portland-born journalist of Jewish heritage whose prolific writing career, progressive convictions and remarkable personal drive would reshape Oregon politics.
Scientists discover that a clogged filter could revolutionize oil refining
Scientists have developed a remarkable new membrane that separates crude oil at room temperature, using the oil itself to create microscopic filtration channels. The breakthrough could cut refining energy consumption by nearly 32%, carbon emissions by almost 38%, and operating costs by 36%, potentially transforming one of the world's most energy-intensive industries.
When papers become currency: a Chinese debate about trust in science
Last Saturday, 31 October, I went to the University of Hong Kong’s Beijing Centre for its Talent Forum. It was the fourth stop in the series this year, following events in Shanghai’s Zhangjiang, Shenzhen’s Qianhai, and on HKU’s main campus. The programme covered a remarkable distance in one afternoon. HKU’s Xiao-Jing Wang discussed computational neuroscience, intelligence, and the prefrontal cortex—before even delivering his inaugural public lecture to students back in Hong Kong. His colleague Bing Zhang took us from the Big Bang to artificial intelligence. Tsinghua’s Xue Lan asked how AI might reshape the institutional infrastructure underpinning higher education. There were lively panels featuring industry leaders from JD.com, Xiaomi, Haier—and Kaiser Y Kuo on the closing panel discussing innovation and international connections. I cannot pretend to have followed every detail of the brain models or the astrophysics. The talk that stayed with me was closer to something we have covered before: Zhou Zhonghe 周忠和 on papers, evaluation, and scientific trust. Zhou is a palaeontologist, an Academician of the Chinese Academy of Sciences, and an international member of the US National Academy of Sciences. He is also editor-in-chief of The Intellectual (知识分子), China’s leading science commentary platform. His subject was uncomfortable enough for a room full of successful academics: what happens when the system for recognising good science starts rewarding something else? Part of my interest came from our sister newsletter, The East is Read, which covered the controversy around “Geng Tongxue” in May. A PhD dropout from Beihang University, Geng has publicly challenged papers by prominent researchers through detailed online allegations of manipulated images and fabricated data. At Tongji University, an investigation into a challenged Nature paper found academic misconduct, and the dean of its life sciences school was removed. The affair brought doubts about academic integrity well beyond laboratories and university committees. How could someone outside the established hierarchy spot problems in papers that had passed through prestigious journals and institutions? And what, exactly, had all that prestige guaranteed? Zhou approached these questions through two essays published in July by The Intellectual: one by Wang Xiaodong, director of the National Institute of Biological Sciences, Beijing, and a response by Wang Liming, of Shanghai’s Shangsi Institute of Natural Sciences. Both began with the controversy over Geng. Their arguments deserve a wider audience, so I want to put parts of them alongside what Zhou said on Saturday. Wang Xiaodong’s starting point is evolution. A research system selects for the behaviour it rewards. Grants, jobs, journals, talent programmes, and prizes collectively determine which scientists prosper and which practices get passed down from advisors to students. “Whatever the system rewards is what it will evolve to produce,” he writes, citing the ancient Chinese saying: The King of Chu loved slender waists, and many in the palace starved to death. That is a more demanding diagnosis than saying there are dishonest people in science. Punishing a fraudster does not change the selective environment that made a particular kind of research profitable. His account also gives scientific success an awkward role in the story. As Zhou put it on Saturday, science became a victim of its own success. Once research became central to industry, national power, and economic growth, universities and laboratories expanded, and public money followed. That created an administrative need for rapid decisions: who should get the next grant, the next laboratory, the next appointment? The difficulty is that the true value of a discovery may take years or decades of testing and building to become clear. Resource allocation cannot wait that long. Publication counts, journal prestige, impact factors, and citations therefore become convenient ways to make an instant judgement. “The real problem is not that these indicators have no value,” Wang Xiaodong writes, “but that they are trying to answer a question that only time can answer.” Telling administrators simply to stop counting papers will never be enough. They still have budgets to distribute and appointments to make. Something has to replace the shortcut. Zhou described the consequences inside publishing. Papers acquire ever more requirements: a complete story, polished presentation, extensive datasets, and accessibility to readers beyond the immediate field. Individually, those demands sound reasonable. Together, he warned, they produce formulaic “eight-legged” papers 八股文 and rigid reviewing, while genuinely original or non-consensus work struggles to get past journal editors—some of whom wield immense gatekeeping power despite having limited laboratory experience themselves. Meanwhile, the demands for sprawling, “complete” narratives have fuelled a wider replication crisis. Wang Xiaodong uses a mahjong metaphor to describe the result: put the complex papers published by the exact same lab over several years side by side, and they often look like “Thirteen Orphans” (十三不靠)—every tile completely unrelated to the next, and none of them reproducible by outsiders. Zhou also spoke frankly as an editor who has trouble finding reviewers. Everyone wants someone else to review their work; qualified senior researchers have little time to return the favour. The labour is anonymous, unpaid, and brings almost no institutional recognition, so it increasingly gets passed down to postdocs and graduate students. And while anonymity protects reviewers from rank and personal favours, hyper-specialisation means an author’s most qualified reviewer is often a direct competitor, shielded from accountability. The protection and the problem coexist. Wang Liming takes the argument a step further. The decisive change, in his essay, is the instant conversion of academic honour into material resources. Once a paper can be cashed in for funding, a job, students, commercial investment, or even a company valuation, scientists are alienated from their work: they must keep minting this “research currency” to keep their teams alive. He is careful not to romanticise the past. The old world of gentleman scientists—financially independent figures like Boyle and Darwin who needed nothing from external funders—was also a closed club that excluded people without inherited wealth, women, and much of humanity outside the West. Professional science allowed ordinary people, himself included, to become researchers. Nobody should want to undo that. The problem, in his account, is an exchange system that becomes too uniform and too difficult to correct. His most pointed Chinese example is the “hat” (帽子): the prestigious talent designation that brings continuing access to money, laboratory space, students, and institutional influence. “If papers are the circulating currency of the research system, then a ‘hat’ is a bond that pays interest over the long term,” he writes. A paper at least requires another round of peer review. A title in the Chinese context can lock in a judgement made years ago and turn it into permanent status rent, regardless of whether its holder is still doing good science. Here, official institutions hire, organise, and evaluate scientists. Unlike honours awarded by autonomous academic communities in the West, a Chinese “hat” blends non-scientist administrative power with state authority. Once granted, it turns a past judgement into permanent status rent that is nearly impossible to revoke—because taking a hat off would imply that official authority erred in putting it on. Both Wangs see China as experiencing, at compressed speed, pressures present across global science. Research expansion, rising investment, publication growth, and elaborate evaluation metrics arrived in China within two or three decades rather than two or three centuries. Zhou agreed with that international framing—noting that recent US White House science policy documents and the new president of the US National Academy of Sciences, a fellow palaeontologist who recently visited Zhou’s institute in Beijing, have raised strikingly similar warnings about consensus-bound peer review, short-term project grants, and the replication crisis. Still, Zhou emphasised that China’s traditional hierarchy, personal networks (guanxi), and the ethos that “a good scholar becomes an official” (学而优则仕) amplify those pressures at home. So what would change things? Here Zhou’s tone differed from the call for a revolution in scientific trust in Wang Xiaodong’s essay. As an evolutionary biologist, Zhou favoured patchwork repair (修修补补). Living systems survive through accumulated adjustments; dramatic mutations are usually fatal. Science cannot return to a small, slow-moving pastoral era, especially after the successive accelerations of professionalisation after the Second World War, the internet, and now artificial intelligence. But it can alter the local environment in which researchers work. He pointed to domestic experiments designed to support unconventional research and diversify funding, including Tencent’s New Cornerstone Investigator Program, the Xplorer Prize, and the Future Science Prize. He also mentioned participating in reviews for “major non-consensus projects” under the National Natural Science Foundation of China. One guiding principle he recalled was wonderfully direct: “Failure is allowed; corruption is not” (允许失败，不允许腐败). That distinction would mean quite a lot if taken seriously. An honest attempt that fails should not have to disguise itself as a success to survive an assessment. Wang Liming’s essay adds a sharp caveat to the optimism about new domestic funders. Multiple organisations do not automatically produce multiple ways of judging science. If the same pool of senior domestic scientists makes the decisions through the same two-round review procedures, it is still “fake diversity.” He argues for three distinct kinds of money: broad baseline funding governed by fair procedures; patient funding for questions that take ten years; and non-consensus funding based on individual taste, deliberately empowering a few genuine experts to make biased, contrarian bets on eccentric ideas that would inevitably be averaged out by a committee. Replacing one monopoly with another achieves little; a healthy ecosystem needs variance. Zhou’s proposals for publishing were similarly concrete: strip papers of their resource-allocation burden and return them to recording discoveries and establishing priority; separate dissemination from evaluation, as eLife and Peer Community In do; adopt more modular “micro-publications” and real-name endorsements; recognize the labour of editors and reviewers; and give replication work proper credit rather than treating it as an unpublishable dead end. AI makes every part of this debate more urgent—and Zhou wove it throughout his talk. In his own preparation, he used AI to survey the declining influence of academic monographs, noting how tools are already changing how scholars gather information. More fundamentally, he placed AI as the latest great acceleration in scientific history: just as the internet sped up the pace of research and tightened external resource pressures, AI is compressing the cycle again. In the essays Zhou cited, AI cuts both ways. Wang Xiaodong expects large language models to erase much of the English-writing disadvantage long faced by Chinese scientists, further swelling the flood of papers coming out of Chinese labs. Wang Liming sees AI accelerating both ends of the trust crisis: it lowers the cost of paper mills and fabricated images just as quickly as it lowers the cost of automated image forensics, data auditing, and code reproduction. “Whoever builds the verification layer wins,” Wang Liming writes. His proposed alternative to the static, packaged “story paper” is a continuously versioned “unit of discovery” containing a falsifiable claim, raw data, analysis code, experimental parameters, and an ongoing log of independent checks—where negative results and failed replications are recorded rather than buried. Zhou ended his keynote by bringing AI back to the question of scientific honour and credit. Citing a recent Intellectual discussion on “What AI Means for Mathematics” featuring Fields Medalist Deng Yu 邓煜—at a moment when AI is already batch-solving mathematical conjectures, as HKU Vice-President Lin Chen noted in his opening remarks—Zhou agreed that human researchers must remain the principal agents: AI is a tool that frees scientists from tedious calculation to think about deeper, messier real-world problems. Yet that partnership creates a thorny new evaluation problem. When a breakthrough is made with AI, what is the human contribution and what is the machine’s? And since AI models distil centuries of accumulated human scholarship, is it right that the credit and value flow so heavily to the private AI companies building the tools? The old struggle over how to assign scientific honour is acquiring a whole new layer. What I took away was a serious discussion of how science can remain trustworthy as its scale, incentives, and tools change. These were scientists with real standing inside China’s system questioning how that standing is produced, and proposing changes that would affect their own institutions and peers. That made the afternoon at HKU’s Beijing Centre worthwhile. At the close, Wang Feng, Director of Communications and Public Affairs at HKU, said the value of the forum series—which heads to Hangzhou in December and cities like Chengdu early next year—would lie in the real cooperation it helped bring about. The university has plenty to celebrate: this week it topped the QS Asia rankings for a second consecutive year, alongside its 11th-place position in the QS World University Rankings 2027. For me, bringing this debate to an audience beyond the people who review papers and allocate grants was a useful contribution. Share [ The East is Read PhD dropout’s exposé forces an academic fraud reckoning in China A former doctoral student turned blogger has shaken China’s academic establishment by publicly accusing prominent university scholars of fabricating data and manipulating papers, triggering investigations at several leading institutions and drawing rare attention from state media… Read more 5 months ago · 43 likes · 8 comments · Yuxuan JIA ](https://www.eastisread.com/p/phd-dropouts-expose-forces-an-academic?utm_source=substack&utm_campaign=post_embed&utm_medium=web&embedding_publication_id=47580)
‘This is a pretty remarkable time,’ Maryland Gov. Wes Moore says on historic governor elections
Business Aviation Pilot Shares His Inspiring Journey From Line Tech to Learjet Captain
Read the remarkable story of a teen who quickly moved from a job fueling aircraft to a Learjet captain, thanks to hard work, determination and professional relationships.
