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Maine Supreme Court affirms Bellow’s decision to invalidate trans sports ballot question
The Maine Supreme Judicial Court Friday affirmed the Maine Secretary of State Shenna Bellows’ decision to remove a question about transgender sports from the ballot this November because its campaign committee did not collect enough valid signatures. The group, called “Protect Girls Sports,” initially submitted enough signatures to qualify for the November ballot, proposing an […]
MAGA's attack on science is even worse than it looks
In my post on America’s 250-year anniversary, I argued that respect for the individual was the “secret sauce” in the U.S.’ long-lasting preeminence among nations. But it was certainly not the only factor. There were plenty of institutional innovations that helped the U.S. stay on top — economically, militarily, and in terms of the attractiveness of its society. One of these was American science. Today we take things like the modern research university, government grants for science, public-to-private research spinoffs, etc. for granted, but a lot of that infrastructure wasn’t there before World War 2. It was either invented or scaled up massively by the U.S. government in the postwar period, led by far-sighted scientist-bureaucrats like Vannevar Bush (pictured above). If you want to read about this history, a good place to start would be Jonathan Gruber and Simon Johnson’s excellent book Jump-Starting America. Those scientific institutions didn’t exist in a vacuum, however. They were backed by the U.S. government’s abiding faith in the power of science — and, even more fundamentally, by deep popular trust in the scientific enterprise. Science gave us radar and the atom bomb in wartime, and in peacetime it gave us plastics, vaccines, cheap food, and a thousand other things that made our lives easier. Science was also the driver behind American industry — chemicals, aerospace, telecommunications, computers, electronics, and so on. We owed science our jobs, our livelihoods, our comfortable living standards, and our greatness and power as a nation. It’s little wonder that both political parties, even as they fought viciously over other issues, were steadfast in their support of science. For a long time, the only people who distrusted science were a hippie fringe on the left who disliked modernity (or thought they did, anyway), who also disliked American industry and American power, and who subscribed to an early version of degrowth environmentalism. America’s scientific enterprise is still strong, especially compared to the systems in Europe, Japan, Korea, and other developed countries. It has lost a lot of ground to China in a relative sense, but a lot of that is because of China’s incredible growth; as China has poured untold amounts of money and talent into its research labs, spending and output have overtaken the U.S. by some measures. There are a few ways in which China’s rise creates problems for American science — for example, top scientists can choose to work in China instead of in the U.S. — and of course there’s the concern that China’s technological strength will help its military to reign supreme. But overall, China’s rise in science should be good for American science, since American scientists can use Chinese discoveries for free and build on them. The much bigger problem is that the scientific enterprise America built during and after World War 2 is now being threatened with absolute decline. The biggest problem, of course, is that much of the country — the Republican half — has basically lost faith in the scientific enterprise. To what degree this loss of faith is justified is an open question, and deserves to be discussed openly. But the larger point — that the system that powered American dominance is under threat — is true either way. Most Americans still trust science, but MAGA Republicans don’t There’s a myth, popular in right-wing circles, that scientists have lost the trust of regular Americans — either due to the increasingly left-wing composition of academic departments, or to misbehavior during Covid, or to DEI-related research taking over science, etc. This also fits with a wider narrative that Americans are losing trust in all of our institutions. But it just isn’t true. Poll after poll shows that on the whole, Americans still trust scientists and want to spend more on science. For example, here’s a Pew poll from late 2025 showing that although about a fifth of Republicans did lose confidence in science in 2020, two thirds still have at least “a fair amount” of confidence: That same poll found that scientists are among America’s most trusted groups — even better trusted than the military! In fact, Americans trust scientists more than people in most other countries do. Other polls show that although Republican trust in science has dropped somewhat, Republican support for spending more on science remains very strong: A Pew poll in 2023 found the exact same thing: So when MAGA types tell you about scientists losing their credibility, or a drop in trust in science, they’re only talking about themselves. Whatever left-wing politicization of science happened during the Biden administration — and there was definitely some of that — it was not enough to make most Republicans lose faith in the scientific enterprise, or favor research cuts in order to purge unwanted ideology from the system. That doesn’t mean I think progressives should continue down the path of politicizing scientific research. They should not, and Biden made real missteps in this area. Objectivity clearly matters for public trust of science in the long term. But as of right now, there’s no crisis of trust in science, except among the smallish minority of people who are running around screaming that there’s a crisis of trust in science. But despite science’s overwhelming popularity and public trust, Trump and his administration are launching an unprecedented and devastating attack on American science — cutting funding, and forcing science projects to undergo ideological review by government commissars. Trump’s comprehensive attack on science
Inside Rolls-Royce's factory, where custom 6-figure cars are made
At Rolls-Royce's factory in Goodwood, England, customers have tens of thousands of customizations to choose from. For some, it's not enough.
Haley Stevens knows how to win in Michigan. Dems must decide if that's enough to win the Senate
Holding Michigan’s Senate seat is essential to any Democratic path back to the Senate majority this fall.
Senate hopeful Haley Stevens knows how to win in Michigan. Democrats must decide if that's enough
U.S. Rep. Haley Stevens is closing Michigan’s Democratic Senate primary by arguing she is the party’s strongest candidate to beat Republicans
Scientists discovered that some invasive tropical plants evolved to reproduce without partners after spreading to new countries, allowing a single plant to start an entire takeover
Just one plant species can be enough to trigger an ecological invasion. Studies have shown that some tropical plants have evolved to reproduce without a mate, allowing a single individual to start a new colony.
You can complete medieval vampire RPG The Blood of Dawnwalker even quicker than previously thought - before even the prologue ends
The limiting factor will be whether you're good enough to do it, and most of you - most of us - will not be.
