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There’s a Reason That Netflix’s Ad Business Has Underwhelmed
Somewhat lost in the company’s slew of firings and engagement warnings over the past few weeks was the fact that Netflix is scaling back its ad forecast for 2026 from $3 billion to $2.7 billion. That’s despite the fact that: CTV is growing by 14-15% this year This year saw a monster upfront Netflix is the biggest streamer out there this side of YouTube, and was the platform that for years brands were supposedly dying to be a part of In other words, that’s an alarming pull-back from Netflix. A Wall Street analyst I spoke with last week was blunt, calling Netflix’s ad business “disappointing.” To me, a red flag on the ad front is that Netflix has never revealed how many ad-supported subscribers it has. Because if I know anything about how big companies work, if they have a positive number that makes them look really good - they tend to share it. (How many subs does go90 have right now? We’re not saying just yet. How are ads going on ChatGPT? Oh, a billion run rate - I see). Yes, to date Netflix has shared some fuzzy ad numbers, such as the idea that the company’s ad tier ‘reaches’ 250 million users globally.’ Here’s why that figure gives me pause: a)they lead with global, and b) they don’t explain how they are calculated. (Are they based on average people in each room? Surveys of some kind?). Regardless, some insiders say that Netflix’s ad tier is scaling nicely - others not so much. Either way, one of Netflix’s biggest challenge on the ad front appears to have been its starting point. Remember, when Netflix launched ads in 2022, it had 73 million subs in the US and Canada. That’s 73 million people who were used to Netflix with zero ads. And when the ad product rolled out, the company clearly was going after new users - a limited pool of potential subscribers by default. That focus seems to have changed over time, as Netflix has tried to convert longtime subscribers to the ad tier. Historically Netflix subscribers are very sticky. But is the company’s low churn a problem? Not necessarily, according to Antenna data. Rather, Netflix’s consumer loyalty is a bit of a double-edged sword. “Netflix is the one streamer which actually has seen substantial “trade downs” but has much lower ‘win backs,’ said Antenna founder Jonathan Carson (win-backs being people who were on the ad-free plan, cancelled, then rejoined on the ad plan). “Netflix has lower churn and so has less opportunity to win back old subs with a lower cost plan option.” This all might explain why Netflix has been so slow to roll out all of these table stakes targeting options until just this week. It likely didn’t have enough users to carve up into various targets. etc. However, what really hit Netflix’s ad business was Amazon’s move a few years ago to turn on advertising for Prime Video by default. Suddenly the market was awash in premium inventory, and Netflix was playing catch-up on multiple fronts. Thus, the streaming giant appears to still be figuring out if if wants lead in ‘programmatic TV,’ or premium ‘upfront’ TV sales. “The CTV market now sorts into three businesses, and Netflix is not the leader of any of them,” wrote analyst Jack Myers. Ouch. So how does Netflix ratchet up its ads business? Get the next NFL package You’re gonna have to wait until 2030 unless one of the bigger media companies like Skydance opts out, but the easiest (not cheapest) way for Netflix to become a huge TV ads contender is to get one of the regular NFL packages, ideally Sunday afternoons. That way it can sell ads to its whole U.S. subs base overnight. Go FAST This one is risky, because to program a compelling FAST channel, you’d likely have to take some older Netflix exclusive shows and make them available for free to non-subscribers. But FASTs, for better or worse, are ad-inventory machines. Go full UGC I’m not sure I see this happening. There is something already off about Netflix carrying podcasts and shows for creators. The experience sticks out in what is such a produced, and generally non-communal environment. But Netflix could open up its platform by allowing creators to upload videos without having to be approved by the service. But that opens a whole other can of worms (policing brand safety, copyright infringement, overall quality). Make a huge RMN Deal I was going to suggest something crazy, such as ‘instead of buying Warner Brothers, Netflix should buy Target. But the company doesn’t want to be in the brick and mortar business. Yet for Netflix’s ad business to compete in an Amazon world, it needs to be able to connect ad exposures to shopping. What if, instead of letting Amazon target Netflix viewers with its DSP, Netflix inked a deal with Target, or even took control of Roundel, and created its version of the Amazon full-funnel for brands? Price us out. I hope they don’t do this, but Netflix’s price increases - while significant - haven’t been enough to push long-term customers out of the ad-free tier. But if they made those prices so prohibitive, it could push large swaths of consumers to trade down. Then again, that could also dent engagement - as binging becomes much less appealing once you bring ads into the equation. Or, they could just launch a bunch of hit shows and maybe everyone will quickly forget all this angst. More from Amazon unBoxed A few weeks ago, I recorded two podcasts live at Amazon’s unBoxed event in San Francisco. I was able to go really deep with several brand partners about how Amazon’s various data and ad products work - particularly the under appreciated Amazon Marketing Cloud. First, I talked with Laura Abadias Velilla, of the Amazon specialty agency Amerge, along with Amazon’s own Charlotte Maines, Vice President, Devices Content & Advertising, about how the two partners helped a very specific printer company Epson launch into a brand new category - high end projectors. It’s a great example of how brands connect audience data across platforms to make budget deployment decisions. Next, I chatted with Monks VP Head of Digital Investment for North America Tom Burchill about how the agency actually brought in data from Linkedin to help target B2B customers across various Amazon properties for the brand Quicken. Check it out: Check these out, or just listen:
Skipped Lunch? Science Explains Why You're Suddenly Craving Happy Hour
Researchers at Brown University found a molecular link between hunger and alcohol cravings.
Sugar House groups suddenly scrap plan for new assessment area 5 years in the making
A plan to create a new assessment for the Sugar House business district, which could fund improvements for the heart of the Salt Lake City neighborhood, is dead after more than five years of planning.
Alabama HC Kalen DeBoer is Suddenly in Danger Yet Again
Alabama Crimson Tide head coach Kalen DeBoer desperately needs a win this week.
In 2025, Trawlers Suddenly Started Pulling Up Rare Hybrid Crabs in Record Numbers in The Bering Sea. Now We Know Why
Scientists were not expecting this.
The Business Behind Matcha
Matcha is a ground green tea powder with roots in ancient Japanese culture, dating back centuries. Only recently has the drink reached a wider global audience, appearing on cafe menus worldwide. Its growing popularity raises a question: How does a product that has been around for so long suddenly become a global trend? During the […]
Ohio millionaire Emil Barr reveals why he suddenly shelved plans to move to San Francisco
This Eerie State of Consciousness Makes Your Brain Feel Broken—but It May Be Keeping You Alive
Suddenly everything becomes unfamiliar...
The Science Of Foundayo: How Eli Lilly’s Daily Weight Loss Pill Works
Managing your weight in middle age can be remarkably frustrating, especially when habits that used to work suddenly stop moving the needle.
Big Ten Preview: Week 7
There’s a headline game in the Big Ten this weekend…and some other games, too. FRIDAY NIGHT Washington (3-3, 0-3) at Purdue (3-3, 2-1), 8 p.m. on FOX Details: Who is the more surprising 0-3 Big Ten team? Washington or Penn State? Well, the Huskies travel west to take on a Purdue team that suddenly has […]
Grand Theft Auto 6 launch trailer suddenly drops, showing a saucy shower scene, a tense police chase, and high-flying heists
Rockstar Games has released the launch trailer for Grand Theft Auto 6 today, which is a showcase of the hijinx players can expect come the 19th November.
Former Flyers Coach Suddenly Departs the NHL
Right now, things aren’t going right for the Philadelphia Flyers, who have yet to win a single game to begin the 2026-27 NHL campaign and are in dead last place in the NHL’s Metropolitan Division.Right now, there is speculation building about the job security of head coach Rick Tocchet.But another notable former Flyers head coach […] The post Former Flyers Coach Suddenly Departs the NHL appeared first on HEAVY.
Some of Sony's First-Party Games Are Suddenly Missing from PS Store in the US
What's going on?
Scientists discover that some of the universe's biggest explosions may have never happened at all
"All the evidence we see for hypernovae is suddenly gone."
SerpApi GC on Fighting Two Tech Giants and Keeping the Business Moving
Speaking with Law.com, SerpApi's Chad Anson discussed what it means to be a startup GC in two David-versus-Goliath legal battles, why he believes companies sometimes need to litigate more openly, and the advice he would give any in-house lawyer suddenly facing a potentially existential lawsuit.