WNMU Graduate Fuses Science and Art to Inspire Next-Generation Conservationists
As Western New Mexico University prepares to celebrate its graduating students at Fall 2026 commencement, the university is spotlighting their remarkable…
National Navy SEAL Museum honors courage and commitment
Just north of Palm Beach County, along Florida’s scenic Treasure Coast, the National Navy SEAL Museum brings to life the remarkable stories of courage, sacrifice and service that have shaped
SLAC scientists find conclusive proof of a mysterious third type of magnetism
For nearly 90 years, scientists believed magnetism fell into just two categories, but researchers have now confirmed a remarkable third type called altermagnetism. Using specialized X-rays, they uncovered a unique magnetic signature that proves these materials behave differently from conventional magnets. Altermagnets combine stability with the ability to efficiently carry information, potentially overcoming major limitations in today's electronics. The discovery could lead to faster computers, more efficient data centers, and breakthroughs in quantum technology.
Funny propofol stories! (And a little science too)
Propofol is a remarkable anesthetic. One minute you're counting backward from 100; the next, you're waking up wondering why the nurses are laughing their asses off. Somewhere along the way, your brain apparently goes completely nuts, taking with it whatever remains of your dignity. Hilarity ensues. Profanity too.
Shohei Ohtani Extends Remarkable MVP Streak Despite Injury-Plagued Season
Dodgers superstar Shohei Ohtani was an MVP finalist once again, marking yet another milestone of greatness for the Japanese import.
UCT researchers name 400 000-year-old fossilised termite nests after Little Karoo town
University of Cape Town (UCT) researchers recently named a series of approximately 400 000-year-old fossilised underground nests of an extinct termite species after Calitzdorp, the Little Karoo town near which they were found. In October 2026, the research team returned to the town to donate a poster documenting their discovery to the Calitzdorp Museum, helping to connect local communities with the region’s remarkable fossil heritage.
Democrat Haley Stevens endorses GOP's Mike Rogers in Michigan Senate race 2 days before election
The remarkable show of support for President Donald Trump's backed candidate in the tightly contested race comes after she was uninvited to a joint event the same day with El-Sayed, who defeated the congresswoman by a slim margin in the August primary.
Cameron Boozer's Breakout Should Quiet Early Efficiency Concerns
Cameron Boozer scored 27 points efficiently against Sacramento, showing why early shooting concerns shouldn't overshadow his remarkable rookie start.
Jane Leeves recalls how David Hyde Pierce rallied “Frasier” team after losing series co-creator David Angell on 9/11
Leeves remembered David Angell, who died alongside his wife in the Twin Towers attacks, as a “remarkable man” who “quietly went about the business of bettering so many lives.”
Michelangelo Rampulla urges Juventus to stick with Spalletti
Juventus have had at least five permanent managers since the start of 2020, a remarkable record for a club of their stature. The frequent changes highlight the instability that has affected the Bianco...
Winston Ewart: A remarkable journey
When the National Chorale of Jamaica (NCOJ) opens its classical season with Songs of Faith & Freedom today, Winston Ewart will be among those in the audience at the University Chapel in Mona, St Andrew. Rather than standing in the spotlight enthusiastically directing the chorale, the ensemble’s founding member will be taking in the performance from his seat.
A mysterious 4,000-year-old wall is rewriting North Africa’s history
A remarkable 4,000-year-old defensive structure discovered in Morocco is rewriting what scientists thought they knew about ancient North African civilizations. The massive fortifications reveal unexpectedly sophisticated prehistoric societies and suggest that the region played a much greater role in Mediterranean history than previously recognized.
Netanyahu survived Israel's election - but a political reckoning may only be beginning
POLITICAL AFFAIRS: Netanyahu's political survival is remarkable. But the election has also revealed a weakened bloc, the beginnings of change, and serious failures by the pollsters.
Science Begins With Wonder and Sometimes With a Salamander.
The Bar Harbor Story is generously sponsored by the Don & Beth Straus Center at Birch Bay Village. BAR HARBOR—The children had come to see the axolotls, those odd little salamanders with pink frills around their heads and the remarkable ability to grow back what they lose. But also there were stickers. There were crafts. There was the kind of excitement that makes a roomful of kindergarteners forget, for a little while, that sitting still is ever a requirement. And then there were the animals themselves, alive in their clear cases at the MDI Biological Laboratory, where 12 children from Pemetic Elementary School got to meet the creatures they had been learning about in class. “Do you love them?” their teacher, Carol Null, asked. The answer came back in a chorus. “I do!” “I do!” “I do too,” Null said, smiling. “I love them even more now.” That was the thing about a day at the lab. Science was no longer a picture in a book, or a word on a classroom wall. It had a face, a tail, and a set of extraordinary powers. And for a child, sometimes that is where wonder begins. Sometimes learning about science is about stickers. Sometimes it’s about bright pink feathers and getting super excited about that glow in the dark. Sometimes learning about science is joy—pure and simple joy. That’s how it was October 28 at the MDI Bio Lab as Miss Hannah (known in the lab as Dr. Hannah Lust, director of STEM, undergraduate and graduate Training), other scientists, graduate students, and MDI Bio Lab staff, hosted 12 students from Carol Null’s Pemetic Elementary School’s kindergarten class. The 2.5-hour program created by Dr. Lust focused on axolotls, a species of mole salamanders, a superhero in the animal world: a superhero with some scientific-study worthy superpowers. One of those superpowers come from the axolotls’ ability to regenerate body parts, including entire limbs. But also, they’re cute. This fall, before coming to the internationally renowned lab nestled in Salsbury Cove, Null has been integrating axolotls into her class. They’ve been part of the kids’ vocabulary and their storytelling. They’ve been part of science. They’ve been part of the children’s learning about facts vs opinions. The Pemetic Elementary kindergarten students learn about invasive species and the impact on the ecology and one student related it to their dad, who lobsters, and his worries about green craps, an invasive species in Maine. “Are they bigger or smaller than you thought they’d be?” the children are asked after the scientists show them multiple see-through cases of axolotls, lined up on a table that they’re told not to jiggle. “Bigger!” “I think they’re bigger.” “Smaller!” The bio lab opening its doors to the collaborations and to students and families is a norm, but this is the first program of this kind. It’s meant to encourage kindergarten students about axolotls. But when the students come to the bio lab something else happens too—something beyond Null’s child-focused teaching—the students see science—and the regenerating creatures in real life. They do crafts. They speak with them. They meet people who know all about them: scientists and educators who talk to the kids like they’re equals. That’s a superhero power, too. Null speaks about meeting the kids where they’re at in her classroom, letting their interest and hearts lead her in their learning. That requires recognition of interests, of individuality, of empathy. Some would argue that’s a super power, too, but it’s also in those 12 students as they listen to the storybook, encounter those live axolotls, and hear about how axolotls might help advance society’s understanding of human health. As Eddie Seckeler (comparative animal models, CORE facility manager), carefully puts the axolotls on a cart and rolls them away, some of the children stop what they’re doing to watch. “Bye axolotls.” “Bye!” “Bye!” The axolotls are not just images in a book, Hello, I’m an axolotl by Hayley and John Rocco; they are real and cool. MDI Biological Laboratory scientists Dr. Prayag Murawala and Dr. James Godwin who both feature in the Roccos’ book. The kindergarteners get to meet them in real life, off the page, in the world, doing science. They learn from them, laugh with them. “The visit is about more than meeting an unusual animal. By introducing children to scientists working in their own community, the experience helps make science tangible and accessible. Students can see that science is not just something they read about in books or learn about at school. It is something real people do every day by asking questions, making observations and working to understand how the world works,” explains MDI Biological Laboratory Director of Communications Rebecca Woods. While the students make axolotl-related crafts around tables, graduate students and staff help out. Ryan holds up his construction paper setting and axolotl to show Omar Maged, a graduate student. “Do you like it?” Ryan asks, eyes wide, turning from his axolotl to look up at Omar. Omar studies the construction paper for a moment, smiles and says definitively, each word important. “It is beautiful.” Null says that she’s so thankful for all the “amazing” community partners that her school and her students get to interact with as they learn and grow and live, but emphasized how the MDI Bio Lab goes out of its way to create something meaningful, something that allows her young students to build their own agency, to know that they can be impactful in their community, to show them how how things they learn about in text is connected to themselves and their community. Woods explains, “Axolotls have an extraordinary ability to regenerate, or regrow, certain body parts, including limbs. Scientists study these animals to understand how regeneration works and what their biology might teach us about tissue repair and healing in humans.” The children enter the space for “a memorable introduction to a big scientific question,” Woods said. “How can some animals regrow body parts? The encounter encourages children to look closely, wonder about what they see and begin to understand how scientists use observations and experiments to investigate questions.” “For the students, the visit is an opportunity to explore a fascinating animal and meet scientists in their own community,” Woods explains. “For MDI Biological Laboratory, it is a chance to share the excitement of research, nurture curiosity, and help young learners discover that science begins with asking questions.“ At the beginning of the school year, Pemetic kindergarteners didn’t know what the axolotl was—at least not exactly—now they know all about the axolotl’s life cycle. “It’s different than a butterfly,” one student told Mrs. Null. It is. The change and knowledge might seem small**,** but it offers a glimpse of what happens when a subject moves beyond the pages of a book and into a child’s world. The children have been learning about butterflies at the Charlotte Rhoades Park and Butterfly Garden. At both the garden and the MDI Bio Lab, the children see the animals, meet the scientists who study them and at the lab encounter a question that researchers are still working to answer: how can some creatures regenerate body parts, and what might that teach us about healing in humans? They leave with gift bags, paper-plate salamanders, new things to wonder about and a connection between the science they learn in school and the work happening in their own community. The axolotls may be remarkable for their ability to grow back what they have lost. For these young students, the day offers something different: a chance to discover how much there is to ask, observe, and imagine. When Null’s students had time to use chalk and draw whatever they want, in the beginning of the year, they drew rainbows. Now? They’re using that chalk and choosing to draw axolotls instead. About MDI Bio Laboratory For more than 125 years, MDI Bio Lab has been a center for training and research in comparative biology. In the last two decades its biomedical research has focused on aging, regeneration, and environmental toxins. The Laboratory houses 11 research groups staffed by an international team of world-class scientists and graduate students. It also leads a statewide network of colleges, universities and research institutions that collaborate to provide training, research experiences and financial support to help young Mainers play a bigger role in today’s biomedical revolution. Located on Maine’s rugged coast, the Laboratory’s 100+ acre campus houses research facilities, cottages and dorms that house visiting scientists and students. It is also home to MDI Bioscience, a subsidiary working to design innovative techniques to speed the drug discovery process. The Bar Harbor Story is generously sponsored by Rick Osann Art. LINKS TO LEARN MORE NIH INBRE MDI BIOLOGICAL LABORATORY Pemetic Elementary School Hello, I’m an Axolotl Photos: Carrie Jones/Bar Harbor Story HELP SUPPORT THE BAR HARBOR STORY When we started The Bar Harbor Story, we didn’t know if anyone would read it. But you showed up. You shared. You sent tips. Now—over 400,000 views every month later—it’s clear: people here care about their community and each other. We’ve kept everything free because news should never be out of reach, but every one of our stories takes time to write, and your support keeps The Bar Harbor Story going. If you value our work, please consider a paid subscription, a founding membership, or a sponsorship. It truly helps us cover one more meeting, tell one more story, shine one more light. Even $5 a month makes a difference. Click here to become a one-time supporter now. Thank you so much for being here. Founding member information can be found here. Have questions about sponsorships? Just send Shaun an email at sfarrar86@gmail.com, he’d love to hear from you. Subscribe Share Bar Harbor Story Share Leave a comment
The Wildlife Science Center: Annual Howl-O-Ween Event
The Wildlife Science Center in Stacy is home to Minnesota's largest wolfpack, and this remarkable non-profit is giving visitors a breathtaking up-close look at gray wolves, also known as timber wolves. The center recently rescued three orphaned cougar kittens and plans to introduce them to an adult female cougar named Nice Kitty, who will serve as their adoptive mom
ARKG: Revolutionary Science, Unremarkable Returns
The ARK Genomic Revolution ETF is rated a HOLD with MODERATE conviction, given high valuations and moderate expected returns. Read more here on ARKG.
