Search headlines

The new "science golden age" looks suspiciously like a grift

This edition of PN is made possible by paid subscribers. Become one ⬇️ 🚀 Subscribe to PN 🚀 The Trump regime is trying to usher in a “Golden Age in Science” where scientific research is run like a Trump family business, artificial intelligence is all that matters, profit is everything, and expertise is for chumps. Or at least that’s the vision emerging from a new 123-page “Report to the President” from Michael Kratsios, the Director of the White House Office of Science and Technology Policy. In a normal administration, you could probably skip over learning about a science policy document — but this is no normal administration, and this is no normal science policy document. Instead, it’s Trump’s attempt to end the actual golden age of science that was kicked off in 1945 with the publication of '“The Endless Frontier” by Vannevar Bush. [ ](https://www.publicnotice.co/p/harmeet-dhillon-portland) [ Harmeet Dhillon demonstrates danger of posting through it ](https://www.publicnotice.co/p/harmeet-dhillon-portland) Liz Dye · Jul 29 [ Read full story ](https://www.publicnotice.co/p/harmeet-dhillon-portland) Bush, at President Franklin Delano Roosevelt’s request, laid out a vision of federal support for science that centered on funding universities to do basic research, saying that as long as those institutions were “vigorous and healthy and their scientists are free to pursue the truth wherever it may lead, there will be a flow of new scientific knowledge to those who can apply it to practical problems in Government, in industry, or elsewhere.” Kratsios’s report is supposed to be the successor to Bush’s, and even apes the format, but this isn’t really a document about science policy. It’s one about ending science research as we know it in favor of shoveling cash at big tech companies. While it might be temping to wave this away as an aspirational policy document, Trump has already begun to shift billions in research funds to AI projects and has taken a hatchet to science funding across the board. He’s teed up the shift Kratsios proposes here, and since neither Congress nor the Supreme Court seem inclined to stop him from doing whatever he wants with taxpayer money, it isn’t doomering or hyperbole to say we are staring down the barrel of a world where the only “science” the government intends to support is for-profit tech and defense advancements. Science for dummies Part of how you can tell this isn’t a document about science is that you are immediately faced with an absolute wall of business-speak of the worst sort. Did you know we must “tightly couple our science and technology enterprises to ensure that groundbreaking ideas invented in the United States are rapidly prototyped, tested, manufactured, and scaled domestically”? You do now! That tone isn’t surprising, because Kratsios has no background in science or research. He has a bachelor’s in political science and spent most of his career working for Peter Thiel at Thiel Capital. After a stint in the first Trump administration as Chief Technology Officer, where he also did not do any science, Kratsios was tasked in 2020 with overseeing the Pentagon’s research budget for a brief time, a position that, as the Wall Street Journal put it, “carries a great deal of power in terms of dictating investment allocations.” He spent the Biden years at Scale AI as “head of strategy,” which you will also note is neither a science nor a research job. But Scale AI has contracts with the Department of Defense and, as the Washington Post wrote in 2023, “has been aggressively pitching itself as the company that will help the US military in its existential battle with China.” And now you have the necessary background for our new golden age, which is going to be a golden age of taking money away from scientists and universities and giving it to companies like Scale AI. A note from Aaron: Working with brilliant contributors like Lisa takes resources. If you aren’t already a paid subscriber, please become one to support our work. 👇 Subscribe In a genuinely galling move, Katsios spends a lot of time slamming universities because of “administrative burdens on researchers” and the “well-documented inefficiencies” in academia, the message being that those damn universities waste the time of amazing researchers with paperwork. Except it’s the administration that is attempting to impose inefficient, unnecessary burdens on those researchers with a proposed Office of Management and Budget rule that would require senior political appointees to approve every science grant and ensure it aligns with Trump’s personal priorities. Researchers would also have to seek prior government approval to attend conferences or publicize their research. And political appointees could terminate any grant at any time if they feel like it. [ ](https://www.publicnotice.co/p/omb-rule-science-funding) [ The murder of expertise ](https://www.publicnotice.co/p/omb-rule-science-funding) Lisa Needham · Jun 11 [ Read full story ](https://www.publicnotice.co/p/omb-rule-science-funding) But when it comes to AI, we’re going to “restore permissionless innovation.” The report proposes to give lucky ducky innovators a pile of cash up front for grants lasting five years or longer, saying “awards should be fully-funded in year one, with all resources earmarked upfront, to minimize administrative burdens and reduce pressure for researchers to generate intermediate results to secure continued funding.” Yeah, wouldn’t want to have to make the Very Special Tech Bros show results or get money parceled out year by year like the plebes at universities. The report also proposes that we should have “fast grants” with “simplified applications requiring just a few pages of writing” because that is definitely how science works, just writing a bit off the dome and getting some cash. [ ](https://www.publicnotice.co/p/trump-ai-action-plan-altman-llms) [ Tech elites are turning AI into ChatGPTrump ](https://www.publicnotice.co/p/trump-ai-action-plan-altman-llms) Paul Waldman · July 29, 2025 [ Read full story ](https://www.publicnotice.co/p/trump-ai-action-plan-altman-llms) Oh, and we should have prizes and challenges, where multiple teams compete. The proposed prizes include incentives like “advance procurement commitments,” which means the federal government agrees to buy whatever is being developed. There’s also “regulatory fast-tracking,” making sure all those great AI thingies don’t have to wait too long to be unleashed on a market. These aren’t incentives to do science. These are incentives to develop things with tax dollars that you can then sell to the government for more tax dollars. In the suggestion that might be the most unhinged, the most very opposite of how both government and research work, our new age will include “golden tickets.” That’s where an individual reviewer in an agency — yes, just one person — can “recommend unconventional proposals that may not pass consensus-driven review panels” because somehow this will “surface valuable ideas too divisive for committees and attract higher quality reviewers by empowering them to exercise independent scientific judgment.” Yes, that’s saying that a random person in an agency should be able to shovel money at some idea even if it can’t pass a review panel, and that the opportunity to do so will attract better employees because apparently all the best minds in science are chomping at the bit to be allowed to unilaterally fund AI research based on their personal vibes. But that isn’t at all how actual science works, and actual scientists aren’t unhappy about review panels. They work collaboratively, not siloed in some secret race to create the next AI chatbot. A 2020 study by the National Bureau of Economic Research examined whether peer review panels succeed in helping agencies predict which research ideas will best advance science. Peer review was better at finding “diamond in the rough” applicants than a single government program official. How about that. Trump always wants a taste It’s painfully clear that what Katsios is trying to do here is turn the whole of government science research and funding into the sort of “move fast and break things” paradigm that is the hallmark of big tech. That method works to line the pockets of tech executives, but it isn’t science. There’s a reason the government funds different kinds of research than private tech companies do. What Katsios either fails to understand or deliberately ignores is that the federal government is the main funder of basic research precisely because it can take a long time for it to bear fruit and is not intended to be profitable as such. “Basic” here does not mean rudimentary or simple, but rather research that is designed to advance scientific knowledge instead of achieving a specific outcome or product. Big tech companies don’t widely fund that sort of research, because it doesn’t make them money. Industry dollars account for only about 20 percent of basic research funding, while the government contributes around 60 percent. Big tech companies and startups do, however, rely on and benefit from that basic research. A 2019 study found that 35 percent of all patents obtained by venture-backed startups from 1976 to 2016 cited federally supported research. Basic research funded by the NIH contributed to every single drug the FDA approved from 2010 to 2016. [ ](https://www.publicnotice.co/p/trump-saudi-nuclear-deal) [ The Saudi nuclear farce and governance by whim and meme ](https://www.publicnotice.co/p/trump-saudi-nuclear-deal) Noah Berlatsky · Jul 27 [ Read full story ](https://www.publicnotice.co/p/trump-saudi-nuclear-deal) Unlike inventing the next ChatGPT, actual science is slow and iterative. Government funding of research that, on its face, would not appear to lead to any big new invention is actually what underpins those big new inventions. If the government hadn’t funded research into desert lizard venom, we wouldn’t know about semaglutide, and we wouldn’t have Ozempic. If research scientists hadn’t studied how bees optimize nectar foraging within a colony, we wouldn’t have the algorithm that assigns internet traffic across computer servers. The report assiduously ignores that a symbiotic, profitable relationship between the federal government, universities, and private companies already exists. Each federal research dollar generates about $1.50 to $3.00 in long-term economic benefits. The $36 billion the government awarded in NIH research funding in fiscal year 2025 generated $94 billion in new economic activity. Trump’s proposed new golden age is intended to strip those billions from universities, resulting in the dismantling of departments and the shuttering of labs. But Katsios has a plan for that: Universities should just become trade schools to churn out no-show STEM degrees! “Require universities and community colleges to embed practical technical training and externships into STEM curricula. Let hands-on experience and industry credentials count toward degrees.” It’s quite the feat to, on the one hand, strip schools of funding for scientific research while simultaneously demanding to control what is taught and, oh, also, colleges need to give degrees to employees at big tech companies just for being employees at big tech companies. The new golden age would also exacerbate the brain drain Trump’s policies have already caused. Nature found that in the first quarter of 2025, US scientists submitted 32 percent more job applications abroad than in 2024. A March 2025 poll by Nature of roughly 1,600 scientists found that over 1,200 said they were considering leaving the country. Europe is investing $565 million to make it a “magnet for researchers” and provide funding for scientists who relocate. The new golden age is also about embedding Trump’s xenophobia into the fabric of American science. The report complains of an “over-reliance on foreign students” that “creates a security challenge our institutions are ill-equipped to address” and that a “reliance on foreign talent sidelines American students.” This is, to put it mildly, nonsense. International students pay far higher tuition and often receive no financial aid. Their tuition dollars are what make it possible for American students to get financial aid. In the 2023-2024 school year alone, international students contributed $43.8 billion to the US economy and supported over 378,000 jobs. Those 1.1 million international students accounted for only six percent of the total number of students in higher education that year, but were such an economic engine that for every three international students, one job was created or supported. It’s impossible not to wonder whether part of Trump’s loathing for universities and their leading role in scientific research is that there is no way for him to corrupt the process and make money off it in the same way he can by giving millions and billions to Silicon Valley types who, in turn, give him millions in cash. There’s no way for his children to invest in universities that the government then gives no-bid contracts to, fattening the family’s bottom line, which is pretty much the Trump sons’ current venture capital practice. Trump and Katsios’s view of science is narrow, cramped, and wrong. We’re not in a crisis, we’re not a failed state. We’ve been a science superpower for decades, and the only thing that threatens that is Donald Trump. Tech bros are already living high off the hog in this administration. They don’t need any more of our tax dollars. Hopefully this new golden age never comes to pass. Thanks for reading Public Notice. This post is public so feel free to share it. Share We’ll be back with more tomorrow. If you appreciate today’s PN, please do your part to keep us free by signing up for a paid subscription. 🚀 Subscribe to PN 🚀 Thanks for reading, and for your support.

Jul 30 • 8:12 AM EDT • Science • publicnotice.co

The US ‘golden age’ science strategy: what Europeans need to know

The US has unveiled what officials claim is the most radical overhaul of the public R&D system in a generation, which if implemented could have significant implications for transatlantic research collaboration. Science: A New Golden Age derides universities as “legacy institutions” and instead wants to prioritise funding on technological challenges, new research labs and funding that follows individual scientists, rather than being linked to their institutions. “Too much of our research enterprise has come to serve itself rather than the scientists within it,” writes Michael Kratsios, director of the White House’s Office of Science and Technology Policy (OSTP), the only named author of the report. “Federal funding agencies should support a broader range of performers.” But some critics argue that the strategy is a smokescreen, using genuine problems in academia as an excuse to further weaken US universities, which US vice-president JD Vance has labelled “the enemy..”Even as it talks of a “golden age” for science, the White House has proposed halving the 2027 budget of the US National Science Foundation (NSF), and has put forward double-digit cuts for other funding bodies, such as the National Institutes for Health. It asked for similarly steep savings in 2026, but Congress stopped them going through. Science: A New Golden Age says success will be measured by the extent to which scientists are “free” to pursue the most “vital questions,,” painting academia as currently hidebound by bureaucracy, sluggishness and consensual conservatism. And yet the Trump administration is simultaneously planning new rules that will hand political appointees unprecedented powers to screen and cancel grants. The report has pretentions to be the successor to Science: The Endless Frontier, the seminal 1945 document in which presidential science advisor Vannevar Bush set out the case for post-war government funding of basic research, helping to spur the creation of funders such as the NSF. Even the title page font is the same. But it remains unclear if the latest report will leave anything like as lasting a legacy.Here, Science|Business explains some of the biggest proposed changes in Science: A New Golden Age, and how Europeans think it might change the landscape of their biggest science partner.Universities under fireA key target of the report are US universities, which it repeatedly suggests are outmoded as research institutions. It criticises the NSF for channelling resources “overwhelmingly to a single type of performer, the university-based, principal investigator-led research group..” Universities “extract” money from researchers’ grants to support “growing administrative bloat,” alongside legitimate uses. The Trump administration has been trying to cut the overhead costs in federal research grants that flow to universities. Instead, new institutions are being built. In May, the NSF announced it would spend $1.5 billion on two new so-called X-Labs, focused on scientific instrumentation and quantum systems. The idea is that they fill a niche in the landscape, tackling problems that are too big for a university lab, but too early stage for private start-up funding. Parallel with Europe?This shift to new research organisations parallels moves in Europe to set up new innovation agencies, such as Germany’s Sprind, the UK’s Advanced Research and Invention Agency, and the EU’s European Innovation Council. The Dutch and French governments are looking to set up their own entities too. There’s now an emerging consensus, evident in a number of new strategies, that public R&D needs to be shaken up, Charles McIvor, an economist at the OECD, has written in response to Kratsios’s plans. “What stands out for me across these strategies [in the US, Germany, South Korea and Japan] is that governments are realising that the old ways of delivering STI [science, technology and innovation] programming no longer works,” he said in a LinkedIn post. Metascience wins?The document is, at least on the face of it, also a big win for some policy thinkers in the US who want far more experimentation with new forms of research grant and institution.It name-checks a litany of new public R&D ideas, from focused research organisations and advance market commitments to “golden tickets,” which allow grant reviewers the power to hand applicants money without requiring the consensus of other review panellists.Related articlesEuropean researchers sound the alarm that Trump rule changes will hit cooperationFocused research organisations: what are they, and how do you set them up? NIH turmoil risks reciprocal EU-US access to health research funding In addition, every federal research funding agency should set up a metascience unit, the strategy says, “with authority to run controlled experiments on review and funding mechanisms.” The UK has already set one up, the strategy points out. This mirrors recommendations to the European Commission. In 2024, a report led by former Portuguese science minister Manuel Heitor also advised the EU to set up an “experimental unit” to test out new methods of funding research. So far, however, Brussels hasn’t put forward any plans to do so. Bypass universitiesBut there’s a worry that the Trump administration is using the metascience movement to justify an overhaul of public R&D that punishes universities, which it sees as centres of political resistance. Last year, it threatened to cut Harvard University’s federal funding unless it hired and admitted a “critical mass” of new faculty and students to create “viewpoint diversity” across campus. It’s also attempted to strip academics of funding for working on politically forbidden areas, like LGBTIQ people’s health.The new strategy appears to be a “move to bypass the power of universities full stop and allow funders and political bureaucracies to handpick the projects and people who will execute them,” said Jean-Claude Burgelman, a former senior official in the Commission’s research directorate, on LinkedIn.The EU’s science counsellor in Washington, Florent Bernard, wrote that the plans risk diverting public research funding so that it “solely serves private interests.” “Who, if not independent universities, will do research that demonstrates the impact of tobacco on lung cancer or the role of human activities in our current climate crisis?” he wrote.Should we take it seriously?“I would view the overall document as a bad faith argument,” said Cole Donovan, director of science policy at the campaigning group Stand Up for Science, and a former OSTP official. “I don’t see the project itself as something that can be isolated from the broader attack on the system.” He thinks the argument that academia has become dysfunctional and in need of radical reform is being deployed as part of a “PR argument” to legitimate moves against US scientists. The strategy presents ideas like metascience units as new, whereas there were moves to set them up at the NSF during the previous administration of Joe Biden, Donovan said. The other caveat here is that the OSTP has limited power to carry out any of these recommendations. While Kratsios has issued a memo to research agencies telling them to implement the recommendations in the report, he doesn’t have direct budgetary control. “As a former OSTPer myself, this does not seem like a document that is realistic,” said Donovan.

Jul 30 • 8:00 AM EDT • Science • sciencebusiness.net

Structural alignments to design functional RNAs

Nature Computational Science - A new method designs RNA sequences by learning from alignments of structurally similar molecules, producing aptamers and ribozymes that are experimentally validated.

Jul 29 • 8:00 PM EDT • Science • nature.com

Hollywood stars who took method acting very seriously

Jul 29 • 6:47 AM EDT • Entertainment • usatoday.com

New microwave frying method could make french fries much healthier

A new cooking method could make French fries crispier in less time while significantly limiting how much oil they absorb. Researchers propose combining microwave heating, which keeps oil out, with conventional frying, which provides the crunch consumers expect.

Jul 28 • 8:00 PM EDT • Science • sciencedaily.com

Biodegradable implant can deliver targeted cancer immunotherapy while protecting healthy tissue

Scientists at Houston Methodist Research Institute have developed a biodegradable implant designed to deliver cancer-fighting immunotherapy drugs directly into tumors over an extended period, a strategy ...

Jul 27 • 4:50 PM EDT • Health • phys.org

When It Comes to Fusion, Materials Matter

Fusion at high temperatures powers the sun and, if harnessed, could provide a potential source of energy here on Earth. But controlling fusion reactions has other benefits. The process also generates subatomic particles called neutrons that are used in a range of applications spanning medicine, research, and national security. Now, scientists at the University of California, Davis (UC Davis), and the Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab) have found that the materials surrounding a fusion reaction can dramatically increase how often it occurs, particularly at low energies where fusion is rare. The study was published July 18 in Nature Communications. Their approach sets up a way to study and engineer nuclear reactions within solid materials, opening a new field of “materials-driven fusion.” Instead of designing materials just to survive the harsh conditions of fusion, researchers might be able to design materials that boost the reaction in specific conditions, similar to the way catalysts speed up chemical processes. “It gives you a new knob to turn that you didn’t have before,” said Arun Persaud, head of the Fusion Science & Ion Beam Technology group in Berkeley Lab’s Accelerator Technology & Applied Physics (ATAP) Division. “If we understand this effect better, it opens the door to engineering new materials that would affect the fusion rate under certain conditions. Someday future progress might enable more compact and efficient neutron generators, which have all kinds of applications, like cargo screening, planetary science, and medical therapy and imaging.” In the experiment, researchers used two different methods to pack deuterium, a heavy form of hydrogen atoms that is often used in fusion, into thin foils of palladium and titanium. They then fired a beam of deuterium ions at the foils at different energies and measured how often fusion happened. Then they compared the rates from the different materials and methods with the “bare” fusion reaction (not in a material). The team found that fusion rates depended on how the deuterium was loaded into the metal foils. The biggest effect was at the lowest energies, below 2.5 kiloelectronvolts (keV), where theory predicts fusion rates drop off sharply. Instead, researchers found a surprising plateau: Some samples showed elevated fusion rates roughly a quintillion times higher than bare fusion reactions. (A quintillion is a 1 followed by 18 zeroes.) Researchers are not exactly sure why that’s happening, though they have some ideas and ways to test them. The electrons and defects within the material might partially shield repulsive electrostatic forces between deuterium nuclei, making it easier for them to get close together and fuse. Tuning the electronic structure, defects, and composition of materials could help make nuclear reactions happen more readily. “It comes down to better understanding the mechanism so that we can try to enhance it,” said corresponding author Jeremy Munday, a professor at UC Davis. “We’ve seen that we can increase fusion rates, but what is the limit? Can we bring it to lower temperatures or energies? There’s obviously a lot of interest and excitement about fusion, so if there’s something we can learn about the physics at these lower energy scales, maybe there’s something we can translate to other areas of nuclear science.” The team plans to explore a wider range of materials and continue probing the unexpected fusion plateau at lower energies. Their work establishes a reproducible experimental platform to study how solid materials influence nuclear reactions, creating a new area of research that links fusion science with materials science and chemistry. “The work shows conclusively that the material environment where fusion occurs at low temperatures is an active participant rather than a passive container,” said Cameron Geddes, director of ATAP. “That adds a new dimension to fusion research.” This work was funded by the U.S. Department of Energy’s Advanced Research Projects Agency-Energy (ARPA-E). ### Lawrence Berkeley National Laboratory (Berkeley Lab) is committed to groundbreaking research focused on discovery science and solutions for abundant and reliable energy supplies. The lab’s expertise spans materials, chemistry, physics, biology, earth and environmental science, mathematics, and computing. Researchers from around the world rely on the lab’s world-class scientific facilities for their own pioneering research. Founded in 1931 on the belief that the biggest problems are best addressed by teams, Berkeley Lab and its scientists have been recognized with 17 Nobel Prizes. Berkeley Lab is a multiprogram national laboratory managed by the University of California for the U.S. Department of Energy’s Office of Science. DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science.

