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Halloween Cleverly Carves Its Own Path Through Horror Multiplayer
Michael Myers comes alive in IllFonic's latest asymmetrical haunting grounds.
BUSINESS UPDATE: Port Perseveres Despite Tariffs’ Negative Impact
‘We are hanging tough ... in an environment that is incredibly difficult to do business in right now,” the port’s director says By Stefan Yablonski Tariffs imposed by the Trump administration have hurt the Port of Oswego by slashing Canadian aluminum cargo volumes and reducing revenue. “We’re doing good. We are hanging tough. It is a tough time for our line of business in general, you know with these tariffs and the amount of Canadian aluminum that we see through our docks,” said the new executive director, Tom Drumm. “Compared to 2025, we are doing exceedingly well in traffic coming in; not necessarily the volumes we were seeing, but yeah we are hanging tough in an environment that is incredibly difficult to do business in right now.” “I don’t know where people get these numbers to be honest. We have never publicly stated how much our revenue is down or up or left to right. We don’t have a strong sense of those revenue numbers until the shipping season really closes up. We won’t have an accurate picture of the revenue standpoint until after the shipping season, typically in late November,” he added. “What I can tell you is several of our Canadian vessels that carry the aluminum cells — the volume of aluminum on those vessels we have seen decreasing. That is attributed to a few factors. One is where Novelis is in in their restart process. Novelis is rocking and rolling right now. They are starting to pull a lot of aluminum from the port of Oswego, the aluminum that they roll down into coils. “Another factor plainly is the tariffs. Canadian aluminum is tariffed at 50%. So, on those vessels we are seeing lower numbers than we would like. We’d like to see vessels carrying roughly 10,000 metric tons of aluminum. Over the course of this year, we have seen more in the range of 4,000 to 6,000. “Every piece of that aluminum that we receive here by vessel at the port is from Canada and is subsequently hit with the 50% tariff. It directly affects us because we’ve received less volume than we would traditionally see pre-tariff times.” When the port receives less aluminum from those vessels it means less hours for the ILA (International Longshoremen Association) as far as folks that work on the dock, he said. When cargo declines, it affects everyone, fewer hours for longshoremen, fewer loads for truck drivers, fewer rail shipments and less business for local suppliers. “Outside of the aluminum that comes in by vessel, the port topped out at having roughly 4,600 aluminum ingots stored on site at the port. That project had never been done before. The port of Oswego had never had that many of those size ingots in our yard,” he said. “It has been a busy summer for the ILA. Would we like to see more work for them? Sure. They are working all those barges when they come in, but as opposed to working 15 hours they might be working seven or eight hours. It hasn’t been a distinct decline in ILA hours. There has been plenty of work to keep our guys busy throughout the summer.” More salt “We just brought salt back to the port in several, several years. Around Harborfest time at one point we had a salt barge here with about 24,000 metric tons of rock salt and we had an aluminum barge here the same week. We had close to 40 men working,” he said. “Yeah, the other products definitely keep us busy. The salt project was a massive project, one that we are proud of. I’ve got 24,000 metric tons of salt on site that has to go somewhere — that’s going to be another project.” It is important for the port to continue to look at different products, different commodities to try to diversify some of its revenue, he said, adding, “We have done a pretty good job of that in my first five months here … particularly with the rock salt we have on site right now. It is important to continue to try to stand out and work through some projects outside our usual business. I enjoy it. It is a challenge every single day we put our head down and we try our best.”
HIRO Report: Nebraska vs. North Dakota
Weeks 1 and 2 were headlined by explosive performances. Week 3 was different. Here's what our HIRO metric thought of Nebraska's methodical win over North Dakota.
Latham & Watkins Advises Spectrum Equity on Growth Investment in Symmetric Health Solutions
Multidisciplinary team represents the growth equity firm in investment in the healthcare supply chain intelligence provider.
The Samsung Galaxy Watch9 Wants to Tell You Everything About Your Body
Samsung’s latest smartwatch adds even more health metrics to its suite. I spent two weeks testing whether they’re actually useful.
Has Flutter Entertainment (NYSE:FLUT) Fallen Far Enough To Look Cheap?
Flutter Entertainment’s share price has undergone a sharp reset over the past year, yet broader valuation checks still suggest the stock screens as inexpensive. This puts recent price weakness in contrast with a more constructive read from its fundamentals-based metrics. The share price has fallen 65% over the past year, indicating a major reset in investor expectations for Flutter Entertainment. Regulatory clarity around U.S. sports prediction markets, including the New Jersey petition...
Observability should start with business outcomes, not infrastructure
A dashboard full of metrics is only useful if it can tell you what those numbers mean for customers and the business.
NASA Watches Earth’s Weight, Finds Center of Mass
Seasonal changes redistribute enough water around Earth to shift the planet’s center of mass back and forth by fractions of an inch relative to its geometric
The clean energy transition's missing metric: Human health
Earlier this year, the First Conference on Transitioning Away from Fossil Fuels in Santa Marta, Colombia, convened representatives from 57 countries to advance a just, orderly and equitable transition ...
Withings and Function Integrate Connected Health Data with Comprehensive Lab Testing
Withings and Function have announced a partnership integrating connected health device measurements with comprehensive laboratory testing, enabling users to access daily biometric data and clinical results through both companies’ digital platforms. The integration aims to provide a more continuous view of individual health by combining routine measurements with periodic laboratory assessments.Under the agreement, Function members can synchronize data from Withings devices directly into the Function app, including body com...
Health Foundation of South Florida Awards $300,000 to Bring Vision Care to Low-Income Schoolchildren in Miami-Dade and Broward
Grant will support mobile optometric clinics delivering free eye exams and prescription eyeglasses through Miami Lighthouse for the Blind’s Florida Heiken Children’s Vision Program Sept. 3, 2026 — The Health Foundation of South Florida has awarded a $300,000 grant over two years to Miami Lighthouse for the Blind to support its Florida Heiken Children’s Vision […]
Vermont teen mental health and vaping rates show improvement
A new Vermont health report shows declining teen vaping rates and improved mental health metrics following the pandemic.
Business Awards Are a Visibility Play, Not a Vanity Metric. Judges Share What It Takes to Win
Explore top business awards, entry costs, judging criteria, and expert strategies for writing a standout submission and extending the value of a win.
Benjamin List, Nobel laureate: ‘Chemists have always been seen as a dark force’
The discoverer of asymmetric organocatalysis defends the discipline’s potential to solve humanity’s greatest problems
Writer makes bold prediction regarding Vikings QB Kyler Murray
Kyler Murray could be a top-12 quarterback in a key metric this season.
The Big Holes in Wearable Heart Rate Variability And Readiness Scores
On September 9th, Apple announced it was revamping its Apple Watch Health Sensing System, rolling out a Readiness score (0 to 10), and increasing the frequency of heart rate variability (HRV) outputs 24-fold. This can be viewed as upping its competition with various other consumer wearable sensors. These “readiness scores” as a composite of multiple metrics, with heart rate variability (HRV) being front and center for most. The majority of Americans are now using wearable sensors, which equates to well over 100 million adults. HRV and Readiness scores are increasingly being marketed as a measurement of autonomic nervous system health, a digital marker for future disease, a clock for biological age, and a holistic metric to promote healthspan and even longevity. (Apple also introduced a new longevity tab and “Health Age”.) None of this has been proven. In this edition of Ground Truths I am going to review what we know about heart rate variability and readiness scores. Heart Rate Variability HRV is the variation in normal heart cycle timing. The variability of the heart rate, the barely perceptible millisecond changes in time between consecutive heart beats (see R-R intervals in the Figure below, left panel), is due to interplay between the sympathetic and parasympathetic (vagal nerve) inputs. Distinct from heart rate, individuals with the same heart rate can have very different HRVs. It is a rough reflection of the autonomic nervous system (ANS) activity, inadequate to say whether a person’s ANS function is abnormal. For more than three decades, heart rate variability (HRV) has been measured and several studies have found an association of low HRV and clinical outcomes, particularly a link with higher all-cause and cardiovascular mortality. There have also been less well established links of low HRV to risk of early cognitive impairment, dementia, mental illness, Type 2 diabetes and substance abuse. An important reminder is that HRV is a surrogate marker without any established cause-and-effect relationship. If you increase your HRV, that doesn’t mean it will improve health outcomes. In fact, there is no hard evidence for that. All that work linking to health outcomes was done with electrocardiogram (ECG) derived HRV. Now, in the era of consumer wearables, this is getting assessed differently, by optical pulse (yes, the lights you see) plethysmography (PPG) or what is called pulse rate variability (PRV). They are not the same, as shown below (right panel) and only concordant when the delay between the ECG and pulse is kept constant, which basically means at rest. I should mention there’s also what I will call MPV, a mattress mechanical movement sensor, a derived heart rate variability, that companies like Eight Sleep use, even further away from directly measuring HRV. HRV has not one uniform measurement but many different types of quantification, such as RMSSD, the magnitude of difference between successive R-R intervals of normal sinus beats (N-N) or SDNN, the standard deviation of NN intervals, both in milliseconds. SDNN is one of the so-called frequency domain HRVs (others are LF, HF, LF/HF). Different wearable sensors use different metics; Apple has relied on SDNN and nearly all of the others use RMSSD, which is generally considered the more accurate metric. There’s also the different length of time measured, such as for a matter of minutes, all day, or an overnight’s sleep. Short measurements are especially problematic since they don’t capture enough of respiratory modulation and other factors that influence HRV. Share Ground Truths How well does HRV correlate with PRV? There are very limited studies, especially independently done. One that is commonly cited was conducted by Air Force researchers in only 13 healthy adults assessing Oura ring 3 and 4, Whoop 4.0, and Garmin Fenix 6 and showed a correlation coefficient of 0.88 to 0.97 and a mean absolute percentage error from 6 to 10%. The correlation is not a perfect 1.0, but there’s at least a fairly high level of correlation. HRV is supposed to increase during the night due to takeover of the parasympathetic nervous system, and higher during deep sleep. A recent example of my 1 week, all day “HRV,” and one during sleep is shown below. As you can see, the N of 1 data are inconsistent for the same days from different sensors (Oura, AppleWatch, Fitbit Air, and Eight Sleep) by patterns, absolute numbers, and comparison with prior days and weeks. The largest study in over 8 million Fitbit users (the old version, not Google Fitbit Air, introduced in May 2026) gives you a sense of the effect of age, sex, and the 2 different main HRV (here PRV) metrics, with RMSSD on the left and SDRR (=SDNN) on the right below. That study, from data collected in 2018, is a major outlier, since all the more recent ones are tiny with respect to sample size. Many of the companies have not had independent evaluation of their HRV, such as Eight Sleep, but have published a low standard error on their website. There are some other published studies on the correlation between HRV and PRV, but they are all small and only in healthy adults. A scoping review emphasized the lack of study in underrepresented individuals, including the aged, people of color (which affects the PPG signal), and individuals who are underweight or obese. Add the typical adult age 60 plus with one or more chronic diseases. For example, one study in over 900 adults found poor correlation of HRV and PRV, non-uniformly underestimated across many chronic diseases (cardiovascular, endocrine, neurological, respiratory, and others), concluding PRV is “an invalid surrogate for HRV.” A recent systematic review of 43 studies comparing HRV and PRV found reasonable pooled absolute standardized error (HRV as gold standard) but only 10 of the studies provided quantitative synthesis in ideal conditions. Their main conclusion was similarly cautious: “PPG-derived HRV [PRV] should not be regarded as universally interchangeable with ECG-derived HRV across all devices, populations, and recording contexts.” Factors Affecting HRV and PRV That gets me to the long list of factors that affect HRV (and PRV) besides the device, the type of measurement (RMSSD, SDNN or others), the person’s signal, the sensor site, the duration of data capture, if weighting by sleep stage is used, how artifact is processed and corrected. And this list is not complete!: Oura puts out data from their community of users (who input data) on what affects their overnight HRV. The factors currently provided are: no alcohol (increase 8%), melatonin (increase 2%, float tank (increase 2%), wine (decrease 4%), and party (decrease 14%) in overnight HRV. Must be some big parties! Subscribe What is a PRV measurement good for? It has been falsely characterized as an index of “autonomic balance” and a specific indicator of stress. A 2018 review of the studies available for HRV and its relationship to stress, not using any of the current wearables, found that stress can lower HRV. But so can many other factors. The non-specificity of the signal, indexed to the table above, is striking. Evidence from a UK Biobank study of over 46,000 participants with actual HRV looked at genetically predicted HRV, a genetic risk score, that failed to show the expected HRV-mortality link, indicating that _HRV is likely not causa_l, but rather a reflection of person’s physiologic state. A review of consumer wearable HRV data from 5 longitudinal studies showed that nighttime PRV was not associated with perceived stress, and surprisingly higher HRV, in the largest cohort (N=717 participants), was correlated with higher stress. An Oura ring cohort of 525 first-year college students found a link between overnight PRV and perceived stress, but that was also seen with resting heart rate, sleep, and respiratory rate. Several very small studies have examined the relationship of HRV and athletic injuries or guiding training with mixed, and predominantly negative results. HRV biofeedback training with paced breathing had no significant effect on reducing stress or raising HRV, as demonstrated with sham controlled trials. When HRV for multiple days showed a decline in conjunction with body temperature, the Oura ring published data for prediction of Covid. The WHOOP company sponsored an observational study, published in 2026, of 30,000 users for 72 weeks, without a control group, that reported reduced alcohol intake (5.8 % points) by self-report. That doesn’t tell us much, and particularly about the merits of HRV for behavioral change. If you use the same device and conditions as longitudinal trends for multiple (at least 2-3) weeks that may be the one way to get something useful from the measurements. Data for overnight sleep with minimal motion and using RMSSD is the best proxy for real HRV. The reason to look at trends rather than any given night is that it more likely represents something, even though you won’t know with certainty what the “it” is. Keep in mind there are no data, no peer-reviewed evidence, to show that HRV fluctuation in-person has any correlation with health outcomes. Share Readiness Scores These are proprietary scores that integrate different metrics for each of the wearables: no algorithms have been disclosed. They are unvalidated against health outcomes. In a review of 14 composite health scores of readiness and recovery, HRV contributed 86% to the scores, followed by reading heart rate (79%), physical activity and sleep duration (both at 71%). That review noted the substantial variability in measurement protools and lack of standardization. Sleep staging is notoriously inconsistent and inaccurate by these sensors, which adds further to the HRV uncertainties for what the scores, which use sleep stage data, mean. Only resting heart rate has been shown consistently across devices to be extremely accurate. I’ve made a Table to summarize what we know about which metrics are included, the scores, any peer-reviewed studies that compared the readiness score with health outcomes, and the corresponding (if any, NA-not available) citation. You will note that some companies do not use the term “readiness," such as WHOOP for recovery, and Garmin, which has 2 different scores, one of which is Body Battery. Eight Sleep uses the term “Fitness Score.” They all include HRV; Apple includes a new metric they call “Recovery HRV” which among other components uses 7-days of sleep, but it is unclear what this means or how it is differentiated from other scores (there are clearly no data for outcomes). We have no knowledge of how the different components are weighted or whether any of these scores are better than resting heart rate, HRV alone, physical activity, or any other single metric. Since none of these are standardized, they are not interchangeable, so if you get a 90 for Oura that has no relationship to a 90 on a Google Fitbit Air. Notably, the company can update its algorithm for readiness score at any point without notification to device users. Without any useful evidence of actionability for these scores or established relationship with health outcomes, it is hard to make a case for their value. At the Apple recent announcement they showed their Readiness score (0-10) on the watch (Figure below) but there are no published data on this score, not even on their website. It’s available only on their new Watch Series 12 or Ultra 4 [of course, ;-)]. That exemplifies the problems with these scores, lack of data and evidence for being meaningful to promote health. Perhaps the best study (which isn’t saying much) is the WHOOP Recovery for golfer performance, because it did correlate with an objective outcome, even though there was no control group and the authors were all from the company. Among the 389 pro golfers, an absolute 10-per cent point increase in Recovery score was associated with about 0.5 fewer strokes per round. But that’s hardly a health outcome! WHOOP is also conducting a study in over 2,700 runners to see if their recovery score will be linked to less injuries and improved performance, but that is not yet published and has no control group or randomization. Putting This in Context For two decades I’ve been enthusiastic about the potential for digital health and particularly wearable biosensors. Over the years, we’ve seen some great progress for their ability to promote physical activity and accurately detect atrial fibrillation (the first FDA cleared deep learning AI for consumers). That work was the subject of rigorous research. But there are holes in the data and evidence for