Hungary moves to overhaul university models banned from Horizon Europe
Hungary’s new government is aiming to overhaul the governance model of the institutions and universities that lost access to Horizon Europe and Erasmus+ funds “in a short timeframe,” according to Péter Horváth, the new state secretary for science policy and innovation. “As of today, the two non-university foundation-controlled institutions under my remit have been transformed,” he told Science|Business. “We hope the universities will follow and that this will be enough to satisfy the EU’s demands.”Under the previous government, led by Viktor Orbán and his Fidesz party, many academic and scientific institutions were restructured and made into special public trust foundations, with members strongly linked to the government given lifelong mandates and significant decision-making powers with little oversight. The European Commission deemed that this undermined academic freedom and transparency in the country, leading to a ban on 34 institutions in 2022, including 21 universities, which saw academics in Hungary lose access to Horizon Europe grants. The new Hungarian government, elected in May and led by Péter Magyar and his Tisza Party, has promised to dismantle this governance model and restore the institutions to EU programmes. As a result, the European Commission has promised to return access to the Erasmus+ education mobility programme, but so far no concrete agreement has been made on the Horizon Europe programme for research and innovation. Hungary has already made legislative changes in June to allow the institutions to be reformed and set a timeline for the implementation.The non-university foundations, which are mainly cultural centres such as the Foundation for Hungarian Culture or the Makovecz Campus Foundation, will all be dissolved by August 31 this year, a date tied to EU-set milestones that Hungary must meet to unlock frozen funds, with control transferred to relevant ministries. Meanwhile, the universities will have until 31 August 2027. For each university foundation, the government will set the dissolution date and the body to take over operations. There is no final decision on a permanent new model for the universities, according to Hungarian MEP Eszter Lakos, who is shadow rapporteur for the Horizon Europe specific programme, a separate piece of legislation detailing implementation rules for the EU’s next research programme, due to start in 2028. “The aim of the transition year is to settle this with [the universities], not to impose a model, and not to put them under state control,” she told Science|Business. “The goal is to give academic independence back to universities.”There are three models that are most likely to be implemented. One would be a return to a traditional, state-run model. Another could be a newer, more self-standing public institution. A third option would be a reformed version of the foundation models that meet EU standards. According to Lakos, the dismantling of the system put in place by the Orbán government is well underway and if all goes according to plan, Hungary could regain access to EU research money by the start of the next academic year in 2027. “I believe that the Hungarian government is doing the necessary changes so the universities could return as beneficiaries to Horizon from the next school year,” she said. In the meantime, “the universities, institutes and cultural assets carry on under proper public stewardship rather than a handful of unaccountable trustees,” said Lakos. The laws passed in June impose new safeguards: board terms are capped at four years and renewable only once, appointments are made through open competitions and sitting politicians cannot join joining these boards.It remains unclear whether a domestic science funding programme set up as a back-up scheme by the former government following the EU funding ban, called HU-rizon, could be continued. “This programme should never have had to have been established in the first place, but it has proven to be quite popular,” he said. “I am considering continuing this programme with a refined focus on helping international collaborations.”Re-organising the research network One of the first priorities for Horváth and his cabinet is to resolve questions over the future of the Hungarian Research Network, Hun-Ren. The network of academic institutes was taken away from the Hungarian Academy of Sciences in 2019 and turned into a quasi-private organisation, with similarities in its governance to the public trust foundations.Horváth and his team have consulted over 5,000 representatives from the network and the conclusion is broad unhappiness with the directors of all the institutes involved. “We have presented the results to the president and the chief executive of the network and this is currently being discussed,” Horváth said. The plan is to re-integrate the network back into the Academy of Sciences but in an improved way, “learning from mistakes of the past,” he added. The government also wants to reintegrate four humanities and social science research centres into the network that the previous government had transferred to Eötvös Loránd University. The transfer brought sharp criticism from the academic community, with a group of Hungarian research heads, including European Research Council grant recipients, sending an open letter to Orbán warning that the transfer would “cause historically significant harm to the entirety of Hungarian scientific life.” The transfer was “one of the biggest shames in Hungarian research in the past 20 years,” Horváth said. “We want to immediately re-integrate them back into the research network and to regain the trust of these institutions, because the way they were treated was really unfair.”Another pressing issue is the Élvonal Excellence Research and Talent Development Foundation, led by Nobel laureate Ferenc Krausz. The foundation signed a financing agreement with the former government earlier this year for a budget of over €730 million over the next five years. The goal is to create a world-class centre to attract top talent from abroad and to develop local researchers. But there was little transparency about this foundation, and news of its huge budget, which is nearly as much as Hungary’s entire research budget, caused a stir in the media following the recent elections. Another issue is that, as with the foundation boards of the institutes banned from Horizon Europe, there was little-to-no oversight of decisions led by Krausz. “It was an excellent idea but an unacceptable execution,” Horváth said of the foundation. “The fact that this is out of the Hungarian funding scheme, mostly concentrating on one person who decides on the budget is unacceptable for us.”The government plans to merge the centre with the National Research, Development and Innovation Office, the country’s R&D funding agency, with a reduced budget. Horváth is hopeful that Krausz will still be involved. The new government’s R&D goalsA phrase that crops up regularly during the discussion with Horváth is “democratic process.” The new state secretary is determined to involve Hungary’s research community in shaping future policies. This marks a departure from the previous government’s approach, and several people in Hungary’s research community have commented on the openness of the new government. In terms of concrete goals, Horváth and his team already have plans. He wants to create a new science fund in Hungary, based on the best practices of other European countries. The fund would not be tied to annual government budgets and would provide long-term, stable financing. “If we were to succeed in creating this fund, then I think it would be one of the biggest achievements for me in this period of government,” Horváth said. On the innovation side, he is looking into how best to bring in the private sector. “We want to make sure that we are working with the private sector to support innovation,” Horváth said. One of his big aims is to introduce entrepreneurship teaching into high schools. Hungary already has a reputable national academy offering research and innovation training in the field of natural sciences, and Horváth wants to expand this to all disciplines and across the whole country. “One of the main ways to elevate our innovative businesses is to teach our children to be innovative,” he said. “This will probably need ten years to pay off, but this is what we should do. Our aim is to make Hungary strong in our region, and this is what is needed.” Related articlesHungary’s Horizon Europe performance in numbersCommission unlocks Erasmus+ cash for Hungary, Horizon could be next‘Academic Huxit.’ Hungarian researchers speak out on impact of EU ban A more difficult task will be funding. The new government is aiming to increase research spending to 2% of the GDP by 2030, and then increase it to 3% in line with EU objectives. Currently, spending sits around 1.3%. But according to Horváth, the current budget, inherited from the previous government, is “heavily in the negative,” so any plans to increase research spending will have to start next year. Achieving 2% by 2030 already needs a big push, almost doubling the research budget. “This is something we’d definitely like to reach, and something I can see us achieving,” he said. “From the 2030s, I’d like to see an innovative generation growing up that can help us reach the 3% target.” Positivity in the new governmentDespite the many challenges facing Horváth and his team, the mood is positive. “It feels a bit like a start-up right now. Everyone is working 24/7, day and night, trying to do as much as they can. There is a lot of energy,” he said. It is a big change for the state secretary who, like many in his cabinet, is coming from a background in research or business, and not in politics. “Six weeks ago, I was sitting with my microscope and my research PhDs, so it’s been a big change for me,” said the computer scientist, who was previously the director of the Institute of Biochemistry at the Hun-Ren Biological Research Centre in Hungary and worked at the Institute for AI for Health at Helmholtz Munich. But he is relishing the task to transform the country’s R&D landscape. “We feel enormous support from the Hungarian people, but also from Europe,” he said. “We’ve received a lot of letters of support from around Europe. There is big trust there, and huge responsibility on our side. We want to get everything back on track, and there’s a lot to do.”