How Ownership and Politics Might Force the Braves to Trade This Star
The Atlanta Braves might have a much bigger problem on their hands than another disappointing postseason exit. Franchise superstar Ronald Acuña Jr. is suddenly at the center of controversy, and the possibility of Atlanta trading its former MVP is becoming a legitimate offseason talking point. During a recent episode of Acuña’s podcast La Bestia ,…
Legendary comedian dies suddenly at 78
Ronnie Golden, the British entertainer known for “Spitting Image” and “The Young Ones,” died suddenly at his home at 78.
Kelly Clarkson’s Viral Feud With Brooklyn Magic Shop Escalates After Shop Rejects Her Claim She Was Treated Like a Prostitute
Art of Play in Brooklyn rejected Kelly Clarkson's claim she was treated like a prostitute at the shop, which it said led to it being "suddenly attacked" online
3 Stocks With Exposure to Prediction Markets as US Event Trading Grows
Prediction markets tied to sports, politics and real world events are suddenly trading like mainstream derivatives, and that surge is colliding with listed US exchange operators that already run futures and options markets. A new player like Kalshi floating an IPO story at a reported US$40b valuation hints at fresh competition and fresh demand. This piece walks through three stocks from the US regulated derivatives and exchange operators screener that appear positioned as potential winners...
The midterm Senate fight spreads to a surprising new battleground
Republicans are suddenly racing to defend a seat in Kansas, where Democrats are trying to win a Senate race for the first time in nearly a century.
Ex-Saints QB Suddenly Released by Eagles
In a successful and well-traveled NFL career, Andy Dalton had a stop with the New Orleans Saints. It wasn’t the most memorable or the longest, but it was substantial time on the field for “The Red Rifle” with the Saints. It came to mind again on Friday, when the Philadelphia Eagles surprisingly released Dalton after […] The post Ex-Saints QB Suddenly Released by Eagles appeared first on HEAVY.
Military & Veterans Campus has new way to build teamwork
On a recent Friday at the Easterseals NH Military & Veterans Campus in Franklin, I found myself about 30 feet in the air. I was holding onto a pole and contemplating what suddenly seemed like a rather narrow log stretching out over a great deal of empty space toward another pole, which also seemed remarkably distant.
Some Gboard users suddenly can't type capital letters
A strange Gboard bug is preventing some users from typing capital letters, and the beta version may be the culprit.
Open science is compatible with research security, says Canada’s chief science advisor
Open science is “not incompatible” with research security and science leaders and policymakers should “demystify” the false dichotomy between the two, according to Mona Nemer, Canada’s chief science advisor. More than a decade ago, EU policymakers were promoting open science, open innovation and open collaboration across the world. It was a political movement that aimed to make scientific research, data, software, publications and methodologies transparent, accessible and reusable for everyone.But that rhetoric has changed over the past few years. After Russia invaded Ukraine in 2022 and Donald Trump came back to power in 2025, international partnerships have become more pragmatic. Countries are trying to implement protectionist policies and governments are increasingly worried about technology espionage. According to Nemer, science can remain open if the sector can come up with improved security protocols that would protect research data from undue manipulation by foreign actors. “If anybody can fiddle with the with the data, then [open science] is actually quite dangerous and quite useless,” she told Science|Business. Universities and research institutions are increasingly vulnerable to attempted espionage and other types of foreign interference. In September, the UK’s domestic counter-intelligence service MI5 issued a security warning against collaborations with the China General Technology Research Institute. And earlier this year, Germany’s Helmholtz Center for Information Security was criticised by federal research minister Dorothee Bär, who told a parliamentary hearing that “existing rules and systems” at the institute “were not suitable” for preventing leaks to China. According to Nemer, universities and research institutions should perhaps follow the example of the private sector, as companies have been able to safeguard their research while still publishing results. “I think that there is a level of research security hygiene that researchers and institutions need to just adopt,” she said. “You don't have to tell Sanofi or IBM how to safeguard their research, which they end up publishing anyway.”While certain areas of research will not be open for collaboration with certain partners, in other areas cooperation is necessary even with researchers based in adversarial countries. “I stress this because politics change,” she said. “Science and politics don't make for good fellows, and whether we like it or not, politics will influence certain things.”Researchers will play an important role in “protecting the integrity of science,” said Nemer. “I think that it's time that there's a commitment to a certain scientific compact, so that citizens don't think that science is actually an open door for espionage and for anti-nationalism.”New partnershipsNemer spoke with Science|Business on the margins of the Hamburg Science Summit on September 17, the day when Canadian Prime Minister Mark Carney called for increased cooperation with the EU, including in science and technology. Canada is looking to strengthen ties with partners in other corners of the world, after the Trump administration threatened to put tariffs on Canadian goods and services and even openly suggested Canada could become the 51st state. In parallel, the US government has indicated it wants to retreat from international science projects, including US collaboration with Europe’s CERN particle accelerator and other big science labs.Related articlesThe stats we need to better understand R&DCanada looks to deepen research and education links with the EUCan researchers trust that AI models won’t leak their ideas?Nemer said the US is still a science “powerhouse,” but Canada and Europe will have to work closely together on global challenges. “It’s important for both [sides], but I think it's also important for the rest of the world, because the cut in funding for development, in health, in regions like Africa and other places, have dramatic effects.” The Trump administration is also planning a review of the Nelson memo, a Biden-era document that mandated that results of federally funded research would be openly available. With that idea being called into question, Nemer said it could be “very disruptive” to scientific collaborations and could jeopardise research on climate change, the Arctic and global health. “When your collaborator suddenly tells you I'm not going to share the data with you as a researcher, if this happens, I think it's very worrisome,” she said. “I'm certainly hoping that a lot of the Canadian institutions, funders, researchers, have started looking at joining forces on databases and using more European research infrastructures,” Nemer added.
Cristiano Ronaldo breaks silence on Portugal exit
Cristiano Ronaldo said he is not retiring from international football in a lengthy social media statement.The 41-year-old’s Portugal future was thrown into doubt after he suddenly left his country��...
Falcons Offense Explodes To 40.0 Points With Penix Back
Michael Penix Jr. returns to lead the NFL's best offense. See the shocking stats, the 45-24 win, and why the Falcons are suddenly scary.
Capitals’ Alex Ovechkin suddenly announces retirement plans
The 41-year-old forward has the end in sight.
What Holding Eye Contact While Someone Speaks Really Reveals About Your Psychology, According to Science
You are mid-conversation with a friend, nodding along, and suddenly you wonder: am I looking at them too much? Or not enough? Most of us treat eye contact like an automatic reflex – something we either do or don’t, without thinking twice. But researchers say the way you hold someone’s gaze while they speak is...
How Kansas Suddenly Became a Battleground State for Senate Control
The state hasn’t elected a Democrat to the Senate in nearly a century. Economic challenges during President Trump’s second term, as well as other factors, have put it in play.
Lane Johnson update: Eagles tackle suddenly questionable for Week 4
The Eagles could be without their All Pro right tackle against the Rams in Week 4.
Warriors’ Former All-Star Suddenly Emerges as Potential Trade Candidate
The Golden State Warriors could be parting ways with a former All-Star they acquired last season. According to NBA insider Brett Siegel of ClutchPoints, the Warriors’ top trade candidate entering the 2026-2027 NBA season is Kristaps Porzingis because his $20 million salary matches, and only $3 million is guaranteed for next season, essentially making it […] The post Warriors’ Former All-Star Suddenly Emerges as Potential Trade Candidate appeared first on HEAVY.
Ranchester artist’s work now in all 50 states
Two weeks ago, Katie Coyne realized her online store hit a milestone — she had shipped orders to customers in 48 states. The only two remaining states were New Jersey and Rhode Island. Suddenly, she had a mission.
Al Roker suddenly exits ‘Today’ during live broadcast, later explains why
Al Roker left “Today” early as Dylan Dreyer stepped in before the veteran weatherman later explained his absence.
Widow turns tragedy into triumph with new Blawnox-based baking business
A Blawnox widow is turning personal tragedy into personal triumph with a new baking business inspired by her late husband. Lisa Collins was devastated when she lost her husband of 27 years, David Collins, suddenly from cardiac arrest in 2023. The couple’s three adult children were grown, so Collins was
How will Packers construct offensive line after making vet additions?
The Packers suddenly have options along the offensive line. How will the starting five look the rest of the way?