other metrics. One notable one is the “VO2 max” story that I wrote about earlier this year. At that time many subscribers asked me to cover heart rate variability, which I finally got to here. When I dived into the research and publication for HRV and readiness scores, I expected to find at least some that were of high quality and demonstrated their utility by linkage to health outcomes. To my surprise, I found none. The wearable sensor measurements for HRV (PRV) are, for the most part, accurate, but that validation work has only been done in small studies of healthy adults and does not take into account the long list of factors, from the device, software side, and the user side, that affect HRV measurements. Moreover, this metric chiefly relies on optical sensing and, as we have learned for heart rate PPG sensing, may be less accurate in people of color. Keep in mind that all of the health outcome association evidence comes from ECG-derived HRV; none are from wearable sensor data. I will repeat the key point: there's no peer-reviewed evidence to show that in-person HRV fluctuation—or efforts to raise your HRV— has any correlation with health outcomes. For those of you who look at your HRV on awakening, or even 2+ week trends of it being low, I hope this context helps to relieve any anxiety. Yes, low HRV (not PRV) has been shown to increase risk of some diseases as summarized above. But efforts to raise your HRV—a surrogate metric— has not been established for improving any health outcomes. HRV does not have any evidence of causality (the genetic evidence actually goes against this possibility). In this summary, I have not included data for other wearable sensors such as Polar, Samsung, Withings, Suunto, Amazfit, Coros, Ultrahuman, or additional mattress sensors. These are beyond my first-hand experience, and as far as I know from my in-depth review none have any peer-reviewed published data that differ from the 6 sensors I’ve reviewed here. From the points I’ve gone over above, we’re not ready for readiness scores. Besides being proprietary, they are predominantly based on metrics that have their own issues. It’s compounding the problem, like building a house without a solid foundation that has never undergone a rigorous inspection, and then selling it. Like I mentioned for PRV, you can look at trends over weeks rather than any single day, to get a handle, but even that may not be helpful. There’s simply no evidence that these scores meaningfully relate to health outcomes. I’d emphasize they might, but that requires doing prospective or randomized studies to prove it. None exist. There’s great promise for HRV/PRV utility_. For example**,**_ Prof Maiken Nedergaard, who discovered the brain glymphatics that are essential in eliminating metabolic waste products from the brain during sleep, has posited that HRV could be a non-invasive marker for neuromodulator oscillations, brain-body regulatory circuits, and brain clearance. That would be extremely useful, but like everything else on HRV and readiness scores it requires solid research and validation. The lay media isn’t helping much to get the story straight. Earlier this year The Economist published a piece entitled “The most useful indicator of your overall health” which ordained HRV as an “accumulated stress score.” That’s akin to the false assertion about VO2max: “V02 max is the singular most powerful marker for longevity.” As I’ve summarized here, that is not established. The fact is that so many things can lower HRV, including physical exercise (especially an intense workout), reduced sleep quality, stress, the list above, no less the device, signal, and software. Whatever fluctuations observed have not been correlated with any health outcome. Sadly, “datamaxxers” are widely using HRV and readiness scores that have never been validated to mean anything. We already know that for some people using the sensors for sleep metrics, it can induce “orthosomnia,” an obsession to get high sleep quality, with associated high levels of anxiety. In an experiment done by a company to promote sleep quality for its employees, “For those employees who did use the trackers, many reported feeling perfectly rested until their tracker told them they had had a terrible night. Others were told that they had slept like a baby when they had actually been lying awake worrying about the quality of their sleep. “ The same problem can result from preoccupation with HRV or readiness scores, with anxiety that would lead to further reduction in both. It you are using a wearable like >100 million American adults, it’s OK to look at these data, but contextualized with the major caveats reviewed here. If you are one to require evidence that HRV or readiness scores are linked to health outcomes, you may not even want to look. The companies make it hard to turn them off! Let me end with the companies that make and sell wearables. Apple’s doubling down on HRV (24-fold more reporting and heart rate very 5 seconds) and introduction of a Readiness score tells us that consumers have bought into these metrics and they are joining the club. However, all of this is occurring with a backdrop of tens millions of users, claims about the data that are not backed up by adequate evidence, marketing way out in front of whatever limited data exists, and not being transparent about their readiness score algorithms. The companies can well afford to do the research that is needed to connect these metrics with health outcomes show, once and for all, that increasing HRV or using readiness scores promotes our health. If they believed and invested in the products they are selling, we’d not be in this position of not knowing. That’s essentially where we are with HRV and readiness scores. Perhaps someday this will change and we’ll have good reason to embrace them. NB: I wrote this post. No AI. I have no conflicts of interest with any of its content. Loading... Ground Truths has 215,000 subscribers from every US state and 214 countries. There are over 300,000 followers of Ground Truths so more than 90,000 folks who can easily convert to be free subscribers. Your subscription to these free essays and podcasts makes my work in putting them together worthwhile. If you’re not a subscriber, please join! If you found this interesting PLEASE share it! Share Ground Truths The proceeds from all voluntary paid subscriptions go to support our summer internship program. It enabled us to accept and support a record number of 62 summer interns that joined us in 2026! These are high school, college and medical students selected from thousands of applicants. We couldn’t do this expanded program without the funds coming in through Ground Truths. Thank you!
Why Is CVS Health (CVS) Reworking Primary Care Around Value Based Care?
CVS Health (NYSE:CVS) is expanding its primary care approach by integrating value-based care across its health system. The company intends to connect health plans, provider groups, clinics, and pharmacies under a single patient-centered care model. Management is targeting shared accountability for outcomes that include social determinants of health alongside traditional clinical metrics. This push to embed value-based care across CVS Health's operations reshapes how the group manages care,...
Fact check: Trump, RFK Jr. and others make false claims on night 2 of GOP convention
(CNN) — President Donald Trump delivered another rapid-fire series of false claims on the second night of Republicans’ midterm convention on Thursday. Health Secretary Robert F. Kennedy Jr. did his own barrage of wrongness. And various other speakers uttered statements that were untrue, misleading or missing critical context.Here is a fact check of some of the assertions from the final day of the convention. This is not intended as a comprehensive list of Thursday’s falsehoods.Trump’s many false claimsTrump made numerous false claims, some of which he also made in his longer speech Wednesday.Trump claimed that there were “no empty seats” in the Dallas arena as he spoke Thursday, which was visibly untrue. CNN White House correspondent Alayna Treene, who was there, wrote in a live chat right after Trump made the claim that “I’m looking at rows of empty seats” and that “the idea that there are ‘no empty seats’ is just laughably untrue,” though she also said the room was mostly full. Trump has for years made false claims about supposedly never having had an empty seat.Trump further inflated one of his favorite fictional figures, claiming Thursday that “$22 trillion” in investment has come into the US; on Wednesday, he had put it at “over $20 trillion,” and even that lower figure has no apparent basis in reality. As of the time he spoke Thursday, the White House’s own website claimed there had been “$11.2 trillion” in “major investment announcements” this term, not “over $20 trillion,” and the White House figure was itself a major exaggeration of actual investment.Trump, talking about elections, lied that “there’s never been bigger cheaters” than Democrats; there is no basis for broadly describing Democrats as election cheaters. For the second straight night, Trump falsely claimed that the Biden administration allowed “25 million people” to pour into the country, though that number is nowhere close to correct. Trump again falsely claimed that former President Joe Biden and other Democrats “created the worst inflation in American history,” though even peak Biden-era inflation, 9.1% in June 2022, was far from the all-time record of 23.7%; it was a 40-year high, but the rate then fell sharply before Trump returned to office.Trump also baselessly claimed that Democrats would “defund the police” and give “voting rights and welfare to 25 million illegal aliens” if they won the midterms. Republicans will still control the White House in 2027 and 2028 and the president would be in position to veto any such changes if a Democratic-controlled Congress sought to make them, but there is no indication that Democrats want to do so. Also, even groups favoring strict immigration policies estimate that the total undocumented population is far less than “25 million” or even 20 million.As he did Wednesday, Trump claimed the US now has the world’s lowest prescription drug prices. The assertion is so broad that it is unclear what exactly Trump is referencing. But experts told CNN they highly doubt that the prices for brand-name drugs in the US are generally less than they are in other countries, and the Trump administration has not provided details to prove the claim.“It’s tough to claim that you’re getting the lowest prices anywhere in the world and then also not have any evidence to support that,” said Andrew Mulcahy, a senior health economist at RAND, while Diederik Stadig, senior healthcare economist at financial institution ING, said, “To say that the US now has the lowest drug prices in the world is at this moment not true.”And as he did Wednesday, Trump said “more Americans are working today than ever before” – which is true but nearly meaningless, since the number of people working in the US generally rises over time simply because the population rises over time.“There are more Americans working because there are more Americans. That’s the entire analysis,” Justin Wolfers, a University of Michigan professor of public policy and economics, wrote in his newsletter in August.RFK Jr.’s false claims on the pandemic, Trump’s record and moreFalse claim about Democrats and the 2024 electionKennedy unsuccessfully ran for the 2024 Democratic presidential nomination before withdrawing to run as an independent and then eventually endorsing Republican candidate Donald Trump. In Kennedy’s Thursday convention speech, he complained of how the Democrats handled the nomination race.At one point, he said, “For the first time in history, they cancelled their own convention. No voter ever cast a primary ballot for Kamala Harris, no elected delegate was ever consulted; the party of ‘No Kings’ simply anointed a queen.”Kennedy is entitled to express unhappiness about how quickly Democratic leaders coalesced around then-Vice President Harris after Biden unexpectedly dropped out of the race in July 2024, after the primaries were over and less than four months from Election Day. But it’s not true that the party canceled its convention or that delegates didn’t get any say.The convention was held; it was a four-day event in Chicago in August 2024. Democratic convention delegates officially nominated Harris in a virtual roll call vote in advance of the convention. It’s true that Harris was the only candidate on the roll call ballot, but that’s because she was the only candidate who gathered enough delegate signatures to appear on the ballot.It’s clear that party elites’ backing of Harris played a key role in the unusual nomination process. But Kennedy’s specific allegations that the convention was abandoned and delegates were cut out of the process are not true.False claim that Democrats closed ‘every church’ during the Covid-19 pandemicWhile attacking Democrats, Kennedy claimed that, during the Covid-19 pandemic, “They closed every church in our country for a year.”It’s not true that every church in the country was closed for a year, nor even that every church in a Democratic state was closed for a year.Every state issued some type of guidance or order about social distancing during the Covid-19 pandemic, but many states – including some led by Democrats and some led by Republicans – incorporated religious exemptions into those limitations on social interactions.According to a Pew Research Center analysis from April 2020, 15 states allowed religious gatherings to continue without a limit on their size. That set of states included Colorado, Michigan and Pennsylvania, which all had Democratic governors. And at least two states with Republican governors, Alaska and Idaho, were among the states that prohibited religious gatherings at least briefly.False claim that Trump ‘ended nine wars’Trump has repeatedly claimed that he has ended “eight wars.” Kennedy went one higher on Thursday, declaring, “President Trump has ended nine wars.”That’s false. Trump hasn’t even ended eight wars.Trump’s list of eight includes two situations that were never actually wars during his tenure: a diplomatic dispute between Egypt and Ethiopia and a mysterious supposed situation between Serbia and Kosovo. The list also includes a war, involving Rwanda and the Democratic Republic of Congo, that hasn’t actually ended despite a peace agreement brokered by the Trump administration.In addition, the list includes the war between Israel and Hamas, but Israel continues to conduct frequent attacks in Gaza despite a US-brokered ceasefire agreement. And it includes the brief 2025 conflict between Israel and Iran, though Israel proceeded to join the US in starting another war against Iran in 2026.Claim about reversing a decline in longevityKennedy speaking of the Trump administration, claimed Thursday: “We have now reversed a 30-year decline in longevity. “Kennedy referenced preliminary data that he said he had received from the US Centers for Disease Control and Prevention this week, but it’s unclear what metric of longevity he’s referring to.CDC data shows that US life expectancy had been steadily increasing for decades before a sharp drop during the Covid-19 pandemic. Life expectancy had already started to rebound in 2022, under the Biden administration, and reached a new record high in 2024 before Trump’s second term began.Preliminary data shared by the CDC in July suggests that life expectancy probably hit another record high in 2025.CNN has reached out to HHS for clarification on Kennedy’s comments.Claim that Democrats ‘lost 360,000 children’Speaking about Democrats, Kennedy said: “They somehow lost 360,000 children and they turned our federal government into the biggest child trafficking operation in world history.”Trump and other Republicans have made similar claims. But there’s no basis for the assertion that Democrats “lost” so many children or that the federal government was engaged in human trafficking.A 2024 report from the inspector general for the Department of Homeland Security said Immigration and Customs Enforcement had reported that more than 32,000 unaccompanied migrant children failed to appear as scheduled for immigration court hearings after being released or transferred out of custody between fiscal years 2019 and 2023 – a period that, notably, includes two years and four months under the first Trump administration. The report also said that 291,000 unaccompanied migrant children during this period were not given notices to appear in court.The report said that ICE had “no assurances” these children “are safe from trafficking, exploitation, or forced labor.” But it did not say all the children were actually “lost” and did not definitively assert that any of them were trafficked – let alone that the government was somehow involved in a trafficking operation. And, again, the report spanned parts of both a Republican administration and a Democratic administration.Aaron Reichlin-Melnick, senior fellow at the American Immigration Council, told CNN in 2024: “Long story short, no, there are not 320,000 kids missing. 32,000 kids missed court. That doesn’t mean they’re missing, it means they missed court (either because their sponsor didn’t bring them or they are teenagers who didn’t want to show up). The remaining 291,000 cases mentioned by the (Office of the Inspector General) are cases where ICE hasn’t filed the paperwork to start their immigration court cases.”Vance on inflation, crime and taxes on Social SecurityA false claim about the media and Biden-era inflationVice President JD Vance mocked the media during part of his speech on Thursday. But he made a false claim about Biden-era inflation while lampooning how the media supposedly challenged him over another false claim on that subject.Vance said: “The president and I would go during a campaign, we’d say, ‘You know, inflation is as high as it’s been in 100 years,’ and the fake news would say, ‘No, no, no, it’s as high as it’s been in 68 years.’ That ain’t good, ladies and gentlemen.”Mainstream journalists, at least, wouldn’t say that inflation under Biden was as high as it had been “in 68 years.” Rather, CNN and others noted that peak inflation under the Biden administration, 9.1% in June 2022, was the highest in about 40 years.Vance is entitled to make his general point that this correction still doesn’t make Biden-era inflation sound good, but his specific number was, again, wrong. And he didn’t acknowledge that inflation fell sharply under Biden after hitting the 40-year high, declining to 2.9% in Biden’s last full month in office, December 2024, and 3.0% in January 2025, when Trump and Vance were inaugurated.The rate was 3.4% in July 2026, the most recent month for which data is available.Trump didn’t end taxes on Social SecurityVance claimed, “We’ve ended taxes on Social Security.” Several other convention speakers, including Rep. Lisa McClain of Michigan, Rep. Ryan Mackenzie of Pennsylvania and Ohio House candidate Derek Merrin, similarly said the administration has achieved “no tax on Social Security.”It hasn’t. The big domestic policy bill Trump signed in 2025 did create an additional, temporary $6,000-per-year tax deduction for individuals age 65 and older (which phases out for individuals earning $75,000 per year or more), but as the White House has implicitly acknowledged, millions of Social Security recipients will continue to pay taxes on their benefits even before the temporary new deduction expires after 2028.The Social Security Administration said in 2025 that “the bill ensures that nearly 90% of Social Security beneficiaries will no longer pay federal income taxes on their benefits.Claim about violent crime rate under BidenWhile criticizing the Biden administration, Vice President JD Vance claimed Thursday that the US “became a country where violent crime exploded, unless, of course, you could afford private security.”But violent crime did not explode under Biden. In fact, as FactCheck.org reported last month, data collected and published by the FBI shows that the national violent crime rate was at a lower level in 2023 and 2024, the last two full calendar years of Biden’s term, than it was in 2020, the last full calendar year of Trump’s first term. The year 2020 was highly unusual in many ways – violent crime jumped amid the Covid-19 pandemic – but Biden nonetheless left office with violent crime lower than it was when he took over. In fact, the 2024 violent crime rate was even lower than the 2019 rate under Trump before the pandemic.There was an increase in violent crime during the earlier part of Biden’s term. But given the subsequent decline, it’s misleading at best to claim violent crime “exploded” with no further context.Asked earlier this month about Trump’s similar previous claims to have reversed a Biden-era upswing in violence, crime data expert Jeff Asher said in an email: “No, crime began dropping significantly in 2023 during the Biden administration. Murder fell at record rates in 2023, 2024 and 2025 and, while 2026 may not feature a record decline nationally, it is still on track to see a sizable double-digit decline this year. Violent crime similarly fell nationally in 2023 and 2024, though the drops were more muted than the decline that was recorded by the FBI in 2025.”Other GOP speakersMike Johnson’s false claim about the inflation Republicans inherited from BidenSome other speakers at the convention took aim at inflation under Biden. House Speaker Mike Johnson claimed that “Republicans inherited from the Biden administration record-high inflation.”That’s not true. The inflation rate was 2.9% in Biden’s last full month in office, December 2024, and 3.0% in January 2025, when Trump took over. That’s lower than the most recent rate, 3.4% in July 2026, and nowhere close to the all-time record of 23.7%, which was reached in 1920, or the highest point of Jimmy Carter’s presidency, 14.8%, which was reached in 1980.Johnson correctly said moments later that inflation reached “a 40-year high of 9.1% inflation” under Biden. But a 40-year high is not an all-time record. More importantly, Johnson didn’t explain that 9.1% was much higher than the rate Trump inherited or that the 9.1% rate occurred in June 2022, with roughly two-and-a-half years left in Biden’s term.The cumulative increase in prices from the beginning of the Biden administration to the end was also not the highest in US history. Federal figures show that beginning-to-end inflation under Biden was less than half of that during Carter’s term.What Johnson left out of his claim about a congressional resolutionWhile attacking Democrats as extreme, Johnson said: “Just last week, nearly every Democrat in the House of Representatives voted against condemning socialism and Marxism. They voted against it.”But the resolution didn’t use the word “Marxism.” And Johnson didn’t mention that the resolution wasn’t only about condemning socialism. Rather, it contained other language that Democratic leadership said was the focus of the party’s opposition to the resolution.The resolution’s first provision said it “condemns and denounces socialism in all its forms, including the Democratic Socialists of America, and opposes the implementation of socialist policies in the United States.” But its fifth provision said it “calls for enactment of the SAVE America Act,” Trump’s favored elections bill, which contains various provisions opposed by many Democrats.So while it’s very possible many Democrats would have opposed the resolution even without its expression of support for the SAVE America Act, the call to pass this elections bill served as a poison pill that ensured most Democrats wouldn’t support it.“House Resolution 1490 explicitly calls for enactment of the so-called SAVE America Act, which is the top legislative priority of far-right extremists,” Democratic House leader Hakeem Jeffries said in a statement last week.A New Mexico candidate left out key context in an attack on his opponentGreg Cunningham, a Republican House candidate in New Mexico, used some of his Thursday speech to criticize his Democratic opponent, Rep. Gabe Vasquez. Cunningham said of Vasquez: “He even voted against a resolution honoring the sacrifices and service of the brave men and women in law enforcement who protect, every day, our communities.”But Cunningham left out important context about the resolution. While its focus was expressing support for law enforcement, its preamble contained statements praising the Trump administration and criticizing “leftist activists,” “progressive politicians” and “sanctuary city policies” for allegedly making law enforcement less safe.In other words, a House member might vote against such a resolution, as the vast majority of Democrats did, because they disagreed with conservative components of it, not the general expressions of support for law enforcement. (CNN has reached out to Vasquez’s campaign and House office for comment on his vote.) It’s common for parties to write resolutions in a way that would make it difficult for opponents to support but would open those opponents to campaign attacks if they voted “no.”An Ohio candidate’s misleading attack about Democrats and votingMerrin, the Republican candidate running against Democratic Rep. Marcy Kaptur for a House seat in Ohio, claimed in his speech, “While Democrats talk about letting illegal immigrants vote in our election, Republicans fight for proof of citizenship, photo ID and fair elections.”It’s a big country, so it’s possible some Democrat somewhere is talking about letting undocumented people vote in some election. But Merrin’s claim is misleading at best. There is no proposal from Democrats in Congress to let undocumented people vote in the 2026 midterms – the election Merrin appeared to be referring to when he said “our election” – or vote in future federal elections.CNN has reached out to Merrin’s campaign for an explanation of his claim.House Majority Leader Steve Scalise invoked a similar theme in his speech Wednesday, claiming that Democrats had voted last week “to allow illegals to vote in our federal elections.” But there was no congressional vote on letting undocumented immigrants vote in any elections.Rather, there was a vote on the non-binding Republican resolution that included multiple provisions, including one that “reiterates the notion that American elections are for American citizens only,” one supporting Trump’s favored elections bill and one denouncing socialism.Opposing that multi-clause resolution doesn’t necessarily mean someone supports voting by any non-citizens, let alone non-citizens in the country illegally.This article has been updated with additional items.CNN’s Deja Oliver contributed to this report.The-CNN-Wire™ & © 2026 Cable News Network, Inc., a Warner Bros. Discovery Company. All rights reserved.
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The science, instinct and hard work behind Roosters’ success
Enter your email address to get each Tribune edition sent to your inbox Subscribe There’s a fair bit of unseen work that goes into winning an NRL premiership, dating back many months - just ask Simon Jones. The Sydney Roosters Head of Performance, who hails from Southland, has been in the thick of it. He played a lead role in guiding the 2026 champions through a marathon campaign that ended with a grand final win over the Newcastle Knights. The Roosters had to navigate the lengthy round-robin competition, including the pre-season, before playing through all four weeks of the finals series. It was a demanding stretch that tested the players and the staff responsible for keeping them on the field. “It is a hell of a beast, mate, to be honest,” Jones told The Roar Podcast. “There’s such a great group of staff there that know what they’re doing, and the boys are pretty professional.” Jones believed the Roosters managed the physical demands well, pointing to the health of the squad throughout the campaign and the decision to rest a significant portion of the playing group in the final round of the regular season. That call, made by head coach Trent Robinson and his coaching staff, proved valuable as the Roosters entered the finals with some energy in reserve. “We did finish the season physically where we needed to be, and we’d sort of had a pretty healthy squad all year,” Jones said. “To the team that do that, mate, mission accomplished, really.” It is the sort of work that often goes unnoticed when the spotlight falls on the players scoring tries and making match-winning plays, but Jones knows the cumulative effect of those decisions can be significant over a long season. After a win over Penrith had helped establish them as premiership favourites, losses to the Wests Tigers and Dolphins were followed by a defeat to the Panthers in the opening week of the finals. Rather than panic, the club refocused to position itself to challenge for the title. “The Tigers’ performance was probably the only one where you’re really quite disappointed because it’s hard to get to the top of the competition,” Jones told The Roar Podcast. “We had proof that we could; we knew what we needed to do. We just had to get back to that.” For Jones, the answer was not necessarily a radical change to the programme. It was about executing the basics consistently, both on the field and in preparation. “We just do the basics better than anybody else,” he said. “Whether that is actually the way you play the game or how you’re preparing, it’s just be really consistent, do the basics really, really well.” Like many professional sports teams, the Roosters are entrenched in sports science and performance data. The club has access to a range of information, including players’ sleep, GPS metrics and neuromuscular scores, helping staff assess how individuals are coping with training and competition. “We are very science-backed, and some people would say data-driven, but it’s people first,” he said. “The reason you collect all this data is to try and be the best for that person.” Jones said the club was also prepared to reconsider testing methods if they were not generating useful discussions or helping staff make better decisions. In an environment where technology is continually evolving, he believes experience and gut instinct remain important. “The data is no good unless you have conversations,” he said. “When you strip it right back, mate, trust the gut still and obviously, you know, just doing the basics really, really well.” The return of halfback Sam Walker provided a further example of the importance of individual determination and the work of the club’s medical team. Walker underwent ankle surgery late in the regular season, with his premiership campaign appearing in doubt. However, he was determined to return for the preliminary final. Jones said Walker was back at the training ground three days after surgery, walking freely enough to surprise those around him. While the surgeon’s work was crucial, Jones credited the halfback’s mindset as a major factor in the remarkable turnaround. “He was quite clear with Robbo after he got the surgery that he was going to make it back for the prelim finals,” Jones said. The Roosters’ performance programme also sits within a wider club culture that Jones believes is central to their success. Each season, players develop their own team mantra through a lengthy process facilitated by Robinson. It provides principles that the squad can connect to its actions on the field. Rather than simply carrying over the previous year’s wording after a successful campaign, the club repeats the process because the players’ ownership of it is what gives it meaning. “When it’s led, player-owned and player-led, mate, it’s really powerful,” Jones said. Get more from Logan Savory in the Substack app Available for iOS and Android Get the app Jones joined the Roosters in 2024 and said the environment had evolved as experienced players departed and younger members of the squad took on greater responsibility. Maintaining continuity in the club’s culture and preparation had helped the group navigate those changes. The premiership was a significant achievement for Jones, who acknowledged how difficult it was to win the NRL’s ultimate prize. However, he is already looking at how the performance programme can improve. “There’s still things within my role and things that I’d like to help improve at the club,” he said. For Jones and his team, the challenge now is to review the season, refine their systems and prepare for another campaign. The celebrations may have followed a memorable title win, but the work behind the scenes never really stops. The Southland Tribune is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Subscribe
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Sundar Pichai: Google’s Frontier Imperative, Compute Scarcity Dilemmas, Future AI Products and Businesses
Alphabet CEO Sundar Pichai has little patience for doubts about Google’s willingness or capacity to compete at the frontier of AI. His company’s latest Gemini 4 Argon model — long-promised and recently delivered — beats OpenAI and Anthropic’s latest public models on coding, math, science, and knowledge-work benchmarks and has placed Google’s AI back among the world’s best. Amid chatter that Google was fine with good-enough lightweight ‘Flash’ models, Pichai pushed back hard against any suggestion that company is limiting its research ambitions. “We won’t do it any other way,” he told me in a Big Technology Podcast interview recorded this week at Google’s Mountain View headquarters. Pursuing cutting-edge research is costly for Google, requiring compute and chips that otherwise could be sold at a high markup by its cloud business. But Pichai said allocating resources to frontier AI development is “ground zero” for Google. “Our cloud business is at any given moment in time forgoing short-term revenues because we are making compute trade-offs to support frontier AI development,” Pichai told me. In our conversation, we discussed Argon (which Pichai says processed three times as many tokens as Gemini 3 in the 72 hours after launch), AI’s role in developing better models, the AI interface of the future, competition with OpenAI, Google’s partnerships with Anthropic and Apple, data centers in space, and the nature of his optimism. You can read the full conversation, lightly edited for length and clarity, below, or listen to it on Apple Podcasts, Spotify, YouTube, or your podcast app of choice. Alex Kantrowitz: Google is back at the frontier with Gemini 4 Argon, which beats OpenAI’s and Anthropic’s public models on benchmarks spanning coding, math, science, and knowledge work. The conventional wisdom was that Google had given up on the frontier to focus on fast, good-enough models for its products. That was wrong? Sundar Pichai: Very wrong. Look, we are so committed to being at the frontier. It’s in our DNA. We won’t do it any other way. We’ve been thinking about the AI frontier for well over a decade now. The frontier is very dynamic. It’s very competitive. It’s very exciting. I couldn’t be more pleased with how Argon has come together. We took our time with it. We made sure we tested it safely and deployed it carefully. We took a bit longer than our other models, given its capabilities. Across the board, be it for agentic work, knowledge work, coding, creative tasks, Argon is one of the really good frontier models. The first 72 hours since we launched, it’s almost up to 25 trillion tokens used, which is about three times what Gemini 3.0 had in the first 72 hours. And we are capacity constrained as we are serving it. Excited, but there are always areas….. You know, the frontier is very dynamic, and you have to keep evolving the models. There are areas which we can see we need to improve as well. We’ll be at work on all of that as well. Which areas? On any given model, Argon would be across the board better at everything if you just look even two months back. But the space is so evolving. Even on coding, for example, there are pockets where we know we need to do better, and there’s clear feedback. We’ll make it better. The argument for standard models is that they’re already good enough to build great products, with the frontier valuable only for certain tasks. Meta built Muse with good models rather than the best, and Google could put standard models into Maps, Gmail, and Search. Why isn’t that sufficient? It’s definitely not how I have thought about it at all. We are deeply committed to driving the state of the art and actually pushing where this technology can go, all the way from transformers. That’s a journey we’ve been on. You will see us continue to do that. When you’re at the frontier, you get an earlier look into the emerging capabilities, earlier than others, which helps you better prepare for the future. We are fortunate to have a wide set of opportunities across consumer and enterprise. Some of our cloud customers, for sure, want the model at the frontier. The frontier models will be better at developing the next set of models in an era of recursive self-improvement. I would argue it matters there. Internally, we have definitely seen a steep point of inflection by deploying Argon to our developers. It definitely tackles problems which our previous models could not do. Being at the frontier puts you at the innovation frontier and helps you drive that as well. There is room for models of all sizes and capabilities. That’s why we did Flash, Flash-Lite, etc. I agree with you that you can develop very good product experiences with not necessarily the most frontier model, because they tend to be slower and more expensive too. But we care about the Pareto frontier, and we’re committed to doing all of that. You said developing frontier models gives you a look at what’s coming. What do you see on the horizon? What makes this moment so exciting is you build something which you think is a culmination of months of work, and you put it out. You already see clear headroom ahead. We’ve all been working on these agentic, long-horizon capabilities, but clearly the frontier is going to have multiple of these agents working together to do things. That’s an example of an exciting paradigm underway. It’s also clear to me that users, both in consumer and enterprise, will have access to some multi-agent framework for them, working all the time doing things. It feels like a moment of infinite possibilities. Sergey Brin said one of Argon’s core innovations was relying more on the model to help develop the model. Yet incidents involving OpenAI’s bots breaking containment and Google’s bots accessing a site they shouldn’t have suggest these systems still aren’t perfectly aligned. Isn’t there reasonable cause for concern about accelerating toward recursive self-improvement? There are three parts to your question. Let’s first talk about RSI itself. You’re right, Sergey mentioned RSI being a critical contributor as we are developing Argon. But to be very clear, today, in a continuum, we are pretty far from the end state of RSI or something like that. The right way to describe it is you have RSI loops along with AI researchers in various aspects of model development. You almost have agents helping AI researchers in some automated way work together to build these models. It’s good to at least understand where we are today, and it’s super exciting. I expect that continuum to keep making progress as we go into next year. The second question is around safety. Security comes from defense in depth. You’re talking about alignment, obviously. We all are doing a lot of work to make sure the models are as aligned as possible. But it’s an active area of research, and there are clear gaps. That’s not the only thing we rely on. You have the work you do on alignment, but beyond that, we put a lot of effort into real-time monitoring as these models are working. Making sure you have good telemetry into what’s happening so that you can intervene in real time if you see unexpected behaviors. How you do that, the architecture with which you do that, how you make sure it’s all sandboxed and isolated in a way that it can continue doing its job during real-time monitoring — these are all areas of investment. Obviously, when we deploy these models, giving customers, enterprises, control, both with real-time monitoring, but their ability to decide where they deploy, what type of data which models ever have access to, etc. All that work is very, very important, and we are doing a lot of that. As an industry, we need to constantly up our game and take the time to do all this stuff, including dedicating the compute required to make sure you can safely deploy these models. The third part is: Is it all enough? This is why there are a lot of conversations in the industry, and I think it’s reasonable to be worried. The right way to approach something you worry about is early on thinking about what more we can do. As an industry, you’re