Colts Stick With Their Pick in 2024 Re-Draft
The Indianapolis Colts made a good enough first-round pick in the 2024 NFL Draft that they didn't have to change their fortunes in a recent projected re-draft.
McConnell speaks to Republican leaders as speculation swirls about his health
Aides have declined to release any information about McConnell's condition, fueling speculation about his prognosis and whether he will be healthy enough to be at the Capitol next week.
Deion Sanders on absence from EA College Sports game: "They're probably not paying enough"
EA Sports used to market its various offerings with this slogan: "If it's in the game, it's in the game."
Why isn’t Deion Sanders in EA Sports’ College Football 27? It might be the money
Sanders said he has a team who handles his business, but if he's not in the game, it means EA Sports wasn't "paying enough."
Opinion | How Socialism Emerged in American Politics
The debate has shifted from whether the government should redistribute wealth to how much redistribution is enough.
Schrödinger’s anthill: Quantum entanglement found in a crystal large enough to hold
A centimeter-sized crystal has revealed clear signs of quantum entanglement, showing that large, everyday objects can display surprisingly deep quantum behavior. The discovery could help solve the mystery of strange metals while opening new possibilities for ultra-precise quantum sensors and other advanced technologies.
Dave & Buster’s Entertainment, Inc. (PLAY)’s Traffic Is Coming Back, But Is It Enough?
Dave & Buster’s Entertainment, Inc. (NASDAQ:PLAY) is among the best get rich quick stocks to buy right now. On June 29, Citizens started coverage on Dave & Buster’s Entertainment, Inc. (NASDAQ:PLAY) with a Market Perform rating and without a price target. Despite its discounted valuation, the company appears fairly valued due to the limited visibility on […]
At $5,000, Could This Project 1999 Porsche Boxster Boxster Get You To Roll Up Your Sleeves?
Is that cheap enough to roll the dice despite the issues and high miles? Or would it be more prudent to give this Porsche a pass?
She quit Google and spent a year traveling; changed her view of success
Sara Wilczynska tried everything before leaving Google. She trained in sound healing, led diversity initiatives, and even cut her hours — but it wasn't enough.
Morocco Return to the World Cup Last Eight
Morocco are going back to the World Cup quarter-finals after defeating Canada in a Round of 16 tie that confirmed their status as one of the most formidable sides in international football outside of Europe and South America. A goal from Amine Ouahbi was enough to separate the teams on Friday in what proved to…
Why Doug Jones Keeps Running
Alabama’s upset artist hopes the state is changing enough to elect a Democrat again.
Ukraine paying big for foreign fighters, longer contracts could help
Foreign fighters told Business Insider that new contracts and higher pay could fix manpower issues if soldiers stick around long enough.
Scientists have now made the most comprehensive tally yet of deep-sea exploration — 43,681 dive records dating back to 1958 — and found that humans have directly seen less than 0.001% of the deep ocean floor, an area roughly the size of Rhode Island, leaving the vast seafloor across 66% of Earth’s surface essentially unobserved.
Humanity has sent cameras to the Moon, Mars, Venus and the outer planets, but on Earth itself there is still a larger frontier that has barely been looked at directly. A 2025 study in Science Advances has now put a number on that gap: since 1958, researchers have compiled 43,681 records of dives deep enough […]
The Persistent Display We Never Got
We all know the e-ink persistent displays, as they’re cheap and plentiful enough to have become ubiquitous in applications such as supermarket price labels. But we don’t often see some …
Mass. to end contract with Biobot for wastewater surveillance
Biobot proved waste water surveillance was valuable enough that governments now want to do it themselves.
Emma Navarro health issue is revealed at Wimbledon
Tennis fans know that Emma Navarro was dealing with health issues that kept her off the court for a few months. It was serious enough to cause her to miss her home tournament, the Charleston Open. Navarro won the Strousbourg…
Could We Have Been Wrong About Fish Oil and Brain Health? New Study Raises Major Questions
Fish oil supplements delivered omega-3s to the brain, but a new study found that was not enough to improve cognitive health in older adults at risk for Alzheimer’s.
Dior, Chanel bags among items offered at Taylor and Travis' wedding
If an invite to Taylor Swift and Travis Kelce's New York wedding wasn't cool enough, guests can also flex what they brought home.
Yankees Mailbag: Aiming for a deadline makeover
There’s gotta be some change on this Yankees roster, but will it be impactful enough?
Cape Fear Valley Health Lays Off 138 People as It Cuts 200 Jobs
The healthcare system says cost-cutting moves aren't enough to offset federal funding cuts and rising costs.
1 in 5 adults make health decisions based on what they see on social media despite widespread mistrust
Every few scrolls, another health expert appears on the screen. While some are genuinely qualified, others simply sound convincing enough to pass as one. With AI-generated content flooding feeds, avoiding ...
Maine group revives push for universal health care ballot initiative
Advocates are hoping to gather enough signatures to get a question about publicly funded health care on the November 2027 ballot.
10 Reasons Philadelphia Is the Best Sports City
The birthplace of the United States has another reason to rebel 250 years later. Philadelphia didn’t get enough votes to register in a recent Sports Business Journal poll of best American sports cities. New York City led the way at 20%, followed by Pittsburgh (16%) and Chicago (13%).
My 11-year-old got me to play the Lotto; we won enough for ice cream
My son asked me to play the Lotto during some bad luck. The clerk drew a ticket with our lucky numbers, and we won enough for a family treat.
IDP Rookie Profile: Anthony Hill Jr. in Redraft Leagues
Anthony Hill Jr. lands in Tennessee with a starting role and enough downhill ability to become a useful rookie IDP option.
The diminishing political returns of a solid labor market
A rebound in the jobs market hasn’t been enough to get Americans amped about President Donald Trump’s economy.
CID businesses voice frustration over lack of foot traffic, safety during World Cup
“The rest of downtown is benefiting. We are not. So, enough is enough,” one business owner said.
Victor Marx’s lead sits outside of recount threshold in Republican race for Colorado governor
Ministry leader Victor Marx on Wednesday night overtook state Sen. Barb Kirkmeyer in the Republican primary for Colorado governor, securing enough votes that — for now — put the race beyond the mandatory recount threshold. The Republican primary race between Kirkmeyer and Marx briefly entered mandatory recount territory on Wednesday afternoon, with just a few hundred […]
Kalamazoo residents submit signatures to put Healthcare Action Plan on November ballot
Kalamazoo residents submitted enough signatures to the Kalamazoo City Clerk Wednesday morning to put an initiative on the November ballot for a local healthcare
Party fever: Another political party is gathering signatures to get on Nebraska's ballot
A party that wants to put Americans and Nebraskans first is collecting signatures to secure a ballot line ahead of the November election. A similar effort is underway to establish a Nebraska Working People Party. Both efforts have a July 15 deadline to get enough signatures.