Jul 23 • 11:00 AM EDT • Science • newscenter.lbl.gov

Google introduces new ‘selfie video’ sign-in method

Google Accounts are gaining a new “selfie video” sign-in method that can be handy if you lose your phone or passkeys.

Jul 23 • 9:00 AM EDT • Technology • 9to5google.com

CMS appeals court ruling on Medicare Advantage star rating methodology as insurers file lawsuits

The agency announced its appeal of a court ruling it lost to Clover Health, which resulted in the agency recalculating the grades it gave to the payer’s Medicare Part C plans. Other insurers are now asking for the same redo, spurring CMS to appeal the initial ruling.

Jul 23 • 7:56 AM EDT • Health • healthexec.com

A business system helped tame summer chaos in my home

I tried the Kanban method with my kids to make summer run more smoothly in our house. It's working.

Jul 22 • 6:07 PM EDT • Business • businessinsider.com

Rice joins Department of Energy’s Quantum Science Center to Advance QEC Research

Rice University joins the DOE Quantum Science Center to research quantum error correction methods for future fault-tolerant quantum computing systems.

Jul 22 • 5:12 AM EDT • Science • thequantuminsider.com

Experts agree at landmark event that simulation should be built into health system

On 15 June 2026, over 80 representatives from simulation societies, ministries of health, hospitals, universities, international organizations, professional associations and industry partners met at the WHO Academy in Lyon for a joint event of WHO and the Society for Simulation in Europe (SESAM). Together they tackled a pressing question: how can simulation move from isolated initiatives to systematic integration within health systems? The consensus was clear: simulation is no longer a niche educational tool. Beyond training, it strengthens health systems by improving quality of care, patient safety, workforce preparedness, team performance and organizational resilience.Participants agreed the evidence for simulation’s value no longer needs to be demonstrated, but that implementation remains fragmented and too often dependent on individual local champions. Bridging that gap, they said, means both generating further evidence and raising awareness among decision-makers.Discussions pointed to a shared path forward. To achieve scale and lasting impact, simulation must be embedded in national policies, workforce development plans, education systems and financing mechanisms. No institution can do this alone; stronger collaboration between governments, health institutions, academia, professional societies, international organizations and industry partners will be essential.“At the WHO Academy, we see simulation not simply as a training methodology but as a strategic tool for capacity-building, workforce readiness and stronger health systems,” said Dr Bart Janssens, Unit Head, Health Learning and Capacity Building. “This event is not only about discussion; it is about moving from ideas to action.”As health systems worldwide face workforce shortages, growing complexity of care and rapidly evolving competency needs, participants concluded that the question is no longer “Why simulation?” but rather how to scale it, how to sustain it, and how to ensure it becomes an integral part of stronger health systems.Looking aheadThe event marked the beginning of a collaborative effort rather than the end of a conversation. Over the coming weeks, WHO and SESAM will consolidate the discussions, recommendations and priorities that emerged, with a joint WHO–SESAM report to be published soon.

Jul 20 • 8:00 PM EDT • Health • who.int

Shaky political "science": breakdown of the peer review process

[This article is the latest in our “Shaky Political Science” series. In our 38 page report, “Shaky political ‘science’ misses mark on ranked choice voting,” released in December 2025, we examined over 40 studies focused on ranked choice voting (RCV). Many of these studies suffered from puzzling research methodologies, poorly constructed surveys, unrealistic simulated elections, cherry picked data and faulty analyses that often were contradicted by results from real-world elections (a link to our full paper is here). Here are links to the first four articles in our series: the first one summarizing the overall results of our report; the second one analyzed a study co-authored by University of Minnesota academic Larry Jacobs, which was one of the most error-prone of all the research we reviewed in our report; a third article showing an admirable example of two political scientists holding two other political scientists accountable for their flawed, sloppy research; and a fourth article that analyzed seven studies sponsored by New America’s political reform program that deployed flawed methodology based on “simulated” elections instead of real-world elections, which when combined with some basic misunderstandings of RCV, produced odd and misleading results]. In this fifth article in our “Shaky Political Science” series, we examine two flawed studies on the impact of RCV on voter turnout authored by San Francisco State University professor Jason McDaniel. McDaniel’s research in these two papers stands out for its puzzling methodology, inadequate and cherry-picked data, and faulty analyses that not only misunderstands ranked choice voting but reflects a basic misunderstanding of politics in general. The first of the McDaniel studies actually passed through a peer review process and then was subsequently published by the Journal of Urban Affairs, despite its obvious errors. It is perplexing that a jury of peer political scientists did not catch the errors and send it back to McDaniel for a rewrite or outright rejection. This calls into question the credibility of the peer review process itself. The peer review process is supposed to represent the intellectual pinnacle of the profession – a way for academics to certify the quality of each other’s work, and to act as a check against sloppy research. In the case of the McDaniel study, the peer review process failed. Yet his flawed study has been cited dozens of times by other political scientists in their own flawed works — an unvirtuous circle of academic research. Here is the first Jason McDaniel study that we analyzed: “Writing the Rules to Rank the Candidates: Examining the Impact of Instant-Runoff Voting on Racial Group Turnout in San Francisco Mayoral Elections,” by Jason McDaniel, 2016, Journal of Urban Affairs. This study covered San Francisco’s use of ranked choice voting (RCV) in mayoral elections, purporting to show that RCV reduces voter turnout overall, increases voter errors, and has a negative impact on “marginal populations,” i.e. racial minorities, mainly as the result of the alleged complexity of RCV asking voters to rank candidates and having to be familiar with multiple candidates and related dynamics. McDaniel reached these conclusions by examining five San Francisco mayoral elections taking place in odd years (i.e. where there are no federal or state races on the ballot) from 1995 to 2011, comparing three earlier non-RCV races (in 1995, 1999 and 2003) with the later two RCV races (in 2007 and 2011). Only two RCV races were studied, and as McDaniel acknowledged, only the contest in 2011 was “competitive” (that contest in 2007 was the first mayoral election using RCV, and incumbent mayor Gavin Newsom won easily in the first round of counting, earning 74% of first choices and far ahead of the second place candidate who had just 6.3% of first choices). Yet even the allegedly competitive contest in 2011was won by an incumbent with a landslide margin of nearly 20 points. No other elections were studied by McDaniel, even though San Francisco elects 17 other offices besides mayor with RCV, including the 11 seats on the Board of Supervisors (the name for the city council) in even years, and six other citywide offices in odd years. Previous academic research has found that competitive elections can stimulate greater voter involvement and higher turnout. For unexplained reasons, this study ignored at least 34 other RCV races between the years 2004 to 2011, many of which were very competitive and had high voter turnout. Instead, McDaniel’s analysis based its conclusions on data from only a single, marginally-competitive mayor’s race using RCV. These 2007 and 2011 mayoral elections were the only two RCV elections that McDaniel used as the sole basis for his small data set to determine the impact of RCV on voter turnout. Despite having no meaningful data to inform his study, McDaniel nonetheless concluded that RCV lowered turnout when compared to the previous three mayoral non-RCV elections using two-round runoffs. Then, using the same inadequate database of San Francisco elections, McDaniel also found that “Instant-runoff voting is associated with a significant decline in Black voter turnout and White voter turnout…On average, Black voter turnout decreases by 18 points and White voter turnout decreases by 16 points …” But how could he credibly arrive at that conclusion when his study was based on voter turnout in two RCV contests that were not even remotely competitive? Beyond that, McDaniel tacitly admits that the key determining factor driving Black voter turnout was not RCV vs non-RCV elections, but the presence of a viable Black candidate. McDaniel wrote, “Black voter turnout was about 17 percentage points higher for the two elections that featured an African American candidate compared to the three elections that did not” — but one of those three elections did not use RCV. The same dynamic was present for White voter turnout, in which higher turnout was not correlated with RCV vs non-RCV elections, but the presence of a viable White candidate. Beyond that, McDaniel’s voter turnout results, whether correlated with the race of the candidates or RCV vs non-RCV elections, showed no clear patterns. In his Figure 1, he shows low Asian voter turnout in the non-RCV elections in 1999 and 2003 when there was no viable Asian candidate running, but in the 2007 mayoral election using RCV, there is still no viable Asian candidate, yet Asian turnout increases dramatically. For Latinos, voter turnout is virtually the same in 1999 (no viable Latino candidate, non-RCV elections), 2003 (leading Latino candidate, non-RCV elections), 2007 (no viable Latino candidate, RCV elections) and 2011 (leading Latino candidate, RCV elections). Meanwhile White voter turnout increased dramatically from a low in the 2007 mayoral election, in which the leading candidate was a white incumbent, to the 2011 election in which there were no leading white candidates that finished any higher than sixth place with 5.6% of the vote. Clearly other factors were determining voter turnout than either the race of the candidates or RCV vs non-RCV elections. Despite these inconsistent findings, McDaniel boldly marches forth to render conclusions about the impact of RCV on different groups of racial voters, even though his conclusions are not remotely supported by his data. This looks like the worst kind of “data cherry picking” to cover up a puzzling conclusion based on a poor data set involving only two RCV elections, neither of which were remotely competitive. McDaniel’s cherry picking didn’t stop there. In calculating voter turnout for the three non-RCV mayoral elections in 1995, 1999 and 2003, he failed to mention that in each of these years there was a two-round runoff election, with a first round election in November in which no candidate garnered a winning majority of the vote, followed by the decisive runoff in December. So there were two non-RCV elections in each election year. But McDaniel only decided to include one of the two elections in his data set, apparently the December runoff in each year (which had higher turnout in two out of the three mayor’s races, and lower turnout in the third). So he ignored the November 1995 election, the November 1999 election when turnout was only 45 percent, and the November 2003 election when turnout was only 45.7 percent. This is flawed methodology based on blatant cherry picking, since McDaniel simply omitted three elections worth of data that did not fit within his frame. His study should never have made it through a peer review process, and it is an embarrassment to political science that not only was it approved for publication, but it has been uncritically cited by dozens of other political scientists. Share A “study” without wider context or credible data Lacking a data set that included even a single competitive RCV mayoral race, McDaniel declared that RCV lowered voter turnout in 2011, when turnout was 42.5 percent. But he also ignored -- or did not realize -- that voter turnout in mayoral elections during 2011 had sharply declined in all big cities, including far more steeply in nearby Los Angeles and other cities. In fact, San Francisco’s election in 2011 had the second highest turnout of any mayoral election in the nation’s 22 largest cities from 2008-2011. Was 2011 just a particularly low turnout year all across the country, perhaps because the country was still reeling from the aftermath of the housing market collapse in 2008-2010? McDaniel ignored this factor and did not search for alternative explanations beyond his flawed thesis. Furthermore, while McDaniel suggested that RCV leads to more “overvotes” – which is an invalidated ballot in which a voter, in either a non-RCV or RCV race, makes a mistake and selects two candidates for a single choice – he failed to address that in the June 2012 US Senate primary contest, which used the typical “one-choice” plurality method and did not use RCV, there was more than five times as many overvotes in San Francisco and Oakland than in the RCV mayoral elections in those cities. Additionally, turnout had been significantly higher and more representative in RCV elections for the San Francisco Board of Supervisors races -- that McDaniel didn’t even bother to study -- as compared to previous “delayed two-round runoffs” for those offices, often higher by as much as 40% in the RCV races. Perhaps the most surprising irony was that an earlier study co-authored by McDaniel (Overvoting and the Equality of Voice under Instant-Runoff Voting in San Francisco by Francis Neely and Jason McDaniel, 2015, California Journal of Politics and Policy) found that overvotes are often more common in lower-income precincts, but that the pattern of overvoting is similar in both RCV and non-RCV contests. Wrote Neely and McDaniel: “[Overvote] errors appear to be a function of complexity in general and not IRV per se…. the pattern of overvoting is similar in both IRV and non-IRV contests…Even among votes cast in a top-of-the-ticket race like U.S. Senate, overvoting occurs in an uneven fashion” (IRV, or ‘instant runoff voting,’ is another name for ranked choice voting in single-winner contests). So McDaniel not only contradicted his own conclusion in his earlier study with Neely, but the earlier study had been an important corrective for one of the most frequently made mistakes made by anti-RCV political scientists – a continual failure to provide crucial context by pairing a comparative analysis of real world RCV elections with an analysis of real world plurality or other electoral methods. Unfortunately McDaniel’s earlier study does not get cited much by other researchers, and McDaniel did not even cite it in his own flawed study analyzed above. Incredibly, McDaniel cherrypicked McDaniel, even as his flawed study has been cited dozens of times. Despite being a textbook example of poor political “science,” featuring both inadequate as well as cherrypicked data, the shelf life of McDaniel’s study has been extended endlessly by other political scientists and media outlets who have cited it uncritically. Equally troubling, the Journal of Urban Affairs put this paper through its peer review process and published it despite its numerous flaws. McDaniel gets it wrong, Part II Not content with producing one shoddy, confused paper, McDaniel produced another one a few years later, here is the link: Electoral Rules and Voter Turnout in Mayoral Elections: An Analysis of Ranked-Choice Voting by Jason McDaniel. San Francisco State Univ. (McDaniel, 2019). In this paper, McDaniel extended his previous flawed research focused on San Francisco, about voter turnout and voter impact, to multiple RCV cities through the 2018 elections. In his data set he included San Francisco, Minneapolis, St Paul, Oakland, Berkeley, San Leandro and Santa Fe. He then compared their turnout in mayoral elections to non-RCV cities, and to mayoral elections in those cities held before first RCV usage, and concluded “a significant decrease in voter turnout of approximately 3–5 percentage points in RCV cities after the implementation of RCV.” But he replicated many of the same mistakes as his first study presented above. While in this study McDaniel attempted to distinguish between various factors, such as odd year vs. even year elections, competitive races vs. noncompetitive, contests with open seats and other factors, the analysis is superficial and inadequate. He attempts to incorporate so many often-conflicting variables that his conclusions are once again unsupported by the actual data, and ultimately unconvincing (this second study never underwent a peer review process). For example, McDaniel declared that for RCV cities “in elections that are more competitive than average (margin of victory less than 20%), there is no significant RCV effect on voter turnout.” Yet McDaniel is a professor in a city, San Francisco, in which the 2018 special election using RCV to fill a mayoral vacancy was exceedingly close, decided by a margin of only one percentage point, and resulted in the second highest turnout in San Francisco history for a mayoral election. Illustrating the complexity involved in assessing the critical factors in turnout, that special election was held on the same election day as federal and state offices, which tends to boost turnout. Yet more voters participated in that RCV mayoral election than voted on the same day in the non-RCV primary for governor in which former San Francisco mayor Gavin Newsom was running. Even more puzzling, in this study McDaniel inaccurately cited his own previous study from 2015 with Neely. McDaniel wrote, “Neely and McDaniel (2015) examine individual ballot image files within a natural experiment, and find higher rates of ballot errors in RCV elections compared to non-RCV elections” (emphasis added). However, we quoted from that 2015 study several paragraphs above, and in actual fact Neely and McDaniel actually concluded the opposite -- that the pattern of overvoting – which is the most common form of ballot error – is similar in both RCV and non-RCV contests. McDaniel also ignored the fact that in Bay Area RCV elections held in even years – at the same time as federal and state elections, when turnout is highest -- the “undervote” (that is, the dropoff in ballots cast for governor or mayor) has declined, which contradicts his thesis that the act of ranking ballots in RCV elections is too complex and presents a barrier for certain demographics of voters. To his credit, McDaniel actually acknowledged another contradiction in his own paper, which found a negative RCV turnout effect in some odd-year elections but not others, admitting that “may present a challenge to the theory that increased complexity [from RCV] will have a marginal negative effect on voter turnout.” But he tried to wallpaper over that contradiction by blaming it on an unlikely source -- bad election administration. McDaniels wrote, “This would suggest that the negative impact of RCV on voter participation may be alleviated by high quality election administration,” without presenting any data or even anecdotes to support such an unfounded theory. While competent election administration of any election, whether RCV or non-RCV, is crucially important, there is no credible research that supports the far-fetched notion that the quality of election administration has much of an impact on voter turnout in US elections, whether using RCV or otherwise. Upgrade to a $5 subscription The unvirtuous circle of academic research It is puzzling how McDaniel’s first study could have survived the peer review process for the Journal of Urban Affairs. The mistakes in McDaniel’s first study above should have been obvious to anyone with a basic understanding of ranked choice voting as well as elections in general, and elections in San Francisco specifically. It undermines faith in the credibility of the peer review process to think that a jury of peer political scientists did not catch the egregious errors and reject McDaniel’s sloppy research and paper. And it remains a black mark on political science that this thoroughly discredited study has been cited dozens of times by other researchers. Indeed, in our research paper it became apparent that many political scientists cite each other’s flawed research to pad their list of citations and to legitimize their own flawed research, creating an unvirtuous circle of political science. More broadly, McDaniel’s voter turnout studies, like other studies evaluating RCV’s impact on turnout, lacked a recognition that no credible opinion or research can claim that RCV increases voter turnout merely because so many voters are excited to vote for their favorite candidates instead of “lesser evil” candidates without worrying about spoilers. Instead, with respect to turnout, the advantage of RCV has always been that, in most places where it has been used, it has eliminated a pre-November primary or post-November runoff, which usually saw about half the turnout of the November general election. This is especially true during even years when there are state and federal elections on the ballot which substantially drive turnout more than local contests. Any study that does not adequately account for this non-November primary/runoff vs November general election dynamic, or odd year vs even year election factors, is simply not credible. Both of McDaniel’s studies largely failed on those grounds. Steven Hill and Paul Haughey Share Upgrade to a $5 subscription Thanks for reading DemocracySOS…your digital portal for the pro-democracy movement. Subscribe for only $5 per month to receive full benefits and to support our work. Subscribe

Jul 20 • 9:29 AM EDT • Science • democracysos.substack.com

An ordinary laptop solved a problem thought to require a quantum computer

A quantum problem once described as impossible for classical computers has now been solved using relatively modest hardware. Researchers used tensor networks to compress the overwhelming wave function created by hundreds of entangled qubits, allowing some calculations to run on a laptop. Their results matched both theoretical predictions and simulations performed with a quantum computer. The method could open new paths for exploring quantum dynamics and materials.