definitely seeing increased levels of work on alignment, testing for safety, etc., as we deploy these models. The next step would be developing better standards so there are cross-industry standards of how we do these things, including the ability to evaluate using independent evaluators. If you look at areas like financial controls, we have accounting standards, we have independent auditors. Those are all the next natural steps for us as an industry to work toward, and regulation will end up playing a role as we go through all of that as well. Google pursues both language models and world models, while some other AI companies like OpenAI have focused more heavily on LLMs as the path to AGI. Why is world-model research important to you? As humans, you obviously perceive the world around you, and you’re taking all those inputs. Making sure these models are able to understand the laws of physics, simulate the world in high fidelity. All that, I think, are key enabling blocks for intelligence. We are working across all possible applications of this. Take an area like robotics. It’s not an accident: If you look at embodied reasoning benchmarks, Argon is state of the art. That all comes from our experience building world models. Inherently, I would expect there will be architectures which will converge all of this in the future. But for us, we view this as, today, this jagged frontier that is intelligence. We want to be at the frontier of all the possible approaches, and that will help us both drive better research, better insights, and develop a much better AGI model, is how we think about it. Some people argue Google should focus on selling its computing resources rather than using them for AI research. Cloud wants to sell compute at a high markup, while researchers need a very big computer to build the best models. How do you balance those demands? Ground zero for us is making sure we are investing in the compute that’s needed to be at the AI frontier. In 2015, I set the company to be AI-first. AI is that key horizontal ingredient across everything we do, all the way from Search to Cloud to Waymo. That is ground zero for us, making sure both for research and developing the models that we have enough compute needed. Beyond that, we have these independent businesses which each have their own long-range plans. They’re using those long-range plans to project forward, and we plan for compute for all of them. The cloud team, they have a business and they have a projection and they have demand signals. They have committed contracts. With that help, we can plan on a long-term compute trajectory for them. We’re fortunate to have this wide set of opportunities. There’s no company in the world which isn’t making trade-offs at any given moment in time. But the first principles we operate on is making sure we have enough compute to invest in the frontier, and that’s non-negotiable, and everything else works on top. Remember, we are building our own compute, our own data centers. There are long lead times. The compute we have today is a function of decisions I made in 2024. Even if you think back to a year from today, last year the agentic coding takeoff hadn’t happened. Today, obviously, when you sit and look at anything, everyone is short—not just us, other companies—and everyone wishes you had two times what you had planned for. That comes with the territory. At any given moment in time, we are planning for what we would need two to three years out in the future. You’re going to find some decisions you make may look suboptimal two years out, depending on where the state of the art is. I don’t spend too much time thinking about it. The way I think about compute allocation is making sure Google DeepMind, both for research and frontier model development, is cutting edge in terms of compute access. After that, we plan for all our businesses. It’s great we can provide our compute to other people too, like we have done. It allows us to scale that up, get real tests for it in the widest application set possible, test it in the real world, and make sure we are at the cutting edge of technology at every layer of our AI stack as well. Ben Horowitz relayed on a podcast that Andy Jassy had said compute was sold out until 2028. Are you seeing the same thing? If today a customer is coming out and asking us for compute in ’27, that is incredibly difficult to do. Even last year we went out and leased some short-term compute to accommodate some customers and help them out. But yes, we are all dealing with similar timelines. Every major technology shift seems to involve overbuilding, from railroads to fiber. Do you think that’s happening here? It depends on the time frames you’re looking at. This level of build, if I take a long enough time frame, it makes complete sense to me. We are at early stages of the most consequential technology ever, and this is not like fiber. It’s not dark. We are using it. We are capacity constrained on a daily basis. The applications, the underlying technology is improving rapidly. But running a company, the way I work through the moment is you look at your demand signals. You look at your committed revenue opportunities that you’re getting in the form of contracts. You balance that with the underlying technical capability, or internally you balance how we are using it internally, the model trajectories. Based on all that, you take a disciplined approach—a confident, aggressive, but disciplined approach—to plan out compute. But when you talk about the broader economy as a whole, you’re having people operate with various levels of risk. I focus on what I can control as a company and plan through it. If your question is, can there be an overbuild? Yes, because you can have some constrained components. Remember, what matters is a set of everything you need to build out that compute. Memory, electricity, electricians…. Land. Like 2,000 components or more. You could get constrained at some point. There could be things which cause bottlenecks, and then you could have overbuilds. There could be external shocks to the economy. There are macro risks. All that is possible at any given time. But am I confident that the compute we are planning for, we will have uses for it given enough time? Absolutely, yes. I was in the room when you said AI would be as profound as fire and electricity. If you believe that, shouldn’t you give researchers the biggest possible computer, even at the expense of today’s cloud profits? We’re all doing some form of that. Our cloud business is at any given moment in time forgoing short-term revenues because we are making compute trade-offs to support frontier AI development. What you’re seeing is true already. But you want to be thoughtful. Even our AI researchers have some constraints, which are also good. That’s what inspires creativity. That’s what helps you come up with a more efficient algorithmic breakthrough, maybe to use less memory. What we are committed to is to invest what’s needed to stay at the frontier. OpenAI President Greg Brockman told me a few months ago that the ideal AI product might have no interface at all—just as natural as conversation. What do you think the interface looks like in the age of AI? Computing historically has been humans adapting to computing. With AI, it’ll be the other way around. The technology will adapt seamlessly to how humans live and go about their day-to-day life. You want to be able to speak to that AI when you want to. It has context. It can be persistently running somewhere, give you continuity. You’re not dealing with a lot of complexity. It’s natural. All that makes sense to me. That doesn’t mean it won’t have any interface, however. Nowadays, even on my phone, Gemini voice models are so good. I can just press the microphone button. I can just ramble. That’s why we call it Rambler. I can ramble. It intelligently corrects with my personal context. Even my friends’ names, weird names, it gets it right, even if it first guesses it wrong. It’s amazing. I’m not going in, backspacing, editing once I finish saying it. It’s remarkable how good it’s gotten. But there are going to be moments you will need an interface. You may want to entertain yourself. You may want to watch a video. You may ask your AI to create something, and you want to watch it, consume it. The way I think about it is, you want it to be as seamless and as natural as possible, and that you are not doing the hard work adapting to whatever the interface is. The technology is adapting to how you’re working at any given moment in time. When I asked Sam Altman about competition from Google, he argued that OpenAI was building AI-native products and implied Google was bolting AI onto existing ones. Do you accept that framing, and can a “bolt-on” compete with an AI-native product? First of all, it’s a very dynamic moment. We are all pushing each other. OpenAI has pushed us as a company too. This is not just we are doing something to them. Far from it. Yes, Google went into its own version of a code red too. In the AI moment, all of us have to respond with varying levels of urgency at any given moment in time. We are constantly building new products as well. Gemini was built from the ground up as a product—the Gemini app I’m talking about. Or tomorrow, as all of us are adapting to agents, are you bolting agents onto ChatGPT, or are they building it natively? How would you think about that? You can always put these questions back. I don’t think of it that way. I think of it as you want to build world-class product experiences that are AI-native and they are winning. Some of it is adapting products, some of it is rethinking new experiences. They will all be part of how you approach this moment. How do you expect to make money from these AI interfaces? If an agent recommends a product and I buy it, should it take a cut of the sale, even if that’s disclosed? I’m going to put enterprise aside. Consumers are going to increasingly value this technology. Take software developers today. Developers are willing to pay for these coding models because it really helps make them more productive. Nobody would want to code the way they were coding three years ago, or even the same time last year. When you’re delivering value, there’s value to be had. I’ve never seen examples where consumer products really scale to billions of users, where people are using it intensely, and haven’t had monetization to go along with it. If you’re providing value to people, there is inherent value to be had. The nature of it may change. You’re asking a scenario in which agents are doing stuff for you. At the end of the day, you will have commercial needs. The agents need to fulfill those commercial needs. The providers on the other side are going to see value in that. There’s going to be some mechanism by which it gets fleshed out. That’s what an efficient system does. But what matters is that you’re building those world-class consumer experiences. I promised myself one product feature request: Can you make Gemini-powered search in Gmail as good as searching Gmail through ChatGPT? What’s going on here? One of the exciting things we announced recently is the unified Gemini agent for enterprise, and we’re bringing that to consumers. These are persistent agents which run 24/7 in the cloud. We’re spinning up a micro VM effectively for every query, and from the runtime, the harness, the model—it’s all a headless service. It’ll work everywhere, and it has your context with you. You can address this agent whether you’re in Workspace, in Search, in Gemini. Agents are going to drive this unification from a customer experience, which people are looking for. When you have a broad product portfolio and you’re moving forward fast, there are always areas where you’re moving forward faster than some other areas. That’s valid feedback. But we are putting a lot of time and effort into making sure, as we build out our agentic experience, that unification and that capability works well across all these services. People have asked where Google’s equivalent of Muse or Dots is. Do you anticipate creating a new product to compete with them? Our goal with Gemini is to be a personal, proactive, and powerful assistant. That’s what we are working toward. You saw us describe the early versions of it at Google I/O this year with Spark. Effectively, already, if you open the Gemini app as a Pro or an Ultra user, you see Chat and Task, and they start giving you that agentic experience. With Argon now, that capability is dramatically accelerated. What we announced recently in our enterprise event, we are bringing that to consumers as well. Soon in Gemini, you will be able to ask something, and it’s a continuum. You don’t need to think about whether you’re asking a chat or an agentic task. It’ll just automatically do the right thing, and it can work persistently in the background securely and get things done for you. Already, empirically, when I look at what’s coming into Gemini in our app, last year you would have tagged them and most of them would have been chats. But a steadily growing percentage is already agentic tasks in Gemini. Yes, we are going to bring personal agents to our consumers. It’ll work in the Gemini app. It’ll work in Google Search. It’ll work in Gmail. You can address it, call it, etc. We want to make sure we’re getting it right. It’ll be powered by Argon, and we are very excited to bring it to our users. Google has invested and committed tens of billions of dollars to Anthropic. What do you see in Dario Amodei that makes you want such a deep investment and partnership? Very early on, when we looked at the founding team of Anthropic, it was very clear to us this was a world-class team which was involved in some of the earliest GPT models. We were quickly able to assess that they would be at the frontier. We’ve always tried to identify and partner with companies which would be at the cutting edge of technology. We’ve done that with SpaceX. We’ve done that with Anthropic. That’s what we saw, and we had a chance to partner. Is your partnership with Apple to license Gemini for Siri expanding, contracting, or standing still? For both us and Apple, that partnership was about translating the capabilities of AI into better experiences for users. I thought Apple has done a phenomenal job of incorporating—they customize these models and build it into Siri—and it’s been great to see the reception. We are committed to doing more. You’re going to do more with them? There’s nothing specific to comment, but it’s a partnership. It’s working well. What have you learned so far about the feasibility of data centers in space? It’s a very exciting project. Projects like this remind me—I still recall that moment in the desert for the DARPA Grand Challenge, watching the Stanley car compete in it, which ended up being the basis for Waymo. With all these technologies, you’re at a moment in time where it looks a bit like sci-fi, but 10 to 20 years down the line, it’s actually working in a meaningful way. I feel the same in space. We’ve always believed in betting big on these technologies. Quantum has been a great example of it. We’re probably 10 years into the journey. Waymo, we are almost 20 years into the journey. Space, we are two to three years into the journey. It’s clear to me that it’s an approach which will make a lot of sense in the future. Being in sub-synchronous orbits with 24/7 access to the most abundant form of energy we have access to will make a lot of sense for this exponential increase in compute that we are going to need. Having said that, this is a challenging project. The team has disciplined milestones. It was a super exciting milestone to send the TPUs up to space. Sometime, as we are speaking, we are expecting a “hello world” moment from them. I look forward to seeing that happen, and we’ll continue investing here too. You previously said 25% of the code written within Google was written by AI. What’s the number today? That number in our world today is meaningless in the sense that every part of what we now touch is influenced by AI deeply. What we are tracking with Argon, for example, it’s been a point of inflection. People are using Argon to really go tackle complex projects, including projects which affect millions of lines of code. In the four weeks since we have launched Argon, we have seen a 30% increase in CLs, and more importantly, almost a similar increase—a one-third decrease in rollbacks. People are writing code more productively and better code with it. We are tracking it with newer metrics now. How are you dealing with opposition to data centers? If you can’t build in the U.S. the way you want to, where else do you go? We’re very committed to building our data centers very responsibly. When I look at our largest data centers in some of the communities where we have been the longest, I visit them, I talk to people. There are people who come and tell us their kids have gone to college because of our investments in these communities, and we’ve grown in those communities. To me, this is about doing it right. Engaging with the communities early, doing it transparently. We are committed to making sure we are bringing incremental power, and we cover 100% of the cost of our power needs for these projects. It’s understanding the impact on neighborhoods and making sure you’re working thoroughly to address them. Done rightly, you can continue making progress. But we are constantly taking feedback into account. I do worry not everyone operates the same way. People have been surprised by data centers showing up in their backyard. Those are all important. As an industry, we should continue to do better. But part of the reason, in a 20-year time frame, we are thinking about things like data centers in space is making sure we are able to put these data centers where maybe the trade-offs will be different. What unproven area of AI is Google working hardest to crack? Is it continual learning—getting models to keep updating after release—or something else? There are multiple parallel paths. You saw with Argon we have a million output tokens. With our Gemini models early on, we had a one-million context window on the input side. These are all examples of breakthroughs we are constantly working on. How do you think about synthetic data? How do you think about continual learning? How do you think about more efficient architectures? We do dedicate a meaningful percentage of our compute to these research bets too. It always goes hand in hand, including our world models. Those are all bets we are placing. Sometimes, as part of these bets, there are ideas that emerge which just make their way into the mainline models. Maybe we don’t fully talk about it, but we have multiple steps in these areas. Working in technology requires optimism that building something will improve the world, but those bets can leave real consequences when they fail. I recently returned to a town in El Salvador where enthusiasm for Bitcoin had given way to unfinished construction and something resembling a ghost town. How do you maintain the optimism you spoke about in your Stanford commencement address while accounting for those risks? I genuinely have a deep conviction that improving technology and improving access to technology makes people’s lives better. It’s been my personal experience in my life, out of which comes that deep conviction, optimism. But with that, I’ve always felt humanity’s journey is always about working hard to harness that technology to make it work well for society. The optimism is not an optimism that you just build whatever you want, whenever. You work hard to make sure you’re building technology in the service of humanity, to make the human condition better. That’s got to be the defining goal as we are approaching it. With that framework, I’m very, very optimistic. We are in very early stages of the kind of progress that we are going to see on many areas. We’re all talking about areas like healthcare. A lot of the progress is ahead. The ability to make things in a fundamentally cheaper way on many things where things have been getting expensive for a long, long time, discovering new materials, etc., which really bend the curve—it’s tough to step today and understand the impact of all that, but they’re going to be very profound. I’m very optimistic, but we have to be rightfully concerned about all the ways this technology can go wrong. Sundar, I know you don’t do many of these. Thank you. Thanks, Alex. Appreciate it.