Control of the Senate Is Up for Grabs, Times/Siena Polls Find
Republicans are defending seats in Alaska, Iowa, Maine, North Carolina, Ohio and Texas as they try to maintain their majority. Democrats are competitive in all six states — but not leading in enough to take the chamber.
Building the Valley: Young Springdale man keeping lawns at bay as business grows
When Justin Burrell started landscaping in 2022, the then-14-year-old wasn’t old enough to drive himself to clients’ houses so he enlisted help from his parents. At first, he mowed lawns for some extra pocket change. Now, at 18, Burrell is working toward turn his Burrell Grounds and Services business into
Xbox is reportedly considering closing State of Decay developer Undead Labs
Having a promising project like State of Decay 3 in development is seemingly not enough to save Undead Labs from being shuttered, according to new reports.
Netflix and Superheroes Are Having a Rough Stretch on Streaming....
(Welcome to my weekly streaming ratings report, the single best guide to what’s popular in streaming TV and what isn’t. I’m the Entertainment Strategy Guy, a former streaming executive who now analyzes business strategy in the entertainment industry. If you were forwarded this email, please subscribe to get these insights each week.) I have a quick prediction before we start today’s article: You might see this data in future news articles. Not my specific charts or analysis, but the core trend I’ve been monitoring—Netflix is having a lackluster Q2—will become inescapable. Often, folks want to know “What does the data say?” Well, that’s what it says. I haven’t seen this analysis hit the trades really yet, but I have a feeling some other outlets are going to start making this case soon. Remember, you read it here first. You probably have read about the problems facing superhero films at the box office this weekend. Well, this week, I explore whether superheroes are dying on TV as well! And the data says: definitely maybe! We have a lot to cover in today’s Streaming Ratings Report, which covers the two weeks of 18-May and 25-May. Today, I’m just looking at TV, like Netflix’s disappointing Q2, superhero shows underwhelming, a few TV shows dropping off the charts, The Pitt finally ending its epic run on the viewership charts (and whether “view counts” change its status as one of the biggest shows of all time), all the flops, bombs and misses, and a whole lot more. Tomorrow, I’ve got a great rundown of the film side of things. Let’s dive right in! (Reminder: The streaming ratings report focuses on the U.S. market and compiles data from Nielsen’s weekly top ten viewership ranks, Luminate’s Top Ten Data, Showlabs, TV Time trend data, Samba TV household viewership, company datecdotes, Netflix hours viewed data, Google Trends, and IMDb to determine the most popular content. While most data points are current, Nielsen’s data covers the weeks of May 18th to May 31st, 2026. You can find a link to my terminology here.) Subscribe Television - Netflix’s Q2 Slump Continues Having analyzed streaming ratings for going on half a decade, I have learned to trust my gut, but I’m always relieved when I can find actual data to back it up. For example, after a string of very popular shows like Stranger Things, Bridgerton, The Lincoln Lawyer and The Night Agent came out, week after week, in January and February, my gut wondered if Netflix had enough new and returning TV shows to sustain them throughout the year. Since then, Netflix’s post-March slate of shows has not impressed me. This week seemed to feature a potential new hit, but then, like a classic Duffer Bros. TV show, there was a twist. I speak of The Boroughs, Netflix’s latest (and last) Duffer Bros. produced show. The pitch is “Stranger Things with older actors”. And it topped the Nielsen charts: With just two weeks of viewership, The Boroughs would have been a top 25 debut show last year: But here’s the twist: Netflix has already cancelled The Boroughs! What happened? Likely a few things. First, the show didn’t do as well globally as it did in the US. As What’s on Netflix showed, it lagged behind several other shows that got cancelled. Second, its completion rate was likely low; after an initial burst of interest, it quickly dropped off on the Samba TV and Luminate charts. Third, the Duffer Bros. left Netflix for Paramount, and that may have factored into Netflix’s decision here. (Though I tend to believe that if a show is doing well, Netflix would have kept greenlighting seasons.) Still, just because I can explain why Netflix may have cancelled this show doesn’t mean I’m justifying it. In particular, as I’ve noted before, Netflix is losing a lot of their bigger shows as they reach their natural ends, and they need to replace those shows. This show had the hallmarks of a big new genre show, and it’s their biggest hit of the last few months (in the US at least), but now it’s done. Netflix’s other show this week—The Four Seasons, the second season of the “hit” show from last year—definitely disappointed. Its sophomore season had about half the viewership of the first, only 12.7 million hours. It also only had a two week run on Samba TV, and its numbers were all down on Luminate too. In other words, even with two successes, the Q2 slump for Netflix looks real: I could add to the list of disappointments: Both Lord of the Files and Man on Fire had short runs on the Nielsen charts. Running Point’s sophomore season also opened to about half its viewership, similar to The Four Seasons. A Good Girl’s Guide to Murder’s second season—see below—didn’t even make any of the three viewership charts I track, unlike the first season. Netflix is absolutely having a dismal second three months of 2026. If this Nielsen data is any indication, and I think it is, I think this will show up in Netflix’s engagement report, and maybe even their financial outcomes. And the rest of June doesn’t look much better. We have two hit shows coming back—Sweet Magnolias, one of their quietest big shows, and Avatar: The Last Airbender, a big hit for them in 2024—but the other big swings are limited series crime thrillers i.e. no future season potential. Like I said above, sometimes when I uncover a juicy nugget like this, other outlets end up writing very similar articles mimicking the data without credit. We’ll see if that happens this time! Share Television - The State of Superhero Shows on Streaming When I first heard the pitch for Spider-Noir—a Sony TV show on Prime Video that binge-released eight episodes first on MGM+ then on Prime Video two days later—I had my doubts. It’s a live-action Spider-Man show set in the 1930s, starring Nicholas Cage, based on a cameo of a character in Spider-Man: Into the Spider-Verse. No, seriously, that’s the pitch. That could either go terrifically well or horribly wrong. Great because, Spider-Man. He’s the biggest superhero we have. I’ve seen tracking numbers that put the new _Spider-Man: Brand New Da_y as the blockbuster of the year and initial pre-sales back that up. And yet this Spider-Noir pitch feels very esoteric. (Also, the eight-episode binge release feels very “Amazon copying Netflix” again.) So what’s the data say? And what does this say about the future of superhero shows?
Careers That Shaped Biology
Every great scientific career begins with a question no one has been able to answer — and a scientist stubborn enough to keep asking it. This series looks back at the careers of some of HHMI’s most distinguished scientists — people whose contributions have changed what we know about life itself, and whose stories reflect the best of what science, and scientists, can be.
