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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)
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The Best Time to Fix Your Business Is When Things Are Going Well by Nathan Tayloe
There's a pattern I've noticed working with growing businesses over the years. Conversations about what needs to change rarely happen when things are going well. They tend to happen when growth slows, a competitor starts winning business, or something that used to work stops producing the same results. By then, the decisions are often harder, more expensive, and more urgent than they needed to be. It's understandable. When revenue is growing, customers are coming in, and employees are busy, there's little incentive to question what's working. Leaders have plenty to manage without creating new challenges for themselves. Running my own business has taught me that it's easy to get caught up in what's happening today and put off improvements you know will matter tomorrow. Those periods of success may actually be the best opportunity a business has to make meaningful improvements. When Success Makes Change Less Urgent Most businesses have things they know could be better. The challenge is finding a compelling reason to address them when everything appears to be working. Maybe the company has outgrown its original positioning. Perhaps internal processes haven't kept pace with growth, or the customer experience has become inconsistent as the organization has expanded. These issues don't necessarily prevent a business from growing. Strong demand can make them easier to overlook, especially when teams are focused on keeping up with the work already coming in. Over time, small inefficiencies become accepted ways of operating. Outdated processes remain in place because they've always worked well enough, and opportunities to improve get pushed aside in favor of more immediate demands. The business continues moving forward, but some of the things supporting that growth aren't getting stronger along with it. The Advantage of Acting Early When a business is performing well, leadership has something valuable: options. There's more flexibility to invest, experiment, develop people, and make thoughtful decisions without the pressure of an immediate problem that needs solving. Compare that with trying to make the same changes when revenue is declining, or the market has shifted. Investments become harder to justify, timelines get compressed, and decisions that could have been made strategically become urgent responses to circumstances. I've seen businesses postpone improvements for years because there was never a particularly good time to address them. Eventually, circumstances decide for them, often when they have fewer resources and less flexibility to respond. Growth Changes What a Business Needs This is especially relevant in a growing market like Wilmington, where new businesses, new residents, and continued investment are creating opportunities across the region. As organizations grow, the expectations placed on them change. Customers expect greater consistency, employees need clearer processes and opportunities, and leadership has to make decisions that support a larger, more complex business. What worked when a company was smaller may still work today, but that doesn't necessarily mean it will support where the organization wants to go next. Sometimes the most valuable improvements are the ones that prepare a business for demands it hasn't experienced yet. That might mean: Strengthening internal processes before they become bottlenecks Developing leaders before the organization depends on them Improving the customer experience before inconsistencies affect retention Revisiting positioning before the market outgrows the company's story None of these changes requires a crisis. They require recognizing that a growing business needs to keep evolving, even when current performance gives leadership little reason to worry. Use the Good Years Wisely Successful businesses don't need to constantly reinvent themselves. There's value in knowing what works and having the discipline to build on it. There's also value in occasionally asking whether the business is as strong as its current performance suggests. Are there problems we've learned to work around instead of solving? Are we still operating the way we did several years ago, even though the business has changed? What would we improve today if we weren't waiting for something to go wrong? Success creates the freedom to ask those questions and act on the answers. The businesses that make the most of that opportunity are often better prepared for whatever comes next. The strongest businesses don't need a crisis to recognize an opportunity to improve. They use the good years to prepare for the years ahead. — Learn more about how we help organizations strengthen their positioning, align their strategy, and prepare for what's next at tayloegray.com, or reach out directly at nathan@tayloegray.com.
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Spotlight on: Advocacy
••• SPONSORED SECTION ••• MAKING THE CASE Helping policymakers understand how their decisions affect the communities they serve. Advocacy means taking action to support a cause deemed worthy, influencing public policy and supporting one’s community. Businesses are increasingly learning the importance of making their case in a transparent, positive manner. This section features three organizations […]
Rising health costs and coverage changes are big concerns for older adults as Election Day nears
Rising healthcare costs are a major concern for older Americans, and it's affecting their finances and political priorities.
Rising health costs and coverage changes are big concerns for older adults as Election Day nears
Rising healthcare costs are a major concern for older Americans, and it's affecting their finances and political priorities.