Jul 19 • 8:00 PM EDT • Science • sciencedaily.com

The New York Times

Packing light is a science, and if you're the list-making type, the 5-4-3-2-1 method is a great place to start. Here’s what it suggests for a weeklong trip: https://nyti.ms/4ffe1pc

Jul 19 • 5:20 PM EDT • Science • facebook.com

Scientists found two powerful new ways to destroy forever chemicals

Scientists are testing two promising ways to destroy PFAS, the stubborn “forever chemicals” that can accumulate in water and resist normal treatment. One method uses collapsing vapor bubbles to generate extreme heat and reactive molecules, while the other uses cold plasma and rising gas bubbles to pull PFAS to the surface and break them apart.

Jul 19 • 8:00 AM EDT • Science • sciencedaily.com

Roberts United Methodist Church hosts Small Business and Entrepreneurship Round-Up

BATON ROUGE — The Roberts United Methodist Church held its Small Business and Entrepreneurship Round-Up event on Saturday, connecting residents to local businesses.

Jul 18 • 8:00 AM EDT • Business • wbrz.com

Two more insurers sue CMS over Medicare Advantage star rating methodology

The lawsuits come days after Elevance Health filed a complaint of its own, asking a court to compel the Centers for Medicare & Medicaid Services to remain consistent in how it doles out stars.

Jul 16 • 7:06 AM EDT • Health • healthexec.com

Microsoft Entra ID gets passkeys default authentication starting September

Microsoft has announced that passkeys will become the default authentication method for the Entra ID enterprise identity service starting September 2026.

Jul 14 • 8:49 AM EDT • Technology • bleepingcomputer.com

Algorithm allows cancer patients to avoid CT scans for pulmonary embolism

There has been increased interest in finding alternative methods to diagnose pulmonary embolism in this patient population.

Jul 13 • 10:51 PM EDT • Business • radiologybusiness.com

Virginia Climbs to No. 3 in CNBC's 2026 Top States for Business — Here's What Moved the Needle

Gov. Spanberger credits strategic investments and affordability gains, while a methodology change rewarding infrastructure does some of the heavy lifting.

Jul 11 • 6:52 AM EDT • Business • alexandrialivingmagazine.com

Machine Learning for Life Scientists: A Practical Methods Guide

Learn practical machine learning methods for life science research, covering supervised learning, model evaluation, and how to choose the right approach.

Jul 9 • 8:00 AM EDT • Science • technologynetworks.com

Science and religion don’t mix? Let’s test the evidence

I suggest a simple use of the “scientific method” to support the historical and current cooperation of science and religion.

Jul 8 • 8:00 PM EDT • Science • aleteia.org

A shoebox-sized satellite could expose hidden nuclear weapons in space

There’s never been a good method to check for violations of the Outer Space Treaty’s prohibition of nuclear weapons in space.

Jul 8 • 11:11 AM EDT • Science • sciencenews.org

Stop Shaming Yourself Into Better Habits. Science Says This Emotion Works Better

New research says joy, not shame, is what makes better habits stick. Here's the 5-step method two UBC psychologists use to build them.

Jul 8 • 5:20 AM EDT • Science • forbes.com

Academic Excellence Award Winner

Academic Excellence Award Winner Erin shares her experiences as a Public and Community Health Major, with double minors in Legal Studies and Health Policy and Management:"I came to Ithaca from the suburbs of Boston, Massachusetts knowing that I wanted an education that would allow me to change the world in a positive light. Admittedly, I was unaware when choosing the public health major just how much of an impact I could make, but through my experiences in this rigorous program, I know public health is where I am meant to be. Being a public health major during the COVID-19 pandemic was a unique experience. My education granted me the opportunity to work on and off campus with different populations to provide support during the pandemic. Professor Srijana Bajracharya was my professor for Research Methods in Health. She encouraged her class to create research projects that would benefit our communities. She was a mentor for me and helped me find my passion in research, which I have brought with me to my job as a research assistant for Rescue - The Behavior Change Agency. I thank Professor Bajracharya for her guidance and support throughout my time as a public health student."

Jul 8 • 2:44 AM EDT • Health • ithaca.edu

Making the ‘invisible’ visible: How high-speed movies could change the way scientists study disease

An advanced imaging method captures chemical processes in living organisms in real time, allowing researchers to observe biology as it happens.

Jul 7 • 4:37 PM EDT • Science • stories.tamu.edu

Elevance Health sues CMS in latest challenge to Medicare Advantage star rating methodology

The complaint accuses the Centers for Medicare & Medicaid Services of failing to properly recalculate its grades for Medicare Part C plans, something it promised to do in June.

Jul 7 • 7:27 AM EDT • Health • healthexec.com

125-million-year-old 'pregnant' fossil displays alien like reproduction method which has intrigued scientists

Moms are capable of magic that is more than just maternal. Nature has imbued its most special being with surprisingly strange ways of reproduction and care for their babies.

Jul 7 • 3:15 AM EDT • Science • timesofindia.indiatimes.com

Windows 11 will soon be able to reinstall itself and your drivers without a USB drive via new 'Cloud Rebuild' recovery method

A new recovery option coming to Windows 11 will let you reinstall the OS and your drivers using the internet without a USB key, even when Windows itself is unbootable.

Jul 6 • 8:18 PM EDT • Technology • windowscentral.com

Nielsen eyes further methodology changes ahead of football season

It appears as if Nielsen is preparing to find yet another way to keep sports viewership trending upward ahead of the upcoming football season. The audience-measurement firm, whose data is treated as the gold standard within the television business and is the currency by which networks sell advertising to media buyers, plans to formally roll…

Jul 6 • 10:30 AM EDT • Sports • sports.yahoo.com

New workflow tool gives scientists a clearer view of how DNA is regulated

Researchers from the Cancer Science Institute of Singapore (CSI Singapore) at NUS have developed a new method that allows scientists to better understand how DNA is organized and regulated inside cells. ...

Jul 6 • 8:40 AM EDT • Science • phys.org

AI and Data Science in Life Science Research: A Practical Guide for Scientists

Discover how AI and data science are reshaping life science research, covering genomics, imaging, ML methods, data management, and LLM tools for scientists.

Jul 6 • 8:00 AM EDT • Science • technologynetworks.com

First experiment to thicken Arctic ice with seawater shows promise — but there’s a big catch

Researchers recently performed the first scientific test of sea ice thickening in the field, but there remains a big question mark over how scalable this method is.

Jul 6 • 5:45 AM EDT • Science • livescience.com

Scientists devise new method for tracing environmental PFAS contamination better

Perfluoroalkyl and polyfluoroalkyl substances (PFAS) are a class of synthetic chemicals widely used in industrial processes and consumer products because of their resistance to heat, water and oil. However, ...

Jul 1 • 6:00 PM EDT • Science • phys.org

ASU scientists unveil new methods to extract reliable truth from imperfect data

Scientists at Arizona State University are advancing how they interpret complex, imperfect data — challenging long-standing assumptions in fields ranging from imaging to cellular biology. In two papers published in Nature Communications and Proceedings of the National Academy of Sciences, the team introduces fundamentally new approaches to solving “inverse problems,” where researchers work backward from noisy observations to uncover the underlying reality.

Jul 1 • 12:40 PM EDT • Science • news.asu.edu

UC Davis to Set Standard for Measuring Airborne Nanoplastic Health Risks

UC Davis researchers have received a nearly $4 million grant NIEH to develop the world’s first standardized method for measuring and describing the neurotoxicity of airborne nanoplastics.

Jul 1 • 12:00 PM EDT • Health • ucdavis.edu

This satellite constellation transformed earth science by creatively tuning in to GPS signals

Governments and companies have launched similar constellations to use the method, called GNSS-R, to monitor and forecast wildfires, flooding and more.

Jul 1 • 9:13 AM EDT • Science • news.engin.umich.edu

Marketers pivot to TikTok, YouTube to target Gen Z shoppers

Top marketers are shifting their platform priorities to target Gen Z and Gen Alpha. They are using Pinterest, YouTube, AI tools, and other methods.

Jul 1 • 8:00 AM EDT • Business • businessinsider.com

Computer scientists develop a new AI tool that rivals AlphaFold 3 in mapping RNA

The method, called RNAbpFlow, was described in a study published on June 30 in Nature Methods, among the most selective journals in computational life sciences.

Jun 30 • 9:15 AM EDT • Science • news.vt.edu

Nokia, SAP and Microsoft Enter Strategic Multi-Year Agreement to Advance Cloud- and AI-Driven Business Transformation

Nokia will accelerate its enterprise transformation using RISE with SAP Methodology, with SAP S/4HANA hosted on Microsoft Azure.

Jun 30 • 9:00 AM EDT • Business • news.sap.com

Gaining biological insights through supervised data visualization

Nature Computational Science - This study introduces RF-PHATE, a supervised visualization method that preserves data structure while revealing biological patterns, enabling insights into disease...

Jun 29 • 8:00 PM EDT • Science • nature.com

Supreme Court to review the legality of mass voter purges in the weeks before an election

The Supreme Court will review the legality of mass voters purges in the final weeks before an election, as part of a larger case the justices are taking up examining the methods Arizona uses to keep non-citizens off the voter rolls.

Jun 29 • 10:11 AM EDT • Politics • cnn.com

This Baker’s Business Is Booming (and It’s Not Just Because of the Cannon Fire)

Justin Cherry’s breads are in demand this semiquincentennial, as is his knowledge of historical baking methods.

Jun 29 • 5:02 AM EDT • Business • nytimes.com

3 Traps Health Systems Fall Into When Trying to Improve Their Culture

Cultivating a positive culture is a priority for hospital leaders, but many are making avoidable mistakes. Myra Gregorian, Seattle Children's chief people and transformation officer, outlined some of these common blunders — such as not involving frontline staff in decision making and assuming that simple communication methods are sufficient.

Jun 28 • 9:44 AM EDT • Health • medcitynews.com

AI Is Helping Small Businesses Get More Done, But It’s Far From The Only Productivity-Booster Helping Them Expand

Getting more done in less time is easier than ever for solopreneurs and small business owners, thanks to the ease of hiring contractors, using QR codes, touchless technology and other affordable methods.

Jun 27 • 4:33 PM EDT • Business • forbes.com

After 80 Years, Mathematicians Give Famed ‘Erdős Method’ an Upgrade

Decades ago, Paul Erdős used randomness to illuminate the vast and weird world of networks. Now mathematicians are making his technique even more powerful.

Jun 26 • 11:26 AM EDT • Technology • quantamagazine.org

How should European scientists respond to the US AI kill switch?

Earlier in June, Europe’s worst fears of technological dependence were confirmed when the White House ordered the AI firm Anthropic to stop non-US citizens using its leading models. This kill-switch moment crystalised anxieties in Brussels that the continent, lagging the US on the creation of leading-edge AI models, is now a technological of vassal of Washington. The shock has specific implications for European scientists and universities. Some governments are now worried that with AI being integrated into labs, Donald Trump now has his finger hovering over an off switch for European science. “Having restrictions on this tool, it can have an impact on our own research,” said France’s research minister, Philippe Baptiste, at the VivaTech conference in Paris on June 18.Baptiste, himself a former academic, said that colleagues in mathematics had recently warned him they were now cut off from leading-edge US models, risking their work. “This model is not available anymore now because of the US restriction, and for the first time this had an impact on mathematics,” a field where large language models (LLMs) are making a significant contribution, said Baptiste. So, should European scientists avoid relying on US models in the future? Or would this be a self-harming overreaction? And how is AI being used in science, anyway? What happened?On June 12, it emerged that Washington, citing cybersecurity concerns, had ordered Anthropic to stop non-US citizens using two models: Claude Mythos 5, and Claude Fable 5, a version of Mythos but with guardrails to prevent abuse. Anthropic said Washington’s concerns were overblown. But forced to follow the order, yet with no way to check who was using the models, the company suddenly shut down access for everyone, US citizens included. There’s still no agreement on how to restore broad access. But last week, Bloomberg reported that select US companies, and the US government, still had access to Mythos despite the ban, but the EU’s cybersecurity agency Enisa had been shut out. Class division of researchersIn the longer term, access outside the US should be restored, said Marcel Salathé, co-director of the AI centre at the Federal Polytechnic School of Lausanne (EPFL), because a permanent restriction would be financially ruinous to US AI firms. “Even Trump will eventually budge to economic pressure,” he said.However, US AI firms might end up operating rather like banks, doing due diligence on users of their leading-edge AI models, he went on.European scientists are unlikely to fall foul of such checks, he said. But having a Chinese postgraduate in their lab, or doing a type of research the US disapproved of, could potentially result in access being denied. “It will create a sort of class division of researchers,” he said. More than frontier modelsHowever, successfully deploying AI in science is about far more than just having access to leading LLMs such as Mythos.Instead, many science-specific tools, most famously Alphafold, which predicts protein folding structures, require “far less” computing power to train than frontier models, well within the capabilities of European supercomputers, according to a recent analysis by the Arq Foundation, a Brussel-based AI think tank. Instead, tools such as Alphafold are possible because certain fields, like protein folding, weather prediction or astronomy, have large, clean, standardised datasets that can be used to train predictive models. Rather than compute, “data is the central constraint for AI for science,” the report says. For example, a less powerful physics model trained on CERN’s data “will be more valuable than the best model without certain data,” said Bengüsu Özcan, author of the report. European advantage?Europe could therefore steal a march by using its scientific data and infrastructure to create models US digital giants cannot. “They might actually match or go even beyond what these big [US] companies are doing,” said Özcan.Indeed, some European start-ups hope to create automated testing labs to create the kind of standardised data that could speed up the discovery of new materials. Materials scientists say there’s currently too little data to train models. AI scientistsHowever, even if the bottleneck for AI in science is often data, rather than compute, being at the mercy of the US for LLM access could still become a problem for European scientists. A new class of “AI scientists” based on leading LLMs is also emerging, Özcan’s report says.Unlike domain-specific tools like Alphafold, these try to automate day-to-day scientific work, by providing an overarching tool that coordinates specific models to synthesise existing literature, generate hypotheses or run analysis of data. The problem for Europe, however, is that these tools are sometimes based on US leading models. Google Deepmind’s AI Co-Scientist, for example, is built on Google’s Gemini LLM. Systematic failureThese scientific automation tools are still in their early stages, and still exhibit “systematic failures on scientific tasks,” Özcan’s report says. One of the problems is that the messy, day-to-day process of scientific discovery is largely not documented, meaning LLMs don’t have a good source of data to learn how scientists actually work. Meanwhile, some tasks, such as literature synthesis, don’t typically require access to leading edge models.However, the performance of AI scientific assistants could improve as companies such as Google pour resources into developing them. Rely on US“Unfortunately, for scientific assistants, there is not much we can do right now except rely on US frontier AI,” said Antoine Bosselut, a natural language processing expert based at EPFL. Chinese-built open models, which can run on local computers, lessening the risk of a shutdown, are touted as one alternative to US dependence. There’s also Mistral, once seen as Europe’s main AI hope, but the Paris-based company has seen its recent models fall behind in performance. But the Chinese alternatives are generally not as capable as US frontier AI models, said Bosselut, unless paired with fiddly, custom tools that allows them to act as independent agents. “Most scientists do not have the time,” he said. Don’t jump ship yetAlthough the kill switch moment is seen a warning shot for European scientists, it doesn’t mean labs should abandon US AI tools immediately. “I do not think the right response is simply to abandon US-based models and systems under the banner of sovereignty or independence,” said Mattias Björnmalm, secretary general of the Cesaer university association. “That would be an overreaction.”Related articlesEuropean sovereignty in AI requires ‘ugly trade-offs,’ say experts Robotic lab start-up makes case for €500M EU-funded materials testing facilityAI in science: is it useful? Instead, European researchers need to ask themselves whether they’re becoming dependent on technology that could be turned off in Washington, said Özcan. “They might not see this today, but they should really start asking this question,” she said. European researchers need a plan B, said Salathé. “I would recommend to every researcher, very proactively explore alternatives.”Own toolsIn addition, Björnmalm and others want European research institutions to develop their own scientific AI tools.Instead of signing AI deals with US digital giants, European universities should be using this money to create their own models, which may end up being superior for research, said Sabine Leonelli, an expert on the use of AI in science at the Technical University of Munich. “Universities in Europe seem to be happy to sign commercial contracts with US companies on the assumption [their AI tools] are better,” she said. But US frontier LLMs are typically opaque, and have been developed without independent scientific input, she said. “This is not good enough for science.”Last year, Swiss researchers released Apertus, an LLM designed to be completely transparent, from its development methods to its training data. The idea is that this makes scientific tools built on top of the model far more reproducible than with closed, commercial alternatives.“Europe needs more of this: serious capacity-building that gives researchers, universities and companies credible options,” said Björnmalm.

Jun 25 • 8:00 AM EDT • Science • sciencebusiness.net

Scientists have just unlocked the secrets of an ancient scroll torched by Mount Vesuvius

After a centuries-long struggle, scholars managed to read five feet of text, using machine-learning methods they hope can unlock further discoveries.

Jun 25 • 4:30 AM EDT • Science • washingtonpost.com

Can Bardella learn the Meloni method?

Also, in Thursday’s edition: Spain sues Commission, EEAS sec gen, Taliban

Jun 25 • 2:36 AM EDT • Politics • euractiv.com

Houston Methodist receives $110M donation, largest in health system’s history

The donation, made by The Brockman Medical Research Foundation, is the largest in the hospital system's history.

Jun 24 • 3:28 PM EDT • Health • houstonpublicmedia.org

2026 Short Course: Putting Social Science in Motion: Concept and Method (QMMR) -

Putting Social Science in Motion: Concept and Method (QMMR) Half Day Short Course | Register here 2026 APSA Annual Meeting & Exhibition — Boston, MA 1:30 pm – 5:30 pm This short course addresses both [...]

Jun 24 • 12:00 PM EDT • Science • politicalsciencenow.com

National Family Planning & Reproductive Health Association et al. v. Robert F. Kennedy, Jr. et al.

The National Family Planning & Reproductive Health Association (NFPRHA) and its member, the Family Health Council of Central Pennsylvania (FHCCP), sued the Trump administration to protect the integrity of the Title X family planning program. Title X is the country’s only dedicated federal program for family planning services. For more than 55 years, the program has provided access to effective contraceptive methods, cancer screenings, testing and treatment for STIs, and other preventive services, with priority given to patients with low incomes.

Jun 22 • 12:57 PM EDT • Health • aclu.org

Digital Health Institute welcomes French delegation to explore pathways to collaboration

The Houston Methodist-Rice Digital Health Institute recently welcomed Frank Marchetti, Consul General of France in Houston, and his team to discuss health care innovation and avenues for international collaboration.

Jun 22 • 8:00 AM EDT • Health • news.rice.edu

A cloud-based miniscope for neurosurveillance of brain health and disease in freely behaving animals

Nature Methods - A miniscope with cloud-based operation and multicontrast capabilities enables continuous recording of neuronal activity, hemodynamics or cellular dynamics over multiple days. This...

Jun 21 • 8:00 PM EDT • Health • nature.com

New Orleans East Hospital breaks ground on $10 million inpatient behavioral health unit

Before Hurricane Katrina made landfall in 2005, New Orleans East was home to a 40-bed inpatient behavioral health unit at The Pendleton Memorial Methodist Hospital—the same campus where LCMC Health’s

Jun 21 • 1:00 AM EDT • Health • nola.com

Researchers found a Wordle strategy that wins 99% of the time

Researchers developed a Wordle-solving strategy that succeeds 99% of the time by focusing on information gain rather than likely answers. The method uses Shannon entropy to identify guesses that reveal the most about the hidden word. Each guess is designed to slash uncertainty and narrow the possibilities faster. The result significantly outperformed more traditional Wordle tactics.