Dear 'House of the Dragon': Enough with the threats of sexual violence
"House of the Dragon" Season 3 veers too close to the worst impulses of "Game of Thrones."
I tested my workout at Gatorade's sports lab: My 3 hydration mistakes
A sweat test at Gatorade's sports science lab for elite athletes revealed I wasn't consuming enough water, electrolytes, or carbs during workouts.
No debut, but loud cheers: Belfast crowd shows love for Vaibhav Sooryavanshi
Teenage sensation Vaibhav Sooryavanshi's India debut is still pending, but the focus shifted to Ireland's historic 34-run victory in the first T20I. Despite the loss, Shreyas Iyer vowed a strong comeback. Ireland's debutants impressed, with Jai Moondra and Matt Hollard making immediate impacts, while Abhishek Sharma's quickfire fifty wasn't enough for India.
Two Yankees Pitching Prospects ‘Turning Heads’ in Minors This Year
The old saying is you can never have enough pitching, which the New York Yankees have apparently taken to heart. The Yankees have a stockpile of potential starting-pitching arms in the minor leagues, including Elmer Rodriguez, and two “head turning” prospects, Ben Hess and Chase Hampton. The Yankees lead the majors in team ERA (3.30) […] The post Two Yankees Pitching Prospects ‘Turning Heads’ in Minors This Year appeared first on HEAVY.
Seattle ups its payout for vandalized small businesses. Is it enough?
For many businesses, the reimbursement "could be the difference between someone making their rent or not, just because this is such a tough time,” said Analog Coffee's owner.
Making Our Own Luck
We are cross-posting a piece that former NIH official Kris Willis wrote for Macroscience. Kris is now the President and Founder of the Woodley Park Institute, for which I’m a board member. Picking winners or hedging bets? Federal science agencies have long wrestled with the question of how to ensure their billions of dollars of grants and contracts result in maximum benefits for Americans. On the surface, it might seem that a goal-oriented, interventionist style of management would be the best policy: prioritize our most pressing problems and distribute funding accordingly.This top-down strategy creates a unique hazard, though: bad choices can send resources in the wrong direction, resulting in slow progress that impedes the delivery of tangible benefits to citizens. Moreover, if decision makers pursue an applied advance when the underlying scientific principles remain poorly understood, they risk costly failures and a loss of support for the research enterprise at large. Examples include Nixon’s 1971 War on Cancer, undertaken on the premise that a cure could be achieved in less than a decade, the drive to build an operational commercial fusion plant by the mid-1990s, and the National Plan to Address Alzheimer’s Disease, which failed to produce the effective treatments and prevention strategies promised by 2025. The contrasting laissez-faire approach is to hedge your bets. If the path to an advance is impossible to predict, then the wisest choice might be to distribute funding to as widely as possible. The main risk of this strategy is that spreading funding thinly may limit the resources available to the most promising research, resulting in the same negative outcomes as the interventionist approach: limited support for the most promising topics, slow progress, and delayed returns. In reality, at science agencies like the National Science Foundation and National Institutes of Health, program managers navigate between these two extremes, setting some funds aside to target high-priority areas and using the rest to cover the widest possible range of meritorious proposals. This middle path seems like the most rational way to proceed, but it still requires making choices. How much should be set aside for high priority topics? What should those topics be? How should we define merit? Expert opinion can provide a helpful guide, but leading experts can have remarkably different opinions about what matters and what should be prioritized. Moreover, experts and administrators alike can be risk averse, giving an edge to high-profile, well-established concepts. What’s really needed is a data-driven framework to help guide decision-making, one that doesn’t simply repackage prestige or incumbency. Recognizing breakthroughs years in advance Many breakthroughs fail to attract funding or recognition at the earliest stages of development. Katalin Karikó, for example, spent years struggling to win grants for work on mRNA that would eventually win her and Drew Weissman a Nobel Prize. Similar stories can be told about Jim Allison’s groundbreaking studies leading to the development of cancer immunotherapy, Stan Pruisner’s demonstration that prions can self-replicate without DNA, or Robin Warren and Barry Marshall’s proof that Helicobacter pylori, not stress, causes ulcers. Yet at some point, the scientific community recognizes and responds to transformative breakthroughs like these. How does that change happen? And what if science funders could identify the areas that are on the cusp of a breakthrough? Those questions led my collaborators and me to study how scientists responded to past breakthroughs. Based on patterns in that data, we developed a means of predicting future breakthroughs, using biomedicine as a proof of concept. It’s worth taking a moment to describe how our approach works. Briefly, our prediction process begins by grouping the 18 million or so peer-reviewed papers in PubMed, the authoritative database of biomedical research, into roughly 50,000 unique topics. A small subset of these topics are so widely acclaimed as breakthroughs that they have been recognized with a major prize like a Nobel or a Lasker Award. We theorized that studying the development of these outliers over time, especially before they gained acclaim, was the key to identifying future instances of them. After defining topics, we chose 21 representative breakthroughs and asked what they looked like before they won prestigious prizes. To answer that question, we re-ran our topic-mapping algorithm repeatedly, winding back the clock one year each time, stringing together the years to follow the progress of each field as it grew and advanced. We found that in each case, the years leading up to a discovery followed a pattern: a burst of papers on a new, rapidly evolving topic, many of which quickly became influential. These characteristics—the percent of papers that are new, the percentage of papers that are brought in from other topics, and the influence of each individual paper—can all be measured separately for any given topic. Together, they act as a predictive signal that is detectable an average of five years before a transformative discovery is made, and up to thirty years before the discovery receives a major prize. Scanning the current research landscape for topics that display this signal allows us to predict what work will likely produce a future breakthrough. Each year we analyzed includes four or five signals, a number that appears to have remained constant across a twenty year time frame. In their classic work on the sociology of science, Bruno Latour and Steve Woolgar established that the desire to participate in a major discovery is an important motivator for scientists as they consider whether they should take up (or abandon) a research problem. Although further work is needed, the simplest explanation for our results is that this behavior is widespread enough to detect at scale. A foundational advance, or something like it, draws the attention of scientists and causes them to change the direction of their research. They vote with their feet, staking their own reputation and careers by publishing on and citing the new idea. That upswell of interest is the foundation of our breakthrough signal. What kind of research does our model identify as a breakthrough? After building a model based on the patterns in our 21 preselected breakthroughs, we tested it by identifying all early signals of discovery from 1994 through 1997. Of the 18 signals we found in that time period, 17 can be traced forward in time to a breakthrough. Examples include super-resolution fluorescence microscopy (see the image above), the directed evolution of proteins and enzymes (Chemistry Nobel, 2018), and sequencing the human genome (National Medal of Science, 2008). The discovery of the role of leptin signaling in obesity is a particularly interesting case study. Around 1950, scientists noticed the existence of a type of lab mouse that suffered from a