USTR's Greer huddles with House Republicans amid Trump trade spats
Trump's plan to lower tariffs on 300,000 metric tons of imported beef caused an uproar among cattle ranchers.
iOS 27.2 Beta Previews New Apple Intelligence Health App
The first beta of iOS 27.2 includes Apple's redesigned Health app, giving developers a chance to try out the features ahead of launch later this year. Apple's developer notes for the feature say the Health app is being tested in this beta, but it won't be in the launch version of iOS 27.2. It will instead come later in the year. The Health app will incorporate Apple Intelligence to turn data and metrics collected by the Apple Watch into personalized guidance.
Netflix’s Summer of Bummer
(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.) Today, I’ve got a guest post from longtime friend of the newsletter, Brandon Katz. I’ve been trying to find time all summer to look at Netflix’s straight-to-streaming film slate, but between a pre-planned trip and Nielsen moving up their streaming data timeline, I’ve been swamped. So I reached out to Brandon, one of my favorite fellow analysts, to write about it. And I feel like he captured the tone and data focus of the newsletter perfectly. You can connect with Brandon on LinkedIn and Twitter. Enjoy! Don’t worry, folks. You’re in safe hands with me. To ease any anxieties about an interloper in ESG’s domain, I’ll start by stealing one of his best framing devices: headlines. Box office flops are covered in the same way the Teenage Mutant Ninja Turtles eye pizza: with cartoonish insatiability. I would know. I’m a former reporter who wrote nearly identical headlines: Yet, intentionally or not, streaming misses get treated with kids gloves, filtered through a rosy lens: In the last six years, U.S. streaming viewership has become nearly as transparent as the box office, but the data often arrives weeks later, in a number of less intuitive metrics, and with nary an official budget to be found. This plays into the Wall Street-whispering narratives major streamers have been cultivating for years. They get a pass in a way that theatrical studios simply don’t. Subscribe Netflix’s Summer Slate Not a single Netflix original film released between May and August this year opened above 20 million U.S. TV hours, per Nielsen. That benchmark usually serves as the EntStrategyGuy’s floor for a streaming hit on Netflix. None of these films enjoyed a hit-cementing single week of 20-plus million hours during their runs. Netflix’s two best films were true crime docs, Maternal Instinct (16.5 million hours) and The Crash (19.7 million), the best overall week for a film this summer. Great for most other streamers, but not necessarily what we’re used to seeing from Netflix. For an overly-dramatic comparison, Happy Gilmore 2 opened last summer to around 47 million hours (celebrity cameos, baby!). Zooming out, the picture looks even worse. In 2026, Netflix’s five biggest scripted summer films posted the lowest average (28.6 million hours) and median (28.8 million hours) eight-week viewership totals of the past four years. Now, it’s unrealistic and unfair to expect Netflix to deliver a _KPop Demon Hunters-_sized hit every year. But it’s also not ideal to see the size of their hits shrinking over the last few summers. Let’s quickly run through some of the notable summer misses. Jennifer Lopez and Brett Goldstein’s perfectly fine romcom, Office Romance, fell off the charts after 20 million hours in its first two weeks. Top films usually last for four-plus weeks. Starry titles ideally don’t decay that fast either. Homegrown star Millie Bobby Brown couldn’t prevent the snappy Enola Holmes franchise from diminishing returns. At 14.3 million U.S. hours, the third film posted roughly half of what the first two films did in their first two weeks. What’s on Netflix calculated that per-day global views were down nearly 60% from the second movie. The Whisper Man did okay with more than 36 million hours over its first four weeks. But I expected a little more juice from a film featuring Robert De Niro, Michelle Monaghan, and Adam Scott. Kevin Hart’s Ladies First collected just 11.2 million hours total across two weeks. That’s a big miss for one of Netflix’s go-to stars. Plopping into the same bucket are Sunny Sandler’s Don’t Say Good Luck (10.3 million in two weeks) and John Cena’s Little Brother (17.5 million). Meanwhile, English-language originals Color Book (June 19), In the Hand of Dante (June 24) and Heartstopper Forever (July 17) never sniffed Nielsen’s Top 10 at all, despite needing only 2 to 5 million hours to land in the top ten most weeks. (By my count, eleven English-language scripted original films released between May and August did chart). It’s only fair to mention that Swapped (1-May) posted nearly 42 million U.S. hours over five weeks (the longest Netflix original run this summer) and is currently their eighth most-watched English-language film ever worldwide. Remarkably Bright Creatures (37 million, 4 weeks) and Voicemails for Isabelle (27 million, 4 weeks) weren’t bombs either. Still, overall, I think it’s fair to say this was a quieter summer season than we’re used to seeing from the market-leader. You might not realize that given the language commonly used in public analysis. The Twist Despite the starkly black-and-white tone of the coverage, here’s the twist: when many box office bombs arrive on streaming, their viewership looks a whole lot like many of Netflix’s supposedly successful summer releases. Hmm, where have we heard that one before? Masters of the Universe topped out at $65 million stateside against a $170 million budget_._ I’ll admit, Skeletor ripping sleeveless curls as a gym bro and bodyslamming Adam’s co-workers was funny. But, much to the chagrin of my bank account, my laughter doesn’t launch franchises. Yet the He-Man reboot opened to 19.6 million hours (from a Wednesday five-day opening instead of just one weekend), on par with Hoppers on Disney+ (19.4 million). It put up nearly 47 million hours over its first six weeks, bigger than all of Netflix’s summer releases. Pretty darn healthy and likely to land among the 25 most-watched movies on streaming this year. Sticking with Amazon, The Sheep Detectives just barely broke even at the box office with $133 million worldwide (and only $66 million domestic). I never expected cloven-hooved, cud-chewing mammals to be able to bring me to tears. Yet that’s exactly how I found myself at the end of this surprisingly affecting movie (#NoShame). It was likely the unexpected quality in a family-friendly film that powered its streaming over-performance. Sheep Detectives delivered a solid run for Prime video netting 26.2 million hours! How about franchise IP? Star Wars: The Mandalorian & Grogu had the lowest opening ($81 million) and lowest-grossing Disney-era live-action Star Wars film ($178 million domestic). One day before release, its Heat score (19.8%)—audiences who list their interest as a 7/7—fell behind blockbusters Wicked (21%), Superman (23%), Fantastic Four: First Steps (23%), Michael (23%), Toy Story 5 (26%) and Avatar: Fire and Ash (27%), according to Greenlight Analytics. The urgent enthusiasm just wasn’t there. On streaming, Mando opened to weeks of 12.1 million, 6.1 million and 2.7 million hours (21 million total) over its first three frames. Not the numbers Lucasfilm was hoping for nor the numbers of a streaming hit. But they’re in the same vicinity as some Netflix summer releases with $345 million at the global box office to offset a smidgen of the pain. Final Thoughts So why oh why does this nuance gap exist? Four key reasons: Data Literacy: A “$100 million opening” just makes sense. After decades of box office reporting, even casual movie fans are well-versed in the benchmarks of hits and home runs. There’s an immediate shorthand. But “16.5 million” hours doesn’t land nearly as cleanly. Despite leaps of progress, the streaming ratings era is still in its infancy compared to theatrical. The EntStrategyGuy and I met thanks to a late 2010s group chat of data nerds hungry to find a shred of certainty in nebulous streaming performance. I’m not surprised to see “No. 1 on Netflix” still getting misconstrued out in the wild. Timing: By Friday morning, we have the box office’s Thursday night previews totaled, allowing us to better project the weekend’s expectations. From there, ticket sales are reported daily. By Sunday, the film’s fate is usually finalized, at least in terms of public perception. In streaming, Nielsen recently improved its delay to…two weeks. The medium isn’t forced to contend with instant gratification as harshly. Financials: Theatrical film budgets are a mere Google away. Profit and loss is calculated in the cold and unforgiving naked light of day for all to see. But finding the vast majority of streaming exclusive movie budgets requires the forensic investigation skills of a Criminal Minds detective. Also, it’s very difficult to calculate how much revenue/value a straight-to-streaming films provides a streamer. This is why there are so few stories about streaming original movies “losing X amount of money”. On top of that, marketing budgets are far greater for theatrical movies than streaming exclusive movies, which leads to earlier and better awareness. This then translates to a wider pool of potential interest. Narrative Control: Netflix is the only major streaming service to publish weekly first-hand viewership data and annual engagement reports. Naturally, some headlines borrow their first-hand framing**.** Other streamers benefit from their comparative lack of transparency. They may occasionally announce vague performance platitudes such as Apple TV’s Mayday becoming its “biggest film debut on the platform to date over its first 18 days,” and that it ranked No. 1 with left-handed viewers in its first weekend. (Fine, I made up that second one). But, for the most part, they keep first-hand viewership shrouded in mystery to avoid bad press. Especially for outlets that demand multiple articles per day from their writers, it’s an easy (and understandable) way for some reporters to hit their daily article quota by just repeating what the streamers have told them. TL:DR version: Streaming-exclusive movies are asked to do different things than theatrical movies, but that doesn’t mean they should escape judgment. Both still need to draw enough eyeballs to justify their cost within the proper performance contexts. The more cleanly we can inject a little nuance into streaming analysis, the better we’ll understand the audience and content trends that drive this industry. And that’s what all of this is really about: knowing what audiences actually want! Brandon Katz is the Director of Insights & Content Strategy at Greenlight Analytics where he focuses on evaluating the ever-fluid media landscape to unearth understanding, opportunity and value. Greenlight Analytics is the entertainment intelligence consulting company redefining how Hollywood finds, understands, and activates audiences. Prior to joining Greenlight Analytics, he served as the senior entertainment industry strategist at Parrot Analytics, and as a full-time entertainment industry reporter covering the Xs and Os of Hollywood, most notably with TheWrap and the Observer.
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UK's Oxford Metrics warns about annual loss on entertainment industry spending cuts
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Should US Court Scrutiny of Prediction Markets Require Action From Flutter Entertainment (FLUT) Investors?
In recent weeks, Flutter Entertainment has seen sentiment improve as the prospect of a US Supreme Court review of sports prediction markets and fresh analyst coverage refocused attention on its core US sports betting exposure and broader global portfolio. This shift comes after a very large reset in expectations over the past year, leaving valuation metrics suggesting the business screens as relatively inexpensive while ongoing regulatory and legal uncertainties remain central to how...
Canada's trade arsenal packs US political punch
To combat tariffs imposed by his country's hulking southern neighbor, Prime Minister Mark Carney is using asymmetric warfare. Retaliatory 15% to 50% duties hit only $20 bln of goods. Tight US elections in border states, however, turn the sums into a powerful super PAC of sorts.
Apple's Health Age Test Doesn't Hold Back (Oof)
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The 20 global cities with the best quality of life, ranked
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The Aral Sea, Once the World's Fourth-Largest Inland Lake, Was Drained Dry. Now It's a Ticking Carbon Bomb
Most of this inland sea is a dry lakebed the size of Ireland, and it has already released 748 million metric tons of CO2. But scientists say there's still time to reverse course.
Hawaiian Telcom Unveils Future-Ready Business Fiber Platform Engineered for 10 Gig Connectivity
Hawaiian Telcom announced enhancements to its business fiber internet portfolio, including expanded symmetrical upload and download speeds across Fioptics Business Internet plans and the introduction of Fioptics Advanced WiFi for business customers. Together, these enhancements provide Hawaiʻi businesses with faster, more scalable connectivity backed by a fiber network engineered to support connectivity solutions up to 10 Gig.