Jun 19 • 8:00 AM EDT • Science • sciencedaily.com

Why I Use a Business School Model to Teach History (Opinion)

Students who can see themselves in historical figures learn how to debate respectfully.

Jun 18 • 2:18 PM EDT • Business • edweek.org

Latvia pilots citizen engagement in research grant evaluations

Latvia has introduced an element of citizen engagement to the evaluation of nationally funded research grants. The aim is to both create more connections between science and society, and to improve the quality of its evaluations. The move comes as research funders across Europe are experimenting with ways to improve evaluation processes in the face of a sharpened focus on science’s impact on society. Evaluators of grant applications submitted to Latvia’s Fundamental and Applied Research Programme (FLPP), the country’s main research funder, will this year have the option of consulting citizen feedback on challenges the public thinks science should focus on to inform their decisions. “In recent years, both public discussions and policy-level debates in Latvia have highlighted the importance of demonstrating how publicly funded research contributes to society, the economy and the resolution of real-world challenges,” said a source at the Latvian Council of Science (LCS), which manages the FLPP. “At the same time, research institutions themselves expressed interest in improving the project evaluation framework while continuing to ensure that funding is awarded to the highest-quality projects,” the source added. The citizen input comes from a survey that was conducted between 25 February and 16 March 2025, to which 1,737 people responded. It gathered information on what the public views as problem areas for Latvia, and the role of science and technology in providing solutions to these problems. A summary of these responses has been included as an annex to the FLPP 2026 call for proposals that evaluators can refer to, purely in an advisory manner, when judging proposals. Results from the survey show that the main problem areas identified by the public were in healthcare and public health, followed by the development of new treatment methods and medicines, and then digital technology, data security and cyber security. At the bottom of the list was research aimed at acquiring new knowledge about the universe, matter and the laws of nature. Further analysis looked at the public view of the possible role of science in solving these problems. The survey charted 4,167 individual responses based on open-ended questions that were derived from the participants’ answers. The analysis again found that medical and health sciences topped the scoring, with 788 responses referring to the field. Humanities and the arts were bottom of the list, with 625. Digging further into the details, the survey suggests citizens are aware of and concerned about a number of research areas. This includes technologies and innovation to improve the environment or reduce pollution, the development of modern military technologies and cybersecurity tools, and the development and application of artificial intelligence, among others. “We hope this initiative will help strengthen public trust in science and create a more meaningful dialogue between researchers and society,” the LCS source said, adding that it offers benefits to researchers, evaluators and to the general public. More space for citizen engagement in evaluationsThere is a gradual but increasing use of citizen engagement in research evaluation processes around Europe, especially in healthcare, but it remains relatively rare, said Henry Sauermann, a professor at the European School of Management and Technology in Berlin and an expert in citizen science.“Given that we are at a point where citizen involvement is extremely limited, there is presumably space for more, but it's not that we should do it just because we want to do it,” he told Science|Business. He said some research lends itself better to having citizen input, and this usually tends to be on the applied end of the science spectrum where the public can offer useful feedback based on their experiences. He added that advising scientists on certain topics to study is also a useful approach, in the way that Latvia is doing. “The public does fund a lot of science, there's a lot of tax money going into this. We of course do want to preserve academic freedom, but it's also not unreasonable to incorporate more feedback or input from citizens where possible,” he said. Related articlesCitizen science: where, when, and how to let the public contribute to researchHow can Europe cope with a flood of AI-assisted research grant proposals?Data Corner: Horizon Europe’s AI, digital and data call success rate is 5.2%There are several ways of involving citizens in science funding. The most minimal way is having a few representatives on a panel, such as members of a patient group or union. The most direct way is crowdsourcing funding for specific projects. There is an increasing number of online platforms that allow the public to chip in to support scientific proposals.Sauermann studied this in a recent paper and found that it can have its uses, but it still is not clear if there are benefits to it. There are various assumptions linked to citizen engagement, for example that it increases public trust in science, or that it provides a representative view of what the public thinks about science. These are not necessarily true, Sauermann found. People who participate in engagement activities tend to already be very trusting of science, and, on the whole, it is generally the well-off and well educated who contribute, giving a narrow view of public opinion. On whether citizen input can help manage the increasing number of proposals that are being submitted due to assistance from AI, Sauermann is more sceptical. “The obvious answer to the flood of AI-written proposals is AI-driven evaluation,” he said, adding that it doesn’t mean citizen engagement shouldn’t be a part of evaluations in a well thought-out manner. Southern Denmark’s successful approachOne successful example of citizen engagement in science evaluations was implemented in southern Denmark. Between 2019 and 2025, citizens in the region were invited to vote to fund one of five pre-selected projects in the field of healthcare. The project, called A Healthier Southern Denmark, was a collaboration between regional authorities, the University of Southern Denmark, and two media partners. Over the seven years, there were 75,000 votes and significant public engagement online and on social media. “It was a bit of a wild project, we’d never done something like that before and we were a bit nervous about what would be said in the media about it. But actually, people were very positive,” said Anne Kathrine Overgaard, one of the main organisers of the project from the University of Southern Denmark. The university and its researchers have learned a lot from the experience, particularly about engaging with society and shaping their research to match real-world needs. This is important with Europe’s increasing focus on competitiveness and bringing innovations to market faster, Overgaard said. She hopes to see more citizen engagement in evaluation processes and in science more broadly. “For many years, citizen engagement has been a bit of an add-on to proposals, just to check a box. But I think things are changing,” she said. It’s less about citizens just gathering data and more “about the dialogue between the public and the scientists,” she said. The initiative ended last year as the team wanted to regroup to find fresh momentum. The development of AI and AI-written proposals has made Overgaard reflect on how the project could be reworked to help evaluators. She hopes to bring it back in the future. “It could be a good idea to try this initiative again in a slightly re-worked format,” she said.

Jun 16 • 8:00 PM EDT • Science • sciencebusiness.net

Merchants of Doubt and the attacks on Extreme Event Attribution science

Last week, I attended a meeting at Columbia University on attribution science and climate law, hosted by the Sabin Center. It was a fantastic event, bringing together scientists and legal experts working at the intersection of extreme event attribution and climate law. Subscribe For those unfamiliar with it, extreme event attribution attempts to quantify the contribution of climate change to an extreme event. For example, several groups analyzed the impact of climate change on Hurricane Harvey’s enormous rainfall totals over Houston, Texas and they found that climate change increased rainfall by 15 to 38%. One thing that came up again and again was how terrified fossil-fuel interests are of extreme event attribution science. They are acutely aware that this research could land them in court. And losing those cases would leave them legally liable for billions of dollars in climate damages. Because the legal stakes are so high, the blowback has turned ugly. I spoke with several scientists at the meeting who are facing ongoing harassment over their work. This blowback is a coordinated campaign to make the entire field look suspect. The goal is to create the impression that attribution science is too uncertain, too political, or too conflicted to be useful in court or in public policy. The strategy is not based on actual science or evidence of misconduct, but on the generation of doubt. The new Merchants of Doubt We’ve seen this before. In fact, not that long ago: We only have to go back a year to the Department of Energy (DOE) Climate Working Group (CWG) report to see an example of using doubt as the tool to push back against well-established science. This strategy is laid out in an email from a member of the CWG, Dr. Roy Spencer, that was released during litigation over the Climate Working Group process. The key quote is: About all I can hope is that what we write will provide sufficient “reasonable scientific doubt” regarding the science claims in the 2009 TSD [technical support document], based upon almost 2 decades of new science, to call into question the original reasoning for the EPA Administrator’s decision that CO2 presents a threat to human health and welfare. This statement is strong evidence that at least some members of the committee were working to support a particular policy outcome: revoking the Endangerment Finding. The email also explains how they planned to do it: by attempting to generate “reasonable doubt”. This is going to be hard, Spencer implies. Despite falsely claiming that “2 decades of new science” weakens the case, Spencer explicitly acknowledges that the actual peer-reviewed science of climate change overwhelmingly rejects his position: But if the science argument is decided upon by a vote, or by the number of published citations, we lose the science argument. We can go back even further: This CWG email shares unmistakable DNA with the infamous 1969 tobacco memo that declared: “Doubt is our product, since it is the best means of competing with the ‘body of fact’ that exists in the mind of the general public. It is also the means of establishing a controversy.” The tobacco memo also acknowledges the limit of this strategy: Like the CWG, they knew the science was not on their side. Share The new new Merchants of Doubt The people attacking the IPCC chapter on extreme event attribution are the newest iteration of the Merchants of Doubt. Their goal, like all Merchants before them, is to introduce doubt into the process. Because the report is not even out yet, they cannot attack its conclusions. So they are attacking the authors instead. Here is a press release from the House Science, Space, and Technology Committee: In the letter, the Chairmen express concerns about potential conflicts of interest involving members of the Attribution Committee, stating that “publicly available information suggests a troubling pattern” in which committee members are affiliated with nonprofits that support climate accountability lawsuits, “raising the appearance of impropriety and member bias.” To be clear, this is just innuendo. There is no actual evidence of bias. And given the robust process that these reports go through, including multiple lines of peer review, it seems very unlikely that significant bias can survive into the report. When the report comes out, critics will have the opportunity to make legitimate criticisms of the report — if any exist. If none do, however, they’ll still make criticisms, but they’ll be bogus, simply designed to generate doubt. We’ll see. A note to the press: Fix your frame To any journalists reading this: The public debate over extreme event attribution science is not going away. The science is simply too dangerous to fossil-fuel interests for them to stop fighting it. You very well might be assigned to write an article about this area of research in the future. When you do, do not automatically adopt the framing that climate misinformers want you to use. They want you to frame the story around questions like: Are climate scientists trying to put their thumb on the scale to achieve a predetermined, politically motivated result? Are climate scientists improperly letting their politics invade the science of the IPCC? That frame is a trap. Instead, you need to view this through the historical lens of the Merchants of Doubt. How does the ecosystem of doubt operate? Who funds it? What methods do they use to misrepresent science and slime researchers? What scientific results are they trying to keep people from understanding are legitimate? Ultimately, you instead need to focus your article on the generation of doubt as a way to maintain the fossil fuel industry’s social and legal license to keep burning oil, gas, and coal. If you treat the misinformers’ frame as a legitimate, good-faith scientific critique, you are helping them produce doubt. Don’t do it. Don’t be a Merchant of Doubt. Thanks for reading The Climate Brink! Subscribe for free to receive new posts and support our work. Subscribe other stuff The Staying Curious Substack has an interesting post about the different flavors of climate sensitivity. This is crucial information if you want to understand how scientists think about how much warming the Earth will experience. I’d be grateful if you could hit the like button ❤️ below! It helps more people discover these ideas and lets me know what’s connecting with readers.

Jun 16 • 4:55 PM EDT • Science • theclimatebrink.com

AI and brain-computer interface allow speechless ALS patient to work a full-time job

The hardware isn't new, but a UC Davis research team's machine learning-powered method of translating brain activity in an ALS patient into sentences with 92% accuracy is

Jun 16 • 2:44 PM EDT • Technology • theregister.com

How Ohio State is helping the US men's World Cup players recover

Ohio State researchers are helping U.S. soccer players recover faster using data-driven methods.

Jun 15 • 6:03 AM EDT • Science • dispatch.com

Is SMIC N+3’s Metal Pitch Smaller than Intel 18A’s?