unique inherited form of obesity. When given the freedom to choose their own diet, these mice ate more than normal and preferred food that was high in fat. Researchers had few clues as to why the animals overate; early experiments pointed to the existence of a soluble ob factor found circulating in the bloodstream that regulated appetite, but its identity was unknown. In 1994, Jeffrey Friedman and colleagues identified and sequenced the ob gene, noting that the protein it encoded appeared to fit the profile of a circulating factor. A year later, a trio of high-profile publications demonstrated that ob was a hormone that regulated body weight and fat deposition by regulating appetite. One of these was co-authored by Friedman, who christened it leptin from the ancient Greek word for thin. Using our model, the data from 1996 make it clear this advance would become a breakthrough. Scientists had flocked to study the biology of the new hormone, generating the flurry of new papers and citations required to produce a signal. One of these demonstrated that serum leptin concentrations reflected the amount of adipose tissue in the human body, providing clinical validation of the earlier mouse studies. Before the identification of leptin, scientists were unable to point to a specific molecule that controlled appetite and adiposity, so that it was impossible to rule out non-physiological causes of obesity; its characterization fundamentally changed our concept of weight gain. In 2010, Friedman and fellow pioneer Douglas Coleman were awarded a Lasker for the discovery. Our work also identifies breakthroughs in clinical practice and behavioral and social sciences, even though these areas are less likely to draw the attention of major prize committees. One example that falls into this category is the introduction of endovascular aneurysm repair, a minimally invasive surgical procedure for the treatment of abdominal aortic aneurysm, a leading cause of death among Americans over the age of 65. Relative to the previous standard of care, it reduces in-hospital mortality by almost four-fold. In 2017, Timothy Chuter received the American College of Surgeons’ prestigious Jacobsen Innovation award for his multiple refinements to the technique. Another under-recognized breakthrough identified by our model is the development of standardized survey instruments to assess the quality of life for HIV+ patients. The antiretroviral cocktails introduced in the mid-1990s reduced AIDS mortality, but treatment came with serious side effects. The new evaluations showed that patients whose disease progressed had worse physical functioning than Americans with other chronic diseases, while those who were asymptomatic maintained a health-related quality of life on par with the overall US population. This evidence made it possible for patients and activists to argue that even in the absence of a total cure, and in spite of the side effects, alleviation of symptoms was a worthwhile priority for clinicians. My colleagues and I have failed to identify any significant recognition for the physicians and health policy experts who pioneered this advance, although in 2016, researchers called for the World Health Organization to set targets for good health-related quality of life as part of its framework to end the AIDS pandemic. From forecasting to funding How should science funders use our predictions? Any serious discussion of what we should do with this new capability needs to begin with an understanding of its limitations. We can’t (and shouldn’t) invest all of our resources in the small number of topics predicted to produce breakthroughs. Innovative new fields are born from existing ones; they rarely arise de novo. If funders don’t maintain a diverse portfolio, the breakthroughs of tomorrow will have no antecedents. Think of this as eating the seed corn, or killing the goose that lays the golden egg. There are also multiple goals of funding beyond basic scientific discovery, including translating discoveries into clinical practice, developing new technologies, supporting economic development, and training new scientists. The investments needed to accomplish these goals are likely different from those required to support emerging breakthroughs. Finally, we must be aware that we may not capture every instance of a breakthrough. The concept is fuzzy, and not every significant discovery is recognized with a major award. Further, breakthroughs are rare, meaning that our dataset is, by necessity, small. This makes formal estimates of accuracy challenging. Although our overall success rate appears to be high, any one signal may turn out to be a false positive. We found one apparent example: the development of the third generation COX-2 inhibitors, Vioxx and Celebrex, which were much celebrated in the early 2000s as effective but non-addictive pain relievers, meets all the algorithmic criteria of a breakthrough. Five years after it received FDA approval, researchers demonstrated that Vioxx was associated with serious cardiovascular complications, and the manufacturer voluntarily pulled the drug from the market. Celebrex remains available, although like other NSAIDs, it carries an FDA warning for increased cardiovascular risk. Decision makers who were overly focused on the breakthrough potential of this research might have wasted substantial resources nurturing an area that ultimately proved to be a failure—but so would those who relied on expert opinion at the time. That said, the potential benefits of funding the next mRNA vaccine or cancer immunotherapy years earlier than we might have are large. When we can’t assume the outcome of an action, it’s worth conducting an experiment. Can targeted support for areas that are poised to produce a breakthrough increase the return on scientific investment without cannibalizing future advances? With the necessary administrative infrastructure in place, conducting this experiment would be straightforward. First, identify all the breakthrough signals between 2018 and 2023, select half at random, and commit to a decade of investment. For biomedicine, a six year window should yield about 30 topics with the potential to produce a breakthrough. Providing strong support to half of these might be accomplished for $300 million a year. That’s roughly half of the recent annual budget of the NIH Common Fund or around 20% of the fiscal year 2025 budget for ARPA-H. After five years, then again at ten, compare to see which group — the one that was actively managed, or the control — produced more breakthroughs, and on what timescale. Although we used biomedicine as an example, the same experiment could just as well be run for physics, materials science, or any other discipline. Any attempt to undertake such an experiment should keep three points top of mind. First, we can predict the topic of future breakthroughs, but the people and vision for how to move the work forward are still important. In practice, this means success requires active program managers with the expertise to develop the science and the authority to do so, including by recruiting investigators. Second, we would be wise to learn from the failures of past attempts to fund transformative research. High among these are funding modestly repackaged work, confusing the genuinely novel with the merely unfamiliar, and relying too much on incumbent investigators. All of these risks can be mitigated by thoroughly and intelligently integrating high quality data into portfolio management. Finally, we need to have patience. Even with strong funding support, producing a breakthrough takes time. If supporting breakthroughs is the best way to nurture the birth of new fields, we also need to accurately describe and properly manage the other two stages, so that we invest wisely throughout the productive lifetime of ideas and divest once they reach the point of diminishing returns. We would benefit from more study of all of these phases, especially the transition from one to another. More research could answer questions like: When does a breakthrough become an established field? How do the availability of funding, the size and characteristics of the available workforce, and the accumulation of evidence that disagrees with prevailing models affect a field’s decline? Exactly how do old ideas give birth to new ones, and can we speed up the process? The more we understand about the dynamics of scientific progress, the better we can maximize the odds that our curiosity leads to results. I’d call that finding a way to make our own luck.