Beyond basic metrics: Proving impact before business metrics move
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Inside one behavioral health CEO’s decision to automate revenue cycle operations
There was no single metric that told Dr. Mary Affee her practice had outgrown its operations, and that was the frustrating part. She had built Horizon
Mom-and-Pop Business Owners Grapple with Harsh Times
Report shows small business owners in NYS less optimistic about the economy. Taxes, inflation, labor costs and competition from larger businesses are major concerns right now, they say By Aaron Gifford [caption id=attachment_11067 align=alignright width=300] Ashley Ranslow is director for New York state at The National Federation of Independent Business (NFIB).[/caption] Owners of mom-and-pop businesses in New York state have been less optimistic lately than their peers in other parts of the country, a recent report indicates. The National Federation of Independent Business (NFIB), based on a survey of 11,000 of its members in the Empire State, reported that taxes, inflation, labor costs and competition from larger businesses are major concerns right now. “Indeed, while taxes are a major problem in New York and the United States overall, New York small businesses notably are struggling more with the state’s onerous, multi-level tax burden,” Ashley Ranslow, NFIB’s director for New York state, said in the July report. Compared with surveys of business owners in other states, far fewer New York respondents rated their businesses as in excellent or good health. The report also said labor costs here are about 25% higher than the national average and are the “single most important problem” facing businesses. One respondent to the New York-specific survey complained that too much red tape, taxes and laws that restrict high-yielding companies have stifled their operation’s growth. Others said high disability and workers’ compensation insurance costs, alarming increases in utility rates and excessive building regulations are discouraging. Statewide, New York has a gross domestic product of $2.53 trillion (third in the nation, followed by Texas, $2.90 trillion; and California, $4.25 trillion), a per capita income of $90,500 (sixth) and an unemployment rate of 4.6% (34th). There are 2.4 million small businesses that employ 3.9 million people. [caption id=attachment_11112 align=alignright width=451] Member of the Greater Liverpool Chamber of Commerce gather at one of the several functions the chamber organizes monthly. “Everyone in this business community encourages each other to shop local. Everyone just wants to see each other succeed,” says Megan Wilmot, the chamber director[/caption] “New York state boasts one of the largest, wealthiest and most diverse cities in the world — and that’s still only about half the state’s population,” the report said. “In other words, the state is both its iconic city and so much more — geographically, demographically, economically. But New York is not without its challenges, challenges that include notably high taxes and other weaknesses that impact the small business environment,” it said. The report includes an optimism index that compares responses from New York (NFIB) members with those of their peers in other states across several categories. This ranges from plans to increase employment to expectations for higher sales, to plans to increase inventory or expand. The scores for Empire State business owners were lower in most categories, but they did score higher than the national average in noting that they have current employment openings, and that they are hopeful that the economy will improve. “The metrics so far paint a picture of a state with a series of challenges for small businesses, from a slightly below national average Optimism Index to a more seriously below national business health to very substantially below national Employment Index. What is going on with businesses that are creating these differences?” the report stated. In Central New York, the regional labor force comprises nearly 398,000 workers. The median household income here is $71,463, and the gross domestic product for the region last year totaled $61.3 billion, according to the CenterState CEO economic development and research organization. About half of the region’s labor force works for small and mid-sized businesses, although the number of people employed in that sector has decreased by 7% since 2010, according to CenterState’s 2026 economic forecast report. “While record-high employment in large-scale enterprises provides a strong foundation for Central New York,” the report says, “the long-term health of communities depends on a thriving small business sector to serve as a stabilizer.” Area employers identify several barriers to Central New York’s anticipated growth, including lack of specialized or skilled workers, government regulations, unaffordable housing options and long-term construction disruptions. In the city of Syracuse, the number of jobs in retail trade decreased by 1,500 or 4.7% between July 2025 and this past July. By contrast, the number of jobs in the leisure and hospitality sector increased by 2.5% or 700 jobs, in the same annual period, according to the New York State Department of Labor. Still, there’s plenty of interest for new businesses across Central New York. U.S. Census figures show that the number of applications for new businesses in all four counties increased significantly in the past 20 years. In Cayuga County, there were 324 applications in 2005 compared to 470 last year. In Madison County, the number increased from 385 to 480; Onondaga County, from 2411 to 4132; and Oswego County, from 553 to 836. Downtown Cazenovia is exemplary of Madison County’s trend: In the past year, the village welcomed a bait shop, a thrift store, a vitamin infusion center, a pizzeria, a Pilates studio and an Italian restaurant. A candy store is scheduled to open on the main drag in the months ahead. Oswego’s list of interesting new businesses in the past year includes a bubble tea shop, a hot dog eatery in Fulton, a specialty grocery store that features New York state products in Mexico, a beauty and esthetics studio in Hannibal and a hardware and farm supply store in Sandy Creek. In Onondaga County, the Liverpool area has also enjoyed a steady stream of new shops and eateries in recent years. That suburban community is unique in that, unlike neighboring communities, most of the restaurants are family-owned and not part of a national chain. [caption id=attachment_11116 align=alignright width=300] Megan Wilmot is the executive director of the Greater Liverpool’s Chamber of Commerce.[/caption] Megan Wilmot, executive director of the Greater Liverpool Chamber of Commerce, said independent business owners in her community maintain a strong sense of pride in holding their own against national companies. The chamber helps boost morale with red carpet events, ribbon cuttings, coffee hours and five-year anniversary celebrations for participating businesses. “We have built such a strong community,” Wilmot said. “Everyone in this business community encourages each other to shop local. Everyone just wants to see each other succeed.” In Syracuse, the downtown retail occupancy rate last year was about 82%, a slight improvement from 2024, according to the Downtown Syracuse Committee’s most recent annual report. Buildings with the largest amount of vacant space included The Galleries, One Park Place, and Equitable Towers, though not all of those spaces are designated for retail use. New businesses that opened in downtown Syracuse last year: Better with Time Clothing, Dakshin Curry & Biriyani, Havana Tattoo Society, Milano Bean Café, Miss Daisy, Pausa Coffee, Sweets for Babe, The Society CNY and Yafah Beauty Studio. The Destiny USA mall’s occupancy rate decreased from 80% in 2023 to 72% by the end of 2024, according to Integra Realty Resources. That leaves more than a quarter of the mall’s retail space vacant. “Looking ahead, the retail market is expected to see minimal rent growth, with vacancy rates likely remaining stable in community and neighborhood centers but continuing to rise in enclosed malls,” Integra’s report said. “New construction activity is low and redevelopment plans for former malls like Shoppingtown and Great Northern are still in the planning stages. The proposed Micron chip plant may spur development, but challenges remain in finding co-developers for large-scale projects.” Nationally, the U.S. Chamber of Commerce expects that small businesses will remain resilient and see their sales and revenues eventually improve. That organization, in a recent national survey, found that 25% of small business owners expect the economy to improve in 2027, while 45% indicated that they plan to increase employment in the next 12 months. And 69% said they believe their small business is in good shape and 70% said they are comfortable with their current cash flow. Thirty-one percent of small businesses reported raising their prices in July and 28% are planning to raise their prices within the next three to four months, the report said. Twelve percent indicated that this is a good time to expand their business. “Small business owners voice optimism for future revenues and hiring,” the report said. “High costs continue to be a wet blanket on reinvestment.” The NFIB reported in July that Main Street, despite gas price hikes, “is OK … for now.” Its small business economics trend report said sales across the country have been strong compared to last year, but continued inflation and higher prices from mom-and-pop establishments are causing some “cracks” to show. “If costs stay this high for much longer, reduced investment will have a tangible economic impact,” the report said. “The status quo is OK, but the outlook? The outlook is uncertain.”
Public Health Metrics Must Be Central to Energy Utility Policy
Public service commissions should require utilities to quantify avoided healthcare costs, reduction in pollution exposure, and improvements in population health alongside traditional metrics.
Sergei Guriev, Dean of London Business School, elected Fellow of the Econometric Society
LBS Dean joins 30 new Fellows announced for 2026
Scientists may have seen dark matter. If they did, what exactly is it?
One theory points to a long-awaited supersymmetric particle called a ‘higgsino.’ But that idea has some issues.
Henri B. Kagan and Kenso Soai win Nobel Prize in chemistry
Henri B. Kagan and Kenso Soai won the Nobel Prize in chemistry Wednesday for their discovery of non-linear effects and autocatalysis in asymmetric organic synthesis.
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Nobel prize in chemistry awarded for work on mirror-image molecules
Henri B Kagan and Kensō Soai awarded prize for discovery of nonlinear effects and autocatalysis in asymmetric organic synthesis
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Intel Panther Lake Teardown, 18A, BSPD, GAAFET, SemiAnalysis STEEL
Panther Lake debuts the first commercial implementation of backside power delivery (BSPDN), introduces Intel’s first iteration of gate-all-around (GAA) transistors, and showcases their advanced packaging capabilities with its Foveros-S assembly. With Panther Lake, Intel’s manufacturing arc has shifted from nebulous roadmaps to shipped silicon, a significant milestone on their long road back to competitive semiconductor manufacturing. To evaluate the extent of Intel’s comeback, we tore down Panther Lake. The SemiAnalysis STEEL teardown lab breaks down advanced datacenter and AI hardware. To learn more about our pipeline or to commission a teardown, contact sales@semianalysis.com. WE’RE HIRING: Architecture, floorplan, packaging, manufacturing, and labs experts. Opportunities from system to transistor and everywhere in between. Check out our Careers page. Our teardown traces 18A from its four-sheet RibbonFETs (Intel’s marketing name for GAAFETs) and gate stacks through contacts, frontside and backside wiring, and the bonded carrier. We explain how these material and integration choices improve gate control and reduce resistance, while adding capacitance, thermal resistance, and process complexity. Our measurements put Panther Lake’s 18A compute logic and TSMC N3E GPU logic at similar logic density. However, 18A does not lead TSMC N3P, N2 or Samsung SF2 in peak density. Panther Lake’s CPU cores are incremental updates, and the high-end GPU still uses TSMC N3E. Panther Lake assembles one compute tile, one GPU tile, and one I/O tile atop a passive base tile using Intel’s Foveros-S advanced packaging. Both compute tile variants use Intel 18A. The Xe3 GPU options are a 4-core GT1 tile on Intel 3 and a larger 12-core GT2 tile on TSMC N3E. Both I/O tile variants use TSMC N6. [1], [2] Our analysis centers on the PTL-U compute tile, both the 4-core and 12-core GPU tiles, as well as the 12-lane I/O tile. In conventional chips, power and signal are routed through the same frontside metal stack towards the device frontend. Power rails consume scarce routing resources near the transistors, while tall via stacks carry VDD and VSS from the coarse upper wires to local rails. Backside power delivery (BSPD) moves the main power network behind the transistor layer, to the backside, separating it from frontside signal routing. We covered BSPD and its impacts in 2024. [3], [4], [5] Intel’s BSPD implementation, branded as “PowerVia”, routes power through dedicated backside metals to nano-TSVs, which connect those rails to local source/drain (S/D) contacts. Implementing that separation requires Intel to build the interconnect stacks from both sides of the wafer. The frontside comprises the M0-M14 signal stack, while the backside comprises the BM0-BM5 power stack. M0 and BM0 are closest to the transistors. The nano-TSVs connect the two sides, but Intel patterns and etches each via from the front after forming the contacts. A narrow via runs from the side of the contact deep into the silicon substrate. Intel then completes the frontside signal metal stack, bonds the wafer to a carrier, flips it and removes the original substrate until the buried via tips are exposed. The backside metal stack is then deposited directly on the revealed vias. The nano-TSV and backside-via profiles taper in opposite directions because Intel forms them from opposite sides of the wafer. The transistor structures form the FEOL. Local contacts and nano-TSVs connect them to the wiring. M0 begins the frontside interconnect stack. The silicon carrier remains attached above the frontside interconnects. It supports the device wafer during substrate removal and backside processing and remains part of the finished chip’s thermal path. PowerVia removes the main power distribution from the congested frontside metals, routing supply through shorter and wider backside wires. Its lateral landing still occupies area in the standard cell, so it recovers less cell area than a direct backside contact. [3] Nano-TSVs beside the logic devices carry VDD or VSS from the backside power network, while signal connections continue upward through the frontside metals. Backside Interconnects Samsung SF2 data is included for comparison to Panther Lake’s within this article. SF2 is the incumbent GAA foundry node but lacks BSPD, serving as a useful reference to evaluate 18A. A full teardown of Samsung’s S26 products, processed on SF2, will be shared soon.Nanosheet-cut EDS comparison. The PowerVia supply path runs from the backside Cu rails through Mo-lined W nano-TSVs to the local transistor contacts. In this cross section, the tapered connection spans roughly 150 nm from the contact level to BM0. The Ta liner confines Cu and promotes adhesion to the surrounding stack; the AlOₓ etch stop controls the next dielectric etch above the rail. Dielectric beneath the ribbons electrically separates the devices from the backside wiring and removes the conducting silicon body below the channel. [6] AlOₓ serves as an etchstop (ES), enabling endpointing and protecting the underlying layers. Low-volatility aluminum fluoride reaction products resist the fluorinated plasma, allowing a thin AlOₓ film to protect the metal while the surrounding low-k dielectric is removed. [6], [7]. While the BM0 and layers above the M1 lines show double AlOx layers, Our SMIC N+3 teardown showed single AlOₓ layers. SMIC uses a simpler local AlOₓ substack, while the remaining cap and etch sequence provide the required landing protection. So why double layers? The closely spaced AlOₓ doublets provide two protected endpoints in the etch sequence. Intel documents an AlOₓ/SiN/AlOₓ stack that explains the benefit. The main dielectric plasma etch stops on the first AlOₓ film; a selective wet clear opens that film; a second plasma etch removes the intermediate SiN and stops on the second AlOₓ film. The final wet clear exposes the metal landing surface. SiN is the intermediate dielectric in Intel’s published example. [8] The second stop protects the metal through a cap breakthrough. Wide openings can etch faster than narrow ones, and etch depth varies across the wafer. Metal under an early-clearing opening would otherwise be exposed while other openings still need more etching. Staged protection widens the process window and reduces metal erosion, corrosion and void formation. [8] TSMC documents AlN/AlOₓ/SiOC/AlOₓ above Cu, with AlN blocking Cu diffusion, and a simpler AlN/SiOC/AlOₓ variant that omits one AlOx film. [9] Levels with different opening sizes, aspect ratios, pattern densities and cap materials need different etch margins. A double AlOx stop is useful where another protected endpoint justifies the added processing. The extra film adds formation, selective opening and cleaning steps, plus another set of interfaces to control adhesion, moisture, and stress. These blanket films are opened through the existing via pattern, so each film does not require another lithography mask. AlOₓ adds parasitic capacitance when it replaces lower-k dielectric; two thin AlOₓ films can nevertheless contain less AlOₓ than one thick film. Total thickness, placement, and theintermediate dielectric determine the electrical cost. Deposition chemistry also changes AlOx permittivity and residual hydroxyl content, which can oxidize the underlying metal. [7], [8], [10], [11] The backside stack separates into relatively fine BM0-BM2 wiring near the devices and coarser BM3-BM5 power distribution. The largest pitch increase occurs between BM2 and BM3. BM0’s pitch closely matches the logic-row height, fitting local power delivery to the cell rows. Higher levels aggregate current through larger conductors: routing density becomes less important than low resistance and current capacity as the network approaches the package. This hierarchy provides wide power wiring for the power delivery network without consuming scarce frontside signal-routing resources. [3] The SemiAnalysis STEEL teardown lab breaks down advanced datacenter and AI hardware. To learn more about our pipeline or to commission a teardown, contact sales@semianalysis.com. WE’RE HIRING: Architecture, floorplan, packaging, manufacturing, and labs experts. Opportunities from system to transistor and everywhere in between. Check out our Careers page. Frontside Interconnects Intel 18A combines Mo-lined W contacts and nano-TSVs with a separate backside Cu power network. Samsung SF2 keeps power on the frontside, using