Almost four years ago, we published that SMIC had started shipping 7 nm (N+1) chips. Now, SMIC is shipping its third-generation 7 nm (N+3) process in Huawei’s Kirin 9030, with a minimum metal pitch of 32.5 nm, about 10% tighter than the 36 nm minimum metal pitch shipping in Intel’s latest Panther Lake CPUs on 18A. The headline is true, but incomplete cherry picked metric. N+3 reaches the density of TSMC N6 through aggressive DUV multi-patterning and design-technology co-optimization (DTCO), but it pays for that in complexity, efficiency and process control. We found this and more in our reverse engineering and teardown where we cover SMIC’s N3 process technology, Huawei’s packaging, memory, architecture, and more. SemiAnalysis has been building a state-of-the-art teardown lab in Oregon capable of analyzing the world’s most advanced and important chips over the last year and half. We have already generated revenue on advanced datacenter chip teardowns including our recent reverse engineering of a major TSMC customer’s COUPE CPO optical engine + EIC 3D stack. This is the first public report from the SemiAnalysis Teardown Engineering & Evaluation Lab, or STEEL for short. The lab is aggressively scaling up and out and we’re excited to announce it publicly. This is a bit of inconvenient timing for TechInsights as they are private equity owned and currently being sold while having enjoyed virtually no credible competition for decades. This has led to TechInsights underinvesting in CAPEX. SemiAnalysis exceeds TechInsights in revenue despite no venture or private equity ownership and being founded only 6 years ago. Because we have no external investors and are founder led, we move faster, build faster, and we can release client chip teardowns for free regularly, while focusing on datacenter for our major clients. Here’s the first public image from our lab, the HiSilicon Kirin 9030 Pro SoC: This report will detail our teardown of the Kirin 9030 and our findings on SMIC’s N+3 process, the most advanced in China. For comparison, we’ll show our teardown of the MediaTek Helio G99, made on TSMC N6. Through this comparison, we can look at the effect of export controls – SMIC N+3 and TSMC N6 are comparable nodes, but one is heavily export-controlled, the other free to use the West’s most advanced equipment. Here we see both China’s progress and constraints. SMIC N+3 reaches TSMC N6-class logic density, but it requires far more aggressive DUV multi-patterning, so it does not match N6 on process maturity or cost. The Kirin 9030 Pro performs similarly to three-year-old Android flagships, and trails far behind the current flagship SoCs from Apple, Qualcomm, MediaTek, and Samsung. The efficiency gap is even wider. Export controls have not stopped Huawei and SMIC from shipping advanced silicon, but they have forced a different path. Without EUV, SMIC is leaning harder on DUV multi-patterning, DTCO, and increasingly complex integration. The roadmap continues forward through tighter design rules and backside power, but each step adds cost and process risk. Huawei’s τ scaling and LogicFolding show another path: stacking active logic and recovering density through advanced packaging and system-technology co-optimization (STCO). To understand the Kirin 9030, we must first understand Huawei’s SoC history. HiSilicon is Huawei’s chip design arm, responsible for the Kirin smartphone SoCs, Kunpeng server CPUs, Ascend AI accelerators, and switch/router networking silicon. Before export controls, Huawei was TSMC’s largest customer – the only customer on TSMC’s first EUV node, N7+, and among the first on N5, alongside Apple. That ended in late 2020. Huawei switched to Qualcomm SoCs in its flagship smartphones, though export controls limited them to 4G-only variants. In late 2023, Huawei returned to in-house silicon with the Kirin 9000s, a successor to the Kirin 9000, fabricated on SMIC N+2 instead of TSMC N5. In the following years, they released the Kirin 9010 and 9020 on the same N+2 process. These chips used Huawei’s in-house TaiShan CPU cores and Maleoon GPU. We have not torn down a Kirin 9020 ourselves, so the predecessor die shot is from Kurnal. The die shots show how Huawei spent its silicon budget: which functional blocks are where, and how their areas compare to the predecessor. First, a quick guide to the major blocks on the die. The total die area is nearly identical, but the 9030 uses that area more aggressively. A denser process lets Huawei fit an extra middle CPU core, more GPU and NPU cores, and larger caches into the same footprint. In contrast, the Helio G99 is a much smaller, low-cost SoC, built for budget smartphones rather than a flagship device. While the Kirin 9030 is ~140 mm², the G99 is only ~29 mm², roughly one-fifth the area. The underlying TSMC process technology, however, is directly comparable as a baseline for analyzing SMIC’s. The Kirin 9030 is an evolutionary refresh, not a clean-sheet design. Its CPU, GPU and NPU cores carry over the 9020’s families, and the gains come from three levers: the SMIC N+2-to-N+3 process step, DTCO and floorplan work, and incremental microarchitecture. Area is where the first two show up, and the 9030 scales well here. Performance and efficiency are the harder test. Huawei’s design holds up better than its node would suggest, but the chip still trails, both because N+3 sits behind the leading-edge nodes and because its cores, while competent, remain a few generations behind the newest designs. The new prime core is an incremental update. The main changes are a 10% frequency increase from 2.5 GHz to 2.75 GHz and a doubling in the L2 cache from 1 MiB to 2 MiB. Despite the increased cache, the core size decreased by 7.6%. Excluding the private L2 cache, the core size decreased by 21%. This is a large reduction for an incremental node. Compared with the TaiShan New V120 core in the Kirin 9020, the Kirin 9030’s middle core is almost unchanged architecturally, yet each core shrinks by ~22%. Most of that comes from the move from N+2 to N+3, with layout likely accounting for the rest. Visually, the most noticeable change is the increase from 3 middle cores to 4. There is also a 20% increase in the shared L3 cache of the big cluster. This helps to improve multi-core performance without sacrificing much in terms of area. Even with each core shrinking, the big CPU cluster’s total area is essentially unchanged. The per-core savings went back into an additional middle core and larger caches. The tiny cores shrank less than the prime core (excluding its L2 cache) and less than the middle cores. This is likely because fixed overhead is a larger share on a small core. We cannot resolve any architectural changes from the die shot alone, but the per-clock and efficiency gains shown below point to more than pure process and layout scaling. The area reduction was offset by a doubling of the shared L2 cache from 2 MiB to 4 MiB, leaving the total tiny CPU cluster area slightly larger. Area is the easiest improvement to see from a die shot, but it is only one part of PPA (power, performance, area). For modern logic, power and performance matter just as much, and often more. Since Dennard scaling broke down in the mid-2000s, voltage and frequency have not scaled in step with transistor dimensions, so each node has had to fight harder for gains in performance and efficiency. The starkest comparison is not Kirin 9020 versus Kirin 9030 Pro. Apple’s efficiency cores run circles around Huawei’s prime core. Apple’s low-power core delivers 20% higher integer performance while drawing only 1 W, compared with 4.5 W for Huawei’s prime core. N+3 matches TSMC N6, but N6 is several generations old. Apple and Qualcomm build on N4 and N3P, which are denser and sit on a better voltage-frequency curve, giving them a larger transistor budget and more performance per watt. The 9030’s own cores did improve. The middle and tiny cores gained 17% and 14% in per-clock integer performance over the 9020, with floating-point flat on the middle core and up 11% on the tiny. The tiny core improves cleanly, with performance rising while power falls and efficiency increases by 45% in integer and 24% in floating point. The middle core is mixed: integer performance rises but power rises faster, cutting integer efficiency by 7%, while lower power lifts floating-point efficiency 16%. Per-clock gains at the same or lower frequency are microarchitectural, so the cores are tuned, not just shrunk. Both also failed to hold their rated maximum frequencies, pointing to thermal, power, or stability limits. Per clock, the middle core sits around Arm Cortex-A720 and the tiny core near the Cortex-A520; absolute performance trails because Huawei clocks them much lower. The prime core is roughly Cortex-X2 class per clock, a 2021 design. Apple’s 2020 M1 Firestorm core is still 35% higher per clock and 57% faster in absolute integer performance at a similar 4.5 W. The current leading edge is further ahead again: the Apple M5 P-core is 60% higher per clock and 2.7× faster, the Arm C1 Ultra 45% higher and 2× faster. Matching older high-end cores per clock is a genuine design achievement. What Huawei cannot match is the voltage-frequency curve and transistor budget of leading-edge nodes, which let Apple, Qualcomm and others spend more transistors in the same area on wider cores, larger caches and deeper buffers while running at lower voltage. Huawei’s LogicFolding roadmap is one answer, stacking active logic to recover density and shorten signal paths. We return to it later. The GPU compute units (CUs) changed more visibly than the CPU cores, moving to a more rectangular layout for both the arithmetic logic unit (ALU) clusters and the CU overall. Even with ray-tracing support added, a CU shrank ~28%. However, that shrink is offset by the increase from 4 to 6 CUs and the area outside the CUs grew 33%. Overall, the GPU cluster is larger by ~10%. The GPU is where Huawei makes its biggest gains. The Maleoon 935 is not competitive with current flagships, but it is a large step up from the 920 and reaches older-flagship territory. In 3DMark it is 70% faster in Wild Life Extreme (WLE) and 79% faster in Steel Nomad Light (SNL) than the 920; with 11% higher clocks and 50% more CUs, the ~67% theoretical uplift roughly matches WLE and is beaten by SNL. It edges ahead of the Snapdragon 8+ Gen 1 in WLE and SNL, and the Dimensity 9200 and Apple A16 in WLE, but stays far behind newer parts: the Snapdragon 8 Elite Gen 5 and Dimensity 9500 are ~2.4–2.6× faster in WLE and ~3.2× faster in SNL. The Maleoon 935 is Huawei’s first GPU with hardware-accelerated ray tracing; there it lands slightly ahead of the Exynos 2200, and on par with the Apple A16, with current flagships up to 3.7× faster. The Neural Processing Unit (NPU) saw the largest structural changes of any block, moving from a Lite and a Tiny core in the Kirin 9020 to a Lite and two Tiny cores in the Kirin 9030. Both core types also show significant layout changes. This is a reversal in Huawei’s NPU design. The Kirin 9000 5G, its last flagship chip on TSMC N5, used two Lite and one Tiny core. The series of SoCs on SMIC N+2 moved to one Lite and one Tiny core, likely for area savings. With the Kirin 9030, Huawei has shifted back toward a larger multi-core NPU cluster, but with the additional area going to a Tiny core rather than a Lite core. We’re diving deep into the most advanced datacenter and AI hardware hitting the market. To learn more about what’s in the pipeline or to commission a custom teardown, contact sales@semianalysis.com. Interested in joining us on this ride and think you can be a difference maker? Check out our Careers page. Before diving into the process stack, the package and memory are worth separating from the SoC itself. The Pro variant of the Kirin 9030 carries 12 GB of Samsung DRAM, with two stacks of four dies each. The dies were identified as the K4L2E165YD, a 12 Gb LPDDR5X-9600 device fabricated on Samsung’s 1a node, the fourth generation of its 10 nm-class DRAM after 1x, 1y and 1z. 1a has shipped in volume since 2022, so this is current memory rather than older-node inventory. The 16 GB Pro Max variants we obtained were found with both CXMT and Samsung packages. The CXMT package is marked CXDD7JEDM, with two stacks of four dies, packaged in week 45 of 2025. The inferred die dimensions from X-ray computed tomography (CT) are consistent with a known density of ~0.3 Gib/mm² for the CXMT G4 process, roughly equivalent to other manufacturers’ 1z processes. The Kirin 9030 uses a typical integrated package-on-package (iPoP) stack: multiple DRAM dies in a memory package sit above an organic redistribution layer (RDL) interposer, which sits above the SoC and package substrate. The full package is then mounted to the printed circuit board (PCB) through ball-grid array (BGA) solder bumps. The memory package substrate is a thin bismaleimide-triazine (BT) laminate carrying the LPDDR5X stack. The organic RDL interposer over the SoC routes the PoP signals around the die and carries possible dummy thermal copper pillars. The package substrate, a thicker Ajinomoto Build-up Film (ABF) build-up over a BT core, fans the flip-chip bumps out to BGA pitch and embeds the power planes. The whole stack is organic. The only silicon is the SoC and the LPDDR5X dies; there is no silicon interposer. Keeping it all-organic brings the package’s coefficient of thermal expansion (CTE) close to the PCB’s, reducing board-level warpage, and avoids the cost of a silicon interposer the SoC’s bandwidth does not need. In an iPoP stack, the memory package connects to the organic RDL interposer through an array of solder bumps. Underfill fills the gap around those bumps, adding stiffness and protecting the joints from mechanical stress. The Pro and Pro Max variants differ here, which we cover behind the paywall. The die shot and architecture tell us how Huawei allocated its silicon budget. The process tells us what SMIC can manufacture. We use the Helio G99 as the process reference for TSMC N6. Both SMIC N+3 and TSMC N6 are evolutions of previous 7 nm-class nodes. We used targeted TEM cross-sections through logic and memory regions, imaged in both fin-cut and gate-cut directions. Each cross-section caption gives its horizontal field width (HFW), the real width of the imaged area. We start at the transistor fins, then move up through standard cells, local interconnect, and SRAM. SMIC has not overtaken Intel or TSMC. It uses aggressive DUV scaling and DTCO to reach N6-class density, but that density doesn’t translate into comparable performance and efficiency, for two reasons: the node gap to leading-edge nodes, and Huawei’s core designs. Fin Profile One of the most important knobs in a FinFET process is the fin profile: the shape of an individual fin and the channel where current passes from source to drain. The ideal fin is tall, narrow, and nearly vertical. A taller fin increases effective channel width, while a narrower fin improves electrostatic control by thinning the body the gate must control. Push either too far, and the process pays for it: weaker drive current, fragile fins, taper, footing and line-edge variation that hit yield and device variability. The Intel 22 nm, 14 nm, and 10 nm fin cross-sections show how FinFET nodes have improved over time. 22 nm fins were a first-generation structure, relatively short, wide and strongly tapered. The shape limits current density and reduces gate control uniformity across the height of the fin. At 14 nm and 10 nm, Intel pushed the fins taller and narrower while also making the sidewalls more vertical. Rather than shrinking the device, these changes increase the effective channel width per fin and improve electrostatic control. The trade-off is that taller fins at tighter pitches are much more difficult to manufacture. Now, let’s compare the Helio G99 on TSMC N6 with the Kirin 9030 on SMIC N+3. Both processes are in the same class, with fin pitch of 30-32 nm on N+3 and 34 nm in our N6 cross-section. The pitch for N6 is especially interesting as N7’s HD library is generally listed with a 33 nm fin pitch, and N6 did not shrink pitches directly. Its density gains came from DTCO instead of tighter pitches. The 34 nm pitch was stable across our sampled region and serves more as a comparison against the SMIC N+3 we have not investigated further. Pinning down N+3’s fin patterning scheme takes more than one core unit. The CPU cores show a dense ~32 nm pitch, with the pitch between N-P fin pairs alternating between 78 and 88 nm. Logic alone may be consistent with dual-pitch mandrels of 120 and 110 nm, but this is a complex and unusual approach. Combining the pitch from the the 8T SRAM, which has more complex repeat unit, with the CPU core sequence allows us to reverse engineer the patterning steps with more confidence. As both the logic and SRAM should share the same base grid, a single CD mandrel lithography pattern with 128 nm pitch undergoing SAQP produces a die-wide ~32 nm grid (128 nm/4), which supports the pitch sequencing seen in both logic and SRAM cells. In the sampled cross-sections, N+3 shows a taller, narrower, higher-aspect-ratio fin than N6. The measured fin aspect ratio is ~9.5:1 on N+3 versus 7.8:1 on N6. N+3 also shows less top rounding, with an estimated radius of ~2 nm, compared with 2.8 nm on N6. Even though the fin widths differ, the ratio of top rounding to fin width tells the same story, with N+3 at 0.37 and N6 at 0.44. In a geometric sense, lower is better; a perfectly rectangular fin would have no top-rounding penalty. These are single-digit-nanometer features measured from a handful of cuts, so treat the absolute numbers as approximate. The important result is the relative gap: N+3’s fins are consistently taller, narrower and less rounded than N6’s. We’re diving deep into the most advanced datacenter and AI hardware hitting the market. To learn more about what’s in the pipeline or to commission a custom teardown, contact sales@semianalysis.com. Interested in joining us on this ride and think you can be a difference maker? Check out our Careers page. Standard Cell A standard cell is the basic building block of chip layout: a fixed-height row pairing one NMOS and one PMOS transistor that share a gate, tiled in a grid to build logic blocks. The key dimensions are contacted gate pitch (CGP), cell height (CH), fin count, and the lower-metal routing grid. To measure density, we use the Bohr metric: a weighted average of NAND2 gate area (60%) and scan flip-flop area (40%). This represents a realistic mix of combinational and sequential logic. This metric has its limitations, especially for complex cell layouts like TSMC’s FinFLEX, which alternates cells with different fin counts. Even so, it is the best metric for a pure process-level comparison. Another important measurement is the fin pitch; it refers to the distance between two fins of the same transistor. In a FinFET process, multiple fins are used in each transistor to increase the drive current and thus performance. TSMC N6 ships both a high-density (HD) library with 2 PMOS and 2 NMOS fins per cell, and a high-performance (HP) library with 3 of each. More fins under the shared gate mean more effective channel width. HP cells switch harder at the cost of area. Designers mix the two on a die, primarily spending HP cells on timing-critical paths, and matching their PPA targets. In the Cortex-A55 core of the Helio G99, we found a cell height of 240 nm for the HD cell. MediaTek has used HD cells in the G99 to minimize die size and thus cost. As an SoC for budget smartphones at ~$100, this is essential. By contrast, we found only one library in the Kirin 9030, with 2 NMOS and 2 PMOS fins. This suggests a narrower library strategy than TSMC N6, where both HD and HP libraries are widely used. This likely reflects the smaller customer base and the more constrained domestic design and electronic design automation (EDA) ecosystem. In all three CPU cores of the Kirin 9030, we found cell heights of 228 nm, 5% smaller than on N6. This is also a reduction of 9.5% over SMIC N+2’s cell height of 252 nm. SMIC N+3 and TSMC N6’s HD library both feature a CGP of 57 nm. For SMIC, this is a 9.5% shrink over N+2. In the past, CGP and cell height alone may have been enough to compare transistor density. Now, however, we must consider scaling boosters and DTCO as well. SMIC’s density gain does not come from EUV. It comes from using every available DTCO booster aggressively. First is fin depopulation: reducing the number of NMOS and PMOS fins in each cell. The first FinFET nodes started with 3 or 4 fins for each transistor. SMIC N+3 and TSMC N6 HD both use only 2 fins per transistor, trading drive strength for density. Next is contact over active gate (COAG). By landing the gate contact directly over the active gate, instead of out over the isolation region, the cell height drops. N+3 integrates COAG while N6 does not. Our N+3 gate-cut cross-sections indicate COAG, with the gate contact sitting over the active region, while N6 shows an off-gate contact. Last is single diffusion break (SDB). Diffusion breaks are inserted between cells in the same row to provide electrical isolation, but they also introduce local layout effects (LLE), layout-dependent shifts in electrical characteristics. In the past, a double diffusion break was used, consuming the space of two CGPs. SMIC N+3 and TSMC N6 instead use SDB, saving area but increasing LLE sensitivity. This must be controlled at the process level and accurately modeled in the process design kit (PDK) so that EDA tools can account for it. Overall, SMIC N+3 has a transistor density of 113.4 MTr/mm², slightly above TSMC N6 at 107.7 MTr/mm². Even without EUV, SMIC has achieved density beyond TSMC’s mature N6 node which utilizes EUV. Metal Stack The smallest critical dimension in the teardown is M0; SMIC N+3 uses a 32.5 nm local metal pitch. That is smaller than the 36 nm M0 pitch on Intel 18A in Panther Lake. However, this does not mean that SMIC has a better process than Intel 18A or TSMC N3P. M0 is a local intra-cell routing layer. Its usefulness depends on the full interconnect stack: M1 and M2 pitch, track count, via and line resistance, design rules, mask count, overlay control, and routing flexibility. The 32.5 nm M0 is consistent with self-aligned quadruple patterning (SAQP), whose four-population line-width loading we read coarsely as alternating widths of 21.5 to 24 nm; M1 and M2, at 38 and 40 nm, are consistent with self-aligned double patterning (SADP), a single A/B split. On TSMC N6, M0, M2, and M3 sit at a relaxed ~40 nm and are consistent with SADP-class double patterning, with no need for quadruple patterning. That said, we measure M2 for example at ~43 nm, likely inflated by sparse routing. We do not assign any specific layer to EUV from our cross-sections; the distinction we can draw is double versus quadruple patterning, not lithography wavelength. Transistor-level density in the front-end-of-line (FEOL) sets an upper bound, but the design is ultimately limited by what the interconnect stack can route. The lowest metals are the most important for standard-cell density, but the semi-global and global layers determine how usable that density is at the block and chip level. Two axes are commonly used for chip cross-sections: the fin-cut and the gate-cut. The micrograph above is a fin-cut and shows metals 0 through 3. This axis lets us see the even-numbered metals, with M0 right above the fins. There are two kinds of M0 lines. The first are the power rails; these are wide wires for the VDD and VSS running horizontally at the top and bottom edges of each standard cell. The wide wires measure 55 nm across, more than double the other M0 lines. Their width minimizes resistance and reduces IR drop. The second kind are intra-cell wires, short segments within the cell that connect terminals to M1. These have alternating widths between 21.5 and 24 nm. The M0 pitch is 32.5 nm, a 19% reduction versus N+2 and N6. At this pitch, DUV patterning requires more aggressive multi-patterning, increasing mask count, overlay sensitivity, process complexity and cost. M0 is below what a single DUV-defined spacer (SADP) can resolve, so SMIC cascades a second spacer step (SAQP). The cross-section reflects the cost: the M0 trenches are visibly more re-entrant (narrower at the bottom than the top) than M1 or M2 on the same chip and carry a bright barrier-rich foot where the trench meets the etch-stop layer. That shape is partly the intended damascene profile, as a slightly narrow bottom helps void-free copper fill, but its magnitude at M0 is driven by the tight pitch and the higher trench aspect ratio. Intel 18A supports an M0 pitch of 32 nm, although Panther Lake has only shipped with a looser 36 nm pitch. This is due to Intel’s heavy usage of HP libraries. Among leading-edge nodes, 18A has the loosest M0 pitches due to PowerVia. With power routing moving to the backside, congestion is reduced, and the entire front-side metal stack can be used for signal routing. M2 is the first true inter-cell routing layer. It runs horizontally like M0 but spans across multiple cells to carry block-level signals. The M2 pitch sets the cell’s track height – the number of M2 tracks that fit between the VDD and VSS rails, defining what the library calls a 6-track or 7.5-track cell. This layer is the most important, limiting the routing of entire blocks. SMIC N+3 features a 5.7-track cell. The M2 pitch is 40 nm, a 5% decrease over N+2 and the same as N6. This shrink keeps the pitch at the edge of what is possible with double patterning. Future nodes will need to increase the number of masks for M2 as reducing the number of tracks is much harder due to the limitations in routing. The micrograph above is in the perpendicular direction, the gate-cut, and shows metals 0 through 4. This allows us to see and measure the odd-numbered vertical metal layers. The M1 pitch is 38 nm, 9.5% less than N+2 and 33% less than N6. The M1-to-gate ratio matters because it sets local routing flexibility. N+2 and N+3 use a 3:2 ratio, while N6 uses a 1:1 ratio, explaining the huge differences in M1 pitch. The more M1 lines there are compared with the gates, the more flexibility there is for power and signal crossing within the cell. Routing flexibility enables more complex and better cells. Clean fractional ratios are also preferred as a grid is periodic and improves layouts. The 3:2 ratio gives SMIC more local routing flexibility than a strict 1:1 grid, but it also complicates layout and patterning. This is a DTCO choice, with SMIC increasing process complexity to recover density and routability without EUV. This 3:2 ratio is not very popular in the leading-edge nodes. TSMC has only used it on N7+, the N5 family, and the short-lived N3(B). They have switched back to a 1:1 ratio for N3E. Intel has only used it on the 10 nm/Intel 7 family, with Intel 4, 3 and 18A all using a 1:1 ratio. Samsung is the only one still using a 3:2 ratio at the leading edge, using it in the SF4 and SF3 families. It remains to be seen if SMIC will remain at a 3:2 ratio or move to a 1:1 ratio with its future nodes. The industry is still actively exploring these local-routing ratios. At VLSI 2026, imec will be presenting work on even higher ratios, including a 2:1 scheme that can reduce area by up to 14%. We will be covering the conference in a future newsletter article. Subscribe We’re diving deep into the most advanced datacenter and AI hardware hitting the market. To learn more about what’s in the pipeline or to commission a custom teardown, contact sales@semianalysis.com. Interested in joining us on this ride and think you can be a difference maker? Check out our Careers page. The final local interconnect layer for N+3 is M3, with a pitch of 44 nm. The M3 pitch is the same as on N+2 and 10% larger than on N6. The semi-global layers carry the majority of block-level signal routing. They have a coarser pitch than the lower local layers. On leading-edge nodes, they are designed to sit at the limit of DUV single patterning. M4 through M11 pitches were found divided between 80–82 nm (M4–M6), 128 nm (M7–M10), and 148 nm (M11). Given limited sampling, it is possible these are divided further in dense routing areas. At the top are two giant metal layers, M12 and M13. These have kept the same pitches as N+2 at 1920 nm and 4600 nm respectively. While the lower layers’ pitches are generally fixed by the process and library, the upper layers vary much more in pitch and count, depending on the design. Even two smartphone SoCs on the same process can have wildly different metal stacks. The Helio G99 carries fewer routing layers, reaching coarse metal pitches of 850 nm by M9, while the larger and higher-performance Kirin 9030 keeps fine pitches until M11. SRAM At the leading edge, SRAM is much more difficult to scale than logic. TSMC’s latest nodes have seen little to no bitcell scaling, while logic still has more DTCO levers to pull. While looking for other logic libraries in the GPU compute units, we stumbled upon the SRAM. The most common type of SRAM has 6 transistors (6T), but this cell had 8 transistors (8T) instead. 8T SRAM adds two transistors to form a dedicated read port. Unlike a 6T cell, where reading disturbs the storage, the decoupled read port removes read-disturb, improving read stability and letting the cell be pushed harder for performance. At first glance, the cut looked like an unusual logic library, with each cell row having 3 fins of one polarity and 5 fins of another. The rows also alternated in orientation. Energy-dispersive X-ray spectroscopy (EDS) resolved our confusion. The cut had not landed on the GPU logic, but on the SRAM macro beside it. The unusual fin pattern was due to the SRAM library. We return to EDS in the process flow analysis behind the paywall. SRAM libraries are not like traditional logic libraries. Due to the unequal number of PMOS and NMOS transistors, they require specialized rules and layout libraries. They do not need the flexibility of logic libraries, so they are hyper-optimized for one purpose: dense, reliable memory. The SRAM cell we found is a 1:2:2-2:2 cell. This means there is 1 fin per pull-up (PU) PMOS transistor, and 2 fins per pull-down (PD) and pass-gate (PG) NMOS transistor. These 2 PU, 2 PD and 2 PG transistors would usually form a single 6T high-current cell (HCC). An 8T HCC adds a read-pull-down (RPD) and a read-pass-gate (RPG) NMOS transistor, each with two fins. We measured a cell height of 406 nm, which brings the bitcell size to 0.0463 µm². That is a theoretical peak density of 21.6 Mib/mm². We estimate that a 6T HCC would have a cell height of 292 nm and a size of 0.0337 µm². This is ~12% larger than a 6T HCC on Intel 3 and 4. We also estimate the 6T high-density cell (HDC) to have a cell height of 228 nm and a size of 0.0260 µm². This is coincidentally the same as the logic standard-cell height measured earlier. The estimate puts the cell near Samsung 7LPP/5LPP and slightly below TSMC N7/N6. That is a theoretical peak density of 38.5 Mib/mm². 6T HDC is arguably the most important cell as it is used for the largest caches in a chip, the L3 caches and system-level cache (SLC). Both the Kirin 9020 and 9030 have split the SLC into 4 banks to raise total SLC bandwidth. In the Kirin 9030, the SLC increased from 2 MiB to 3 MiB per bank. Correspondingly, the number of arrays within the bank also increased by 50%, from 16 to 24. Each array can store 128 KiB and forms an orderly pattern on the die shot. From the Kirin 9020 to the Kirin 9030, the area of a 128 KiB SLC array decreased from 0.0477 mm² to 0.0392 mm², an 18% shrink. The achieved density is 25.5 Mib/mm², 66% of the theoretical maximum. While the SLC was quite similar across both chips, the L3 has seen some major changes, particularly in terms of its layout. The total capacity also went up from 10 MiB to 12 MiB. Much like the SLC, the L3 is also split into 4 banks. In the Kirin 9020, an L3 bank consisted of 16× 128 KiB arrays and 16× 32 KiB arrays. However, an L3 bank in the Kirin 9030 instead consists of 48× 64 KiB arrays. In the Kirin 9020 L3, a 128 KiB array was 0.0513 mm² and a 32 KiB array was 0.0154 mm². The size of the 128 KiB array is different on the L3 and SLC as the assist circuitry for the two arrays differs depending on their purpose. In the Kirin 9030 L3, a 64 KiB array is 0.0210 mm². Although not a like-for-like comparison, normalized for capacity, it is 18% smaller than the 9020’s 128 KiB L3 array and 31% smaller than its 32 KiB L3 array. The achieved density is slightly lower than the SLC, at 23.8 Mib/mm², 62% of the theoretical maximum. Unlike the L3 and SLC, the prime cores’ private L2 cache uses a 2-bank design. As the prime cores’ L2 is latency-critical, it likely uses 6T HCC instead of 6T HDC. The 9020 has 16 arrays in each bank while the 9030 has 32. Each array has a capacity of 32 KiB. A 32 KiB array in the L2 shrank from 0.0171 mm² to 0.0142 mm², ~17% smaller. The density is 17.6 Mib/mm², ~59% of the theoretical maximum for 6T HCC. SRAM scaled well from N+2 to N+3, shrinking by ~19%, close to the theoretical logic shrink. The caveat is that N+2’s bitcells were unusually large, bigger than comparable 7 nm-class nodes, so part of the gain is catch-up rather than true scaling. With the insights from STEEL’s teardowns, we will be doing a deep dive into SRAM in a future newsletter article. Subscribe Everything above came out of a single STEEL teardown: die annotation, block-level area analysis and TEM cross-sections through logic and SRAM. We’re diving deep into the most advanced datacenter and AI hardware hitting the market. To learn more about what’s in the pipeline or to commission a custom teardown, contact sales@semianalysis.com. Future Roadmap The same cross-sections that pin down N+3 also show where SMIC can go next. Although N+3 is already close to the practical limits of DUV multi-patterning in several layers, SMIC still has a few scaling levers left. A theoretical N+4 would likely start with cell height. N+3 uses 5 M0 tracks between its power rails. Moving to 4 M0 tracks, as on SMIC N+2 and TSMC N6, could reduce cell height by roughly 15%. The routing grid is only one side of the shrink; the front end also must fit into the smaller cell. One possible FEOL lever is reducing the p-to-n isolation spacing from two diffusion grid units to one. Intel used this scaling booster on Intel 4, and TSMC did so on its N3 family. This path trades layout flexibility for density. Fewer M0 tracks reduce local routing resources, while tighter p-to-n spacing raises integration and design-rule difficulty. M2 is also constrained by the cell height shrink. For SMIC to maintain a ~5.7-track cell, M2 would need to move toward ~35 nm. That would move another layer into SAQP territory. SMIC could also reduce the CGP from 57 nm to 54 nm. Intel reached a similar CGP on Intel 10 nm/Intel 7 without EUV. The local interconnect is also tougher. If SMIC keeps the 3:2 M1-to-gate ratio, M1 would need to shrink to 36 nm and would likely require SAQP as well. If SMIC moves to a 1:1 ratio, M1 could relax to 54 nm, but it would give up routing flexibility. Under this theoretical path, we estimate that SMIC N+4 could reach a cell height of 198 nm and a CGP of 54 nm, implying a Bohr density of 137.8 MTr/mm², on par with TSMC N5 or Samsung SF4. However, the difficulty is cumulative. Each step is individually plausible, but together they make N+4 harder than the transition from N+2 to N+3. It will likely take longer, cost more, and carry less process margin. A theoretical N+5 would require a larger integration shift. One possible path is backside contacts (BSCon), moving power routing and source/drain contacts to the backside, which would reduce front-side routing pressure and enable another reduction in cell height. The front-side metal pitches could relax to reduce the process complexity. M0 would likely relax slightly to ~34 nm, and M2 and M4 pitches could relax further. CGP is unlikely to shrink much further. Even with EUV, 48 nm has been the practical limit for yield and process control. This approach would allow N+5’s cell height to fall to 170 nm and its CGP to 53 nm. This implies a Bohr density of 163.6 MTr/mm², on par with Intel 18A’s HP library. However, this would not make N+5 cost-competitive with the leading edge. It would reach a similar density through a much more expensive route. The integration difficulty rises sharply, with new process flows for backside alignment, wafer thinning, contact reveal, and backside metallization. Past this point, standard density and interconnect scaling become increasingly unattractive. That is where Huawei’s roadmap stops looking like a normal foundry roadmap and starts looking like a packaging roadmap. At ISCAS 2026, Huawei unveiled its tau (τ) scaling law, reframing process scaling in the time domain. τ is the time cost of data movement and processing: switching delays in transistors, RC signal propagation delays in circuits, compute, memory, and networking latency. Outside Huawei’s terminology, this is called system-technology co-optimization. This is Huawei’s answer to its lack of EUV lithography. Without EUV, planar density cannot keep pace with TSMC, Intel, or Samsung. If transistor density cannot shrink further, Huawei’s alternative is to shorten wires, reduce buffering, and stack logic vertically. “LogicFolding”, Huawei’s implementation of this new scaling idea, is, in practice, an aggressive 3D stacking approach. AMD V-Cache places SRAM above or below a CPU die. AMD’s MI350X places active interposer dies (AIDs) underneath accelerator and compute dies (XCDs), with the AIDs handling cache, IO interfaces, the network-on-chip (NoC) and embedded metal-insulator-metal (MIM) capacitors. With LogicFolding, parts of the same logic block are split across multiple active dies bonded face-to-face at ultra-fine pitch. This allows Huawei to shorten some critical paths and reduce buffer overhead, not merely add cache capacity or offload the IO and interconnect. Shortening wires is where the higher clocks come from. A large share of a modern core’s delay and energy budget goes into driving long interconnects and the repeater buffers along them. LogicFolding distributes a block’s critical-path gates across multiple stacked tiers bonded at a very fine pitch, so the bond interface behaves like an additional metal layer and the longest paths get shorter. That is how Huawei expects to recover frequency and efficiency it cannot get from the process alone. Huawei’s roadmap shows its intent. Prime core frequency is targeted to rise from 2.75 GHz in the Kirin 9030 to roughly 5 GHz by 2031, far beyond what planar scaling alone could deliver. Prime cores with 3.1 and 3.39 GHz clocks are being tested in its labs, although their power consumption is unknown. Beyond that, chips are in the design, simulation or pathfinding phase, meaning the frequencies are targets. However, the direction matters more: LogicFolding also helps with performance, not just density. The catch is that Huawei’s density claim is not directly comparable to foundry densities. A stacked design can report more transistors per package footprint by adding active layers, even if each patterned die remains well behind TSMC or Intel in front-end density. This is how Huawei can claim to reach foundry 14A-equivalent density by 2031. This is not a like-for-like foundry comparison, with Huawei using stacked logic and measuring density per package footprint. On a normalized Bohr-density basis, SMIC N+3 is ~114 MTr/mm², 38% less than Intel 18A’s HD library. Huawei’s 3D roadmap closes the gap by stacking active logic, reaching 215 MTr/mm² by 2030. In 2031, the roadmap density jumps to 295 MTr/mm², implying either a third active layer, partial EUV insertion or aggressive planar DUV scaling. Huawei’s methodology makes other foundries look much denser as well. Applying it to AMD’s MI450X with an N2 top die on an N3P base die yields a theoretical density of 460.2 MTr/mm² in 2026, compared with Huawei’s 295 MTr/mm² in 2031. This Kirin 9030 does not use LogicFolding, remaining in a conventional mobile SoC package. Instead, it forms the baseline for how far Huawei and SMIC can push planar scaling. Future teardowns of Kirin and Ascend chips will show both planar logic density and Huawei’s hybrid bonding solutions. Export controls changed China’s optimization problem rather than ending it. EUV restrictions raised the cost and complexity of leading-edge manufacturing without freezing it. SMIC reaches N6-class logic density through DUV immersion, SAQP and DTCO, while Huawei shifts more of the burden onto architecture, packaging and system-level integration. Future nodes will be tougher. N+3 still had room to tighten local metals and reduce cell height and CGP. Further scaling without EUV leaves fewer levers. More aggressive multi-patterning adds masks and overlay error. SMIC can keep pushing DUV, but each step will get more expensive and less forgiving. The design side is just as critical. Huawei had domestic EDA tools and flows before the Kirin 9030, with the Kirin 9000s, 9010 and 9020 making that clear. Huawei was able to ship multiple consumer SoCs on SMIC N+2 and N+3 while cut off from the Western EDA stack. US export controls restricted EDA tools for advanced chips in 2022 but did not target tools for more mature chips. In 2025, the US government briefly placed much broader restrictions on EDA software from Synopsys, Cadence, and others, before lifting them less than two months later as part of a trade deal tied to rare earths. Huawei has been unable to access those tools because it remains on a US trade blacklist. That forced Huawei, SMIC and Chinese academic institutions to build their own tools and flows. Researchers at Peking University recently announced a prototype EDA tool for Huawei’s LogicFolding architecture, which requires a new flow to handle the multilayer layout and floorplan. This is not the same as replacing the full Synopsys or Cadence stack, but it shows where domestic EDA is headed: toward tighter co-optimization between architecture, process and packaging. These advances are also diffusing into the Chinese ecosystem. SMIC is licensing its N+2 and N+3 processes to HLMC/Hua Hong at the government’s direction rather than by choice. If the same process learning feeds into Ascend accelerators for AI training and inference, the choke point shifts from one named fab to an ecosystem. Alibaba’s T-Head silicon arm and Cambricon, a Chinese AI chip designer that is expected to supply ByteDance, could also be major beneficiaries. Sanctions aimed at SMIC alone become less effective once the manufacturing knowledge has spread to other fabs and design houses. China is not closing the gap with Intel, Samsung and TSMC. The teardown shows the opposite in several places: no EUV, no backside power, higher process complexity, and visible trade-offs. But China is still advancing. If domestic chips become good enough for phones, inference, networking and security-sensitive workloads, they can matter strategically without matching TSMC at the leading edge. Behind the paywall, we show what else STEEL can do, with material and process flow analysis of SMIC N+3, and analysis of the Kirin 9030 package. We’re diving deep into the most advanced datacenter and AI hardware hitting the market. To learn more about what’s in the pipeline, access the full Kirin 9030 and SMIC N+3 analysis or to commission a custom teardown, contact sales@semianalysis.com.