Good science requires much more than evidence
Empiricists believe that scientific theories are true only if they make correct empirical predictions: if we can't verify these predictions, then there is no reason to expect that they tell us anything about reality. However, Professor of Philosophy at King's College David Kyle Johnson argues that this is mistaken. In response to Bas van Fraassen, who has written on this subject for the IAI, he argues that we have many reasons for believing a theory to be true, such as it being parsimonious and having large scope — qualities which have been used throughout the history of science as criteria for judging theories. In 2024, Princeton philosopher Bas van Fraassen wrote a short article for IAI News entitled “Science Does not Describe Reality: The Limits and Benefits of Explanation.” At the time, I was working on two projects (a science book and a Great Course) that, when completed, would (among other things) defend science’s ability to describe reality. I wanted to write a response to van Fraassen, but the projects demanded too much of my attention. But now that those projects are complete, I am in a position to explain the objections to van Fraassen’s thesis. Summarizing van Fraassen’s argumentIn a nutshell, his argument is this: What scientists do is make predictions based on theories and then invite others to test to see whether those predictions are borne out. “If theory T is right, result R should happen in experimental condition C.” Many think that running an experiment that shows that R happens in condition C is proof that theory T is true (and should be believed). But, van Fraassen argues, that R happened in condition C is only a reason to think that R happens in condition C. That’s the only observable, or empirical, result we can actually see, so that is all that we are really justified in believing. (The underlying theory that made that prediction still may or may not be true.) That is why he calls those who accept his position “empiricists.”Before I explain what is wrong with this position, let me explain what it gets right. What van Fraassen Gets RightFirst, a theory correctly predicting the results of an experiment is not, strictly speaking, “proof” that the theory is correct. The basic line of reasoning is this:If the theory T is true, result R should happen. Result R did happen. Thus, theory T is true.In other words:“If T then R. R. Thus, T.”This is a deductively invalid, fallacious mode of reasoning, called “affirming the consequent.” Those premises do not guarantee that the conclusion follows. “If I am in Pennsylvania, then I am in the USA. I am in the USA. Thus, I am in Pennsylvania.” Clearly that argument doesn’t guarantee its conclusion; neither does the above argument.However, science is not a deductive method of reasoning; it is an inductive one. And inductive arguments merely try to raise the probability of their conclusion, not “prove” them for certain. Thus, the fact that an experimental result doesn’t prove a theory is true is irrelevant; it’s not supposed to. That is not what scientific reasoning is about.___If the hypothesis that something exists clearly provides the best explanation for what we can observe, then the belief that it exists is what is rational.___Second, it’s also true that a single experimental result doesn’t provide enough justification to believe that a theory is true. Scientists do not come to a consensus about whether a theory is true by looking at a single experiment; they look at all the evidence to determine where the preponderance of evidence points. The mere fact that I am in the USA raises the probability that I am in Pennsylvania, but not nearly enough to conclude that I am in Pennsylvania. However, if I am also regularly encountering people wearing Eagles and Phillies hats and seeing advertisements for Founding Father tours, I probably am. In the same way, a theory successfully predicting the outcome of one experiment is not enough to conclude that it is true; but if a theory makes a wide variety of predictions that are all vindicated by multiple experiments, performed by many different groups and people, all actively trying to prove the theory false (which is what good scientific experiments are designed to do)—that is a good reason to conclude that the theory is true. In other words, if you repeatedly try to prove something false but can’t, that is a very good indication that it isn’t. The problem of underdeterminationIn reply, those whom van Fraassen calls “empiricists” often point to the “problem of underdetermination.” For any given theory that makes successful predictions about what happens in experimental conditions, there are countless other possible theories that make exactly the same predictions—and since they do, the experimental evidence in question is just as much reason to accept any of those theories as it is to accept our original one. Thus, the argument goes, we have no way of knowing whether our original theory is true, or one of the other “predictively equivalent” theories is true. SUGGESTED VIEWING How Occam's Razor changed the world With Johnjoe McFadden As an example of underdetermination, philosophers often offer this example. The evidence of fossils seems to provide reason to conclude that the universe is quite old; ancient fossils are what the “ancient universe” hypothesis predicts. But it’s also possible that God created an ancient-looking universe 200 years ago, complete with a “fake” fossil record for us to find, to make it look old. The existence of fossils is what that theory predicts too. So, the argument goes, the fossil record can’t be used as evidence that the universe is ancient; the fossil record supports the “200-year-old ancient-looking universe” theory just as much. The problem of underdetermination points out that, for any theory with supporting evidence, we could invent another completely different theory that predicts exactly the same evidence, and thus undermine that evidence’s ability to support the original theory.But this “argument from underdetermination” betrays a fundamental misunderstanding of what scientific reasoning is and how it works. To explain, let me use another rather strange (but very real and commonly discussed) philosophical thought experiment called “The Grue Problem.” The “Grue” ProblemSuppose I want to know what color emeralds are, so I observe a few, see that they all appear green, and form the theory that “all emeralds are green.” I thus predict that the next 100 emeralds I find will also appear to be green. And let’s say that happens, and so I thus conclude that my theory that all emeralds are green is true. Now, one might rightly point out that I don’t know for sure that all emeralds are green—I have not seen them all. Maybe some I haven’t found yet are blue. Fair enough. After all, we used to think that all swans were white, until we found some black ones. But let’s say that I go on a quest and collect every emerald in the universe—and, for the sake of the argument, let’s say I can do this, and can even know that I have every one of them. So, I collect them all, look at them all, and verify that they all appear green. Can’t I now rightly conclude that all emeralds are green?Inspired by the problem of underdetermination, a friend might argue that I cannot.Sure, they all appear green now—but there could be another kind of color called “grue.” Something is grue if it is green up to a certain point in time, but then spontaneously turns blue. And there could be an infinite number of “shades” of grue. Something that is one shade of grue will turn blue at noon today, but something that is another shade of grue will turn blue at noon tomorrow, etc. So yes, the emeralds appear green now; and since they haven’t turned blue yet, they are not some “past” shade of grue. But they might be some “future” shade of grue (e.g., they may turn blue at noon tomorrow). And since all future shades of grue are consistent with “being green up to this point in time,” the evidence you have is completely consistent with the notion that all emeralds are some future shade of grue, rather than green. Indeed, that they would appear green until now is what the “some future shade of grue” hypothesis predicts. So, we have just as much reason to conclude that all emeralds are some shade of grue as we do to conclude that they are green.You’re probably thinking “It’s not equally possible that the emeralds are grue; they are obviously green.” You are right! But explaining why your instinctive reaction to my friend’s argument is correct will help inform why van Fraassen’s “empiricist” is wrong and science actually does describe reality.The main mistake my friend makes is in thinking that the “empirical evidence” (of all the emeralds appearing green) is (or even should be) all I am using to draw the conclusion that all emeralds are green. It is not. I am also considering known facts about how colors typically work; things don’t usually change color, and when they do, they don’t do so suddenly, without cause, and all at once. So, even though the simple evidence of the emeralds all appearing green up to this point is consistent with them being some future shade of grue—that is even what the grue hypothesis “predicts”—it is still exceedingly unlikely that they are. The hypothesis that they are green is much more likely. Understanding science refutes the problem of underdetermination The misunderstanding about science that the “empiricist” pointing to “the problem of underdetermination” makes is similar to the one that my friend made. Science is not just about considering experimental evidence; in fact, it’s not even just about considering empirical evidence. As Ernan McMullin and many other philosophers of science have pointed out, the inference that makes science is “inference to the best explanation” (sometimes called “abduction” or “retroduction” by McMullin). While, depending on the circumstances, scientists use many different kinds of reasoning, science as a whole is, simply put, the process of considering multiple competing explanations and comparing them to certain criteria—explanatory criteria (the kinds of things explanations must be and do, by definition, to be a good explanation)—to see which explanation is the best.And these criteria do not deal only with empirical results. Yes, successful predictions raise the probability of a hypothesis, but it’s also the case that the more new assumptions a theory makes, the less likely it is to be true; every new assumption presents an opportunity for the theory to be false. (The fewer assumptions a theory makes, the simpler or “more parsimonious” it is said to be.) Likewise, the more existing evidence a theory contradicts, the less likely it is, because in order for a theory to be true, every piece of evidence it contradicts has to be somehow faulty. (The fewer established theories a new theory contradicts, the more “conservative” it is said to be.) And, obviously, the more something explains, the better explanation it is. (This is called having “scope.”) If a theory raises unanswerable questions, it’s not expanding our understanding, and thus is not wide-scoping. Scientists consider all these things when deciding which theory to accept, because the theory that adheres best to these explanatory criteria is most likely to be true.