Rising health costs and coverage changes are big concerns for older adults as Election Day nears
Rising healthcare costs are a major concern for older Americans, and it's affecting their finances and political priorities. Open enrollment for Medicare began in October, with changes in costs and
Top healthcare worries weigh on older US adults before the midterms
Rising healthcare costs are a major concern for older Americans, and it's affecting their finances and political priorities.
Rising health costs and coverage changes are big concerns for older adults as Election Day nears
Rising healthcare costs are a major concern for older Americans, and it's affecting their finances and political priorities. Open enrollment for Medicare began in October, with changes in costs and
Rising health costs and coverage changes are big concerns for older adults as Election Day nears
Rising healthcare costs are a major concern for older Americans, and it's affecting their finances and political priorities.
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TCAI’s Jai Jaisimha on artificial intelligence and mental health: How should AI be used? — Transparency Coalition. Legislation for Transparency in AI Now.
Transparency Coalition Co-founder Jai Jaisimha recently sat down with Rachel Harrison, host of the podcast “The Mental Health Evolution,” to talk about how AI is affecting health care.
Implementation of Immigrant Eligibility Restrictions for ACA Marketplace Subsidies Under the 2025 Reconciliation Law: Issues to Consider
Beginning January 1, 2027, the 2025 reconciliation law will limit immigrant eligibility for ACA Marketplace subsidies. This brief provides an overview of implementation of the immigrant eligibility changes for Marketplace subsidies and issues to consider for affected individuals and states.
Trucking surveys ask: How does driver health affect industry operations?
Drivers face “unique” challenges, such as finding healthy food and being physically active, the American Transportation Institute says.
HEALTH INSURERS AND PHARMACY BENEFIT MANAGERS URGED TO ASSIST FAMILIES AFFECTED BY LULU M. ROSS ELEMENTARY SCHOOL FIRE
State calls for swift, flexible action to help affected families replace essential medications DOVER, Del. (October 30, 2026) – This week, the Delaware Department of Insurance was notified by Secretary of Health and Social Services, Christen Linke Young and Secretary of Education Cindy Marten that the October 25 fire at Lulu M. Ross Elementary School […]
How Election Day can affect your heart
Political campaigns can do more than raise your blood pressure. Studies link election stress to irregular heartbeats and an increase in heart attacks.
Heated Tobacco: A New Trend That Is Raising Heart Health Concerns
By HealthDay Staff HealthDay ReporterFRIDAY, Oct. 30, 2026 (HealthDay News) — Heated tobacco is gaining popularity around the world, marketed as a less harmful alternative to cigarettes. But new research is raising red flags — finding that just one session can affect cardiovascular function. These ...
Virginia Tech leads women's health research project
Hormones are a big part of the women’s health conversation, and Virginia Tech professor Raffaella De Vita is leading a multi-million dollar project that will look at how they affect women’s bodies throughout their lives. News4’s Juliana Valencia and Molette Green spoke with her about her work.
Can creatine help your mental health? Here’s what the latest evidence says
The brain needs a lot of energy. Without a sufficient supply, mood and mental health may be affected.
How does daylight saving time affect our health?
The chicken or the egg? Cats or dogs? What about pineapple on pizza?
Maine adopts $600K mental health safety net for people affected by PFAS
The program will provide counseling and peer support to farmers, workers and neighbors coping with contaminated land and water.
Commentary: Science shapes Michigan policy. Voters deserve to know candidates’ views.
Policy decisions do not happen in isolation, nor are they confined to Capitol Hill or Lansing. Decisions made across all levels of government directly affect Michiganders’ health and livelihoods. From monitoring our food supply to protecting drinking water, scientists help governments identify risks, evaluate possible responses, and decide what actions to take. Recent events in […]
Commentary: Science shapes Michigan policy. Voters deserve to know candidates’ views.
Policy decisions do not happen in isolation, nor are they confined to Capitol Hill or Lansing. Decisions made across all levels of government directly affect Michiganders’ health and livelihoods. From...