Jun 14 • 3:14 PM EDT • Technology • newsletter.semianalysis.com

Destiny 2 Players Find Quick Farm For New Tier 5 Armor Sets

Destiny 2 players discover an efficient method to quickly farm some of the newly added Tier 5 armor sets from Monument of Triumph.

Jun 14 • 3:00 PM EDT • Technology • gamerant.com

Georgia's vote-counting method will soon be banned. Lawmakers will try to find a fix this week

Legislators passed a law two years ago barring the use of the QR code printed on ballots that the state relies on to tally votes beyond July 1 of this year, but no replacement method was ever implemented.

Jun 14 • 12:22 PM EDT • Politics • pbs.org

Interpretable AI in materials discovery: Uncovering how models make predictions

A method to interpret artificial intelligence (AI) models used in materials discovery by analyzing their learned features has been developed by researchers from Japan. The method extracts key features from an AI model trained on atomic structural data and optical absorption spectra, and then groups materials with similar structural and spectral characteristics. This approach can be extended to reveal how atomic arrangements influence other material properties, paving the way for more efficient materials design.

Jun 14 • 8:00 AM EDT • Science • eurekalert.org

Coast FIRE offers a flexible path to financial independence

FIRE is known as a path to financial freedom but also has a reputation for extremes. Some who have tried say they've found a more relaxed method.

Jun 14 • 5:35 AM EDT • Business • businessinsider.com

Yellowstone wolves may not have reshaped the national park after all

One of the most celebrated claims about Yellowstone’s wolves is facing a major challenge. Scientists say the study behind the famous trophic cascade story relied on flawed methods that overstated the ecological impact of wolf recovery. Their reanalysis found no evidence for a dramatic, park-wide surge in willow growth. Instead, the effects appear smaller and vary from place to place.

Jun 13 • 8:00 PM EDT • Science • sciencedaily.com

Courts block Alabama nitrogen execution

Lower courts had found the method of execution to be a cruel and unusual punishment

Jun 12 • 10:51 AM EDT • Politics • theweek.com

Supreme Court blocks Alabama from executing inmate with method lower court found cruel and unusual

The Supreme Court on Thursday blocked Alabama from executing a man using nitrogen hypoxia, a relatively new method of carrying out the death penalty that experts say causes “air hunger” and that a federal court ruled violates the Eighth Amendment’s ban on cruel and unusual punishment.

Jun 11 • 9:45 PM EDT • Politics • cnn.com

New OMB rule could break science in the United States

The drug that saved your mother. The treatment your doctor recommended. The clinical trial that bought someone you love more time. None of it was inevitable. It required a system built to operate outside politics and sustained over decades, because science doesn’t operate on the timeline of a politician. That system is now under direct threat. The Office of Management and Budget (OMB) has proposed a new rule to regulate all federal grants, not just science, but housing, education, defense, NASA and everything in between, that would fundamentally change how research is conducted in the United States. There have been a lot of fires in the past 16 months, and if everything is an emergency, nothing is an emergency. But this is a very big deal. These rules would strip away the independence that has kept science from becoming a political tool. The good news is there’s still something we can all do. How the grant system was designed to work When I was a new faculty member, I was full of millions of ideas, so I sat down and wrote an NIH proposal. I worked on it for months and thought it was so good. Then I sent it to my mentor. It came back covered in comments. Places where my reasoning wasn’t as airtight as I’d thought, methods that could be stronger, gaps in my thinking that I had been too close to the work to see. It stung, as honest feedback always does, but peer review almost always makes the work better. In fact, it’s the backbone of how American science has functioned for generations. At NIH, submitted proposals go to a panel of scientists who have experience in the field. These are the people who can read research methods and spot their weaknesses, who understand when an experiment is designed well and when it isn’t. Applications are scored rigorously, and often only the top 3-20% of proposals receive funding. The people making funding decisions are required to justify them based on these reviews. To be clear: this is not a perfect system, and good science still goes unfunded more often than any of us would like due to limited resources. There is also criticism that peer review may undervalue bold ideas that are risky but could have high payoffs. But the peer review system is nonetheless a meaningful part of the grant selection process. While thoughtful and careful changes could improve the system, the changes being proposed by OMB will not make things better. The rule that could change everything Through this OMB proposal, the system that helps decide what gets funded is being dismantled. There are many troubling elements buried in this proposal, but three provisions stand out in particular. Each would be damaging alone. Together, they would change what kind of science gets done in America, and who it serves. 1. Political appointees would decide which science gets funded, and peer review would be explicitly sidelined or ignored. The guidelines your doctor follows, the standards that determine what’s in your air and water, the drugs that get approved for your family: all of it starts with a funding decision. Right now, that decision is made by scientists who can evaluate whether the work is actually sound and whether it could move the needle forward. Under this proposal, funding decisions could be made by political appointees. The careful, expertise-driven review process that shapes grant funding would be effectively sidelined. That means that a poorly designed study could get funded simply because someone in a political office liked the sound of it, while rigorous, important work doesn’t get funded because it no longer aligns with the administration’s priorities. In other words, critical work that benefits all of us could now be missed just because it has become politically inconvenient. 2. Grants could be canceled at any point, without warning, in the middle of ongoing work. Say your tax dollars have been paying for a cancer study for two years. The grant was awarded for five years, so the team is mid-experiment. There are three additional years’ worth of answers that could change how the disease is treated for hundreds of thousands of people. With this new rule, the federal government could cancel the remaining funding tomorrow, walk away from the commitment it made with your money, and have no legal obligation to finish what it started. This is a huge waste of money. There are rarely other sources of funding for this work, which means the team, the graduate students, postdocs, and research staff who have dedicated years of their careers to this project could lose their jobs. Patients who have contributed their time to studies may not see it turn into useful learnings for others. Every hour of work already completed could result in nothing useful. Science can take decades to get to tangible outcomes. It needs a stable funding system to flourish. 3. Researchers would have a harder time communicating their findings without pre-approval from the federal government. There is a saying from Sir Mark Walport: “Science isn’t finished until it’s communicated.” Science is no use to anyone if it is kept locked away in the labs that produced the data. The proposed rule could make communicating research findings harder in a number of ways: Make it harder for scientists to widely share their findings in scientific journals. Publication costs, including journal fees that allow for broad public access, could not be paid for by federal funds which is often how scientists pay these costs. Restrict researchers from engaging publicly about how their findings should inform policy or public health guidelines. This would restrict scientists from doing the work that transforms years of lab work into decisions that actually affect people’s lives. Make it harder for scientists to attend conferences. Conferences would now need to be approved by the federal agency at the time of grant award. This disadvantages conferences or publications that are not politically aligned. Conferences are a key way in which scientists learn about work happening in their field so they can collaborate and build on each other’s findings. What good is science with a muzzle? The long-term impact These changes could (and hopefully would) be reversed under the next administration. But by then, damage has been done. Once projects are halted or denied funding by political appointees, people leave their science careers for other paths or even leave the country to do their amazing science elsewhere. You cannot pause a scientific study the way you pause a subscription you decided isn’t useful anymore. You cannot freeze a research team that depends on salaries to feed their families, causing a scramble for replacement funding that, in most cases, simply does not exist. When the money stops, everything stops, and all the work in progress and its potential are lost. Despite all of the language about reducing waste, fraud, and abuse, this new proposed rule increases the administrative burden tremendously. Every researcher watching this unfold will make a rational decision: don’t start anything that will take a decade to finish. This includes not building a team around funding that could vanish, or asking the big questions that need patience and stability to answer. The most consequential science, the kind that produces the treatments and the breakthroughs that reach your doctor’s office twenty years from now, is exactly the science that would be abandoned first. This is still a proposal, so we can all do something Some worry this rule is already a done deal. But by law, OMB is required to open a public comment period. Those comments matter because they inform members of Congress, they can be used in litigation, and they create a public record. So here’s what you can do: Submit a public comment. The public comment period on this proposed change is open until July 13. Anyone can submit a comment, and OMB is required to respond to substantial ones. Each comment must be different to count as distinct; identical comments will be counted only once. Comment as an individual, not on behalf of your organization. Here’s a full resource to help you, with useful examples, but in general: Share a story about how science or federal funding has benefitted you or is involved in your work. Are you or someone you loved a cancer survivor? Do you know someone with Alzheimer’s? Have you received NIH/NSF or other federal funding? All of these can be stories you use to highlight why you care. Explain why you’re worried about these proposed changes. You can use the wording found here or in other resources to help you. Ask them to withdraw this proposed rule. Contact your elected representatives. Congress allocates money to federal agencies to spend, and it has oversight of how that process works. You can let your representatives know this proposed change concerns you and ask them to intervene. There are levers they can push that can help at this moment. Let others know why federal funding matters. This isn’t just about science, but ALL federal grants, including for education systems, defense projects, and more. The process, including the importance of federal funding, is invisible to many. We can all make it more visible by sharing how science benefits us and why we value it. You can also share this article, or any of the resources linked here, to help spread awareness! Bottom line We are quickly losing ground in scientific research in the U.S. More changes, like the proposed rule by OMB, would decimate our ability to conduct research here, leaving us all worse off: fewer treatments for pancreatic cancer, less research on pollution impacts, fewer answers for patients with rare disease, and more unaddressed health needs. The impact will be very real for all of us, regardless of where we stand politically. Using our voices for science is more important than ever. Love, LM Big thanks to Dr. Megan Ranney for reading this over and providing brilliant insights, as always. Dr. Liz Marnik, PhD, is Executive Director of The Evidence Collective at YLE and a science communicator and immunologist working at the intersection of public trust, science, and public health. You can find her on Substack, LinkedIn, Instagram and Threads. Your Local Epidemiologist (YLE) comprises a team of experts, ranging from physicians to immunologists to epidemiologists to nutritionists, working together with one goal: to “Translate” ever-evolving public health science so that people are well-equipped to make evidence-based decisions. The YLE suite of newsletters reaches over 475,000 people across more than 132 countries. This newsletter is free to everyone, thanks to the generous support of fellow YLE community members. To support the effort, subscribe or upgrade below: Subscribe

Jun 10 • 6:04 AM EDT • Science • yourlocalepidemiologist.substack.com

Westfield council OKs tax break for accounting firm's new HQ

The two-story office building will be constructed on North Union Street, next to Basile Westfield Playhouse and near Christ United Methodist Church.