A golden age of science is coming
It’s almost hard to remember, but just a few years ago, a lot of very smart people thought that science was in terminal decline. Respected researchers were writing papers with titles like “Are Ideas Getting Harder to Find?”, “Papers and patents are becoming less disruptive over time”, and “Slowed canonical progress in large fields of science”. In 1996, science writer John Horgan even published a book called The End Of Science: Facing The Limits Of Knowledge In The Twilight Of The Scientific Age. The fundamental idea was that the Universe only has so many insights to discover, and that we’ve picked the low-hanging fruit. It was the idea that Joseph-Louis Lagrange expressed when he said that “we cannot find more than once a system of the world to establish.” As the big ideas and the simple ideas get mined out, we’re forced to throw ever more brains at the mysteries of nature just to keep scientific progress going at a fraction of its old pace: It looked like science was hitting a wall. Then along came AI. It’s far too early to tell how much AI will eventually speed up the growth of total factor productivity. But already we can see signs of a speedup in science. Anthropic Founder Jack Clark assembled some of the hopeful data points in a recent lecture: [ Dror Poleg@drorpoleg "If you pick different parts of science, you see the same pattern show up: Progress is accelerating, and it has started to accelerate in the last two years." Jack Clark @jackclarkSF I’m speaking at the IMF in an hour about the singularity and why I believe it has begun and the choices we'll need to make. Watch live here: https://t.co/Hj9HzcXx5h 6:08 PM · Oct 18, 2026 · 21.2K Views 2 Replies · 10 Reposts · 123 Likes ](https://x.com/drorpoleg/status/2111882070376980529) Anthropic is accelerating its investment into drug discovery, and is already announcing some impressive preliminary results: [ BioTender@Junioryu136689 BREAKING: Anthropic unveils early results from six Claude-powered drug development collaborations. • 70% shorter CAR-T signaling domain • ~35,000 antibody designs • >10× tighter antibody binding • 89% less batch-record review time Still largely preclinical. Anthropic @AnthropicAI Over the past few months, Anthropic scientists have engaged in deep research partnerships with six organizations developing new medicines. We've also begun drug discovery efforts of our own. In doing so, we’ve learned much more about how Claude can support the many stages of 9:43 PM · Oct 27, 2026 · 11.2K Views 3 Replies · 24 Reposts · 205 Likes ](https://x.com/Junioryu136689/status/2115197821150495150) Claude also appears to be enabling rapid progress toward a treatment for food allergies. OpenAI, meanwhile, announced a possible breakthrough treatment for neurodegenerative disease. Meanwhile, Google Cloud Chief Scientist Pushmeet Kohli has a list of recent scientific advances that have been enabled by its new Gemini model, including breakthroughs in nuclear fusion reactor design, rare disease research, and quantum computing: [ Pushmeet Kohli@pushmeet Gemini 4 Argon is a step change in model performance. In recent weeks, it has had a transformative impact on the Science projects in our team at @GoogleDeepMind and our external collaborators, and helped make a number of remarkable advances across scientific disciplines. 🧵👇 4:47 PM · Oct 13, 2026 · 36.5K Views 8 Replies · 41 Reposts · 497 Likes ](https://x.com/pushmeet/status/2110049807385702623) But as cool as these stories sound, they’re just very minor, preliminary efforts. There are a number of reasons to think that AI is going to propel us into a golden age of scientific discovery. That age might not last forever — AI might still run into diminishing returns eventually. But the next few decades are probably going to be an absolutely amazing time for human science. The number of “effective researchers” is no longer limited The most important input into science is scientists themselves. Until this year, that meant human brains — talented, highly trained human brains. The number of trained human brains could be increased by sending more people to grad school, but only to a point — the smartest people tend to be sent into the hardest research fields first, and if you 10x the number of researchers, the average quality will go down. This constraint was already starting to bite, as Ekerdt and Wu argued in 2024: We argue that a substantial portion of the downward historical trend in U.S. research productivity is a composition effect resulting from self-selection in researcher ability and the dramatic expansion of the research sector…[W]e find that this composition effect has lowered average researcher ability by between 37% and 53%[.] And of course, low fertility was making the problem worse, because fewer children meant fewer people who were able to become future scientists. AI just blows up this constraint completely. If an AI agent can function as an autonomous researcher, there’s no constraint on the number of researchers in the world — you can just build more of them, by building more computer chips and data centers that enable the running of more AI agents. Whether or not massive hordes of agents can collaborate to solve individual problems much faster, increasing the number of agents allows them to tackle many different research questions in parallel. What’s more, these AI “researchers” can be trained incredibly quickly compared to human beings. A human scientist takes decades to train, and more years to reach the frontier of their research field by diligent reading and conversation. This is the “burden of knowledge”, and it’s commonly believed to be one reason ideas have been getting harder to find — by the time human scientists can get up to speed, they’re often so old that their ideas are no longer novel. AI just annihilates this constraint — it can assimilate the entire literature and reach the frontier of research extremely quickly, and it can also tell human scientists where the frontier lies without forcing them to discover that for themselves. It can also pivot to new research directions more easily than humans can. And there’s also a self-reinforcing economic cycle here. Because scientific advances enable higher GDP, they enable more resources to be invested into the creation of yet more electronic “scientists”. Now that doesn’t mean the amount of scientific research goes to infinity — there may still be some essential bottleneck task that human researchers are still needed to perform. There are some indications that AI’s progress on open-ended conceptual research tasks is slower than in other dimensions, and it may be that humans are still needed to provide some of this long-term conceptual thinking. I’d bet against this being true for much longer, but it might be true for a long time. Even in this most “pessimistic” case, though, the amount of effective capital that scientists can use to leverage their work just went up by a lot. AI eliminates the theory bottleneck Science proceeds by an iterative process of theory and experiment. The theory part of that cycle is typically short, but non-trivial — it took a couple of years after the blackbody radiation spectrum was observed for Max Planck to come up with the quantum hypothesis to explain it, and decades longer before quantum theory as we now know it was created. It took about a year for Watson and Crick to figure out the shape of DNA after the requisite data was gathered. AI will basically eliminate the theory bottleneck entirely — or at least shorten the turnaround time between experiment and theory by an order of magnitude. AI is an absolute beast at math. Recently, an OpenAI model solved some of the most important open problems in computer science, math, and theoretical physics, and no one even batted an eyebrow because that sort of triumph is becoming increasingly commonplace. One of those solutions was a proof that the Standard Model of Particle Physics could be mathematically well-defined — a problem that human theorists had so far been unable to tackle. Not all research relies equally on theory, but understanding novel experimental results almost always involves some important component of either mathematical or spatial reasoning. That part of the task has now been made much, much faster. And on top of that, science is now open to a greater number of humans who aren’t naturally good at theorizing. AI can read the whole literature Much of the work of human scientists involves reading and understanding endless amounts of papers and going to endless conferences and seminars. The purpose of that work is to understand the existing scientific literature. Understanding the literature allows scientists to do the following things: Come up with new ideas for hypotheses to test Avoid doing research that someone else has already done Synthesize approaches from different areas or fields AI can reduce this effort to almost zero. Consider this excerpt from OpenAI’s blog post about their new research into neurodegenerative disease: The team divided the analysis among thousands of AI agents powered by GPT‑Rosalind, an approach we call distributed biological reasoning. The agents examined a whole-brain CRISPR atlas…a dataset showing how gene disruptions affect different types of cells across the mouse brain. Each agent investigated a gene disruption, analyzed cellular responses, searched scientific literature, and proposed explanations for the results. Their reports were combined into a reasoning atlas linking genes, cellular effects, relevant publications, and possible biological mechanisms. The research team estimated that comparable human analysis and literature review, conducted one perturbation at a time, would take months to a year. The agents reproduced findings from human analyses while uncovering additional leads. Their assessments of novelty and scientific value also aligned with judgments from blinded human experts. These findings help prioritize further experiments needed to test the proposed biological mechanisms. Some of these insights point to new leads for understanding brain disease. [emphasis mine] This is one case in which parallel work by a large number of agents really does make a huge difference: [ Haider.@haider1 this is actually insane openai deployed thousands of GPT-Rosalind agents to analyze millions of mouse brain cells in 32 minutes, work that could take human researchers months to a year also the agents uncovered new leads for brain diseases like Alzheimer's and Parkinson's OpenAI @OpenAI GPT-Rosalind surfaced a new lead for drug discovery: could restoring cholesterol transport protect neurons from degeneration? DCTN1 is a gene linked to Perry syndrome, a rare neurodegenerative disorder. In mouse-brain data, disrupting it increased expression of genes involved in 2:41 PM · Oct 21, 2026 · 51.5K Views 26 Replies · 95 Reposts · 1.26K Likes ](https://x.com/haider1/status/2112917197903540516) Not only does instantaneous literature review vastly speed up the research process, but it allows AI to make novel conceptual leaps from combining approaches from wildly different fields of research. AI regularly does this in math research, combining results, approaches, and theorems from far-flung places that no human mathematician would have thought to combine. It can do it in science, too. Much of scientific innovation, historically, has been “recombinant” innovation — scientists applying insights from one field to another. With AI, essentially all research is now cross-disciplinary — AI can read not just the literature on a particular subject, but the literature on a million other subjects that might have produced useful techniques or insights for the problem at hand. Superscience So far, all of the factors I’ve listed are ways that AI can speed up science as it’s already done. I’ve basically described how AI can send gigantic hordes of superhumanly fast, superhumanly well-read, superhumanly mathematically gifted researchers to re-accelerate scientific discovery. But it’s also possible that AI will enable types of discovery — and ways of understanding the natural world — that no network of humans, no matter how large or how brilliant it was or how long it had to work, would ever be able to discover. In a post back in July, I wrote about how that might work: What if there are lots of…aspects of the Universe that [are] too complex to understand in terms of simple laws, but not so complex that they just dissolve into unknowable chaos? It’s possible that we can reliably control these complex phenomena with AI, even if we never reduce them to the kind of principles that we can teach a grad student in a textbook… Another way of saying this is that there may be laws of the universe that humans can’t understand but AI can. I call these “cloud laws” — causal regularities that can be exploited by technology, but which are too diffuse and complex for an individual human being to either intuit or communicate… Perhaps social sciences like economics, sociology, and political science obey similarly complex regularities, and AI can help us find them. Perhaps there are physical processes — plasma, or topological materials, or aerial turbulence, etc. — that obey cloud laws instead of chaos?