___the mere fact that a theory’s predictive success is why it “sticks around” or “becomes accepted” in the scientific community is not a reason to be skeptical about its truth.___The reason the grue hypothesis is no good is because it invents an entirely new kind of color—not just a new shade, but an entirely different category of color (a different way colors work)—and thus is not parsimonious. It raises unanswerable questions about how and why emeralds would just spontaneously change from green to blue (and thus does not have wide scope). And it contradicts what is already well established about how color works (and thus is unconservative).The theories that the problem of underdetermination points to do the same thing. Yes, the theory that God created an “ancient-looking universe” (complete with an ancient-looking fossil record) two hundred years ago is also consistent with the empirical evidence (of a fossil record) that presently exists; but that theory is monumentally unparsimonious (it requires many extra assumptions about infinite entities) and not wide-scoping (it raises unanswerable questions about why God would do such a thing). So, I can rationally conclude that it is false.Indeed, the history of science includes many examples of theories that were rejected because they lacked parsimony and/or scope, even before their falsity (and the truth of their competing theory) was confirmed by observation. As I point out in my book, geocentrism was rejected by the scientific community because it lacked parsimony, almost 200 years before the observation of parallax confirmed that the Earth moves around the sun. And the continuum theory of matter was completely rejected by 1860, because it couldn’t explain chemical reactions or organize matter into a periodic table, even though the experiments that eventually confirmed atomic theory weren’t even proposed until the 1870s. Solving the best of a bad lot problemIn response, the “empiricists” are likely to object, this time pointing to the “best of a bad lot” problem. “We have no reason to conclude that an explanation that has been shown to be better than others is true because we have no guarantee that the true theory was among those that we were considering.” If you have a “lot” (a collection) of poor explanations, even the best one is not true.The responses to this problem, however, are numerous. Peter Lipton argues that the set of hypotheses that scientists consider are not just randomly selected and thus unlikely to contain a theory that is true; they use existing knowledge to home in on what is most likely to be true. A doctor trying to explain abdominal pain is not going to bother wondering whether demons are causing it; they are going to stick with things like appendicitis and kidney stones, because they are most likely. Further, despite its name, inference to the best explanation is not just the process of comparing hypotheses and accepting the best one; we also want one that is a good explanation in its own right. If it’s not, we are going to keep looking until we find an explanation that is. And while that process does not guarantee that we will come across the exact truth, it’s very likely that the theory that emerges as the best will be at least approximately true, and thus we will be justified in believing it. And lastly, as I point out in my book, although many theories not based in scientific evidence (like geocentrism and continuum theory) have been completely overturned, science almost always progresses by the refinement of scientifically established theories—not their replacement. (Although our sun is not the center of the universe, heliocentrism was our first step in understanding the Earth’s true place in the universe.) So even if a theory we accept today may not be completely right, accepting it is a step on the journey toward the complete truth. The example of atomic theoryNow, it’s worth pointing out that most empiricists are not skeptical of all scientific theories; they are only skeptical of the ones that hypothesize the existence of “unobservables.” It’s not like they think that round Earth, heliocentrism, and germ theory are just useful (but untrue) “instruments” for making predictions about how to most efficiently navigate the seas, predict planetary motion, and treat diseases. They admit that the Earth actually is round, that the planets revolve around the sun, and that germs exist and cause disease. These facts and entities can be observed; the theories that suggest they exist are true. It’s only when theories start hypothesizing the existence of unobservables—like electrons, or quantum fields—that can’t be observed directly, that we should start doubting the theories’ truth. And to be fair to van Fraassen, in this published work, he doesn’t really say that we should doubt the truth of such theories. Only that scientific reasoning does not rationally force us to accept them as true. Skepticism, or agnosticism, he argues, is warranted. SUGGESTED READING Science is based in metaphor By Andrew Reynolds But the history of atomic theory throws a monkey wrench into that argument. Atoms used to be unobservable; again, scientists first accepted the theory that they exist because it had such grandiose explanatory power. But then atoms were seen with electron microscopes. They thus moved into the category of the observable. But this didn’t substantially change anything about what scientists were justified in believing; it certainly didn’t change any “atomic skeptics’” minds. It just confirmed what everyone already knew! If the hypothesis that something exists clearly provides the best explanation for what we can observe, then the belief that it exists is what is rational. The fact that the thing itself is not technically observable does not make doubting its existence rational.What’s more, the atoms were seen with an electron microscope. But electrons are themselves unobservable. How can an electron microscope reveal an atom if electrons are not real? This leads us to what is famously known as Hilary Putnam’s “miracle argument.” It’s (not) a miraclePhilosopher Hilary Putnam’s miracle argument is somewhat famous. Basically, he argued that a scientific theory being able to repeatedly make successful predictions—even about unobservables—without being at least approximately true would require a “miracle.” In other words, it would be such an improbable occurrence that it could not rationally be believed—the better explanation for why scientific theories about unobservables make the right predictions is because the unobservable entities and structures they hypothesize exist.Van Fraassen has addressed this argument. Indeed, in his original article, where he references Alison Gopnik’s point about orgasms not being “necessary for procreation” even though the desire for orgasm “drives the creation of progeny,” he is pointing to his own argument about how organisms are not naturally selected by evolution to get true beliefs; to the extent that belief-forming processes are selected for, the ones that are selected are the ones that are useful for survival—not the ones that produce true beliefs. In the same way, van Fraassen argues, scientific theories are accepted, not because they are true, but because they aren’t falsified; they make successful predictions; that’s what makes them “stick around.” So, the fact that they make successful predictions (and thus became accepted) is not a reason to think they are true.This argument is similar to C. S. Lewis’s “argument from reason,” which he used to argue against evolution: “The truth of evolution undercuts our ability to know that it is true.” Lewis’ argument famously failed; Elizabeth Anscombe, by Lewis’s own admission, demolished Lewis in a debate on the topic, and I have explained elsewhere why modified versions of the argument fail as well. In short, it’s because it fails to recognize that a belief-forming process can make an organism more likely to survive because it reliably produces true beliefs. It is therefore not the case that beliefs generated by naturally selected belief-forming processes are automatically false or unjustified.In the same way, the reason a theory “sticks around” could be because it’s not falsified, because it “makes correct predictions.” But the reason it makes correct predictions is most likely because it is true. (In pointing this out, I am echoing the arguments of Musgrave, Lipton, Psillos, and Kitcher, who refuted van Fraassen’s argument and analogy long before his 2024 article.) It would be a huge coincidence that it could do so without being true. And that is the point of Putnam’s miracle argument. Thus, contrary to van Fraassen’s suggestion, the mere fact that a theory’s predictive success is why it “sticks around” or “becomes accepted” in the scientific community is not a reason to be skeptical about its truth. ConclusionLet me close by saying something about the fact that empiricists don’t doubt the truth of all scientific theories, just the ones that hypothesize unobservables. In today’s society, this theory is dangerous to espouse publicly. The nuance between being skeptical about all of science, and just the highly technical theories about unobservables, is guaranteed to be lost to the average reader. And there is so much unjustified skepticism and doubt about the findings of science and experts that a headline like “Science Does Not Describe Reality” could easily fuel the anti-science movement, worsen climate change denial and cause the next pandemic.This is why I believe it was important to still respond to van Fraassen’s article, a full two years after he wrote it. Not only, as I have argued, does it represent a philosophically inaccurate view of how scientific reasoning works and what scientific reasoning can do, but it is a dangerous view to boot. It should thus be rejected.