Ti-based contact interfaces and Ta-based barriers and Co liners around Cu wiring. In 18A standard-cell rows, backside power rails supply the devices through nano-TSVs within the cells, freeing frontside routing resources. Samsung’s M0 accommodates both power and signal connections. From the device toward M0, the connection runs through a Ti-based S/D interface, W contact fill, a Mo-lined W via, and the Cu M0 wire. Mo supplies a conductive nucleation and adhesion layer for W, replacing the resistive TiN liner used in conventional W integration. This increases the effective conduction volume within the feature while retaining W fill and its established polishing, cleaning and etching processes. Intel’s Mo/W patent describes this integration tradeoff. The nano-TSV uses the same Mo-lined W construction in the backside supply path. [12] The move from TiN to Mo is an incremental change. While a full Co or Mo fill can also reduce the volume lost to liners in very small features, it requires new integration schemes that increase complexity and risk. Cu remains attractive for wider wires due to its low resistance. As wires and vias shrink, the diffusion barrier consumes an increasing fraction of their cross-section. [12], [12], [14] Intel uses Co/Ru liners at M0-M1, Co at M2-M4, and Nb at M5-M9. The lower-level liners help Cu adhere and reduce void formation during trench fills. Applied Materials’ Endura has new thermal control that facilitate wetting process, so the thin film continuity is good enough that good capillary pressure will drive Cu atoms to the via bottom without voiding. Intel’s choice to use Nb is particularly interesting. Intel’s Nb patent describes a conductive diffusion barrier intended to reduce the barrier’s contribution to resistance relative to conventional Ta-based barriers, particularly at via bottoms where all current crosses the barrier. The patent pairs Nb in coarser levels with the option of lower-cost PVD processing. [15], [16] The upper metal layers support thicker barriers formed through physical vapor deposition (PVD) despite its worse coverage and uniformity. Meanwhile, the lower metal layers require thinner barriers deposited through conformal atomic layer deposition (ALD). Co/Ru adds another material interface and requires controlled deposition and Cu fill. Changing liners and barriers by metal layer allows Intel to optimize interconnect resistance, process complexity, and reliability. [15, 16] RibbonFET, Intel’s name for its gate-all-around FETs (GAAFETs), replaces the FinFET’s vertical fins with four stacked horizontal silicon nanosheets, allowing the gate to surround the channel on every side. The path to GAAFET begins with the planar transistor. A planar MOSFET places the gate above the channel between its source and drain. Pairing an NMOS with a PMOS transistor creates a CMOS inverter, in which the NMOS pulls the output low for a high input, and the PMOS pulls it high for a low input. The gate must retain electrostatic control of the channel to ensure clean switching. As gate lengths shrank, the drain began to compete with the gate for that control, increasing off-state leakage. Electrostatic control was restored through an architectural evolution that raised the channel into a vertical fin and wrapping the gate around three sides. Called “FinFET”, this new architecture packed more effective channel width into a smaller footprint. Further scaling made it harder to maintain both drive current and leakage within smaller cells, and reintroduced the same problems planar MOSFETs faced. Nanosheet GAAFETs close the fourth side by replacing the vertical fin with a stack of horizontal nanosheets, each surrounded by the gate. The tighter electrostatic control suppresses leakage at shorter gate lengths while stacking adds effective channel width within the cell footprint. In a FinFET process, channel width changes in discrete steps as designers must add or remove whole fins. Nanosheet width can instead be adjusted continuously within the process’s design rules. Wider sheets increase drive current, while narrower sheets reduce capacitance at the cost of drive current. Intel 18A uses stacks of four nanosheets each and varies their widths across logic and SRAM. At the process level, adding more sheets to each stack increases effective channel width and drive current, but complicates fabrication. RibbonFET vs MBCFET Samsung began GAAFET production in 2022 with SF3E, following with SF3 and now SF2. Its ‘MBCFET’ provides a useful structural comparison with Intel’s first RibbonFET implementation. [17] STEEL is digging deeper into SF2, used in the Exynos 2600, and TSMC’s GAAFET N2, used in Apple’s A20 Pro, in upcoming newsletter articles. We’re throwing some teasers on X. Let’s compare Samsung SF2’s MBCFET with Intel 18A’s RibbonFET. Subscribe Even to the untrained eye, Intel’s extra nanosheet is obvious. Intel stacks four ribbons to Samsung’s three. Samsung’s sheets are much wider in these fields, so both sheet count and width matter to the available channel perimeter. Sheet width also changes which silicon surfaces carry current. On conventional (001) silicon, wide nanosheets emphasize the broad top and bottom surfaces, favoring electron transport; the larger sidewall contribution in a narrow sheet favors hole transport. Thinner sheets improve gate control but increase confinement and scattering. This makes width and thickness part of the NMOS/PMOS balance, alongside strain and threshold voltage. [18], [19] GAAFET designs like 18A use different work-function-metal (WFM) stacks for NMOS and PMOS. Around each ribbon, a thin SiOx interfacial layer separates the silicon channel from the HfOx high-k dielectric, with La providing dipole tuning and the WFM wrapping the dielectric. NMOS uses a TiAl-based stack, while PMOS uses TiN WFM. W fills the remaining gate trench, providing a lower-resistivity path where the work-function layers are no longer needed. In this field, the PMOS stacks leave room for W between ribbons, while the NMOS stacks occupy more of those gaps. A silicon-based dielectric marks the P/N boundary, allowing the PMOS and NMOS gates, sharing the same gate trench, to be processed sequentially. Fast logic paths, retention circuits, and SRAM need a family of threshold options. Changing threshold without substantially changing device dimensions, capacitance or fabrication complexity is valuable. FinFET processes typically use different work-function-metal stacks. In a four-ribbon GAA stack, the narrow sheet-to-sheet gap limits how much WFM can fit around each channel. La in the gate dielectric creates interfacial dipoles at the SiOx/HfOx boundary, shifting effective work function and tuning threshold voltage. This gives Intel another control alongside its NMOS and PMOS WFM stacks. Low-threshold devices improve critical-path drive; higher thresholds reduce leakage elsewhere. Dipole tuning is especially useful in GAA because it changes threshold without consuming the narrow intersheet gap with thicker WFM. Precise control of La incorporation, diffusion and interface quality has long been a challenge, limiting viability in high volume production but is now seen from every leading-edge foundry. Intel’s patent describes depositing a dipole-forming oxide above HfOx and annealing it toward the interfacial oxide before completing the work-function and fill metals. This separates threshold tuning from the space available for metal. Newer research addresses the thermal cost: imec’s 2026 dipole-middle research inserts the shifter between two HfOx depositions, shortening the diffusion path while protecting SiOx during patterning. [20], [21]Matched-cut EDS, Intel 18A (left) vs. Samsung SF2 (right). Intel retains raised source/drain epi beneath its contacts, while Samsung recesses W deep into the epi to form a V-shaped Ti-lined interface. The deeper contact increases metal-to-semiconductor area and shortens the current path from the lower sheets, reducing contact and spreading resistance. It also removes epi volume and brings the contact etch closer to the channel ends. Retaining more epi preserves the material available for strain transfer, especially from SiGe into PMOS. These geometries balance contact access against stress engineering and etch margin. [22], [23] Samsung stacks three sheets to Intel’s four ribbons, and both processes use sheet width to tune drive strength. In our Samsung cross-sections, widths range roughly from 19 to 30 nm in the NPU rows and 37 to 50 nm in the CU cell. The Samsung nanosheets taper, with the widest sheet at the bottom and the narrowest at the top. Both processes use HfOx gate dielectric and Ti-based work-function stacks, with Al in the NMOS stack. In the Samsung devices shown here, the dielectric and WFM occupy the intersheet gaps, leaving W above the top sheet. Intel’s PMOS stack leaves more room between ribbons, and W fills those gaps while the thicker NMOS stack leaves W mainly in the upper trench. Gate-stack EDS maps. The W between Intel’s PMOS ribbons provides a conductive path close to the lower gates. Where WFM fills the entire gap, the gate still surrounds the channel, but voltage reaches it through the more resistive work-function films. Thinner WFM and dipole tuning preserve room for low-resistivity fill; Mo and Ru are alternative fill metals being developed for further scaling. [24] A masked, sequential WFM flow explains the different gate heights and inter-nanosheet fill. The proposed sequence below shows how separate NMOS and PMOS work-function steps produce that geometry. Enabled by the BSPDN process, Intel replaces the dense-logic silicon subfin with dielectric, removing the parasitic conduction path below the ribbons and reducing substrate-related capacitance. A retained silicon body as in classical, non-SOI, planar and FinFET designs needs junction and punchthrough-stop engineering to suppress leakage. Dielectric isolation makes that leakage less sensitive to the subfin doping profile but adds removal and fill steps. It also weakens the direct thermal path through silicon, making the contacts, metal stacks and package more important for heat extraction. [24], [26] Fluorine is concentrated around selected Intel device structures in the maps. WF6 is a standard precursor for W nucleation and fill, while barrier films protect adjacent dielectrics from fluorine attack. Low-fluorine W processes reduce the residual-F burden. Chloride-based precursors avoid introducing F during W deposition, but require control of chlorine attack, nucleation and fill quality. The integration target is a continuous, low-resistance W path with a thin protective liner and minimal chemical damage to the surrounding stack. [20], [27], [28] The SemiAnalysis STEEL teardown lab breaks down advanced datacenter and AI hardware. To learn more about our pipeline or to commission a teardown, contact sales@semianalysis.com. WE’RE HIRING: Architecture, floorplan, packaging, manufacturing, and labs experts. Opportunities from system to transistor and everywhere in between. Check out our Careers page. We measured cell height, gate pitch, metal geometry, and ribbon dimensions at the XTEM sites shown below. The tables group these dimensions by site and device polarity. Our “sheet cuts” cross the silicon channel and show the ribbons end-on. “gate cuts” run along the channel through successive gates. The 18A logic cell dimensions point to a five-track logic library while the N3E and Intel 3 cell dimensions evidence a seven-track logic library. The DDR-PHY uses wider M0 wires and much larger spacing than core logic. That trades routing density for lower wire resistance and weaker coupling between neighboring nets. The geometry suits the current delivery and coupling requirements of analog, clock, and I/O circuitry. PowerVia lets 18A combine a compact cell height with wider M0 geometry by moving the main power rails off the signal-routing tracks. That relaxes local wire scaling while preserving a small cell footprint. Cell height and gate pitch set the geometric density; pin access and routability determine how much of it a real block can use. [29] The biggest takeaway from our gate-pitch measurements is that Intel 18A compute logic and TSMC N3E GPU logic have similar density in the Bohr representative-cell model. The 18A example is 18.6% denser than the Intel 3 GPU example. Gate pitches are nearly identical across the three sites, so cell height drives most of the difference. The Bohr model combines a four-transistor NAND2 spanning three gate pitches and a 32-transistor scan flip-flop (SFF) spanning nineteen pitches, weighting their densities 60:40. The sensitivity column shows how independently changing cell height and gate pitch by ±1 nm changes the result. This compares representative cell geometries; whole-die density also depends on cell mix and placement. The 18A P-core gives M0 substantially more metal cross section than the N3E vector engine. Treating each profile as a trapezoid gives 2.63 times the area per line and 1.84 times the area after normalization by routing pitch. The larger section reduces the geometric contribution to line resistance and lowers current density for a given current. Taller and wider wires also add capacitance, so circuit delay depends on the balance of resistance and capacitance. The DDR-PHY has less metal area per routing width than the 18A core fields, while remaining above N3E. [30] Area = height × (top CD + bottom CD) / 2, including liners. Area/pitch normalizes by routing width. Taper is the symmetric sidewall angle from vertical, with the largest angle belonging to the DDR-PHY. Compute tile The measurements show how ribbon dimensions and gate-stack geometry vary across the compute tile and between NMOS and PMOS to balance channel drive, gate load and the space needed for the dielectric/WFM stack across logic, SRAM and the DDR-PHY. Width mainly changes available channel perimeter; thickness also changes electrostatic control and carrier confinement. Gate-stack thickness then determines the space left for low-resistivity fill P-core and LP E-core logic Both the P-core and LP E-core use multiple nanosheet widths. Widths are measured on high-magnification XTEMs while wider-field images demonstrate additional width choices within the LP E-core. Multiple widths are expected even within an LP E-core. Timing-critical paths, buffers and cells with different fanout need different drive strengths. The lower-magnification fields show this width diversity beyond the sites quantified in the table. L2 and L3 SRAM GAA gives SRAM designers another way to balance the pull-up (PU), pass-gate (PG), and pull-down (PD) transistors. FinFET bitcells set device strength through fin count while GAA adds nanosheet width as a sizing knob. In a 6T SRAM cell, a strong pull-down relative to the pass-gate limits read disturbance, while a strong pass-gate relative to the pull-up improves writability. During a write, the pass-gate and write driver pull the node storing “1” below the inverter trip point. During a read, the pull-down holds the node storing “0” low. Bias, threshold voltage, mismatch and assist circuitry set the remaining margin. FinFET high-current cells commonly use a PU:PG:PD fin-count pattern of 1:2:2, a device-sizing ratio rather than a current ratio. Ribbon width lets Intel balance SRAM strengths without adding whole fins. The L2 cell uses its narrowest ribbons for PU and widest for PD, improving writability and read stability respectively. Intel’s disclosed HCC operates without assist; its denser HDC uses negative-bitline write assist. Pulling the selected bitline briefly below ground increases pass-gate overdrive so it can overpower the pull-up at lower supply voltage. That buys density and low voltage writability at the cost of boosting circuitry, switching energy, and additional voltage stress that must be controlled. [31], [32] Four rectangular ribbons give the perimeter = 8 × (width + thickness), before corner rounding. PG/PU is 1.49 and PD/PG is 1.16. The L3 structures closely resemble L2 in layout and cell height. Fewer L3 nanosheet widths are tabulated because fewer high-magnification images were available. DDR PHY The DDR-PHY trades density for controlled analog behavior and reliable off-chip signaling. It contains drivers, receivers, delay circuits, and calibration logic that set drive strength, sampling time, and voltage margin. Repeated four-sheet devices with similar widths fit the use of regular transistor units for matching and programmable drive. Its wider local wiring provides room for current delivery and separation of sensitive signals, while consuming more area than a dense core-logic grid. The layout serves the memory channel’s electrical requirements as well as digital logic density. [33] The SemiAnalysis STEEL teardown lab breaks down advanced datacenter and AI hardware. To learn more about our pipeline or to commission a teardown, contact sales@semianalysis.com. WE’RE HIRING: Architecture, floorplan, packaging, manufacturing, and labs experts. Opportunities from system to transistor and everywhere in between. Check out our Careers page. Intel 3 GPU devices Vector engine logic Intel 3’s XVE logic uses two-fin PMOS and NMOS devices with power rails in M0. Its cell height and M0 pitch give a seven-track geometry, two tracks more than the 18A logic. One-fin groups also appear among the two-fin devices. Intel 3 L2 SRAM The Intel 3 L2 SRAM uses the familiar HCC sizing pattern: one PU fin, two PG fins, and two PD fins. N3E GPU devices Vector engine logic The N3E XVE field contains repeated two-fin devices with seven-track cell geometry. N3E remains a FinFET process, giving Panther Lake a direct FinFET-to-RibbonFET comparison. N3E L2 SRAM The N3E L2 SRAM uses the same PU:PG:PD fin-count pattern of 1:2:2. Panther Lake-U follows Lunar Lake’s floorplan quite closely. Both pair 4 P-cores with 4 LP E-cores and NPU, media and display engines in similar locations. Lunar Lake also uses Xe2, the direct predecessor to Panther Lake’s Xe3 GPU. This makes Lunar Lake the most direct basis for our comparisons. Arrow Lake differs in core count and uses the older Xe-LPG GPU architecture, so we only use it where it offers a more direct component-level comparison. Compute tile Panther Lake compute-tile floorplans remain sparse even months after launch. Intel 18A’s backside metal and dielectric stack must be removed without damaging the underlying structures before a clean transistor-level floorplan can be imaged. Most published die shots hide or heavily process the background, but we are quite proud of the die shot we achieved and are excited to show the work we have done. We measured the areas of the key components on the compute tile and compared them with their Lunar Lake predecessors on TSMC N3B. These help us to capture changes in block area and compare the two chips across process nodes and designs. Our total tile areas exclude the scribe-line area. The compute-plus-GPU subtotal below uses the PTL-U compute tile and GT1 GPU; it excludes the I/O tile and passive base. Individual block areas use the boundaries marked on the floorplans The compute-plus-GPU row is recomputed from the displayed PTL-U and GT1 areas. Component rows use their stated per-region counts and are not an additive partition of the whole tile. The P-core area remains almost unchanged between Lunar Lake and Panther Lake, despite L2 capacity increasing from 2.5 MiB to 3 MiB. Arrow Lake uses