… [H]uman collaboration is bottlenecked — it’s limited by our ability to intuit patterns at an individual level, and to communicate these patterns from one individual to another. AI, being a computer, just doesn’t have this sort of limitation; it can work with vast, diffuse patterns without having to break them into pieces or simplify them in order to compress them into the tiny pipelines of person-to-person explanation… If much of the Universe turns out to be ruled by cloud laws, we could be on the precipice of a scientific renaissance. In order to discover cloud laws, AI will need huge amounts of data about the natural world. AI figured out human speech by assimilating essentially all of the text humans have ever written. If it’s going to figure out hidden patterns in biology, neuroscience, materials science, etc., it’s going to need similarly massive amounts of data from physical instruments. That data will be far, far more than humans — individually or collectively — would be able to parse, label, characterize, or model. But AI was built to do this. If scientists simply build huge arrays of sensors to measure complex phenomena like the brain, the cell, the economy, etc., they may be able to feed this flood of data to AI directly and bypass human cognitive intermediation entirely. AI would then learn about the world directly, and it might learn things that humans never could. This “superscience”, if you want to call it that, would actually go beyond the kind of science humans have done heretofore. Many of the technologies it yielded would be beyond human comprehension — indistinguishable from magic. But to the AIs, they would make perfect scientific sense. In any case, it seems clear that the scientific slowdown that threatened human progress will now be delayed — at least for a while. Unless humans have somehow found most of the actual exploitable regularities in our Universe, we’re about to enter a new golden age of science. Subscribe Share
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Sundar Pichai: Google’s Frontier Imperative, Compute Scarcity Dilemmas, Future AI Products and Businesses
Alphabet CEO Sundar Pichai has little patience for doubts about Google’s willingness or capacity to compete at the frontier of AI. His company’s latest Gemini 4 Argon model — long-promised and recently delivered — beats OpenAI and Anthropic’s latest public models on coding, math, science, and knowledge-work benchmarks and has placed Google’s AI back among the world’s best. Amid chatter that Google was fine with good-enough lightweight ‘Flash’ models, Pichai pushed back hard against any suggestion that company is limiting its research ambitions. “We won’t do it any other way,” he told me in a Big Technology Podcast interview recorded this week at Google’s Mountain View headquarters. Pursuing cutting-edge research is costly for Google, requiring compute and chips that otherwise could be sold at a high markup by its cloud business. But Pichai said allocating resources to frontier AI development is “ground zero” for Google. “Our cloud business is at any given moment in time forgoing short-term revenues because we are making compute trade-offs to support frontier AI development,” Pichai told me. In our conversation, we discussed Argon (which Pichai says processed three times as many tokens as Gemini 3 in the 72 hours after launch), AI’s role in developing better models, the AI interface of the future, competition with OpenAI, Google’s partnerships with Anthropic and Apple, data centers in space, and the nature of his optimism. You can read the full conversation, lightly edited for length and clarity, below, or listen to it on Apple Podcasts, Spotify, YouTube, or your podcast app of choice. Alex Kantrowitz: Google is back at the frontier with Gemini 4 Argon, which beats OpenAI’s and Anthropic’s public models on benchmarks spanning coding, math, science, and knowledge work. The conventional wisdom was that Google had given up on the frontier to focus on fast, good-enough models for its products. That was wrong? Sundar Pichai: Very wrong. Look, we are so committed to being at the frontier. It’s in our DNA. We won’t do it any other way. We’ve been thinking about the AI frontier for well over a decade now. The frontier is very dynamic. It’s very competitive. It’s very exciting. I couldn’t be more pleased with how Argon has come together. We took our time with it. We made sure we tested it safely and deployed it carefully. We took a bit longer than our other models, given its capabilities. Across the board, be it for agentic work, knowledge work, coding, creative tasks, Argon is one of the really good frontier models. The first 72 hours since we launched, it’s almost up to 25 trillion tokens used, which is about three times what Gemini 3.0 had in the first 72 hours. And we are capacity constrained as we are serving it. Excited, but there are always areas….. You know, the frontier is very dynamic, and you have to keep evolving the models. There are areas which we can see we need to improve as well. We’ll be at work on all of that as well. Which areas? On any given model, Argon would be across the board better at everything if you just look even two months back. But the space is so evolving. Even on coding, for example, there are pockets where we know we need to do better, and there’s clear feedback. We’ll make it better. The argument for standard models is that they’re already good enough to build great products, with the frontier valuable only for certain tasks. Meta built Muse with good models rather than the best, and Google could put standard models into Maps, Gmail, and Search. Why isn’t that sufficient? It’s definitely not how I have thought about it at all. We are deeply committed to driving the state of the art and actually pushing where this technology can go, all the way from transformers. That’s a journey we’ve been on. You will see us continue to do that. When you’re at the frontier, you get an earlier look into the emerging capabilities, earlier than others, which helps you better prepare for the future. We are fortunate to have a wide set of opportunities across consumer and enterprise. Some of our cloud customers, for sure, want the model at the frontier. The frontier models will be better at developing the next set of models in an era of recursive self-improvement. I would argue it matters there. Internally, we have definitely seen a steep point of inflection by deploying Argon to our developers. It definitely tackles problems which our previous models could not do. Being at the frontier puts you at the innovation frontier and helps you drive that as well. There is room for models of all sizes and capabilities. That’s why we did Flash, Flash-Lite, etc. I agree with you that you can develop very good product experiences with not necessarily the most frontier model, because they tend to be slower and more expensive too. But we care about the Pareto frontier, and we’re committed to doing all of that. You said developing frontier models gives you a look at what’s coming. What do you see on the horizon? What makes this moment so exciting is you build something which you think is a culmination of months of work, and you put it out. You already see clear headroom ahead. We’ve all been working on these agentic, long-horizon capabilities, but clearly the frontier is going to have multiple of these agents working together to do things. That’s an example of an exciting paradigm underway. It’s also clear to me that users, both in consumer and enterprise, will have access to some multi-agent framework for them, working all the time doing things. It feels like a moment of infinite possibilities. Sergey Brin said one of Argon’s core innovations was relying more on the model to help develop the model. Yet incidents involving OpenAI’s bots breaking containment and Google’s bots accessing a site they shouldn’t have suggest these systems still aren’t perfectly aligned. Isn’t there reasonable cause for concern about accelerating toward recursive self-improvement? There are three parts to your question. Let’s first talk about RSI itself. You’re right, Sergey mentioned RSI being a critical contributor as we are developing Argon. But to be very clear, today, in a continuum, we are pretty far from the end state of RSI or something like that. The right way to describe it is you have RSI loops along with AI researchers in various aspects of model development. You almost have agents helping AI researchers in some automated way work together to build these models. It’s good to at least understand where we are today, and it’s super exciting. I expect that continuum to keep making progress as we go into next year. The second question is around safety. Security comes from defense in depth. You’re talking about alignment, obviously. We all are doing a lot of work to make sure the models are as aligned as possible. But it’s an active area of research, and there are clear gaps. That’s not the only thing we rely on. You have the work you do on alignment, but beyond that, we put a lot of effort into real-time monitoring as these models are working. Making sure you have good telemetry into what’s happening so that you can intervene in real time if you see unexpected behaviors. How you do that, the architecture with which you do that, how you make sure it’s all sandboxed and isolated in a way that it can continue doing its job during real-time monitoring — these are all areas of investment. Obviously, when we deploy these models, giving customers, enterprises, control, both with real-time monitoring, but their ability to decide where they deploy, what type of data which models ever have access to, etc. All that work is very, very important, and we are doing a lot of that. As an industry, we need to constantly up our game and take the time to do all this stuff, including dedicating the compute required to make sure you can safely deploy these models. The third part is: Is it all enough? This is why there are a lot of conversations in the industry, and I think it’s reasonable to be worried. The right way to approach something you worry about is early on thinking about what more we can do. As an industry, you’re definitely seeing increased levels of work on alignment, testing for safety, etc., as we deploy these models. The next step would be developing better standards so there are cross-industry standards of how we do these things, including the ability to evaluate using independent evaluators. If you look at areas like financial controls, we have accounting standards, we have independent auditors. Those are all the next natural steps for us as an industry to work toward, and regulation will end up playing a role as we go through all of that as well. Google pursues both language models and world models, while some other AI companies like OpenAI have focused more heavily on LLMs as the path to AGI. Why is world-model research important to you? As humans, you obviously perceive the world around you, and you’re taking all those inputs. Making sure these models are able to understand the laws of physics, simulate the world in high fidelity. All that, I think, are key enabling blocks for intelligence. We are working across all possible applications of this. Take an area like robotics. It’s not an accident: If you look at embodied reasoning benchmarks, Argon is state of the art. That all comes from our experience building world models. Inherently, I would expect there will be architectures which will converge all of this in the future. But for us, we view this as, today, this jagged frontier that is intelligence. We want to be at the frontier of all the possible approaches, and that will help us both drive better research, better insights, and develop a much better AGI model, is how we think about it. Some people argue Google should focus on selling its computing resources rather than using them for AI research. Cloud wants to sell compute at a high markup, while researchers need a very big computer to build the best models. How do you balance those demands? Ground zero for us is making sure we are investing in the compute that’s