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Research funders are asking how they can stop confidential scientific ideas in grant proposals from leaking out through large language models (LLMs), for example if reviewers use AI to help them judge applications. Last week, a row erupted in mathematics after OpenAI announced it had solved a notoriously difficult problem, only for another mathematician to demand answers over whether the company had used ideas he had fed into its models. The spat, and the broader issue of idea leakage through AI models, was discussed by funders at an R&D policy conference held in Paris on September 14. At worst, it threatens to undermine the correct attribution of breakthroughs, one of the foundations of modern science. The mathematics dispute around OpenAI is “certainly something we're looking at” Jason Gallo, head of the newly established Office of Metascience at the US National Science Foundation (NSF), told the Blue Sky Forum, hosted by the Organisation for Economic Co-operation and Development. The controversy started on September 8, when OpenAI announced it had cracked a mathematical problem that had gone unsolved for 90 years. Using a swarm of AI agents, millions of dollars’ worth of computing power and a new internal model, the company said it had finally proved that a long-used formula for modelling fluid dynamics breaks down under certain conditions. However, Tristan Buckmaster, a New York University mathematician who had been independently working with collaborators on the same problem using OpenAI’s Codex tool, hit back with a statement questioning whether the company had snooped on his Codex sessions to gain an advantage. OpenAI has always denied it looked up the “specific user data” of Buckmaster and colleagues. However, the company initially admitted that “while unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models,” although its proofs “differ significantly” from Buckmaster’s. The firm later said that, following an investigation, it concluded that Buckmaster’s Codex prompts “could not have influenced the [OpenAI] system in any way, including through training.”Funder concernYet OpenAI’s initial admission that its model might have ingested Buckmaster’s ideas, then spat them out to its own mathematicians, has scientistsworriedthat their work could leak out if shared with AI. Some AI tools give users an opt-out option to stop their sessions from training the model. If such guarantees can be trusted, this gives scientists some confidence they can use an LLM to develop an idea without the risk of it leaking out.But there’s a bigger potential vulnerability. To win money to investigate ideas, scientists have to share them with funding bodies. These grant proposals are normally kept strictly confidential, to prevent other scientists from scooping them, or to protect commercially valuable intellectual property. To preserve this confidentiality, when the NSF uses AI models, “we have to be sure that it's not making server calls out to an external party, leaking that data,” said Gallo to delegates in Paris. Leaks through reviewersHowever, funders normally use external academic reviewers to assess proposals. And there are growing worries that these reviewers are feeding grant ideas into AI models to help them make a judgement. Research funders have noticed that peer review reports and funding recommendations have “suddenly become much longer, more detailed and complex,” said Diogo Machado, head of the data science unit at Technopolis, a science and technology-focused consultancy. “The sense is that reviewers are increasingly using generative AI in their review work, even where guidelines sometimes forbid it,” he told Science|Business. “This is very difficult for funders to control or prove.” Happening at scaleThis sharing of confidential proposals with AI models is “happening at scale already,” said James Wilson, executive director of the Research on Research Institute, based at University College London, during the debate in Paris. In response, Gallo said the NSF had “strict guidance” around the uploading of proposals to AI models. But he added the NSF was mulling new types of assessment to make sure applicants were truly the originators of their ideas, such as following a short-form proposal with an oral presentation, which would allow the foundation to “really interrogate the investigator on their intellectual contribution.” Related articlesHow can Europe cope with a flood of AI-assisted research grant proposals?The risks and benefits of AI in screening research grant proposals Viewpoint: AI could make scientific overload worse“For us as funders, a lot of the ways to ensure that the application remains the applicant's own intellectual contribution, those ways are quite regressive,” Peter Clifford, head of strategy at Research Ireland, told delegates. “They're maybe ten or 15 or 20 years old, and they don't scale particularly well.” Disputes over the origin of ideas are as old as modern science. Isaac Newton and Gottfried Wilhelm Leibniz spent more than a decade arguing over who invented calculus, for example. And long before LLMs emerged, academics would agonise over how much of their early work to reveal at conferences, in case their colleagues scooped them, Jack Leahy, a senior metascience advisor to the UK government, told delegates. But AI was “accelerating” the “problems of the system,” he said.
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The politics and possibilities of ‘AI could kill us all’
I found myself fielding a lot of questions from folks who don’t usually talk much about AI this week. They were mostly along the lines of “do you think AI is going to kill us all?” or “how worried should I be about this human extinction stuff?” Motivating this wave of existential anxiety was the highly dramatic resignation of now-former Anthropic employee Jacob Coxon, who quit his job while publicly sharing his concerns about safety practices at the leading AI companies. More specifically, he declared that almost everyone at OpenAI and Anthropic, the leading AI labs, believes that there’s a decent chance the AI systems they’re producing could “kill us all” by the end of the decade, and the companies aren’t “acting responsibly.” Other AI safety researchers, including those still employed at Anthropic and OpenAI, all confirmed that yes, Coxon is correct, they’re all worried that their company’s products might prove fatal for the entire human race as well. Two more AI employees quit and joined the chorus. Now, the warning shot has been covered everywhere from the Wall Street Journal to Fox News to WIRED to the Guardian. I understand why all this sounds scary, but my response to those who have asked, has generally been: No, you don’t need to worry that AI will kill go rogue and kill us all. But that does not mean we shouldn’t worry, period. Far from it. The companies building AI products are now among the wealthiest and most powerful entities in the world. And they very much are building enormous engines of mass surveillance, extraction, and automation. They can and have allowed their AI systems to carry out felony hacks of other companies, provided the government with autonomously generated kill lists, and sold enterprise technology to firms around the world that is explicitly intended to replace jobs. But “AI” has done these things not because they have all-powerful minds of their own but, ultimately, because people have programmed, calibrated, and directed them to. In other words, it’s not AI we need to worry the most about. It’s the people and corporations working to profit from and gain power by deploying it. The technology is sophisticated, sure, and, especially in cybersecurity contexts, potentially disruptive to plenty of existing systems. But if we want to stop this predatory, profiteering, and extractive form of AI—and it’s worth noting that at this point, most people do—we absolutely can. A quick note/plea: I can only do all of this with the support of readers like you, so if you find value in independent, critical tech journalism and analysis, please consider becoming a paid subscriber. I want to keep as much of this un-paywalled as absolutely possible, and I need your support to do so. Many thanks to all who continue to chip in, it’s very much appreciated. Onward. Subscribe First, some context: AI industry folks like Coxon have been discussing the prospect that AI will destroy humanity for years. Even before the beginning of the AI boom, many working in the industry, from the executive staff to the rank and file researchers, have obsessed over ‘x-risk’, or the possibility that AI will become sentient or semi-sentient and move one way or another to exterminate humanity. This is ostensibly why Elon Musk bankrolled OpenAI in the first place, and is the grounds for his lawsuit alleging OpenAI betrayed its charter by abandoning its nonprofit status to become a commercial enterprise. Many AI engineers and startup founders have calculated their own personal p(doom), or the probability that the tech product they are working on will initiate an actual humanity-extinguishing apocalypse. 10-25% p(doom)s are pretty common. (I wrote about a long weekend I spent among these folks at one of their top conferences here, to give you an idea of their ideas and belief systems.) Sam Altman himself drove the narrative of the imminent rise of a super-powerful AI, or artificial general intelligence, to prominence by declaring that the technology he was building posed an existential risk to humanity. This idea is in other words baked into the DNA of modern AI companies and into the products they engineer. It’s also why the industry is routinely accused, by myself and others, of “doom marketing,” ie, using such proclamations and framings to impart the sheer power of the technology behind your product onto investors, partners, consumers, and the state. Some ambient understanding of this tendency may have helped prevent the press from repeating the claim every time one of the x-risk folks made it over the years, including when they quit their jobs at AI companies while doing so. Yet Coxon’s AI x-risk alarm has broken containment, as they say, and has exposed the idea to the mainstream media once again. This has happened, I think, for a number of reasons. First, when AI CEOs were going around saying AI might kill everyone in 2023, their companies were well-capitalized, but not nearly to the extent they are today. They were more easily dismissed as eccentric geeks of the sort that Silicon Valley is supposed to produce. Now, not only do their products have much greater market saturation, but people are more aware of a) the often unethical ways the executives and companies comport themselves b) the other adverse impacts of AI that have already arrived, and c) the physical cost of building these systems, particularly when it comes to data centers. Finally, toss in the constant stream of headlines in 2026 about AI models going rogue or potentially upending the world’s infrastructure. [ ](https://www.bloodinthemachine.com/p/with-the-backlash-to-data-centers) [ With the backlash to data centers, Flock and AI glasses, a mass opposition to big tech is underway. Silicon Valley is in denial. ](https://www.bloodinthemachine.com/p/with-the-backlash-to-data-centers) Brian Merchant · Aug 27 [ Read full story ](https://www.bloodinthemachine.com/p/with-the-backlash-to-data-centers) As