Jun 8 • 11:31 PM EDT • Business • ibj.com

We can create the future of science right now

Paul Litvak is the founder and Executive Director of the Robyn Dawes Institute and a Visiting Scholar at UC Berkeley. He has a PhD in Behavioral Decision Research from Carnegie Mellon where he studied emotions and the sunk cost bias. Over 15 years in industry, he solved a wide range of challenging technical problems. At Meta he created models optimizing the ad review process. At Google he ran experiments to measure social influence. At Airbnb, he was a product manager leading machine learning teams optimizing search ranking and price suggestions. He also co-founded and led product at Rhythmic Health, a venture-backed biosensing startup, creating an accurate low cost system using a color changing strip and a smart phone to measure salivary lactate. The bottleneck At this point, it is uncontroversial to say that science needs to stop using the PDF article as the unit of knowledge and currency. The unbearable slowness of scientific publishing, the profit motive and margins: I’m not saying anything new. The PDF also sucks because it’s hard to extract structured information, which makes it hard to do evidence synthesis. As a result, we do much less evidence synthesis than is needed. And evidence synthesis ultimately undergirds most policy and medical decision-making. I can see second-by-second real-time odds for any sporting or newsworthy event, but a school board can’t see the best evidence on whether their 8th graders should be taught algebra. As a society, we don’t treat this as an important problem. Again, not controversial. Not only is the problem well understood, but the solution has already been laid out. What we need is AI-assisted living evidence synthesis - (1) an open knowledge graph of atomic claims, (2) claims linked to evidence, (3) assessment and synthesis of each piece of evidence, and (4) continuous updating with new data. What few realize (yet) is that the technical capacity to build this vision for a significant portion of science already exists. Not only that, scientists and startup teams are already building many of these components. I know this because I’ve been surveying the space and talking to many of the builders. There are some missing pieces: for example, evaluations of how well some of the components work. But at this point, most of what’s missing is a fully end-to-end working integration of all of these parts. In the rest of this essay, I’m going to lay out all the parts of a working living evidence layer for science and who is working on them, and propose concrete next steps for building this system. What’s now possible The diagram above outlines the components of a living evidence synthesis platform, including some of the teams working on each component1. Scientific PDFs are processed into claims with associated evidence. The evidence is subjected to a forensic audit, methodological evaluation and robustness and reproducibility checks. Finally it’s given a weight in a continuously updating synthesis. What follows is a description and status of each component and a few of the teams working on them. Document understanding The first thing you need to be able to do is turn an article into structured data. Mostly that means parsing PDFs. There are often multicolumn layouts that confuse non-specialized PDF to text processing libraries. For scientific papers, there is the added complexity of parsing formulas and tables and figures. This is a really hot area - there are startups offering APIs, and it seems like a new open source package gets posted to Github every few weeks. What follows isn’t exhaustive. A package called GROBID was the state of the art for a while, they didn’t update their package for nearly two years until very recently. In the meantime reducto.ai released an AI powered PDF extraction API, PaddleOCR became popular, IBM released a model called Docling, and both Mistral and Gemini created models and libraries. I also know of at least one other well-funded psychology research group working on a paper parser. By contrast, there are few open evals in this space, with no extensive evals for complex table comprehension in particular. Nonetheless, I’m confident this will be a solved problem soon, given the combination of LLM advances and developer interest. Hypothesis level extraction There has been increasing interest in comprehending the extracted text of papers and linking information to evidence for each hypothesis. A lot of work has already been done. Trialstreamer (Marshall et al. 2020) and RobotReviewer LIVE (Marshall et al. 2023) demonstrated automated extraction of trial population, intervention, and outcome at scale on clinical RCTs. PaperQA2 (Skarlinski et al. 2024) and Ai2 ScholarQA (2024) extended this to retrieval-augmented question answering with citation grounding. Elicit, Consensus, and SciSpace operationalized claim-level extraction for end users. OpenEval (Booeshaghi et al. 2026) is the most recent and most ambitious: 1.96 million atomic claims extracted from 16,087 eLife manuscripts using Claude Sonnet 4.5, grouped into ~299,000 results, with LLM evaluations showing 81% agreement with human peer review on a 2,487-paper subset. None of these solutions link claims to test-statistics, as you would need to evaluate randomized controlled trials. This is why I built the evidence.guide API - to extract hypotheses and associated test statistics from behavioral science papers. The best public eval of this kind of extraction I’m aware of comes from the recent SCORE project - they had humans code thousands of psychology papers to extract their claims by hand. It would be extremely helpful to the world if all scientific PDFs were available as structured open data. I’ve been working to make this happen, both directly at Berkeley and through coordination with large entities I can’t yet speak of; as hard as it is to do, I think it’s possible2. Forensic audit A lot of work has been done on forensic audit, but some gaps remain. Of course, for biology papers that rely on images for evidence, there are a variety of tools (notably Proofig and ImageTwin) to spot anomalies. These are still well short of what sleuths like Elizabeth Bik can do on her own, but these tools are constant companions among fraud analysts. There’s someone working on auditing Excel files for anomalies, and a number of teams are automating numerical checks like GRIM and SPRITE, including Scrutiny project, the INSPECT-SR team as well as statcheck. The regcheck team is building a way to use AI to compare preregistrations to analyses in papers, to ensure there aren’t significant deviations. Nonetheless, there are many other kinds of anomalies to screen for, both public and less publicly known. And there are no formal evals for anomaly detection that I’m aware of. Still, there’s a lot to draw from in this space and I’m pretty certain we will be able to scan papers for most kinds of obvious anomalies in the near future. Methodological review This area has been white hot, though I fear for many of the startups in this space, because this capability may become commoditized. There are at least six different AI peer review companies, including Refine.ink, Reviewer3, ReviewerZero.ai, Q.E.D. Science, Paper Wizard, and Isitcredible. Coarse (a pun on refine) was also recently created as an open source alternative. These systems provide qualitative feedback on the content of papers, spotting methodological weaknesses and mathematical errors. They seem to work pretty well, and many academics report bitterly that they exceed the average quality of typical peer reviewers. But there are few evals here either. What evals exist so far involve using LLM-as-judge (circularity problems abound) or comparing against human reviews of questionable quality. What you’d ideally want is an eval that measures capturing known errors in papers3. Reproducibility and robustness Another active area has been using AI agents to automate computational reproducibility4 and robustness5 checks in papers that report numerical results. For more recent papers where data and code are available, AI agents can see whether they can re-run the analyses and produce the numbers reported in the published paper. In addition to a handful of individual academics who have been experimenting using Claude Code for this, the Institute for Replication is a leading group working on building an end to end system. The evals related to this problem are the most mature, with CORE-Bench (Siegel, Kapoor, Narayanan 2024) and PaperBench (OpenAI 2025) available to benchmark agents on this task. There is also work on getting AI agents to test alternative ways of analyzing the data to ensure the results are robust to small analytic design choices. Synthesis This is the most underdeveloped area where significant investment is required. Although some automated evidence synthesis systems exist — for example, otto-sr is building an AI agent to write systematic reviews — none of these incorporate the full range of paper level signals to weight evidence appropriately. Nor is there anything like an eval or a gold standard for a good systematic review. Arguably Cochrane reviews are the closest we have to gold standard human systematic reviews, though I’ve heard academics in the know complain about their uneven quality. A key question for a synthesis platform is how to weight anomalies and methodological issues in assessing the quality of a piece of evidence. This is an unsolved problem and one I’m very keen to work on. Continuous updating There are many pieces of basic infrastructure available for monitoring for new research and initiating updates. OpenAlex is the current open citation graph. Retraction Watch integrated into Crossref in October 2023. Scite tracks how citations support, contrast, or mention prior claims. The Living Evidence Network demonstrated continuous-update workflows in clinical guidelines. Engineering this is a relatively straightforward task. When you look over this technical architecture and all the progress being made, it’s hard not to be optimistic that a living guide to scientific evidence will be built. The stakeholders are ready The social infrastructure for this is starting to coalesce — it’s not just a pie in the sky academic exercise to imagine this coming into existence. Institutions like the Center for Open Science, the Institute for Replication, the INSPECT-SR, the Living Evidence Network and more are all working on scaling work to improve research quality. Funders are also aligned. The Sloan Foundation has funded living evidence work through COS. Coefficient Giving supports the Institute for Replication and COS. The Astera Institute and the Institute for Progress have shown interest in this space. NIH has established an Office for Replication and Reproducibility. Although there are (very unfortunately) serious headwinds in science funding generally, there is an active group of funders interested in metascience. A brief word about what I’ve been doing at RDI. First, as a Visiting Scholar at Berkeley I’ve been actively figuring out how a non-profit and a public university can conduct and make public the results of large-scale academic article data mining. With some of the money I raised from donors, I commissioned a legal analysis of recent case law and publisher text data mining (TDM) agreements in order to understand whether a massive open data mining of academic articles is possible (with caveats, it is). I’ve also been working to bring together stakeholders in this space, and identify gaps. I’ve also been doing some software development in this space, with more to come. A pilot proposal The assumption undergirding all of this is that an AI, given all this information, would make the right judgment about a scientific claim with lots of conflicting evidence, weighing all the factors appropriately. That’s the hypothesis we need to test. Randomized control trial research is the best place to focus on first. RCTs are used to make many of the important decisions in society - from medical trials to public policy changes. And they use a relatively uniform set of inferential statistics with lots of known and available diagnostics. Behavioral science experiments, within the broader realm of RCTs, should be first used as a testbed whose results can be generalized. Because behavioral science is at the vanguard of open science practices, replications abound (there are thousands of them) to serve as ground truth training data. Key Hypothesis Therefore the pilot would test, in behavioral RCTs that have been replicated, whether the quality of evidence for a claim can be used to accurately predict whether that claim will replicate. Secondary Hypotheses Compared to claims that replicated, non-replicated claims demonstrate a greater share of forensic anomalies in their source literatures. Hypothesis level claim and statistic extraction is accurate enough to scale living evidence without onerous human review costs. Replication prediction is more accurate than prediction markets6 or journal prestige. If all the different quality signals we gather do accurately predict which studies will replicate, then we can use that model to score evidence to power the living evidence layer. Why this is informative regardless of outcome If the pilot succeeds, the architecture extends to medical RCTs (where Living Evidence already operates and integration is mostly about claim representation), then to slices of basic biology with stable replication structure. If it fails, the field learns which quality signals are load-bearing and which ones metascience has oversold. Either result is a contribution to knowing what the literature supports. Implications for funders Because this burgeoning ecosystem of builders already exists, a well-informed philanthropic or government funder could play a crucial catalyzing role in bringing this future about. They could play at least three roles: creating open structured datasets, publishing open benchmarks and incentivizing the solving of key technical challenges. First, open archives of papers that the government maintains, like PubMed, could be turned into structured data amenable to large scale metascience and claim aggregation. I know the US government already has an interest in doing this, though some key open questions remain unanswered. How do you determine the best models and systems for accurately extracting information from papers? How can you establish a robust way to allow researchers to flag errors and correct them? And finally, how do you create a legal regime in working with publishers to maximize the scope of available papers? For the latter, a university or a private philanthropy may be better positioned to make structured data publicly available under journal subscription terms or fair use. Philanthropists or government funders could also coordinate to create or commission benchmarks that evaluate whether important problems have been solved. For example, an open benchmark for claim extraction from a range of different scientific article types would be extremely helpful. Ensuring the underlying data are accurate is vital for creating these evaluations. I’ve discussed opportunistically using various human-created datasets for this purpose, but a consistent problem is that errors in human data make it difficult for them to serve as a gold standard. Finally, with structured data and benchmarks available, the government or private philanthropy could use them to incentivize groups to develop machine learning systems that meet these benchmarks. Prizes are one potentially valuable tool for this. For example, you could establish a prize for a system that accurately updates a living meta-analysis for a small set of claims. Prizes are particularly useful as signals of problem importance, and can help create vibrant ecosystems of public and private research—see, for example the role the government played in kickstarting the current work on nuclear fusion. Conclusion The drawbacks of the current scientific publishing system are known. Scientists agree, metascientists agree, philanthropists agree: the published PDF plus citation graph isn’t the right substrate for maintaining a representation of the evidence base in science. The pieces needed to build the alternative either already exist or are rapidly taking shape. The community is forming around exactly this problem, with concrete partnerships and shared infrastructure. A pilot should start on behavioral science RCTs because that’s the slice of empirical science most amenable to legibility, where replication ground truth is richest, and where the failure modes are best documented. What’s been missing is the galvanizing mission to assemble these pieces into something that works. That’s what I’m proposing to build. *** 1 I have a broader field map that I’ll release publicly soon. This is me, building in public! 2 If this is something that you are excited about, please reach out and talk to me. 3 More on this very soon too! 4 This tests whether, given the code and the data, you can get the same statistics as reported in the published paper. 5 This tests whether the results are the same as a paper’s given alternative analytical decisions in conducting the analysis (like outlier omission). Closely related is the idea of a “multiverse” where you come up with many different ways of answering the same underlying research question with the same data, and test whether the results hold in all those alternative methods. There’s been work on the latter as well. 6 Some of the replications, e.g. those from the SCORE project, had paired the experiments with forecasts from prediction markets. So we get to look at this for free.

Jun 8 • 4:44 PM EDT • Science • goodscience.substack.com

What It Takes To Be A Top Tier Entertainment Lawyer in 2026

Share I’ve recently run several popular posts breaking down data related to sought after legal jobs. General Counsel Big Law Appellate Attorney Here is another in this series. Two Lawyers, One Elite Market Entertainment law can sound like a single professional category. In practice, the lawyers who reach the top of the Hollywood market often look quite different from one another. Consider two attorneys from the 2025 top-entertainment-law universe. Lesley Freeman represents one route: the company-side entertainment lawyer. She is chief legal officer of AGBO, where she oversees company-wide business and legal affairs across film, television, video game and interactive experiences, and technological innovation, after senior legal roles at MGM, Amazon MGM Studios, HBO, and O’Melveny. Daniel Petrocelli represents another route: the outside-counsel trial lawyer. He is chair of O’Melveny’s trial practice and a vice chair of the firm, with a national litigation practice that includes entertainment, sports, and media disputes. Their careers differ by platform, role, practice area, and professional identity. One sits inside an entertainment company; the other practices from a major law firm. One is associated with corporate and governance work; the other with litigation. Yet both fall within the same publicly recognized top tier of Hollywood lawyers. That contrast points to the article’s central question. If there is no single mold for a top entertainment lawyer, are the paths simply idiosyncratic, or do they follow recurring patterns? The data suggest the latter. The attorneys recognized on The Hollywood Reporter and Variety’s 2025 top-attorney lists do not follow one career template, but their paths are not random. They cluster around several defined routes: entertainment-focused private practice, company-side or operator experience, corporate and finance conversion, litigation conversion, public-service-to-litigation pathways, and smaller specialized lanes in labor, employment, and celebrity family law. Across those routes, the recurring ingredients are platform strength, educational capital or Los Angeles market proximity, long career tenure, specialized practice identity, and entertainment-industry fluency. The article examines five dimensions of the top-attorney sample: route into entertainment law, firm or organizational platform, education pipeline, seniority, and practice specialization. Data and Methodology The dataset includes 103 attorneys drawn from The Hollywood Reporter and Variety’s 2025 lists of top entertainment or Hollywood attorneys. For each attorney, the dataset tracks current organization, law school, J.D. year where available, first-known bar admission year, practice area, prior roles, platform type, and route into entertainment law. The sample is best understood as a recognized-attorney dataset, not a census of all entertainment lawyers. It captures lawyers who reached public top-tier recognition in 2025, rather than every lawyer practicing in the entertainment sector. Multiple but Defined Routes Into Entertainment Law The first question is how these lawyers entered the entertainment-law market. Because every attorney in the dataset is entertainment-related by definition, the key distinction is not whether they practice entertainment law. It is how they got there. The largest group followed what might be called the entertainment private-practice route. These attorneys appear to have built their practices around entertainment, media, talent, music, rights, production, intellectual property, or adjacent industry work relatively early. That route accounts for 40 of the 103 attorneys in the sample, or 38.8%.

Jun 8 • 12:46 PM EDT • Entertainment • legalytics.substack.com

"It's top of mind and being worked on" Xbox confirms anti-scalping methods will be in place ahead of the Xbox Series X25 preorder

The Xbox Series X25 will drop as a limited-edition console in November 2026, and Xbox want to make sure they aren't all nabbed by scalpers.

Jun 8 • 9:54 AM EDT • Technology • windowscentral.com

How to keep ticks out of your yard

Skip the essential oils and try expert-recommended tick prevention methods to make your yard less attractive to ticks.

Jun 6 • 8:00 AM EDT • Science • popsci.com

The fastest way to board an airplane, according to science

Better, faster boarding methods exist, so why don’t we use them?

Jun 5 • 1:29 PM EDT • Science • popsci.com

Giant fire tornadoes could clean up oil spills faster with less pollution

Researchers have shown that controlled fire whirls can clean up oil spills faster and more cleanly than traditional burning methods. The spinning flames consumed up to 95% of the oil, cut soot emissions by 40%, and could help prevent spills from reaching sensitive marine habitats.

Jun 5 • 8:00 AM EDT • Science • sciencedaily.com

Hidden supermassive black hole pairs may finally have a visible signal

Scientists have proposed a new method for finding tightly bound supermassive black hole pairs by searching for stars that flash repeatedly as their light is magnified by the black holes’ gravity. The timing and brightness of these bursts could provide a unique fingerprint of black holes slowly spiraling toward a future collision.