needed to be at the AI frontier. In 2015, I set the company to be AI-first. AI is that key horizontal ingredient across everything we do, all the way from Search to Cloud to Waymo. That is ground zero for us, making sure both for research and developing the models that we have enough compute needed. Beyond that, we have these independent businesses which each have their own long-range plans. They’re using those long-range plans to project forward, and we plan for compute for all of them. The cloud team, they have a business and they have a projection and they have demand signals. They have committed contracts. With that help, we can plan on a long-term compute trajectory for them. We’re fortunate to have this wide set of opportunities. There’s no company in the world which isn’t making trade-offs at any given moment in time. But the first principles we operate on is making sure we have enough compute to invest in the frontier, and that’s non-negotiable, and everything else works on top. Remember, we are building our own compute, our own data centers. There are long lead times. The compute we have today is a function of decisions I made in 2024. Even if you think back to a year from today, last year the agentic coding takeoff hadn’t happened. Today, obviously, when you sit and look at anything, everyone is short—not just us, other companies—and everyone wishes you had two times what you had planned for. That comes with the territory. At any given moment in time, we are planning for what we would need two to three years out in the future. You’re going to find some decisions you make may look suboptimal two years out, depending on where the state of the art is. I don’t spend too much time thinking about it. The way I think about compute allocation is making sure Google DeepMind, both for research and frontier model development, is cutting edge in terms of compute access. After that, we plan for all our businesses. It’s great we can provide our compute to other people too, like we have done. It allows us to scale that up, get real tests for it in the widest application set possible, test it in the real world, and make sure we are at the cutting edge of technology at every layer of our AI stack as well. Ben Horowitz relayed on a podcast that Andy Jassy had said compute was sold out until 2028. Are you seeing the same thing? If today a customer is coming out and asking us for compute in ’27, that is incredibly difficult to do. Even last year we went out and leased some short-term compute to accommodate some customers and help them out. But yes, we are all dealing with similar timelines. Every major technology shift seems to involve overbuilding, from railroads to fiber. Do you think that’s happening here? It depends on the time frames you’re looking at. This level of build, if I take a long enough time frame, it makes complete sense to me. We are at early stages of the most consequential technology ever, and this is not like fiber. It’s not dark. We are using it. We are capacity constrained on a daily basis. The applications, the underlying technology is improving rapidly. But running a company, the way I work through the moment is you look at your demand signals. You look at your committed revenue opportunities that you’re getting in the form of contracts. You balance that with the underlying technical capability, or internally you balance how we are using it internally, the model trajectories. Based on all that, you take a disciplined approach—a confident, aggressive, but disciplined approach—to plan out compute. But when you talk about the broader economy as a whole, you’re having people operate with various levels of risk. I focus on what I can control as a company and plan through it. If your question is, can there be an overbuild? Yes, because you can have some constrained components. Remember, what matters is a set of everything you need to build out that compute. Memory, electricity, electricians…. Land. Like 2,000 components or more. You could get constrained at some point. There could be things which cause bottlenecks, and then you could have overbuilds. There could be external shocks to the economy. There are macro risks. All that is possible at any given time. But am I confident that the compute we are planning for, we will have uses for it given enough time? Absolutely, yes. I was in the room when you said AI would be as profound as fire and electricity. If you believe that, shouldn’t you give researchers the biggest possible computer, even at the expense of today’s cloud profits? We’re all doing some form of that. Our cloud business is at any given moment in time forgoing short-term revenues because we are making compute trade-offs to support frontier AI development. What you’re seeing is true already. But you want to be thoughtful. Even our AI researchers have some constraints, which are also good. That’s what inspires creativity. That’s what helps you come up with a more efficient algorithmic breakthrough, maybe to use less memory. What we are committed to is to invest what’s needed to stay at the frontier. OpenAI President Greg Brockman told me a few months ago that the ideal AI product might have no interface at all—just as natural as conversation. What do you think the interface looks like in the age of AI? Computing historically has been humans adapting to computing. With AI, it’ll be the other way around. The technology will adapt seamlessly to how humans live and go about their day-to-day life. You want to be able to speak to that AI when you want to. It has context. It can be persistently running somewhere, give you continuity. You’re not dealing with a lot of complexity. It’s natural. All that makes sense to me. That doesn’t mean it won’t have any interface, however. Nowadays, even on my phone, Gemini voice models are so good. I can just press the microphone button. I can just ramble. That’s why we call it Rambler. I can ramble. It intelligently corrects with my personal context. Even my friends’ names, weird names, it gets it right, even if it first guesses it wrong. It’s amazing. I’m not going in, backspacing, editing once I finish saying it. It’s remarkable how good it’s gotten. But there are going to be moments you will need an interface. You may want to entertain yourself. You may want to watch a video. You may ask your AI to create something, and you want to watch it, consume it. The way I think about it is, you want it to be as seamless and as natural as possible, and that you are not doing the hard work adapting to whatever the interface is. The technology is adapting to how you’re working at any given moment in time. When I asked Sam Altman about competition from Google, he argued that OpenAI was building AI-native products and implied Google was bolting AI onto existing ones. Do you accept that framing, and can a “bolt-on” compete with an AI-native product? First of all, it’s a very dynamic moment. We are all pushing each other. OpenAI has pushed us as a company too. This is not just we are doing something to them. Far from it. Yes, Google went into its own version of a code red too. In the AI moment, all of us have to respond with varying levels of urgency at any given moment in time. We are constantly building new products as well. Gemini was built from the ground up as a product—the Gemini app I’m talking about. Or tomorrow, as all of us are adapting to agents, are you bolting agents onto ChatGPT, or are they building it natively? How would you think about that? You can always put these questions back. I don’t think of it that way. I think of it as you want to build world-class product experiences that are AI-native and they are winning. Some of it is adapting products, some of it is rethinking new experiences. They will all be part of how you approach this moment. How do you expect to make money from these AI interfaces? If an agent recommends a product and I buy it, should it take a cut of the sale, even if that’s disclosed? I’m going to put enterprise aside. Consumers are going to increasingly value this technology. Take software developers today. Developers are willing to pay for these coding models because it really helps make them more productive. Nobody would want to code the way they were coding three years ago, or even the same time last year. When you’re delivering value, there’s value to be had. I’ve never seen examples where consumer products really scale to billions of users, where people are using it intensely, and haven’t had monetization to go along with it. If you’re providing value to people, there is inherent value to be had. The nature of it may change. You’re asking a scenario in which agents are doing stuff for you. At the end of the day, you will have commercial needs. The agents need to fulfill those commercial needs. The providers on the other side are going to see value in that. There’s going to be some mechanism by which it gets fleshed out. That’s what an efficient system does. But what matters is that you’re building those world-class consumer experiences. I promised myself one product feature request: Can you make Gemini-powered search in Gmail as good as searching Gmail through ChatGPT? What’s going on here? One of the exciting things we announced recently is the unified Gemini agent for enterprise, and we’re bringing that to consumers. These are persistent agents which run 24/7 in the cloud. We’re spinning up a micro VM effectively for every query, and from the runtime, the harness, the model—it’s all a headless service. It’ll work everywhere, and it has your context with you. You can address this agent whether you’re in Workspace, in Search, in Gemini. Agents are going to drive this unification from a customer experience, which people are looking for. When you have a broad product portfolio and you’re moving forward fast, there are always areas where you’re moving forward faster than some other areas. That’s valid feedback. But we are putting a lot of time and effort into making sure, as we build out our agentic experience, that unification and that capability works well across all these services. People have asked where Google’s equivalent of Muse or Dots is. Do you anticipate creating a new product to compete with them? Our goal with Gemini is to be a personal, proactive, and powerful assistant. That’s what we are working toward. You saw us describe the early versions of it at Google I/O this year with Spark. Effectively, already, if you open the Gemini app as a Pro or an Ultra user, you see Chat and Task, and they start giving you that agentic experience. With Argon now, that capability is dramatically accelerated. What we announced recently in our enterprise event, we are bringing that to consumers as well. Soon in Gemini, you will be able to ask something, and it’s a continuum. You don’t need to think about whether you’re asking a chat or an agentic task. It’ll just automatically do the right thing, and it can work persistently in the background securely and get things done for you. Already, empirically, when I look at what’s coming into Gemini in our app, last year you would have tagged them and most of them would have been chats. But a steadily growing percentage is already agentic tasks in Gemini. Yes, we are going to bring personal agents to our consumers. It’ll work in the Gemini app. It’ll work in Google Search. It’ll work in Gmail. You can address it, call it, etc. We want to make sure we’re getting it right. It’ll be powered by Argon, and we are very excited to bring it to our users. Google has invested and committed tens of billions of dollars to Anthropic. What do you see in Dario Amodei that makes you want such a deep investment and partnership? Very early on, when we looked at the founding team of Anthropic, it was very clear to us this was a world-class team which was involved in some of the earliest GPT models. We were quickly able to assess that they would be at the frontier. We’ve always tried to identify and partner with companies which would be at the cutting edge of technology. We’ve done that with SpaceX. We’ve done that with Anthropic. That’s what we saw, and we had a chance to partner. Is your partnership with Apple to license Gemini for Siri expanding, contracting, or standing still? For both us and Apple, that partnership was about translating the capabilities of AI into better experiences for users. I thought Apple has done a phenomenal job of incorporating—they customize these models and build it into Siri—and it’s been great to see the reception. We are committed to doing more. You’re going to do more with them? There’s nothing specific to comment, but it’s a partnership. It’s working well. What have you learned so far about the feasibility of