The Ole-Miss All-Transfer Team: Offense
Now that NIL and the transfer portal are in full swing, creating NCAA Free Agency, there has been enough time for us to be able to go back and look at who have been the most impactful transfer Rebs so far. There will be an 11 man offense and 11 man defense and maybe an […]
Brad Stevens discusses ‘excitement’ surrounding Chris Cenac Jr.
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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.
Athlon Sports picks Bengals to resurface an old, heartbreaking trend
Would this be enough for Zac Taylor to get another season as the Bengals head coach?
Athlon Sports picks Bengals to resurface an old, heartbreaking trend
Would this be enough for Zac Taylor to get another season as the Bengals head coach?
Overwatch Fans Revolt Over New Skins That Cost Too Damn Much
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Celtics' star Jaylen Brown's future remains murky
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Yankees even series, Malgeri gets two hits in debut
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Science Will Not Save the Abortion Pill : The Hastings Center for Bioethics
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Roku May Help Fox Avoid Aggregeddon
(Welcome to the “Most Important Story of the Week”, my bi-weekly strategy column analyzing the most important (but often not buzziest) news story of the last two weeks. I’m the Entertainment Strategy Guy, a former streaming executive who now analyzes business strategy in the entertainment industry. Please subscribe.) Scrolling through links over the last week, I stumbled across this fun headline: Wow. Formula 1 (the sport, not the docu-series) is the perfect “dog not barking”. As a reminder, each week in my Streaming Ratings Report, I call out the shows that miss every viewership chart. I dub them “dogs not barking”—like the Sherlock Holmes mystery—because without any data, we forget they even exist. This is in contrast to something like, say, a film flop—cough The Mandalorian and Grogu cough—where even underperforming at the box office is widely discussed here, there and everywhere. In the US, Formula 1 is now in “no public viewership data, so not discussed” territory. After moving to Apple TV from its former home of ESPN, basically no one talks about it. Apple did publish an initial, unsourced, unsubstantiated, (dare I say unserious) datecdote claiming more folks are watching Formula 1 on Apple than ESPN, but we haven’t gotten any updates since. This stands in contrast to when the sport streamed on ESPN, and ESPN PR provided weekly viewership figures. Formula 1 was, at best, a niche sport in America—averaging 1.3 million viewers in the Big Data Plus era—but now it’s basically anonymous. (And yeah, after moving to Apple, I very, very, very much doubt its ratings increased.) Unfortunately, that story isn’t quite big enough to warrant a section in today’s “Most Important Story of the Week” column, but I wanted to call it out, because otherwise, no one else will! Certainly, no one will write articles about the silence/ratings decline, unlike when they wrote breathless articles connecting the rise in viewership to Netflix’s Drive to Survive, including Reuters just last month. (This is a topic I’ve tried to provide a moderate/nuanced/non-hyped take since 2022.) Anyway, on to this week’s issue. I was a bit worried I didn’t have a juicy topic, then the Murdochs went out and did their Murdoch thing: buying Roku. So that’s the story of the week, and it happens to touch on quite a few themes of the streaming wars and the disruption therein. I’ll cover that, plus why more consolidation in Hollywood media looks likely, more good news on the Hollywood labor front, whether we’ll see an uptick in production in Los Angeles, some Broadway and theme park news, cellphone prices going up in the third world (and possibly everywhere), and more. Subscribe Most Important Story of the Week - Another Big Media & Entertainment Merger The story of the week is clearly Fox is buying Roku for $22 billion. I read a lot of good strategy takes on why Fox bought this streaming TV device maker—and I’ll have mine below—but what fascinates me more is how this deal connects to quite a few themes of the streaming wars, linking to everything from the pace of M&A to “aggregeddon” to Netflix’s recent M&A actions/inactions to the shift to advertising from pure play streaming and more. The only topic I can’t really connect it to is my old theory, “never bet against Rupert Murdoch” because he isn’t the one who did this deal; his son Lachlan inked it. (Do I think he provided advice, even at his 95 years of age? Sure.) That plus I have one additional piece of strategy for all entertainment players, inspired by this deal. So let’s dive into all those topics, starting with why I like this deal. Roku is a Great M&A Buy
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Voluntarism, Free Speech, and American Labor’s Growing Political Divide
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Monday morning observations about JJ Wetherholt, Masyn Winn
Folks, I don’t think I got it today. I spent all of Thursday getting ready for a weekend trip, of course not giving myself enough time to do everything I wanted to do, so the entire day was hectic. I arrived at my destination that night, and then drank heavily for three straight nights. I […]
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Mamdani won New York opposing Israel. Now, his movement wants power in Congress.
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Carroll shines and bullpen grinds to victory over Twins
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Hidden geological process offsets carbon emissions from thawing permafrost
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Italy's Meloni pushes back on Trump's 'fabricated' claim as top diplomat cancels U.S. trip
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Inside Iowa Politics: How Zach Lahn responds to being called ‘part-time Iowan’ by opponent
Zach Lahn responds to criticism about whether he will be in Iowa enough to serve as its next governor.
Inside Iowa Politics: How Zach Lahn responds to being called ‘part-time Iowan’ by opponent
Zach Lahn responds to criticism about whether he will be in Iowa enough to serve as its next governor.
Inside Iowa Politics: How Zach Lahn responds to being called ‘part-time Iowan’ by opponent
Zach Lahn responds to criticism about whether he will be in Iowa enough to serve as its next governor.
Inside Iowa Politics: How Zach Lahn responds to being called ‘part-time Iowan’ by opponent
Zach Lahn responds to criticism about whether he will be in Iowa enough to serve as its next governor.
Georgia Republicans backtrack on redistricting plans
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'Clarke to drop Shankland for Christie or McLean'
If we rewind 36 years to 16 June 1990 and the Italian city of Genoa, Stuart McCall was busy scoring to help Scotland secure a 2-1 win over Sweden. The former midfielder jokes that he "was always deadly from a yard out" and ultimately that victory wasn't enough to ensure Scotland progressed to the knock-out stage, but up until this weekend, it was their last win at a World Cup finals. Now the 62 year-old is assistant to Paul Heckingbottom at Preston North End, but he's also enjoying absorbing all the action from the United States, Canada and Mexico.
Thanks For Making Me 12th Highest on Substack’s List Of “Rising” Business- and Economics-Related Newsletters
A big thank you to those of you who upgraded to paid subscriptions to read my two most recent paid memos: https://richardkatz.substack.com/publish/posts/detail/201675746?referrer=%2Fpublish%2Fposts%2Fpublished and https://richardkatz.substack.com/publish/posts/detail/201774434?referrer=%2Fpublish%2Fposts%2Fpublished As a result, total paid subs rose by 5.6% over the past seven days. And that put me at 12th on Substack’s list of “rising” newsletters in business and economics. “Rising” means those with the biggest percentage increase in revenue from subs over a short period of time. Of course, as is often the case with the issues I discuss, this is a good-news/not-so-good-news story. The good news is a rush of new subs. The caveat is that it’s easier to get a big percentage increase when the base is relatively small. I have enough paid subs to be in the initial rank of Substack’s “best seller list,” but a way to go before enough of the 12,000 subs to Japan Economy Watch are paid subs. For most hybrid newsletters—a combination of free and paid posts—2-7% of the total subs are paid. 5% is my initial goal. If you gain insight from reading this blog, please join those who’ve already upgraded; help me reach 5%—and beyond. Subscribe
Japan’s DJ Rinoka bobs to the beat as a child prodigy techno artist
Never mind she isn’t old enough to get into a club.