Ballad Health experiencing ‘disruption’ to several software systems
JOHNSON CITY, Tenn. (WJHL) — Ballad Health said on Thursday that a “disruption” is affecting several of its software systems. Ballad Health said the disruption began at approximately 9:…
DoorDash to acquire Instacart, maintain brand identity
DoorDash's $17B acquisition of Instacart could expand delivery options, affecting gig workers' opportunities and app functionality.
Small Business Administration loan program available to WV residents affected by August flood
West Virginians affected by severe storms and flooding in August still have time to apply for federal assistance through the U.S. Small Business Administration’s Office of Disaster Recovery.
Small Business Administration loan program available to WV residents affected by August flood
West Virginians affected by severe storms and flooding in August still have time to apply for federal assistance through the U.S. Small Business Administration’s Office of Disaster Recovery.
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
Bayern Munich coach Vincent Kompany's health scare highlights the need for better support for coaches
Vincent Kompany’s health concern is a reminder that elite football's pressures affect coaches too. Better support, clearer structures and mental health safeguards are increasingly vital.
Photo Essay: College of Science and Engineering Research Showcase
Fourth-year Mechanical Engineering major Jess Visaya and Fourth-year Mechanical Engineering major Dorette Pirie show off their soft robots. The robots are made to mimic worms, whose bodies bunch up before extending to propel themselves forward. The robots use pneumatic actuators to make linear movement outwards. Visaya and Pirie set up two of their worms with syringes attached to tubing which was then threaded through the end cap into the worms. Visitors to their station were encouraged to race the two worms by pumping the attached syringes. Third-year Biochemistry major Ira Evetts worked in Dr. Christopher Whidbey’s lab studying the vaginal microbiome, in an attempt to better understand the different microbes that build it up and how it affects health outcomes. Evetts’ research was specifically focused on lactobacillus iners, one of several bacteria naturally present in a healthy vaginal microbiome, and methylation systems. Fourth-year Mechanical Engineering major John Diesko Boehm and Fourth-Year Mechanical Engineering major Ian Agopsowicz hold up their “DAQMobile.” They built their project, a modified RC kit car, to help teach mechanical engineers about circuits and electrical design through real-world application. Fourth-year Mechanical Engineering major Ben Murphy holds up his mole crab and crawfish-inspired burrower. Murphy wanted to imitate the motion of a crab’s legs through robotics, with the primary goal to “turn the rotation of one motor into four alternating legs that would successfully displace soil.” Murphy was inspired by works that take inspiration from the natural world, and he found mole crabs particularly interesting. Although a mole crab is at an advantage with its burrowing being underwater, thus the sand being fluidized and easier to displace, Murphy’s machine is able to successfully burrow three centimeters into the ground. Second-year Mechanical Engineering major and Physics major Arabelle Miller shows off her rubber gripper, inspired by kirigami and origami. She took a piece of rubber and strategically cut slits into it to make it fold the way she needed, then glued googly eyes to the front. The gripper is able to hold up to 38 times its weight, or 226 grams. Third-year Mechanical Engineering major Joonseong Park talked about how his project took an unused and broken 3-D printer and transformed it into a testing platform for soft robotic grippers. The former-printer was reprogrammed and had its extruder part modified to be a mount for the grippers. Park shows off some of the other grippers that can be attached to the testing platform. Park classified grippers into two large categories. The first set of grippers is designed to deal with small delicate objects with great precision, and the second is made to lift heavy or large objects. Third-year Mechanical Engineering major Jiashuo Liu set out with a goal to deploy free open-source AI models to pre-existing robots to integrate object recognition and retrieval and command. The models are used to process the data received from the robots’ cameras in order to detect certain objects and their locations. Fourth-year Mechanical Engineering major Cole Purohit focused on agricultural automation of raspberry picking. His project utilizes kirigami to make grippers to close around a raspberry when the two ends are pulled. “Nobody wants to eat a squished raspberry,” Purohit said. Fourth-Year Biochemistry major Mariel Nolan’s project focused on bacteria and proteins within the bacteria whose functions are unknown. Nolan’s research is finding a way to isolate those proteins with the ultimate goal of determining their functions. Fourth-year Mechanical Engineering major Kai Boydon and Fourth-year Mechanical Engineering major Evan Nguyen show off their project, which uses custom extensors to help with the rehabilitation of stroke patients. They compared their project to a “party-popper” in the way it unfurls itself when placed under a patient’s fingers, helping the stroke patient rehabilitate finger movement. Boydon shows off the testing rig built for their project. It works as a mount for their extensor, as a way to test against resistance. Their program inflates the extensor through an air pump, which then makes the extensor push against the bed whilst an arduino calculates the force created and air pressure associated with the force. Navigate Left Navigate Right
Disaster loans available for small businesses, nonprofits, residents affected by Sept. storms
The U.S. Small Business Administration announced the availability of low-interest federal disaster loans for Indiana small businesses, private nonprofits, and residents affected by severe storms and flooding on Sept. 17.