Jun 5 • 8:00 AM EDT • Science • sciencedaily.com

How Science Works

The 2nd Weather and Climate Livestream is now underway. It is organized by a group of early-career researchers concerned about declining funding for the field and eager to demonstrate how weather and climate research makes a difference in our lives. Last year’s event was a great success, drawing terrific press coverage including a piece in the NY Times. This year features a strong lineup of talks aimed at a general audience — I highly recommend tuning in. Share I gave a talk yesterday about How Science Works in Three Steps. You can see the short presentation here (I’ve appended a transcript below): And please tune into the livestream here. It runs through tomorrow at 6 pm ET. Thanks for reading The Climate Brink! Subscribe for free to receive new posts and support our work. Subscribe Cleaned up transcript: Thank you, and thanks to everyone tuning in. I want to talk about something I think a lot of people don’t really understand: how science actually works. Arguments over any scientific topic — climate change, vaccines, you name it — revolve around competing claims. For climate change, the claims are: Is the Earth warming? Are humans to blame? What will the impacts be? Over the last 150 years, the scientific community has developed a remarkably robust method for sorting out which claims are true and which aren’t. That method is what I want to walk through. So how does science generate knowledge? If you ask a high schooler, they’ll give you the version they learned in ninth grade: an individual scientist forms a hypothesis, runs an experiment, and draws a conclusion. That’s more or less what happens at the individual level, though in practice it’s more iterative — you design, test, and refine all at once, landing on a slightly different idea each time until you reach a conclusion about whatever hypothesis you’ve ended up with. But this isn’t science. It’s only step one. Any individual scientist can make mistakes — scientists are human. Maybe there’s a bug in the code, maybe there’s an error in the experiment. Just because someone ran an experiment and reached a conclusion doesn’t mean it’s right, and scientists don’t treat a single result as settled truth. Step two is peer review, the first layer of quality control. The scientist writes up what they did and submits it to a journal, which sends the paper to other experts in the field. Those experts judge whether the methods are sound, whether it properly references prior work, and whether the conclusions actually follow from the data. Ask any scientist and they’ll tell you peer review is miserable — the comments come back brutal, often harsh, and you have to revise and resubmit, sometimes multiple times, before an editor finally accepts the paper. Peer review catches an immense amount of bad science, but it can’t catch all of it. Reviewers get sloppy or overworked, they miss obvious mistakes, and they can’t catch hidden errors — a bug in the code, a misread instrument. So a peer-reviewed paper making it into a journal doesn’t mean the paper is right. Nobody treats a single paper as the final word. That’s where step three comes in: the crucible of science. Important results get retested by the broader community. If you publish something interesting, it gets dissected. Sometimes people try to reproduce your work directly but more often they test its implications. If someone claims X is true, and that implies that Y is also true, then scientists will go check Y. If a claim survives this gauntlet long enough, it becomes accepted. That’s how we generate knowledge. Let me give an example: the ozone hole. In 1985 — and I doubt many people watching were around then, but I remember it well — Joe Farman and his colleagues published observations from Antarctica showing that a huge chunk of ozone was disappearing every year. This was shocking because most atmospheric chemists had expected ozone loss to occur at mid-latitudes and high altitudes, not over the South Pole. When scientists see something they don’t understand, they rush to explain it, and several competing hypotheses quickly appeared in the peer-reviewed literature. One pointed to chlorine chemistry from chlorofluorocarbons. A second blamed nitrogen chemistry, possibly driven by solar proton events — meaning the sun was responsible. A third argued it wasn’t chemistry at all but dynamics: winds were carrying naturally low-ozone air from the lower atmosphere up into the stratosphere. Then the community went to work testing which theory could survive the crucible. Aircraft flew into the ozone hole and found no nitrogen, ruling out the nitrogen theory. Measurements showed the air in the polar vortex was descending, not rising — which would bring high-ozone air down, eliminating the dynamics theory. Meanwhile, those same flights measured enormous amounts of chlorine, strongly correlated with exactly the regions where ozone was being destroyed. That became known as the “smoking gun” paper, and it established that chlorine chemistry was the cause. Through this process, a consensus emerged. And it’s worth being clear that this consensus is organic. There’s no vote, no poll, no meeting where it gets decided. Scientists go to conferences, talk to one another, and independently arrived at the same answer. It’s the ultimate free market of ideas. After the consensus was established, the peer-reviewed literature doesn’t even mention the rival theories — it simply takes chlorine chemistry as given. That’s what a consensus looks like. It doesn’t mean every single scientist agrees, but it does mean there’s no longer any legitimate debate. So where can you see what scientists actually think? It’s all in the peer-reviewed literature, which contains the entire historical record of the argument: the discovery, the competing theories, the debate, the testing, and finally the community coalescing around one answer. But there’s a lot of room for misrepresentation. You can dig up an old paper claiming the ozone hole was caused by dynamics and wave it around as if there still was a debate about the cause of the ozone hole — without mentioning that the idea was disproven long ago and that even its own authors no longer believe it. There’s a bigger problem, though: the peer-reviewed literature is written in a language I call “nerd.” It’s extremely hard to read — honestly, some of it is hard for me to follow. It takes graduate students years to work through the literature in a single field, so we can’t expect policymakers or ordinary people to do it. This is where scientific assessments come in. The most famous is the IPCC — the Intergovernmental Panel on Climate Change. The job of an assessment is to read and summarize the peer-reviewed literature, synthesizing what’s settled, what’s been disproven, and what remains genuinely debated. To ensure the assessments accurately summarize the peer-reviewed literature, assessments are written by large teams, which are far less prone to bias than individuals and which dilute the influence of any one scientist with an axe to grind. The teams are deliberately assembled to avoid stacking the deck, and the reports themselves go through multiple rounds of peer review. That rigorous process is exactly why you can trust them and why people consider the IPCC to be the gold standard of what we know about the climate system. An assessment produced through a different process may well not be credible. You can even watch the consensus evolve across assessments. Take the attribution of warming. The 1990 IPCC report said the observed warming was broadly consistent with model predictions but also comparable to natural variability — in other words, we don’t know whether humans are responsible. By 1995, it concluded that the balance of evidence suggested a discernible human influence — a sentence only a committee could write, and one that barely commits to anything. By 2001, most of the warming over the previous 50 years was judged “likely” due to greenhouse gases; by 2007, “very likely”; by 2013, “extremely likely.” The 2023 report says essentially the same as 2013 — there’s not much stronger language available. So, to wrap up: science is our ultimate tool for deciphering the universe — the most successful method we’ve ever developed for determining what’s true and what isn’t. Our understanding is written into the peer-reviewed literature, so if you want to know what scientists think, that’s where to look. And for those of us who don’t speak nerd, scientific assessments are the Rosetta Stone — they translate nerd into English. Let me open the floor to questions. Thank you.

Jun 2 • 10:35 AM EDT • Science • theclimatebrink.com

The methodology of an AP-KFF Health News investigation into medical neglect at ICE detention centers

KFF Health News and The Associated Press have been investigating allegations of medical neglect from people detained by U.S. Immigration and Customs Enforcement during the second Trump administration.

Jun 2 • 9:07 AM EDT • Health • seattletimes.com

The methodology of an AP-KFF Health News investigation into medical neglect at ICE detention centers

Jun 2 • 9:06 AM EDT • Health • 10tv.com

Willard’s ‘small ball’ tactics a recipe for success

WILLARD–The Willard baseball program has been a winning machine, under Head Coach, Scott McGee. The Tigers will play in their 7th State Semifinal, in McGee’s 19th and final season, Friday night. The bulk of their success, offensively, has come from a method that is “outdated” by today’s standards — ‘small ball.’ Rather than adapt to […]

Jun 1 • 1:22 AM EDT • Sports • sports.yahoo.com

Scientists shatter 30-year superconductivity record with zero-resistance material that works at normal pressure

"Our method shows that it is possible to retain that state without maintaining pressure."

May 31 • 1:00 AM EDT • Science • yahoo.com

Trump Squeezes Immigrants by Cutting Them Off From Jobs, Healthcare and Housing

The methodically planned strategy is intended to pressure noncitizens, including many with legal status, to leave the United States.

May 30 • 5:00 AM EDT • Health • nytimes.com

Scientists used a method from ecology to identify whether icy moons could hold conditions for life

Future missions may be able to take only a small, damaged sample from space back to Earth. A simple analysis tool could help determine whether its contents suggest the presence of life.

May 29 • 8:36 AM EDT • Science • theconversation.com

Goal-Concordant Care Collaboration a Driver in Health Equity Improvement

Some hospices have found success employing more community-based methodologies in their health equity improvement efforts. Forging deeper relationships

May 28 • 9:26 AM EDT • Health • hospicenews.com

A Scientific Method of Resisting

This post originally appeared on If You Can Keep It, a publication of Protect Democracy. The second Trump administration has set about dismantling the institutions of American science. Over the past 16 months, the administration has eliminated thousands of federal scientific positions, imposed

May 28 • 8:00 AM EDT • Science • blog.ucs.org

UToledo Scientists Develop New Method to Estimate Hidden Species

The new model for collecting species data within ecosystems is published in the May issue of Ecological Informatics.

May 28 • 4:00 AM EDT • Science • news.utoledo.edu

Many people skip colonoscopies. Experts just added a blood test to the options.

Blood tests miss early cancers and should be limited to people who decline other methods, new guidelines say.

May 27 • 7:00 AM EDT • Health • washingtonpost.com

Why is hantavirus so deadly? It’s not what you may think

Andes hantavirus causes deadly lung failure, but its method of attack differs from other respiratory illnesses. The details might inform future treatments.

May 26 • 9:00 AM EDT • Science • sciencenews.org

Advancing high-threat pathogen preparedness in WHO South-East Asia Region: 2025 in review

Effective preparedness for high-threat pathogens demands more than technical tools — it requires a coherent strategy, sustained country engagement, and the institutional infrastructure to translate evidence into action. In 2025, the Pandemic and Epidemic Management (PEM) Unit advanced all three, working across the full spectrum of high threat pathogen (HTP) preparedness: from methodology development and evidence generation to country-level technical support, emergency response, and regional workforce strengthening.At the core of the PEM unit's work is building the regional evidence and policy architecture needed to prioritize and respond to HTPs systematically. A major milestone was the development of the HTP Prioritization Methodology — a structured, multi-criteria approach to ranking pathogens by epidemic potential, severity, and national context — and its national pilot in Bangladesh, where SARS-CoV-2, Nipah, dengue, and cholera emerged as the highest-priority threats, informing the PEM unit's contribution to 2026–27 biennium prioritization and workplan development (Access link here).Underpinning this work, the PEM unit advanced the peer-reviewed evidence base for HTP preparedness in the South-East Asia Region (SEAR), with three publications in international journals in 2025: Development of a zoonotic influenza distribution assessment and ranking system (ZIDAR): Technical application in Nepal to support cross-sectoral risk-based surveillance in One Health; Implications for influenza A virus surveillance in Southeast Asian Region countries: a scoping review of approaches for the surveillance of swine influenza viruses at human-swine interfaces in BMJ Public Health; and Operationalizing multisector partnerships: a Theory of Action and Reflection tool for zoonotic influenzas in Health Policy and Planning. Together, these contributions move the Region’s HTP preparedness agenda from practice to science — generating the transferable methodological foundations that will inform evidence-based capacity strengthening in Member States.Country-level engagement in 2025 reflected the breadth of contexts in which HTP preparedness must function. Technical support was provided for Mpox and cholera events across the Region, including coordination of cholera and acute watery diarrhea prevention and control in Myanmar in the wake of the March 2025 earthquake. In Myanmar, the PEM unit contributed technical leadership to the earthquake emergency response — one of the most complex humanitarian emergencies in the SEAR — as Health Operations and Technical Support lead within the Incident Management Support Team. This included strengthening emergency response planning, supporting operational and after-action reviews, and providing monitoring and evaluation support for both acute and protracted crisis response. The breadth of HTP support provided to emergency operations across the SEAR was documented in the PEM unit’s contribution to the regional report for the Health Security Interface Technical Advisory Group.In Sri Lanka, technical collaboration with the WHO Country Office and the Ministry of Health laid the groundwork for the National Steering Committee's 2026 annual meeting, development of Standard Operating Procedures for specialized emergency response, and a national training programme — all structured around evidence-based risk assessment for specialized hazards including HTPs.Across the SEAR, the unit contributed to strengthening the workforce architecture that underpins HTP response. Technical inputs shaped the WHO South-East Asia Regional Health Emergency Workforce Strategy 2025–2030, and the PEM unit supported conceptual development of the health emergency workforce framework for the Pandemic Fund Round 3 proposal.Alongside this, the unit's sustained engagement on the meningitis agenda culminated in the launch of the Regional Implementation Framework to Defeat Meningitis in South-East Asia by 2030 at the Seventy-eighth Session of the Regional Committee, ensuring the Region's priorities were reflected in the Global Technical Task Force and expanding the unit's HTP engagement beyond outbreak-prone zoonotic pathogens (Regional Implementation Framework to Defeat Meningitis in South-East Asia by 2030).Taken together, 2025 demonstrated that meaningful HTP preparedness is built incrementally — through methodology, engagement, and the steady accumulation of institutional capacity across Member States.Bangladesh piloted the HTP Prioritization Methodology and identified the highest-priority pathogens in the country context (Photo credit: WHO Country Office, Bangladesh).

May 25 • 8:00 PM EDT • Health • who.int

How integrating tradition and self-care has strengthened public health in the Americas

On 13 May 2026, a regional dialogue for the Americas titled, Innovative Experiences to Strengthen Health and Self-Care through Traditional, Complementary, and Integrative Medicine, was hosted by EsSalud, the government agency responsible for social security and health care in Peru.The event brought together representatives from the World Health Organization (WHO), the Pan American Health Organization (PAHO), WHO collaborating centres, the health sector and academia. It presented regional perspectives from BrBolivia, Brazil, Mexico and Peru to explore how self-care and traditional medicine can strengthen public health, empower communities and support more inclusive models of care. Across all four countries, a clear message emerged: traditional medicine is not being positioned as an alternative to formal systems, but as a way to strengthen them. In the Americas region, the challenge is to consolidate intercultural and holistic care, with the aim of strengthening the healthcare system – making care more preventive, culturally relevant and community-based.Peru: institutionalizing complementary care over 28 years Dr Martha Villar López from EsSalud Peru demonstrated how integration can be institutionalized over time. With nearly three decades of investment, including a research programme dating back to 1998, traditional medicine is now embedded within public health infrastructure. EsSalud’s flagship programme, Reforma de Vida, operating as Prevenir, takes multidisciplinary teams into workplaces to reduce and detect risk factors for chronic noncommunicable diseases. Education cycles are structured around three pillars: celestial nourishment, focused on life purpose and movement; terrestrial nourishment, centred on regional food and healthy diets; and human nourishment, addressing identity, relationships, stress and spirituality. Grounded in Andean cosmovision and the principle of the ayllu, the programme aligns with local cultural values. Since 2007, it has trained over 6600 health leaders, certified more than 3100 health-friendly organizations and built alliances with nearly 11 000 employers.Bolivia: legal recognition and medical pluralism Adelino Pau Carpacheco, an 82-year-old Callawaya healer, described working with more than 220 medicinal plants, supported by deep generational knowledge. Traditional healers and plant medicine are highly respected in the country. Bolivia’s contribution also highlighted the role of policy in enabling integration. Through Law 459, traditional medicine has been formally recognized within a legal framework and led the country to medical pluralism where traditional medicine coexists with biomedicine, and both are now offered free of charge through the public health system. Mexico: preserving Indigenous knowledge and reinventing food culture Mexico presented two complementary approaches focused on knowledge preservation and food systems. In Veracruz, communities partnered with a university to safeguard Totonac traditional medicine through a diploma programme launched in 2019. This collaboration has already produced practical outputs, including manuals and a dictionary, helping to sustain knowledge at risk due to migration and generational change. Alongside this, Dr Hernán García, Directorate of Traditional Medicine and Intercultural Development – Mexico, explained how the Dieta de la Milpa programme addresses Mexico’s dual burden of malnutrition and rising noncommunicable diseases. Rooted in traditional Mayan cultivation systems and ingredients, it promotes healthier diets through community-led, intercultural approaches involving local authorities, Indigenous leaders and cooks. By reconnecting food, culture and health, it offers a practical pathway to prevention. Brazil: community therapy as a public health tool Brazil’s experience centred on Integrative Community Therapy, a methodology developed over 40 years ago by Dr Adalberto Barreto and now used in more than 47 countries. Therapy circles create spaces where participants share experiences and coping strategies, building social support networks at very low cost. Within Brazil’s Unified Health System, the approach has expanded rapidly since its inclusion in national policy in 2017. By 2025, more than five million integrative practice procedures were delivered annually in primary care, with registrations for this therapy increasing by over 500% in eight years. The main challenge now is equity, with access still concentrated in urban areas such as São Paulo. A shared regional direction against a global backdrop Drawing these experiences together, Dr Natalia Aldana of the TCIM Network of the Americas highlighted the shared outcomes of the interventions discussed. Such approaches strengthen healthy behaviours, social networks and community resilience; they are low-cost, adaptable and enable active participation in care, while showing potential to reduce the burden of noncommunicable diseases.The regional momentum mirrors a broader global shift. Dr João Paulo Souz, Director of BIREME (Latin American and Caribbean Center on Health Sciences Information), the specialized center of PAHO/WHO, emphasized that the Global Traditional Medicine Strategy 2025–2034 promotes a vision centred on people, evidence and integrated use. He noted that health should be understood through the relationships between people, community, nature and spirituality. Self-care interventions as a critical pathway towards universal health coverage Dr Manjulaa Narasimhan, Unit Head for Sexual Health and Well-being across the Life-course at WHO, delivered a presentation titled Advancing Self-Care in Traditional Medicine: Aligning the WHO Traditional Medicine Strategy 2025–2034 with the WHO Self-Care Framework, co-authored by Dr Geetha Krishnan Gopalakrishna Pillai, Unit Head for Research, Data and Innovation at the WHO Global Traditional Medicine Centre. WHO recommends self-care interventions for every country and economic setting as a critical path to reach universal health coverage – and traditional medicine acts as a bridge for self-care. Dr Narasimhan explained that traditional medicine contributes most effectively to self-care when embedded directly into primary health care, not operating in parallel, siloed systems. This, she stated, “is possibly the only sustainable way to deliver continuity of care that meets the needs, rights and priorities of communities and individuals”. The Global Traditional Medicine Strategy 2025–2034 is a move towards a more people-centred approach to health care that champions holistic approaches to health equity and patient autonomy.The integration of traditional medicine and self-care requires collaboration across disciplines, clear referral pathways, trained health and care workers, and strong leadership that supports integration. The WHO self-care competency framework defines 10 key competencies for health and care workers to support self-care in their clinical practice, supported by the WHO guideline on self-care interventions for health and well-being. These documents help health-care workers safeguard their own well-being and ensure that care is consistent, safe and grounded in shared standards and values.Together, the discussion through this dialogue points to a fundamental shift in how health systems are designed in the region, and globally, towards models that are more inclusive, culturally-grounded and responsive to the needs of the communities they serve. It is a move towards a system where traditional medicine is respected and responsibly integrated, where self-care provides empowerment and evidence-based care, and where health systems are supportive rather than being distant from these systems.Traditional medicine perspectives from Bolivia, Mexico and Peru - WHO's "Restoring Balance" seriesInnovative Experiences to Strengthen Health and Self-Care through Traditional, Complementary, and Integrative Medicine was streamed in Spanish, with Spanish and Portuguese subtitles. Recordings are available through the CABSIN YouTube channel with Portuguese subtitles and on the BVS MTCI Americas YouTube channel with Spanish subtitles. Dr Narasimhan’s session can be watched in English on both channels.

May 24 • 8:00 PM EDT • Health • who.int