a result, general sentiment was already overwhelmingly skeptical of AI and its overlords, so the table was pretty well set for someone to come along and say ‘just a reminder, the companies that are building the product that promises to take your job and leave a data center in your neighborhood also think that it might exterminate the human race’ and get a strong reaction from the media and the public. The question is: Should we understand this stuff as hype, strategically fanned to feed already swelling valuations? Is it doom marketing? Genuine cause for alarm that the infrastructure that undergirds modern life is facing a novel threat vector? Or reason to be sincerely worried that AI companies are amassing too much power, and that their products are genuinely dangerous? The answer, I’m afraid, is “yes.” Let me try to untangle all of this a bit, because arguments over how to navigate this moment are extremely heated right now, as they are essentially arguments over how to approach the politics of AI at a moment where there may be a unique opening for action. Those sympathetic to AI alignment concerns and x risk arguments—which increasingly includes a faction on the left who want to shut down AI over safety concerns—argue that people who dismiss AI as all hype have their heads in the sand. Meanwhile, critics of the x-risk narrative—which I might note includes a cadre of investors and tech folks on the right, too—argue that it is hype and can be used to further inflate valuations or for pursuing regulatory capture. The challenge is that many feel that dismissing AI as just hype or purely marketing also diminishes the urgency of taking on the AI industry as the novel and threat to labor, civil society, and the public sphere it is; others that by accepting the industry’s own terms, we imbue it with undue power and enable it. But let’s be clear: Declarations that AI is so powerful it might end the world are a kind of marketing, and anyone who says otherwise is just as off base as those who say that’s all that it is. If you don’t think that these sub-trillion dollar companies have higher-ups who noticed that when their founders talked about super-powerful dangerous AI they got spikes in media interest and phone calls from investors, or that those founders didn’t notice that themselves, and lean into certain narratives to advantage their products, then I don’t know what to tell you. Not all marketing is a Pepsi ad campaign with a celebrity spokesperson. Yet confronting the AI industry should certainly be considered an urgent project. Do I share the x-riskers’ fear that out-of-control, super-intelligent AI agents might end the world? I do not. I’ve read a good deal of AI extinction literature over the last couple of years and I have not come across a credible, step-by-step documentation of how exactly AI might move from self-recursively improving AI to killing every single human on the planet. Most of what I’ve read seems predicated on a sort of reverse Ian Malcolmian logic: Eventually, it becomes smart enough and AI, uh, finds a way (to exterminate humanity). Are the AI companies also overstating and dramatizing what their products can do? Yes, pretty much all the time. They’re in a knife fight for market share and are trying to win customers and government contracts before their investors come knocking. And yet. They have concentrated enormous amounts of compute, have extensive data collection and surveillance capacities, have inserted themselves into the state in numerous capacities, including military kill chains, and they are being run by egomaniacal billionaires who are rushing to monopolize an entire new market. The way I think about their most recent frightening-seeming exploits is not as a “swarm of rogue AI agents building a new civilization” or whatever, but as corporations with a hitherto-unimaginable amount of compute at their disposal recklessly experimenting with automation programs, completely unafraid of any repercussions because we have been unwilling or unable to impose any on them. So I think we should welcome any newfound imperative to hold them accountable. I also think that ultimately, the AI critics, Pause AI folks, leftists, doomers, effective altruists, and, honestly, most of the public, want a lot of the same things: legitimate checks and limits on AI companies’ power, actual transparency into what the companies are doing, and for more of AI to be under public control. (Ultimately, a lot of what animates the x-risk fears are rooted in just that: a fear of losing control.) How we move towards all this, exactly, is the question of the day, and while there’s much to be argued over in terms of building a viable political platform to challenge the AI industry’s power, I do want to cast a vote against one particular approach. Not to pick on Chris here, as there are a lot of folks out there proposing stuff like this, and the policy ideas actually stem from AI safety groups. But not only would this be challenging to land politically (I can already hear the ‘China will beat us to AGI’ calls) and all but unworkable in practice, this approach is a) far too limiting, b) fails to address the current harms caused by AI and c) would likely only wind up serving Anthropic and OpenAI; it’s what regulatory capture looks like in action. Full model transparency is the floor for what should be on offer here. If these companies believe their products will kill us, the very least we deserve is to know how. It’s in the public interest. I would also argue we might get a lot of the way to stopping any currently envisioned robot apocalypse simply by forcing AI companies to assume liability, and to submit to the full brunt of the law. If Sam Altman were liable to be charged with a felony for approving the hack on Hugging Face1, if Google was forced to pay defamation fines each time it published a false and injurious AI Overviews, these companies might suddenly find cause to restrain their models’ output, and we might hear less about rogue AI. We would need to introduce new frameworks and available tools for tracking automated lawbreaking, to be sure, but I’d wager that little would frighten the AI companies more than actually being held accountable for what their products enable. To that end, Illinois has passed an AI liability law, which the industry fought tooth and nail, and Florida is considering one. The next steps would be towards moving AI under public control; again, it’s only reasonable, since everyone, not just AI insiders, should get a say over how a technology whose developers say might kill us is developed and deployed. Dismantling the whole industrial project as currently structured should be on the table, too, pending democratic input. But that’s for another post. For now, suffice to say that while I won’t be losing any sleep about an AI-enabled extinction event, Mr. Coxon and co. have given us an opportunity to underscore the urgency of the clear and present damage AI companies are doing, the extreme power they wield and the extent to which they hold themselves unaccountable, and the abundance of political capital there is out there for taking them on. Subscribe 1 Purely speculative! I do not know if he did or not.
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He was seen walking off the field mid inning with the training staff.
15 discouraging hours with Onimusha: Way of the Sword, and 10 brilliant ones with He Who Watches
In the last few weeks, while playing some video games that I might review, I emailed two cries for help. I sent the first to a rep for Capcom, confessing that the company’s samurai game Onimusha Way of the Sword (out today for PC and console) was crushing me. “Feels like I’m playing ‘hard’ mode, not ‘normal,’” I wrote. “And I don’t want to have to knock it down to “story”. I’m exploring, trying to level my gear, but these two-phase boss fights with no mid-fight checkpoints are brutal.” I wagered I was only about halfway through the game, if that. I wasn’t sure I could keep up with the steepening difficulty curve. Was I missing something? Then, on Monday, I took some photos of some puzzles that were baffling me in the mind-bending He Who Watches (out now on PC), wrote out lengthy descriptions of how I’d been trying to solve them and asked Bobby Vanden, the game’s solo developer, for a nudge in the right direction. I told Vanden I’d spent hours on these puzzles. “I’m stuck in triplicate,” I told him. Could he tell me if the solutions I was attempting were even on the right track? I didn’t mention that the puzzles—coupled with major time pressures from other work—were stressing me out so much that playing the game was giving me headaches. This double dose of panic was unusual. I’m used to managing a workload full of reporting and reviewing, used to a crowded schedule and the need to stay calm amid the bustle. But I was stressed about these games. No one was forcing me to review them, nor even play them. I’d simply found them interesting enough to start, hoped they’d be interesting enough to write about and I’d sunk hours into them assuming I’d made the right call. Suddenly, however, I felt trapped. I was emailing for a way out. Above: This guy took me about an hour to beat. The feedback I got from Capcom confirmed my fears. They didn’t say it, but I will: Onimusha Way of the Sword is not for me. It’s a brutally hard game in need of a normal difficulty level. It’s a game that spikes so severely during its abundant boss fights—yet offers such flawed ways to improve when outside of them—that it feels like a bait-and-switch. In the new Onimusha, you play as famed samurai Musashi Miyamoto, aided by a magical soul-absorbing gauntlet that is possessed by a lady who offers advice. (Way of the Sword is a continuation of Capcom’s long-dormant Onimusha series, but that set-up had me wondering if the company was cribbing from their ill-fated Bionic Commando reboot; read about “wife-arm” when you get a chance). Way of the Sword is partially set in 17th century Kyoto, an explorable city where Miyamoto can fight demons, help civilians and eventually rescue ghostly dogs. The city evolves over time, with new mini adventures and obtainable loot on offer, all feeding into systems that promise to upgrade your gear and sword-fighting skills. Upgrades, however, are so incremental as to be imperceptible, causing the exploration of Kyoto to feel like inconsequential busywork. From that hub, players can go on linear missions into forests and old temples, where they will encounter many of the game’s tough bosses. Combat in Way of the Sword is akin to many modern melee games. Players are asked to mix attacks with dodges and parries. They’re encouraged to deplete an enemy’s stamina bar in order to do greater damage to its health bar. The old Onimusha games’ signature move was the issen, a counter-attack so sudden it’s all but pre-emptive. You strike just as they begin to strike toward you, beating them to the cut. By definition, the issen is a high risk move, leaving you wide open to pain. It feels risky in the game, especially against bosses, who can maul you in just a few blows. A game might train you to perform an issen well by offering a variety of lesser enemies who are not as tough as the boss but get close. Or it might offer a toehold against bosses by saving or checkpointing the player’s progress when a boss’ first health bar has been destroyed