data centers in space? It’s a very exciting project. Projects like this remind me—I still recall that moment in the desert for the DARPA Grand Challenge, watching the Stanley car compete in it, which ended up being the basis for Waymo. With all these technologies, you’re at a moment in time where it looks a bit like sci-fi, but 10 to 20 years down the line, it’s actually working in a meaningful way. I feel the same in space. We’ve always believed in betting big on these technologies. Quantum has been a great example of it. We’re probably 10 years into the journey. Waymo, we are almost 20 years into the journey. Space, we are two to three years into the journey. It’s clear to me that it’s an approach which will make a lot of sense in the future. Being in sub-synchronous orbits with 24/7 access to the most abundant form of energy we have access to will make a lot of sense for this exponential increase in compute that we are going to need. Having said that, this is a challenging project. The team has disciplined milestones. It was a super exciting milestone to send the TPUs up to space. Sometime, as we are speaking, we are expecting a “hello world” moment from them. I look forward to seeing that happen, and we’ll continue investing here too. You previously said 25% of the code written within Google was written by AI. What’s the number today? That number in our world today is meaningless in the sense that every part of what we now touch is influenced by AI deeply. What we are tracking with Argon, for example, it’s been a point of inflection. People are using Argon to really go tackle complex projects, including projects which affect millions of lines of code. In the four weeks since we have launched Argon, we have seen a 30% increase in CLs, and more importantly, almost a similar increase—a one-third decrease in rollbacks. People are writing code more productively and better code with it. We are tracking it with newer metrics now. How are you dealing with opposition to data centers? If you can’t build in the U.S. the way you want to, where else do you go? We’re very committed to building our data centers very responsibly. When I look at our largest data centers in some of the communities where we have been the longest, I visit them, I talk to people. There are people who come and tell us their kids have gone to college because of our investments in these communities, and we’ve grown in those communities. To me, this is about doing it right. Engaging with the communities early, doing it transparently. We are committed to making sure we are bringing incremental power, and we cover 100% of the cost of our power needs for these projects. It’s understanding the impact on neighborhoods and making sure you’re working thoroughly to address them. Done rightly, you can continue making progress. But we are constantly taking feedback into account. I do worry not everyone operates the same way. People have been surprised by data centers showing up in their backyard. Those are all important. As an industry, we should continue to do better. But part of the reason, in a 20-year time frame, we are thinking about things like data centers in space is making sure we are able to put these data centers where maybe the trade-offs will be different. What unproven area of AI is Google working hardest to crack? Is it continual learning—getting models to keep updating after release—or something else? There are multiple parallel paths. You saw with Argon we have a million output tokens. With our Gemini models early on, we had a one-million context window on the input side. These are all examples of breakthroughs we are constantly working on. How do you think about synthetic data? How do you think about continual learning? How do you think about more efficient architectures? We do dedicate a meaningful percentage of our compute to these research bets too. It always goes hand in hand, including our world models. Those are all bets we are placing. Sometimes, as part of these bets, there are ideas that emerge which just make their way into the mainline models. Maybe we don’t fully talk about it, but we have multiple steps in these areas. Working in technology requires optimism that building something will improve the world, but those bets can leave real consequences when they fail. I recently returned to a town in El Salvador where enthusiasm for Bitcoin had given way to unfinished construction and something resembling a ghost town. How do you maintain the optimism you spoke about in your Stanford commencement address while accounting for those risks? I genuinely have a deep conviction that improving technology and improving access to technology makes people’s lives better. It’s been my personal experience in my life, out of which comes that deep conviction, optimism. But with that, I’ve always felt humanity’s journey is always about working hard to harness that technology to make it work well for society. The optimism is not an optimism that you just build whatever you want, whenever. You work hard to make sure you’re building technology in the service of humanity, to make the human condition better. That’s got to be the defining goal as we are approaching it. With that framework, I’m very, very optimistic. We are in very early stages of the kind of progress that we are going to see on many areas. We’re all talking about areas like healthcare. A lot of the progress is ahead. The ability to make things in a fundamentally cheaper way on many things where things have been getting expensive for a long, long time, discovering new materials, etc., which really bend the curve—it’s tough to step today and understand the impact of all that, but they’re going to be very profound. I’m very optimistic, but we have to be rightfully concerned about all the ways this technology can go wrong. Sundar, I know you don’t do many of these. Thank you. Thanks, Alex. Appreciate it.
Trump takes transactional politics to a new level at latest campaign rally
Trump effectively told Kansans he’s prepared to hurt the state on purpose if he dislikes an election result, which is every bit as remarkable as it sounds.
Trump takes transactional politics to a new level at latest campaign rally
Trump effectively told Kansans he’s prepared to hurt the state on purpose if he dislikes an election result, which is every bit as remarkable as it sounds.
'Office Space' star Richard Riehle dies at 78
Actor Richard Riehle arrives at the premiere of New Line Cinema's 'A Very Harold & Kumar 3D Christmas' at Grauman's Chinese Theatre on November 2, 2011 in Hollywood, California. (Jason Merritt/Getty Images)Richard Riehle, known for his role in the 1999 film Office Space, has died. He was 78.A statement shared by Artists & Representatives and Wright Entertainment, Inc. announced Riehle's passing on Monday, writing, "Our industry has lost an exceptional talent, and our community has lost a truly wonderful man.""We are deeply saddened to confirm the passing of our beloved client, Richard Riehle, this past weekend," the statement said. "A remarkable actor whose career in theater, film, and television spanned nearly five decades and more than 400 projects, Richard leaves behind an extraordinary legacy."The statement continued, "Beyond his immense talent, he will be remembered for his genuine goodness, boundless kindness, and unwavering generosity, particularly toward emerging actors and filmmakers, whom he encouraged and supported at every opportunity."Born on May 12, 1948, Riehle starred in many television series and films over the years.Notable projects include Casino, The Man from Earth and Deuce Bigalow: Male Gigolo.He got his start as an actor at the University of Notre Dame, where he was involved in the University Theatre and starred in several stage productions. He went on to earn a Master of Fine Arts in acting and directing from the University of Minnesota.While he's played characters that have an "average Joe" presence, he always made the most of his brief screen time.Some roles that he is remembered for include The Quartermaster in Glory, the train guard in The Fugitive, Reverend Scroggins in Fried Green Tomatoes and Bill Cozbi in Bridesmaids.On television, he starred as Principal Ed Rooney in the 1990 series Ferris Bueller and as grandfather Walt Finnerty in the early 2000s sitcom, Grounded For Life.In 2023, he also played Warden Reynolds in Barry.Riehle is survived by his wife, Jane Latham, and their four children.Copyright © 2026, ABC Audio. All rights reserved.
What Does a Human Heart Need to Grow? Scientists Found the Answer in a Bioprinted Model
Heart problems that babies are born with, called congenital heart defects, often begin developing early in pregnancy. Approximately three weeks after fertilization, the human heart is still a simple, straight tube of cells and, over the course of about five weeks, this tiny structure must undergo a remarkable transformation to reshape itself into the complex organ that eventually pumps blood throughout the body.
The remarkable bond between a man and a deer
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This bird flies thousands of miles, but its wings have a catch
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Scientists discover a plastic-eating “Pac-Man” enzyme with a surprising secret
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A quantum highway just one atom high could transform superconductors
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One win from World Series, these Milwaukee Brewers are simply 'remarkable'
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Stanford Scientists Find New Way to Revive Bleached Coral
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Cubs Lead National League With 5 Gold Gold Finalists
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NASA’s Chandra Breaks Down ‘Treble Clef’s’ Galaxy Cluster Collision
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Tales of Eternia Remastered Review
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Travis Kelce Is Doing Something Remarkable at 37 Years Old
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Matthew Lillard calls Neve Campbell a ‘remarkable final girl’ weeks after sharing regret over “Scream 7” return
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How worried should Catholics be about the pope’s health?
Pope Leo XIV announced on Sunday that he will undergo surgery this week to remove a “nodule” from his lung. The pope made the announcement at the end of his Sunday Angelus address, asking for prayers. “Dear all, recently, during some checkups, the doctors discovered a nodule in my lung. It was detected at a very early stage and was well-localized,” Leo said. “The doctors felt it was necessary to intervene, and so, following their advice, I decided to have surgery to remove it. The procedure is already scheduled for the next few days. I thank you for your spiritual support and I entrust myself to your prayers.” The Vatican press office subsequently added that Leo is scheduled to undergo surgery at the Gamelli hospital on Tuesday, Oct. 13. The pope is expected to spend up to a week in the Gamelli recovering, after which, for the moment, he is still expected to undertake his largest and longest to-date Apostolic journey, heading to Argentina, Uruguay, and Peru, beginning Nov. 6. Prayers have, understandably, poured in from dioceses around the world, accompanied by the best wishes of heads of state and international institutions. So how worried should Catholics be for the health of the pope? The Vatican’s messaging around Leo’s pending surgery is, in many ways, a new approach to papal health issues. But, despite the pope’s personal candour, the Holy See’s messaging perhaps raises as many questions as it answers. Subscribe — Leo’s decision to announce his own medical status and pending hospital stay during the Sunday Angelus is, it should be said, already something of a big deal. Traditionally, the health of popes simply hasn’t been discussed publicly or officially, until circumstances made it absolutely necessary. Memorably, in 2023 Pope Francis was rushed to the Gemelli in an ambulance, exhibiting signs of cardiac arrest according to many close to him, only for the Sala Stampa to put out a statement insisting he was merely going in for “pre-scheduled” tests. That Pope Leo has decided to announce his condition himself, with remarkable frankness, is a significant comms policy shift around the Apostolic Palace. This might reflect a deliberately more open posture, as opposed to the traditional, otiose evasiveness, and the first fruits of an American pope and American prefect of the Dicastery for Communications favoring honesty as a