Americans are living longer, increasing the need of geriatricians. Does Louisiana have enough?
As the baby boomer generation reaches older adulthood and average lifespans continue to increase, the number of geriatricians needed to meet demand is also rising. Here's where the data currently stands in each state.
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. 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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.
Apple’s New Siri Is Just Good Enough to Ease Its AI Crisis
The company prepares for the foldable iPhone and touch-screen MacBook.
Essex GPs trial for adults with learning disabilities
Not enough eligible people are having life-saving annual health checks, say experts.
Opinion | It's time for Anthropic to get out of the business of killing people
The AI giant won’t allow the military to use its technology for autonomous weapons. That’s a good step. But it’s not enough.
Odem Area Lions Club hosted a free Star Spangled Health Fair
Joan McKaughan, President of the Lion's Hall said the residents of the rural community don't have enough information on services in their area.
'All Night Wrong' review: Dating is hard enough without a killer on the loose
Is it a rom-com? Is it a neo-noir? Is that blood?
What Genres and Streamers Won 2025? And Who Lost? Plus Six Strategy Thoughts
(Welcome to the Entertainment Strategy Guy, a newsletter on the entertainment industry and business strategy. I write a weekly Streaming Ratings Report and a bi-weekly strategy column, along with occasional deep dives into other topics, like today’s article. Please subscribe.) Okay, time for the tenth and final article in my ten-part series recapping 2025. As I wrote two articles ago, my barometer for whether these articles are worth writing/publishing is whether they yield strategic insights, and once again, every subsection in this article has a strategic takeaway (or two). Honestly, these are the most important takeaways, since I step back and look holistically at the streaming wars in 2025. After I declare which streamers won and lost the year and which genres won and lost the year, I have six bonus thoughts. If you’d like to review the whole series... You can find the film flops here and here. You can find the TV shows flops here and here. You can find the top films here. You can find the top TV shows here, here and here. Then I declared my winners and losers in various categories here. You can find my 2024 recaps here. You can find the 2023 recaps here and here. And my 2022, 2021 and 2020 are all stored here. Yeah, it’s halfway through the year, and I’m just finishing this series up now. This year, I tried to space things out to not clog up my writing calendar, plus I had to wait for Fallout to (finally) drop off the charts. Well, that ended up pushing this series wayyyyy too far back on the calendar. Oh well. Next year, the goal will be to finish this series in March, but frankly, I just need more staff to make that happen. So please subscribe. Or, if you’re an advertiser (movie studio, FYC firm, or other), please reach out. Subscribe Streamer of the Year: Netflix Honorable Mention: Paramount (and CBS) So, just last week, I wrote about how Netflix has lost seven of its top twelve scripted shows in the last year. And I shared two very dour looks at Netflix’s potential slowdown this year and last. Guess what? They’re still the number one streamer in America. In 2025, they dominated new streaming shows (even if most of those new hit shows aren’t coming back for future seasons), they had the two biggest films, and they had the top returning TV show by a mile. The world is complicated, nuanced and messy. There may be warning signs of a future Netflix slowdown, but in 2025, Netflix was still the number one streamer. Note what I didn’t say? That Netflix has “won” the streaming wars, because obviously the streaming wars are still ongoing and, more importantly, YouTube is still growing—so now YouTube has “won” the streaming wars?—while Netflix’s share of TV consumption has stalled out. Avoid simplistic talking points, especially if they’re constantly repeated and could fit on a bumper sticker. I had trouble picking the second-place streamer this year, because all of the candidates for second place—Prime Video, HBO Max, and Paramount+—had some hits, but no one stood out. Then I saw this update from Nielsen on the top shows on TV in the 2025-206 season. Sure enough, Netflix had five of the top ten shows! And they had ten of the top 31 shows and fifteen of the top fifty. But CBS/Paramount+ actually had more shows in the top thirty and the top fifty. Paramount+/CBS had twelve of the top thirty shows and nineteen of the top fifty. Let me emphasize that: CBS/Paramount+ had more top shows in the 2025-2026 season than Netflix. And this look was just for TV shows, not live sports, an arena Netflix barely plays in. Meanwhile, Paramount-Skydance’s market cap is a fraction of Netflix’s. That’s weird, right? Streaming Loser of the Year, TV… We’re just getting started with this issue, but the rest is for paid subscribers of the Entertainment Strategy Guy, so if you’d like to find out… ...what streamer lost the year in TV... …whether Netflix could win the title for “film” streamer too… …who won the Disney vs Warner Bros. battle for theaters… ...what TV genres won and lost the year... ...what film genres won and lost the year... ...what film genre people think is thriving on streaming but isn’t… …why F-BOSSS TV shows don’t hold the same sway in the 2020s… …what it means to “flop” as a film on streaming… …UK shows underperforming on streaming… And a lot more... ...please subscribe! We can only keep doing this great work with your support. If you’d like to read more about why you should subscribe, please read this article about the Streaming Ratings Report, why it matters, why you need it, and why we cover streaming ratings best.
Eating 5 fruits and vegetables a day may not be enough for heart health, study finds
When it comes to eating fruits and vegetables for heart health, the choice of fruits and vegetables may be just as important as how many they eat, new research suggests.
L.A. County health officials ask state for emergency funds
Measure ER isn't enough, according to Dr. Christina Ghaly. She leads LA Health Services, which has joined other California hospitals in lobbying for emergency funds.
Rural health care shifts in Audrain County four years after hospital closed
MU Health Care highlights the success of its Mexico urgent care clinic, but a community members questions whether the services it offers are enough.
Eating 5 fruits and vegetables a day may not be enough for heart health, study finds
New research suggests that meeting fruit and vegetable guidelines may not provide enough flavanols for heart health benefits without choosing specific foods.
England player ratings: Anthony Gordon proves his value but has Jude Bellingham done enough to guarantee World Cup start?
England finished their pre-tournament warm-up campaign with a much-improved 3-0 win over Costa Rica; Goals were scored by Declan Rice, Anthony Gordon and Ollie Watkins; Thomas Tuchel has a few starting spots still up for grabs - so, who made their mark?