and before the second health bar appears. It might offer the less skilled player a chance to over-level their character, should the player simply commit to playing through its optional sidequests. Way of the Sword does none of this. Fighting its trivially easy grunt enemies and then its ferociously adept bosses is like playing a game of chess where I’ve got a rook, while the opposing side is all pawns and five queens. Bosses simply don’t checkpoint. You may be able to clear a boss’ first phase without taking much damage. Good for you. Do it again, every time you fail the second phase. As for the the central Kyoto hub, I kept pace with all of its added side activities and never felt like I was overpowered. Bosses could still easily buckle me. The new Onimusha, I concluded, is just too discouraging to keep playing. The advice I got from Capcom had been well-intentioned. They reminded me of the game’s various systems. They alerted me to an optional assist that flashes recommended button inputs (basically: counter this move; dodge that move). It was a little helpful. So was dropping down to “story mode,” which I tried last night. Story mode turns on those button prompts by default. It makes countering and dodging way too easy, nearly automatic. I don’t consider myself a master of action games like these, but I’ve cleared the likes of God of War, Stellar Blade, Star Wars Jedi and others of sub-Sekiro difficulty and had a fun time doing so. Not here. Not yet. Unless they patch Onimusha: Way of the Sword and add a middle difficulty or just checkpoint the damn bosses when they’re between health bars, my streak of loving Capcom games released in 2026 will likely end at two. It’s a shame, because I was having a good time finding those ghostly dogs. And then there’s He Who Watches, a phenomenal first person puzzle game with Portal vibes, except instead of a portal gun you’ve got a magical bow that shoots one arrow that can activate switches or be used to drag blocks. The twist is an actual twist: you can also walk on walls and the ceiling, reorienting gravity as you do, thereby placing blocks onto those other surfaces. Walking on walls and ceilings to solve problems is really the best thing. Would that I could in reality. He Who Watches consists of locked-room challenges, each brief enough to only require about a minute to actually solving, though it will take five, 10, eventually 30 minutes to figure out said solutions. They are not obvious! It’s a game of layered mechanics and shocking solutions. For example, see if you can follow this: You can drag a block to a wall. Then you can walk on the wall, which now feels like the floor, and drag that block across the wall. Later, back on the floor, you might realize you can look up. The block is still on the wall, stuck to it. You can shoot your magic arrow to its underside. Doing so creates a tether, so that you can yank the block off the wall and carry it, as if it were a balloon, into the spot where you need it to be to solve the puzzle. Here, watch Vanden explain some of the game’s basics in this launch trailer: As with any great puzzle game, the solutions to He Who Watches’ puzzles elicit relief and amazement. Oh my god, that worked! I didn’t even think that could be possible! Learning to solve the game’s puzzles feels like learning magic. But, oh, does the game get hard. Its Steam reviews, mostly glowing, are full of players remarking how quickly He Who Watches made them sweat. Wrote one: “loving this one already although my brain is hurting!” Wrote another: “As you get further in the game it feels like you need an IQ level of at least 120+.” Vanden has shown some mercy. Each locked room puzzle includes an optional junior version of the puzzle, meant to teach you. Difficulty nevertheless ramps severely. By the time I was emailing Vanden for help, I was struggling to even clear one of the hint puzzles. When I messaged him, my stress was exacerbated by strange things I’d found in the game’s various hubs: suspicious passageways, odd blocks and some intriguing locked doors. These were hints of secrets, I realized, yet I sensed I needed to play further into the game to understand them. I was stuck, but I wanted to see the rest. Vanden offered to give me the exact solutions, to solve those three puzzles for me, but first he gave four nudges. Three were for the specific puzzles, but his best hint was for all and ultimately proved to be a terrific life lesson: go back a bit, he suggested. Do the puzzles right before those. They were teaching you something. Focus on what their lesson was. Don’t rush, in other words. Recognize what you’ve accomplished. Build off of that. I did so. I absorbed the lessons. I saw those three tough puzzles in a new light. I solved one the night after he wrote back, another the morning after. I left a third for another time. I didn’t need it and I wanted to plunge deeper into the game, closer to the moment when I was sure I could start unlocking those secret doors. My head stopped hurting, too. He Who Watches feels special. It’s got more challenges, and I’m undeterred. It’s also nice that its puzzles don’t have a surprise second health bar. Game File is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Subscribe Item 2: In brief… 🎮 Ilari Kuittinen, co-founder of Helsinki-based Housemarque (Super Stardust HD, Resogun, Returnal) has stepped down from his studio, after a 31-year run, saying he’s “ taking a rare and well-deserved breather.” Sony purchased Housemarque in 2021, and the studio released its newest game, Saros, earlier this year. Trend-watch: Sony-owned Insomniac saw its founder Ted Price retire in early 2025, after a 30-year run. Sony-owned Sucker Punch saw its co-founder Brian Fleming step down in late 2025, after a 28-year run. 👀 Savvy Games Group chief Brian Ward is stepping down from the Saudi-government-backed games conglomerate, Bloomberg reports. No word on a long-term successor yet, nor if this augurs any closer integration between Savvy and Electronic Arts. EA was purchased by a consortium led by Saudi’s sovereign wealth fund, in early August. 💿 Square Enix has denied a Japanese media report that the company was planning to go private. In very different Square Enix news, the company revealed that the physical version of Final Fantasy VII: Revelation, the April 2027 finale of its radical remakes of FFVII, will include just one disc in its case, requiring a download for the rest. The first two FFVII remakes in the trilogy shipped on two discs apiece. While Square hasn’t commented on the reason why, a feature here in Game File last month broke down the processes and costs for physical games. The expense of a second disc comes out of the game publisher’s cut of each copy. Square could be saving in excess of a dollar a copy with this move. 🟥 Grand Theft Auto IV’s 26-minute ’‘extended look” gameplay showcase that premiered on Netflix last week—and was exclusive to the platform for six hours—drew 31.1 million views in its first four days, the streamer announced. (Netflix calculates views as total viewed hours divided by runtime; excludes replays). Compared to YouTube: The version that later premiered on Rockstar Games’ YouTube channel is sitting at 22.6 million views after seven days (YouTube’s more liberal counting system tallies anyone who viewed even just the first few second.) Compared to other Netflix mega-events: Last year, Stranger Things season 5’s first four episodes, which debuted together, drew a record 59.6 million views in their first few days on Netflix. For more of a live event type of comparison, in 2024, the Jake Paul vs. Mike Tyson boxing match drew 65 million concurrent streams as it happened; Netflix didn’t release live numbers for the GTA premiere. ☁️ Microsoft is changing the way it charges for cloud gaming, from an all-you-can-play offer for Xbox Game Pass subscribers, to caps for the subscription’s tiers (15 hours per month at the Ultimate tier), with the option to buy more hours in bulk beyond that. The company also said it will sell batches of cloud gaming time to non-Game Pass subscribers, details TBA. Microsoft does not release figures for cloud game usage, but said its changes would impact 4% of Game Pass subscribers. That implies a small portion of its subscribers exceed the 15-hour monthly mark. Cloud gaming offers the promise of playing games without the need for console or PC hardware, as the graphics, sound and controls are all transmitted via a streaming connection. Microsoft notes that its cloud gaming service can be used for a range of things, including Xbox One players using it to play newer-gen Xbox Series games via streaming; and people playing games via streaming, sans any console, “in markets where consoles are less available or affordable.” (That latter use case could even be relevant in Xbox’s home market soon, as console prices keep rising.) Take Two Interactive chairman Strauss Zelnick recently told investors he expects game-streaming tech, which has been only lightly adopted by gamers for over a decade, to be widely used within three years. 🇺🇸 The Trump administration has published multiple agenda-driven web video games to the White House’s website. One called Build The Wall partially clones Tetris as it asks players to build a wall to stop a “zombie border siege.” While actual Tetris involves clearing lines and basically not building a wall, the Trump-backed game omits the line-clearing aspect (and omits the fun as well). On Instagram, Tetris’ official license holders reacted by stating: “At Tetris we believe in the power of connection and bringing people together, not dividing them. To our fans everywhere: we love you, we see you, and we’re grateful to have you in our community. P.S. The Tetris Company was not involved in the creation of ‘Build the Wall.’ P.P.S.: We take copyright infringement very seriously.” Item 3: The week ahead: Tuesday, September 8 Game releases: Mewgenics (consoles; already out on PC) is an engrossing tactical combat game (with cats). It is getting its console port right after the release of a Star Wars tactics game and ahead of the late September launch of a Fire Emblem–a bumper crop for the genre. Wanderburg (PC) is an auto-shooting game like Vampire Survivors, but you’re a castle on wheels Event: Nintendo airs a 30-minute Nintendo Direct (10am ET) focused on The Legend of Zelda’s 40th Anniversary. A full unveiling of the upcoming remake of The Legend of Zelda Ocarina of Time is expected. Will they also show footage from next year’s live action movie? Tease the next big 3D Zelda? Add Link to Mario Kart World? Shadow-drop a new Tingle game? Wednesday, September 9 Event: Nintendo again! On this day, they’re planning to air a 45-minute Nintendo Direct (10am ET) focused on games heading to Switch 2 this winter. Followed by about an hour of gameplay demoed by the company’s Treehouse team. The September Nintendo Directs are always some of the year’s biggest. The 2025 edition included announcements of several major 2026 Switch/Switch 2 games: Pokémon Pokopia, Mario Tennis Fever, Yoshi and the Mysterious Book, Fire Emblem Fortune’s Weave. Plus the return of the Virtual Boy. Friday, September 11 Game release: EA Sports NHL 27 (PlayStation, Xbox) is a hockey game. There are so few that an indie studio that had been making wacky sci-fi first-person shooters just announced that, hey, we’re going to fill a void and make a hockey game for PC.