Small business owners meet in Iron Mountain to discuss tax law changes
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Disney's theme parks division lays off at least 100 employees
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Need health insurance? Here’s how 2027 ACA options may affect immigrants and more
Learn about 2027 ACA health insurance provisions, including premium increases, new enrollment checks, broker restrictions and immigrant subsidy eligibility.
Opinion: What would you tell your children about your lowest-paid employee?
Former Exelon executive Sonny Garg argues that business leaders need to look beyond spreadsheets and understand how their decisions affect workers' lives.
YouTube Down for Thousands of Users Wednesday, Downdetector Reports
Thousands of users are facing issues with YouTube today. Discover the current status and reported problems affecting video streaming.
Opinion | Mississippians Deserve Transparency on Candidates’ Stances on Scientific Issues
Two Mississippians write on the need for political candidates to be transparent about their stances on scientific issues affecting their constituents.
Health insurance rules are changing. Here’s how to avoid an unanticipated bill.
Older adults not yet eligible for Medicare could be the most affected, particularly if they are self-employed or ineligible for workplace plans. Some in this group could face annual premiums of more than $20,000.
Pentagon creates advisory council on human performance, health
After creating a new directorate on warfighter optimization within the Department of Defense, the Pentagon announced it will form a federal advisory committee to weigh in on issues affecting troop performance and health.
High metal exposures after wildfires may affect lung function
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Health Insurance Markets Provide Fewer Choices For Enrollees
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How hot you drink your tea may affect heart health
A study of 485,000 adults in China links “burning hot” tea to higher vascular disease risk, while comfortable-temperature tea was associated with lower risk.
How dental health affects your overall health
Your mouth is connected to more than your smile. Learn how oral health can affect your heart, lungs, blood sugar, pregnancy and more.
Georgia Republicans are trying to court Latino voters. National politics are complicating things.
In a battleground state with tightening margins, Georgia’s Latino voters have the potential to affect the outcome of the governor’s race in November.
Oct. 26 "Colorado Chamber Office Hours": Pushing back on Colorado's sinking business reputation
The latest "Colorado Chamber Office Hours" features two economic-development leaders discussing how national rankings affect their work.
‘It affected my health’: Neighbors complain about building implosion, cloud of dust
“My eyes were watering and burning, my nose was like a sieve."
iPhone AI Images and Edits Now Have a Hidden Watermark
Images generated with Image Playground and some photos edited with Apple Intelligence will now include a SynthID watermark. Apple announced plans to add SynthID support back in June, and the feature is live in iOS 27.2. SynthID is a Google-created tool that identifies AI-generated content. It watermarks images and videos at the pixel level instead of adding metadata. Google says it does not affect image quality and is meant to survive cropping, filters, and compression.
iPhone Duo owners report cracks in Apple’s first foldable handset
Company says small number of devices affected by display glitch after posts appear on Reddit and social media
Denver Health Medical Plan Discloses Vendor Breach Affecting 238K Members
Denver Health Medical Plan has notified more than 238,000 individuals about a vendor-related data incident. Data breaches have also been announced by Denver Health Medical Plan has notified more than 238,000 individuals about a vendor-related data incident. Data breaches have also been announced by Johns Hopkins Bayview Medical Center and BASS Medical Group.
Sanford Health says it will end contract with Wellmark insurance
Sanford has signaled its intent to end its contract with Wellmark. If contract negotiations fail, around 130,000 patients in South Dakota and northwest Iowa could be affected. Sanford's Nick Olson explains the move.