baseline. Equally, it must be allowed, it could be that the pope’s situation is serious enough that there would be no keeping it under wraps or playing it off, and the decision was made to be as open as possible to head off speculation about the papal health. Certainly, Leo appeared to make every effort to sound reassuring — stressing that, whatever the diagnosis is, exactly, it is “well-localized” and “early stage.” Of course, for everyone listening, talk of a “nodule” in a lung will immediately send thoughts — and prayers — running to concerns about words not used, like “cancer,” “tumor,” “begnin” or “malignant.” To be clear, none of those words may yet be medically appropriate. And there is every reason to believe and assume that Leo is giving almost as much information as he may have himself at this stage. But the context of the pope’s announcement and the timing of his surgery do reasonably raise reasonably serious concerns for Leo. We don’t know, and this isn’t to say anyone has the right to expect to know, when the routine medical checks made this discovery. It could have been last week, last month, or even earlier. As such, it isn’t really possible to say with what kind of urgency Leo is being brought in for surgery. However, there is clearly some serious urgency to the matter. Leo making the announcement and going into hospital this week, of all weeks, means he is having to miss the balance and conclusion of his global meeting of the heads of the world’s bishops conferences, which he convened in Rome this week. That, as the Vatican has announced, has meant some serious changes to the schedule, with the newly minted dean of the College of Cardinals, Cardinal Tagle, subbing in for the closing Mass on Wednesday, and the meeting’s organizers announcing that the final working document/summary of the meeting being delayed until Leo can read and feed into it. Those changes suggest that the timing of Leo’s surgery isn’t of his own choosing, and he is acting on the best medical advice he can get by moving urgently. Had this issue been discovered weeks ago, it seems reasonable to assume the pope would have seen it dealt with before the meeting began. And were it possible to delay it, even by a few days to allow the meeting to conclude as scheduled, the expectation would surely be he’d have opted for that. It cannot be excluded that Leo is simply having to fit in with the schedules of his medical team, but a man who occupies arguably the most important and prominent role in Italy, if not Western Europe, could generally be assumed to be the one whose calendar others work around. All this points to a very recent medical discovery leading to a “days matter” diagnosis, or at least suspected possible diagnosis. Of course, another factor weighing in the balance is Leo’s upcoming apostolic visit to three South American countries, including a return to Peru, where he spent many years as a priest and bishop. It is entirely possible that the doctors, and the pope himself, are more concerned about the potential knock-on effects of surgery, and the time needed for recovery, for a 71-year-old — even one as physically sound and actively sporty as Leo. The pope is due to depart Rome November 6 for his 10-day three-country trip, returning on Nov. 17. It may be that Leo has simply made the decision to allow maximum time for his own post-op recovery, and even allow for potentially unforeseen circumstances, so that he is at full strength for the landmark trip. While it might be an inconvenience, and clearly a last-minute wrench in the works for the Amoris meeting, it is possible that Leo simply weighs the importance of that conference more lightly in the balance than even the possibility of missing his homecoming trip to Peru, or even having to scale back his itinerary for the trip. If that is the case, it would suggest a real abundance of caution by the pope approaching his Latin American tour, and a sobering indication of where Leo ranks the non-synodal meeting currently underway in Rome. In any event, what can be said for certain is that the pope having to take this, of all weeks, out of his schedule for surgery and an extended hospital stay is extremely unfortunate timing. It is clear that this is a decision Leo has made on the advice of his doctors. Together, they clearly consider that the risks of delaying, even by a little as a few days, represents an unacceptable risk for the pope. Even expecting and allowing for Leo’s full and speedy recovery, that should be a very sobering thought for Catholics everywhere. Subscribe
The science, instinct and hard work behind Roosters’ success
Enter your email address to get each Tribune edition sent to your inbox Subscribe There’s a fair bit of unseen work that goes into winning an NRL premiership, dating back many months - just ask Simon Jones. The Sydney Roosters Head of Performance, who hails from Southland, has been in the thick of it. He played a lead role in guiding the 2026 champions through a marathon campaign that ended with a grand final win over the Newcastle Knights. The Roosters had to navigate the lengthy round-robin competition, including the pre-season, before playing through all four weeks of the finals series. It was a demanding stretch that tested the players and the staff responsible for keeping them on the field. “It is a hell of a beast, mate, to be honest,” Jones told The Roar Podcast. “There’s such a great group of staff there that know what they’re doing, and the boys are pretty professional.” Jones believed the Roosters managed the physical demands well, pointing to the health of the squad throughout the campaign and the decision to rest a significant portion of the playing group in the final round of the regular season. That call, made by head coach Trent Robinson and his coaching staff, proved valuable as the Roosters entered the finals with some energy in reserve. “We did finish the season physically where we needed to be, and we’d sort of had a pretty healthy squad all year,” Jones said. “To the team that do that, mate, mission accomplished, really.” It is the sort of work that often goes unnoticed when the spotlight falls on the players scoring tries and making match-winning plays, but Jones knows the cumulative effect of those decisions can be significant over a long season. After a win over Penrith had helped establish them as premiership favourites, losses to the Wests Tigers and Dolphins were followed by a defeat to the Panthers in the opening week of the finals. Rather than panic, the club refocused to position itself to challenge for the title. “The Tigers’ performance was probably the only one where you’re really quite disappointed because it’s hard to get to the top of the competition,” Jones told The Roar Podcast. “We had proof that we could; we knew what we needed to do. We just had to get back to that.” For Jones, the answer was not necessarily a radical change to the programme. It was about executing the basics consistently, both on the field and in preparation. “We just do the basics better than anybody else,” he said. “Whether that is actually the way you play the game or how you’re preparing, it’s just be really consistent, do the basics really, really well.” Like many professional sports teams, the Roosters are entrenched in sports science and performance data. The club has access to a range of information, including players’ sleep, GPS metrics and neuromuscular scores, helping staff assess how individuals are coping with training and competition. “We are very science-backed, and some people would say data-driven, but it’s people first,” he said. “The reason you collect all this data is to try and be the best for that person.” Jones said the club was also prepared to reconsider testing methods if they were not generating useful discussions or helping staff make better decisions. In an environment where technology is continually evolving, he believes experience and gut instinct remain important. “The data is no good unless you have conversations,” he said. “When you strip it right back, mate, trust the gut still and obviously, you know, just doing the basics really, really well.” The return of halfback Sam Walker provided a further example of the importance of individual determination and the work of the club’s medical team. Walker underwent ankle surgery late in the regular season, with his premiership campaign appearing in doubt. However, he was determined to return for the preliminary final. Jones said Walker was back at the training ground three days after surgery, walking freely enough to surprise those around him. While the surgeon’s work was crucial, Jones credited the halfback’s mindset as a major factor in the remarkable turnaround. “He was quite clear with Robbo after he got the surgery that he was going to make it back for the prelim finals,” Jones said. The Roosters’ performance programme also sits within a wider club culture that Jones believes is central to their success. Each season, players develop their own team mantra through a lengthy process facilitated by Robinson. It provides principles that the squad can connect to its actions on the field. Rather than simply carrying over the previous year’s wording after a successful campaign, the club repeats the process because the players’ ownership of it is what gives it meaning. “When it’s led, player-owned and player-led, mate, it’s really powerful,” Jones said. Get more from Logan Savory in the Substack app Available for iOS and Android Get the app Jones joined the Roosters in 2024 and said the environment had evolved as experienced players departed and younger members of the squad took on greater responsibility. Maintaining continuity in the club’s culture and preparation had helped the group navigate those changes. The premiership was a significant achievement for Jones, who acknowledged how difficult it was to win the NRL’s ultimate prize. However, he is already looking at how the performance programme can improve. “There’s still things within my role and things that I’d like to help improve at the club,” he said. For Jones and his team, the challenge now is to review the season, refine their systems and prepare for another campaign. The celebrations may have followed a memorable title win, but the work behind the scenes never really stops. The Southland Tribune is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Subscribe
Crystal Palace 3-1 Nottingham Forest: Oliver Glasner's Selhurst Park return ends in defeat as Eagles complete remarkable comeback
Report and free match highlights as Crystal Palace come from behind to beat Oliver Glasners Nottingham Forest 3-1 in their first reunion since his summer exit; Dan Ndoye gave Forest the lead before goals from Daichi Kamada, Jefferson Lerma and Yeremy Pino completed a turnaround
Column: A great place for business, family
Commentary by Zackary Jerome Darring When I think about Carmel, Indiana, I don't just think about a city — I think about home. As a 33-year resident and one of the first minority-owned business operators in Carmel, my story is woven into the very fabric of this remarkable community. From
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Scientists discover the genetic secrets that may have helped Jonathan the tortoise live to 194 years old
DNA samples from Jonathan the 194-year-old tortoise reveal gene variants and epigenetic changes that could contribute to his remarkable lifespan.
Ranking Lane Johnson’s five most dominant seasons with the Eagles
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From Building Homes to Building Hope: Larry and Heidi Canraelli Commit $50 Million to Intermountain Health Nevada Children’s Hospital
LAS VEGAS — Intermountain Healthcare Foundation today announced a remarkable $50 million commitment from Larry and Heidi Canarelli to help bring Nevada's first comprehensive, stand-alone children's hospital closer to reality. This gift advances Intermountain Health's Nevada Campaign for Kids, expanding access to specialized pediatric care clos...
Scientists finally see how nature moves energy so efficiently
Researchers have captured key steps in a chemical reaction that helps nature transfer energy with remarkable efficiency. Ultrafast X-rays revealed how changes involving electrons and protons are closely linked to the rearrangement of surrounding water molecules. Because similar reactions drive photosynthesis and other energy-conversion processes, the technique could help scientists develop better catalysts, fuel cells, and flow batteries.
José Altuve Continues to Add to His Remarkable Astros Career
At 36, Altuve added another solid season and moved within one home run of the all-time postseason record.