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Although US President Donald Trump still harbours ambitions to take over Greenland, for US researchers his actions seem to have had the opposite effect. Over the summer, Greenland’s two largest research institutions, the Greenland Institute of Natural Resources and the University of Greenland, both announced policies of not starting new research projects with US researchers.Both institutions cite a mistrust of the US as a motivation for the decision. At the University of Greenland, the change of policy has already led to the rejection of specific proposals for new collaborations, rector Mari Kleist told Science|Business. “The reason is the changed political situation between the US and Kalaallit Nunaat [Greenland], and the uncertainty that the American interest in Kalaallit Nunaat has created,” she said.For the Greenland Institute of Natural Resources, a partially state-funded environmental research institution, the decision was also prompted by a lack of trust in US intentions. In a July interview with local broadcaster KNR, director Josephine Nymand cited concerns about data ownership, US “influence operatives” and social media monitoring of researchers entering the US.The Greenland Institute of Natural Resources has long collaborated with the US National Science Foundation (NSF). The policy change will not affect these existing partnerships but will apply to collaborations with new, “unknown” partners, Nymand said. At the University of Greenland, the policy is the same.The changes come amid proposals of severe cuts to the NSF, which would likely also see the US research presence in Greenland reduced. In spite of this, when asked about the Greenlandic policy change, the NSF remained optimistic of its continued presence in Greenland.“We are grateful to our partners in Greenland for their collaboration in advancing scientific knowledge and training the next generation of researchers. NSF remains committed to the long-term collaborations with Greenland that enable scientific research near communities and on Greenland’s ice sheet,” an NSF spokesperson told Science|Business.Fewer US researchers in GreenlandMost research published on Greenland is on natural science topics such as the cryosphere, ice dynamics, permafrost and climate change. In recent years, US researchers have been the most prolific publishers on Greenland.The US research presence in Greenland goes far beyond the capital of Nuuk, where the two research institutions are located. It includes the Pituffik Space Base in northwest Greenland, various projects in settlements and research stations along the coast, as well as research stations on the Greenland ice sheet itself.The largest of these sites, Summit Station, is located at the highest point of the Greenland ice sheet, about 3,200 metres above sea level, and since the 1980s it has been used for drilling cores out of the ice sheet. These ice cores provide valuable information on the global climate going back at least 100,000 years. About 30 kilometres from Summit Station, the Danish-led Greenland Ice-core Project (Grip), funded by the European Research Council, is also drilling ice cores. Although they initially competed, the relationship between the two research teams has “long been amiable,” Jørgen Peder Steffensen, a Danish researcher who has been part of Grip for more than 40 years, told Science|Business.However, since Trump took office in early 2025, Steffensen has noticed a reduction in US research in the country. “Several of our American partners did not make it into the field this year. Their field seasons were cancelled because they lacked the budget,” he said.He ascribed part of the reduction in US researchers to a renovation of Summit Station. “A very large share of NSF funding has gone into renewing the station. Money has been taken from research and allocated to rebuilding it,” he said.A report published in August by Arctic Hub confirms Steffensen's observations of fewer US researchers. It shows that US research publications on Greenland took a dip towards the end of the period spanning 2015 to 2024. In 2024, before Trump took office, the number of publications had fallen from an average of about 250 articles a year, to just 164, second behind Canada at 169.Data from the NSF logistics provider Battelle also shows a reduction in US research presence in Greenland in recent years. In 2023, Battelle counted 48 projects across 78 locations, but in 2025 that number had fallen to 40 projects across 38 locations. And while relations with US personnel in Greenland have remained strong, some tensions have arisen since Trump took office. “On a personal level, there is nothing. But it’s hanging in the air. It hangs unspoken,” Steffensen said.Cutting ties with US researchers entirely would come at a higher cost for the ice core researchers than the Nuuk-based institutions. To get cargo to and from their bases, both Grip and Summit Station rely on unique, ski-equipped Hercules LC-130 aircraft operated by the New York Air National Guard. Without these, maintaining a research base on the Greenland ice sheet would not be viable on current budgets, Steffensen said. “[If the Hercules planes were not available], we would have to think outside of the box. We would have to use smaller planes, and we would have to build a base closer to the coast. But staying in our current location would be too expensive and it would create a huge carbon footprint,” he said.Suspicious people in NuukIn her explanation of the severed US ties, Greenland Institute of Natural Resources director Josephine Nymand compared the decision to past situations when the institute had to cut ties with China and Russia, the latter due to Russia’s full-scale invasion of Ukraine in 2022. And although the current situation is less severe, the comparison reflects the seriousness with which Nuuk sees the US threats. “From Greenland’s perspective, the US may not look so different from Russia right now: a much larger neighbouring power threatening to invade,” Lin Alexandra Mortensgaard, a researcher of international politics in the Arctic at the Danish Institute for International Studies, told Science|Business. “From a European perspective, it is not a comparable situation, because we are entangled with the US on all possible fronts and do not want to destroy more than is absolutely necessary. But from Greenland’s side, there may well be a need to send a clear signal to the US,” she went on. Suspicions have been fuelled by instances of Trump-affiliated people in Greenland trying to persuade Greenlandic citizens to support a US takeover. The most prolific among them is Tom Dans, a former venture capitalist and pecan farmer who was appointed by Trump as the chair of the United States Arctic Research Commission. Observers fear that he is now using research to achieve a US takeover.“Greenland is a small society with a small population, so when Americans with unclear affiliations wander around, trying to be good friends with people, and you don't know what they want, that creates mistrust. This probably played into the research institutions taking these drastic steps,” Mortensgaard said.Related articles:The US ‘golden age’ science strategy: what Europeans need to knowEU polar research melts into the backgroundAnchor Greenlanders in Arctic climate research, experts tell EU ahead of policy updateAnd although Greenland’s population is small at just 57,000, for Mortensgaard, it serves as a microcosm for the geopolitical situation as a whole: global powers fighting for their interests to the detriment of the common interest. Arctic research already suffered when collaborations with Russia broke down in 2022, she said, so a split with the US would be a serious hit to climate science.“The Arctic climate system does not respect borders or geopolitical divides. When collaboration across those lines suddenly becomes impossible, it is a huge problem for knowledge production,” she said. European alternatives?The Greenland Institute of Natural Resources is funded partly by research grants from external sources like the NSF. To replace the US funding, the institute will have to look for alternative revenue sources, and Nymand said that she is looking to Europe for those. Aside from Denmark, of which Greenland is formally a part, she also noted increased interest in research collaborations from the UK, France and Switzerland. Kleist of the University of Greenland told Science|Business that it was too early to say if the severed US ties would lead to more collaborations with Europe. Meanwhile, Mortensgaard believed that the tensions in Arctic research could well leave room for closer European partnerships, or stronger links with Canada. “I spoke to Canadian researchers who had long-standing relationships with American colleagues and who collaborated with the US Navy, but who had gotten worried that their data on sea ice could be used if Trump suddenly decided to follow through on his threats of invading,” she said. “Like Canada, I think Greenland is considering creating closer ties to Europe and I think European capitals will be open to this,” she said.
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