Yale School of Medicine On the Science of Childhood Anxiety, Say, Anxiety Disorders Are the Most Common Mental Health Challenges In Youth
Credit: Matt Bradbury October 5, 2026 - By Isabella Backman - Anxiety disorders are the most common mental health challenges in youth. Left untreated, they can disrupt the lives of both children and their families. The good news is that with intervention, most children will overcome these conditions. Across Yale School of Medicine, scientists are working to understand anxiety at every level, from common anxious behaviors to molecular biomarkers in the brain. They are using their findings to develop and disseminate new evidence-based treatments for childhood anxiety. Today, the go-to treatment for childhood anxiety disorders is cognitive behavioral therapy (CBT). This is a form of psychotherapy that teaches children skills for confronting anxious thoughts and helps them practice managing situations that cause anxiety. While it is the gold-standard treatment backed by considerable scientific evidence, up to 50% of children will not see sufficient benefit from CBT alone. Wendy Silverman, PhD, Alfred A. Messer Professor in the Child Study Center, co-directs the Anxiety and Mood Disorders Program alongside Eli Lebowitz, PhD, associate professor in the Child Study Center. One of their main interests is learning how to improve outcomes beyond CBT. “We’re developing cutting-edge, research-based knowledge that can reduce the suffering that anxiety causes children and their families,” says Silverman. Changing parent behavior YSM experts are investigating how to improve CBT outcomes for children by involving the parents. Silverman’s research has uncovered two main components of parent intervention that improve childhood anxiety: not enabling children to completely avoid the things that make them anxious and taking steps to enhance their autonomy. Parents may unintentionally reinforce their child’s anxiety by allowing them to avoid what makes them anxious. They also may unintentionally limit the children’s sense of autonomy by being overly intrusive. “One of the things that we take pride in is that we’ve focused on trying to understand what parents need to do, and to test our ideas and see if changing the parents’ behaviors is enhancing the effects of CBT,” Silverman says. “Our findings thus far suggest that they do." As much as CBT can be helpful, it can also be challenging to get one’s child to do the necessary steps for CBT to work. This is one important reason why Lebowitz created a novel intervention program for parents named Supportive Parenting for Anxious Childhood Emotions (SPACE). Existing intervention programs often teach parents to act as therapists for their child, such as training them on how to practice breathing exercises. “It makes sense, but this doesn’t work very well in practice,” says Lebowitz. “And part of the reason, I think, is that it’s not easy to get your kid to do things, especially if they’re not excited about doing it.” SPACE is unique because it focuses entirely on parent involvement and changing parental behavior—children are not involved in the sessions. For example, parents learn how to use supportive messages that convey confidence that their child can tolerate and manage distress. “It might sound like a parent saying to a child, ‘I get that this is really hard for you, but I know that you can handle it,’” Lebowitz says. The program also works with parents to identify the ways in which they are accommodating anxious behaviors. “We’ll pick one thing that parents are doing that is an accommodation and help them make a detailed plan for how they’re going to change that,” Lebowitz explains. Treating Anxiety in Children and Adolescents Much of the existing research on SPACE has focused on parents of children under age 14. Ongoing studies are now exploring its use with parents of older teens. “Both anxiety and accommodation can interfere with normative developmental shifts during the teen years, including increased autonomy and individuation from parents,” says Rebecca Etkin, PhD, associate research scientist in the Child Study Center. “In this sense, SPACE may be particularly well-suited for anxious teens and their parents. We want to see whether it is effective during this distinct developmental window.” Unfortunately, many families in need of CBT face barriers, including limited availability of services and geographic constraints. One way to improve access is digital interventions. Silverman and her team are developing an evidence-based digitized intervention program for parents that they can access directly from their computer or smart phone. “The work we’re doing will be one of the very few parent interventions that is digitized and importantly tested for effectiveness,” she says. Creating interventions for anxiety-related challenges Silverman and Lebowitz recently received a generous gift to develop and test other interventions that help parents reduce other child anxiety-related behavioral and emotional difficulties, such as restrictive eating and unexplained somatic symptoms. One of these projects in particular focuses on understanding the risks of social media and its potential benefits, including offering a sense of connection. “A lot of research has focused on the idea that social media is harmful and the less of it the better,” says Lebowitz. “But we actually see is that this is not quite right—there are negatives, but there are also positives. So, we’re trying to get a little bit more nuanced of a picture.” The team is working with teens with social anxiety and their parents over an extended period to better understand their social media habits and how their anxiety levels affect engagement with different platforms. The teens will answer questions sent to an app on their phones about mood and social media usage in an effort to capture emotional responses as they unfold. “We hope to develop interventions that can help make the best of social media while protecting against the more problematic effects,” Lebowitz says. The brain’s role in anxiety Researchers are also testing therapies to address anxiety at the neurological and molecular levels. In collaboration with Dylan Gee, PhD, professor of psychology in Yale's Faculty of Arts and Sciences, and Hilary Blumberg, MD, John and Hope Furth Professor of Psychiatric Neuroscience at Yale School of Medicine, Lebowitz and Silverman are using brain imaging to identify changes in a child’s brain before and after parents enroll in SPACE. In one study, children viewed anxiety-inducing images while undergoing magnetic resonance imaging (MRI); the researchers conducted scans with and without the children’s parents nearby. Before SPACE, children’s brains were better able to activate the regulatory circuitry needed to turn off an anxious response when their parents were nearby. But after SPACE, children could activate this circuitry even without the parent around. “As parents work on gradually reducing some of their accommodations, you can see a child get better at regulating their own fear system in the brain,” Lebowitz says. “It’s remarkable.” Research into the molecular underpinnings of anxiety can also inform new childhood anxiety treatments. In a recent study, Lebowitz, Silverman, and Flora Vaccarino, MD, Harris Professor in the Child Study Center, discovered that a protein known as fibroblast growth factor 2 (FGF2) could be protective from the toxic effects of stress. FGF2 levels in children and their parents were linked to the children’s risk of developing anxiety and depression, the study showed. The findings could help explain why some children who are exposed to early life trauma such as poverty or abuse are more prone to developing mental health disorders. And FGF2 could be a target for treatment. “This is very novel because it starts to give a clue to what is the molecular chain that connects those lived experiences to the actual psychological outcomes,” Lebowitz says. New ways to study and treat childhood anxiety Michael Crowley, PhD, associate professor in the Child Study Center, collaborates with Silverman and Lebowitz to study the role that attention plays in development and maintenance of childhood anxiety. There is a large body of research that shows that anxious children, like anxious adults, are prone to focus on threatening stimuli such as angry faces compared with neutral faces. This has led to innovative interventions that involve attention retraining. The idea is that if experts train children to look away from threatening stimuli, it may reduce their anxiety—especially children with social anxiety who are most prone to attend to threats. The researchers have just completed a clinical trial for attention retraining with 10- to 14-year-olds with social anxiety disorders and are currently analyzing the findings. Besides this innovative attention retraining research, as Crowly notes, “I like to design tasks that are engaging to kids,” Crowley says. “My goal is to assess something without the kids knowing what we are assessing.” With this goal in mind, Crowley has created a virtual game, named Boom, to study threat processing in children with anxiety disorders. The game is similar to that of hot potato—the child and three digital players take turns virtually passing a ball to each other’s gloves. At some point, the ball turns into a bomb, and as the bomb lands in each player’s glove, the outline of the glove turns yellow. The goal is to avoid having the bomb go off in your glove. What isn’t obvious is that the game is designed to measure different types of threatening stimuli, both ambiguous and direct. In the game, the direct threat occurs as the bomb is traveling towards your glove. The ambiguous threat is the yellow outlined glove as it is unknown where the bomb will travel next. While children play the game, Crowley’s team measures their brain activity using electroencephalography (EEG). The researchers have discovered that in kids with anxiety, the brain reacts more strongly to ambiguous threats than it does in their peers, but less strongly to direct threats. They believe that the initial abnormally large brain response to not knowing where the bomb is going impairs the brain's ability to properly respond when the threat is actually traveling the child’s way. “The brains of children with anxiety are unable to differentiate between threats you need to do something about and those that are not your problem.” Michael Crowley, PhD, develops innovative games for studying anxiety in children and adolescents.Credit: Matt Bradbury Based on these insights, Crowley hopes to study whether interventions like attention training could restore appropriate threat processing. Crowley’s team is also working on a test called the Balloon Risk Avoidance Task, which evaluates risk-taking and avoidance behaviors. It features a digital balloon that is full of air and about to burst. Kids have six seconds to let air out of the balloon. The more air they let out, the less risk they face that the balloon will pop. But at the same time, the balloon becomes less valuable as it deflates. “The more air you keep in the balloon, the more points you get,” Crowley explains. So far, the researchers have found that when the balloons pop unexpectedly, teens with social anxiety show distinct brain responses. Studying these responses can help psychologists understand the underlying pathways driving the various manifestations of anxiety. The genetics of anxiety When Thomas Fernandez, MD, associate professor in the Child Study Center and of psychiatry, was still in training, there was a lot of excitement about understanding the genetics associated with autism spectrum disorder. Since then, scientists have identified around 250 genes associated with autism. The genetic contribution to anxiety disorders, on the other hand, has historically received less attention. Anxiety is less heritable than autism, but the genetic contribution for anxiety disorders that emerge in childhood may be higher than for anxiety disorders overall. While scientists estimate the heritability of anxiety disorders in general to be around 30% to 50%, some studies suggest higher heritability for certain childhood-onset anxiety presentations. “I saw firsthand how researchers in the field went about finding vulnerability genes for autism,” Fernandez says. “So, we’re using a very similar playbook for childhood anxiety.” “I saw firsthand how researchers in the field went about finding vulnerability genes for autism. So, we’re using a very similar playbook for childhood anxiety.” Thomas Fernandez, MD Associate Professor In the Child Study Center and in Psychiatry Now, Fernandez and Emily Olfson, MD, PhD, assistant professor in the Child Study Center, are studying children and their parents to identify genetic changes that are present in the child but not the parents, known as “de novo mutations.” “All of us have some de novo mutations—maybe about 50 to 100 sprinkled throughout the genome,” Olfson says. “But when they occur within the coding regions of genes, they can be really disruptive.” Previous research shows that people with autism have higher rates of damaging de novo mutations than the general population. In 2022, Olfson, Lebowitz, Silverman, and Fernandez published a study on 68 children and their families that found that children with anxiety had similarly high levels of these mutations. Studying de novo mutations can help point the researchers to where they should be looking for genes associated with anxiety. “The end game is using the genes to steer us toward the right part of biology that we can then target to come up with better treatments,” Fernandez says. Building on those findings, the team is now studying more families to better understand how these de novo mutations, along with other genetic and environmental factors, shape pediatric anxiety disorders. They recently received a National Institutes of Health grant to enroll 750 new families over the next five years. Olfson is the principal investigator, with co-investigators Lebowitz, Fernandez, Silverman, and Shuangge Steven Ma, PhD, department chair and professor of biostatistics at Yale School of Public Health. Neurodevelopment, Risk Genes, and Mental Health Conditions - The Olfson Lab Joel Gelernter, MD, Foundations Fund Professor of Psychiatry, is interested in how different anxiety disorders differ genomically. “We are studying social phobia, panic disorder, and generalized anxiety disorder, working to understand why people differ in their risk to these specific anxiety disorders and evaluating various risk factors,” he says. Gelernter was recently involved in one of the largest studies to date of the genomics underlying anxiety disorder. The study included around 122,000 people with anxiety disorders and around 730,000 without. It found that some genetic differences associated with anxiety were linked to signaling that helps reduce overactivity in the nervous system. Many anxiety medications available today work by targeting this process. “It’s nice when the biology that you get out of a large genome-wide study ratifies things that we already know because that can help increase confidence in further findings from the study,” Gelernter says. Uncovering the neurobiology of psychiatric disorders John Krystal, MD, Robert L. McNeil, Jr. Professor of Translational Research and chair of the Department of Psychiatry, is interested in the neurobiology of psychiatric disorders, including post-traumatic stress disorder (PTSD), of which anxiety is a major symptom. In the late 1980s, Krystal’s team discovered that the drug yohimbine activated symptoms in patients with PTSD. “This was the first time we could link a specific biological mechanism to the symptoms of PTSD,” Krystal says. At the time, he adds, this finding was highly controversial. “A lot of people felt that PTSD was a purely psychological syndrome that didn’t have an underlying biology.” Since then, Krystal has dived deep into understanding the neurobiology of PTSD to learn how to better treat it. His team is evaluating the use of ketamine and psychedelics. These would be among the first treatments to be developed specifically for PTSD. They may also be applicable for other disorders including anxiety disorders, Krystal adds. An important gap in PTSD treatment is the absence of biological tests that inform how to best help patients manage their PTSD symptoms. A doctor doesn’t diagnose cancer based on how they feel. Rather, they use tests of the biology of the cancer to determine the best course of treatment. “And we can’t do that in any psychiatric disorder other than Alzheimer’s disease,” Krystal says. “But now we are building a foundation for this approach to the treatment of anxiety disorders for the first time.” Source: Yale School of Medicine
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