the same Lion Cove core as Lunar Lake but also has a 3 MiB L2. Cougar Cove fits 20% more L2 into the same P-core area. The larger private cache keeps more of each core’s working set close to its execution units, reducing access to shared L3 and DRAM. Extra capacity adds storage leakage and lookup energy, so designers balance it against avoided lower-level accesses. The shared P-core L3 cache also shrank by 14.8%. [2] Cougar Cove combines a similar footprint with Intel’s reported power-efficiency improvements. RibbonFET’s tighter channel control reduces leakage, while PowerVia reduces supply droop and allows tighter voltage guardbands. [1] Darkmont’s four-core LP E-core cluster is 5.0% smaller than Skymont’s on Lunar Lake, with most of the reduction in its L2 regions. The 1 MiB region shrank by 8.4% and the 1.5 MiB region by 14.9%. The tag arrays also use one fewer visible row. Tags identify which memory addresses the data array holds, so rearranging them changes the cache’s layout and wiring without requiring less data capacity. [2] The LP E-cores share one L2. This pools capacity and avoids duplicating all the cache machinery, but the four cores contend for its banks and bandwidth. Their separate cluster also keeps light work away from the performance cluster and its L3, allowing that larger domain to sleep. [1], [2] Cache area includes more than the storage cells. Tags identify each line, decoders select rows, sense amplifiers read the small bitline signal, and wires connect to the banks. Splitting an array into smaller sections shortens wordlines and bitlines, improving access speed, but duplicates peripheral circuits. Panther Lake’s smaller cache regions therefore reflect the complete memory implementation, including how much of each region is devoted to storage. [34] Unlike Meteor Lake and Arrow Lake, Panther Lake has no separate SoC tile. The NPU, LP E-cores, memory controllers, PHYs, media and display engines now share the compute tile. This removes an active die and keeps CPU memory traffic on one die. The cost is moving PHY and I/O-related circuitry onto 18A: drivers, receivers and analog circuits must still meet external voltage, loading and signal-integrity requirements, so their area does not shrink like dense digital logic. [1], [2] The biggest shrink comes from the NPU, which occupies 36.9% less area. NPU 5 consolidates the same total INT8 MAC count into half as many neural compute engines. Each of the three NCEs has a larger MAC array to make the complete NCE envelope 22.6% larger than an NPU 4 engine. Consolidation also halves the number of scratchpads and SHAVE DSPs, from 12 to 6. The MAC array handles matrix multiplication and convolution, while SHAVE executes vector and custom operations that fit the array poorly. [1], [2], [35] The paired floorplans identify each NCE envelope and its scratchpad, MAC, and SHAVE regions. Each measured MAC polygon is counted once per NCE in the area accounting below. The scratchpads store weights, activations, and intermediate results near the MAC arrays, allowing repeated use without fetching them again from DRAM. Halving their number delivers the largest measured area saving but leaves less local storage for the same total MAC count. Layers that no longer fit locally require smaller working tiles or more transfers of intermediate data. The benefit depends on keeping the enlarged arrays busy while managing that tighter storage budget. [36] NPU 5 also adds native FP8. Using half the operand width of FP16 reduces storage and transfer demand, helping workloads fit the smaller local memory budget. Lower precision and format-dependent range make scaling and model validation part of deployment. Hardware activation functions further reduce work that would otherwise occupy the programmable DSPs. [1], [2] Microsoft requires an NPU to deliver at least 40 TOPS for Copilot+ PCs. Both Lunar Lake and Panther Lake meet this threshold, but Panther Lake uses significantly less silicon. GPU tiles Panther Lake is Intel’s first product with Xe3, its latest GPU architecture. It offers two different GPU tiles: a smaller GT1 tile with 4 Xe3 cores on Intel 3 and a larger GT2 tile with 12 Xe3 cores on TSMC N3E. Panther Lake allows us to compare the same GPU architecture across both Intel 3 and TSMC N3E. Wildcat Lake adds a third Xe3 implementation on Intel 18A. A future newsletter will detail Xe3 and its implementation differences across all three process nodes. GT2 scales Xe3 to a different physical layout, with render slices arranged vertically instead of GT1’s horizontal arrangement. Slice placement sets the distances to shared cache banks and the D2D interface. Those wires consume area and add delay, so scaling the number of Xe cores also requires a new balance of cache placement, routing and timing. [1] What’s immediately obvious is that the GT2 tile on TSMC N3E has much smaller Xe cores than GT1. These block areas include logic, caches, and routing. An Xe core on the GT1 tile is ~69% larger than one on Lunar Lake, and ~55% larger than one on GT2. Intel 3 therefore uses substantially more area per Xe core. The block-area gap exceeds the measured logic and SRAM density gaps, bringing routing, timing targets, cell mix, and floorplan allocation into the comparison. The measured vector/matrix engine region is almost unchanged between Lunar Lake and Panther Lake’s GT2 tile. Xe3 retains eight 512-bit vector engines and eight 2048-bit XMX engines per core. Its gains also come from feeding those engines more effectively: more resident threads hide stalls, and variable register allocation lets shaders trade registers per thread against the number of threads kept active. [1] The shared L1/SLM capacity increased by 33% from 192 KiB to 256 KiB, while its area increased only 5%, raising effective density by 27%. L1 retains reused cache lines, while software-managed SLM lets a thread group share data locally. Both reduce traffic to more distant memory. Allocating more SLM per group can also limit how many groups reside on a core at once. [1], [37] The GT1 tile carries 4 MiB of L2 against 16 MiB on the GT2 tile. GT1 divides its L2 cache into four 1 MiB banks, while GT2 uses eight 2 MiB banks. Each bank contains 128 macros, but each N3E macro stores 16 KiB, twice the Intel 3 macro’s 8 KiB capacity. The N3E macro is only 54% larger while holding twice as many bits, giving it 30% higher density: ~23.7 Mbit/mm² versus 18.3 Mbit/mm². Including bank-level circuitry, the gap widens to ~16.9 Mbit/mm² on GT2 versus ~10.4 Mbit/mm² on GT1. GT2 gains density with its macros storing more bits per unit area, and those macros occupy more of each cache bank. Larger macros spread decoder and sense-amplifier overhead across more storage, while a more compact bank layout reduces the share spent on control and routing. The compromise is longer wordlines and bitlines that carry more capacitance. [34] I/O tile Panther Lake uses two I/O tile variants, both fabricated on TSMC N6. The smaller one provides 4 PCIe 5.0 and 8 PCIe 4.0 lanes and serves lower-tier systems as well as those without a discrete GPU, while the larger one adds 8 PCIe 5.0 lanes, bringing the total to 20 lanes, for discrete-GPU connectivity. Panther Lake SKUs with the larger 10- or 12-Xe GPUs use the smaller I/O tile. [38] The smaller I/O tile adds a PCIe 4.0 block and a Thunderbolt block to Lunar Lake’s I/O layout, providing four additional PCIe 4.0 lanes and another Thunderbolt 4 port. Its repeated N6 blocks retain nearly identical areas and layouts. Reusing these proven PHYs and controllers avoids porting and requalifying external interfaces on 18A, where faster digital logic offers less benefit to circuits constrained by the off-chip link. [38] SemiAnalysis’s teardown lab (STEEL) dives deep into the world’s advanced datacenter and AI hardware. To learn more about our pipeline or to commission a teardown, contact sales@semianalysis.com. We’re hiring technical experts from system to transistor and everywhere in between. Check out our Careers page. Panther Lake offers scalability and modularity through its disaggregated packaging that partition compute, GPU, and I/O silicon into separate tiles allowing for a suite of tile configurations. This partitioning makes the package part of Intel’s node economics as it determines how much leading-edge wafer area each product consumes, which functions can remain on other processes, and how much configuration freedom Intel can offer from a shared set of tiles. Furthermore, fabricating the compute and GPU tiles separately confines the new 18A process to the compute tile and allows graphics and I/O to use other, more established, and more cost-effective processes. For Panther Lake, the GPU and I/O tiles are assembled alongside the compute tile on a passive silicon base using Foveros-S. Intel’s current technology brief lists a nominal 36 µm pitch for Foveros-S. Through-silicon vias (TSVs) in the base connect the fine wiring above to the larger package connections below. The functional tiles sit side by side on that passive base in a 2.5D configuration. [39] Our cross-section through the compute and GPU tiles shows the package’s wiring hierarchy. Microbumps connect each active tile to the passive silicon base; its fine redistribution layer (RDL) carries the short, dense tile-to-tile links. TSVs carry connections through the base to the package substrate, which fans them out to the much coarser motherboard solder joints. The base supplies interconnect, while computation remains in the active tiles above it. [39] At the compute-tile edge, the higher-magnification inset shows a local microbump spacing of approximately 25.24 µm and a feature width of 12.33 µm. These local spacings are finer than Intel’s nominal Foveros-S value. The X-ray fields further confirm tighter neighboring bumps, consistent across every die-to-die area found on each tile. Additional X-ray analysis is offered after the paywall. Putting the memory controller beside the CPU removes the D2D transfer that CPU memory requests required in Meteor Lake and Arrow Lake. This avoids the extra transmitter, receiver, and link traversal, saving interface energy and latency. Panther Lake’s separate GPU still crosses a D2D link to reach DRAM, so its larger local caches also help contain package traffic. [1], [40] Smaller dies are less likely to contain a random fatal defect, and screening them before assembly prevents one bad tile from consuming a complete package of good silicon. Reuse also spreads design and qualification work across more products. Against those gains, Intel pays for the passive base, D2D circuits, extra bonding and test steps, and losses during assembly. Cost per working product across the portfolio captures the combined effect of wafer yield, reuse, test, and assembly. [29] Wildcat Lake packaging Intel launched Core Series 3, formerly Wildcat Lake, on 16 April 2026 for value mobile and edge systems. Wildcat Lake keeps 18A but removes the passive base and combines more functions on one die to simplify the package. The two products therefore reveal two distinct ways to commercialize the same leading-edge process. [41] Wildcat Lake’s 18A die combines up to two Cougar Cove P-cores, four Darkmont LP E-cores, two Xe3 cores and a smaller NPU. A separate platform-controller die supplies I/O, connected through UCIe, Intel’s first processor implementation of the standard. Consolidating graphics remove a tile boundary and the passive base, reducing assembly complexity for a modest-bandwidth value product. It also ties CPU and graphics scaling to the same die, giving up Panther Lake’s ability to swap in a much larger GPU. [42], [43] In July 2021, Intel CEO Pat Gelsinger set out an ambitious process roadmap aimed at regaining performance leadership by 2025, later described as five nodes in four years. Five years and one CEO later, Intel’s comeback story is not as unambiguously positive as Pat may have hoped. [44], [45] Intel once set the pace for process technology, bringing high-k metal gate technology and FinFETs into volume production years ahead of the rest of the industry. Its 22 nm FinFET process reached consumers with Ivy Bridge in 2012. [46] Intel’s integrated device manufacturing (IDM) model allowed its architects and process engineers to co-optimize products and processes. Starting with Sandy Bridge, Intel dominated x86, while AMD struggled with Bulldozer. That lead faltered at 14 nm and broke at 10 nm. Intel targeted a massive 2.7× density increase, but the node arrived years late and required several revisions before it could support Intel’s full lineup. This delay forced Intel to stretch 14 nm across six generations, while TSMC moved ahead in process technology and AMD recovered in x86. By 2019, Intel was still shipping 14 nm across most of its product stack, with its 10 nm client ramp focused on Ice Lake mobile processors. Meanwhile, TSMC was shipping N7 and N7+, and AMD’s Zen 2 compute chiplets used N7 to raise core counts and improve efficiency. Intel’s process failures were central to its decline, but unsound business decisions furthered their downward slide. Product delays compounded product mistakes, pushing client, server, and FPGA roadmaps off schedule. Several attempts to enter AI (Nervana and Gaudi) and networking (Tofino) also failed to establish lasting businesses. Intel’s recovery has focused on consumer CPUs and advanced packaging. Tiger Lake, Alder Lake, Lunar Lake and now Panther Lake have restored Intel’s consumer roadmap. On the process side, Intel 4 shipped with Meteor Lake, Intel 3 with Granite Rapids and Sierra Forest, and Intel 18A with Panther Lake. Intel has also made advanced packaging part of its foundry offering. However, Intel is still playing catch-up in servers. Several Xeon generations arrived years late and trailed contemporary AMD and Arm server CPUs in performance, efficiency, and core count. The process roadmap is back, but Intel does not hold the same process-technology leadership position it held prior to 10 nm. The introduction of gate-all-around nanosheets and backside power delivery are two of the biggest changes to transistor integration in a decade. Intel took on both changes at once: 18A paired its first RibbonFET with PowerVia in Panther Lake. Panther Lake is a substantial manufacturing milestone. Our cross-sections show how RibbonFET and PowerVia reshape local contacts and wiring, while the floorplans show where architectural consolidation and process choices save area. A sustained competitive lead depends on product performance, cost, yield, and the next implementation. The SemiAnalysis STEEL teardown lab breaks down advanced datacenter and AI hardware. To learn more about our pipeline or to commission a teardown, contact sales@semianalysis.com. WE’RE HIRING: Architecture, floorplan, packaging, manufacturing, and labs experts. Opportunities from system to transistor and everywhere in between. Check out our Careers page.. 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(Feature Impact) Driven by rising rates of obesity, diabetes, high blood pressure and other risk factors, cardiovascular disease has surpassed cancer as the leading cause of death among Hispanic adults in the United States. googletag.cmd.push(function() { googletag.display('fixed-big-ad-top-asset'); }); Hispanic people represent nearly 1 in 5 of the U.S. population and are the nation’s largest ethnic minority group, yet many continue to face barriers to achieving heart health and accessing high-quality healthcare. A new scientific statement published in the American Heart Association’s flagship journal, “Circulation,” revealed how social, economic, cultural and environmental factors contribute to persistent disparities in cardiovascular health, calling for culturally tailored prevention strategies, equitable access to care and greater representation of Hispanic populations in cardiovascular research.“Hispanic populations in the U.S. are incredibly diverse even within their own communities with differences in genetic ancestry, language, cultural traditions and social experiences that can significantly influence cardiovascular health,” said Johanna Contreras, M.D., M.Sc., FAHA, director of the Division of Heart Failure and medical director of the Hispanic Heart Center within the Mount Sinai Health System. “Yet Hispanic people remain underrepresented overall in the research that guides prevention and treatment strategies… Without better representation and more detailed data, we risk overlooking important differences that can help us improve care and save lives.”Hispanic Cardiovascular Health by the NumbersCardiovascular risk factors – obesity (nearly 46%), type 2 diabetes (15.5%) and high blood pressure (approximately 44%) – are prevalent among Hispanic adults and often emerge at younger ages and occur more frequently among Hispanic adults compared with white adults.According to the report, only about 1 in 5 Hispanic adults achieves ideal cardiovascular health as defined by the American Heart Association’s original Life’s Simple 7 metrics. Updated analyses using the Life’s Essential 8 framework demonstrated persistent disparities for heart and brain health, as well as suboptimal dietary quality, sleep patterns and levels of physical activity.Social and Economic Barriers MatterBiology alone does not explain cardiovascular health disparities. The environments where people live, work and age, along with social and economic challenges, impact heart health. In fact, approximately 17% of Hispanics live below the federal poverty threshold, compared with 8.2% of white adults. googletag.cmd.push(function() { googletag.display('fixed-big-ad-middle-asset'); }); “Many Hispanic adults face obstacles that extend far beyond the doctor’s office,” Contreras said. “Limited health insurance coverage, language differences, food insecurity, environmental exposures and concerns related to immigration status can make it more difficult to prevent disease, manage chronic conditions and receive timely treatment.”Contreras emphasized the cultural values and practices of Hispanic people also influence how they perceive their health and healthcare options.“Family plays a central role in many Hispanic communities and can be an extraordinary source of strength, support and resilience,” Contreras said. “At the same time, family members are often called upon to translate medical information, navigate health systems and help make healthcare decisions for loved ones. Those responsibilities can shape how health information is understood and acted upon.”An Action Plan for Improving Hispanic HealthThere are practical opportunities to achieve equitable cardiovascular health and reduce disparities through community engagement, culturally responsive care, inclusive research and policies that address the underlying drivers of health.“Reducing cardiovascular disease among Hispanic populations demands action at every level,” Contreras said, “from improving access to culturally responsive care and expanding research participation to addressing the social and environmental conditions that shape health.”By addressing both medical risk factors and the social conditions that shape health, experts believe there is an important opportunity to reduce disparities and help more people live longer, healthier lives. Learn more at Heart.org.Photo courtesy of Shutterstock googletag.cmd.push(function() { googletag.display('fixed-big-ad-bottom-asset'); });
Inconsistency Of EV Battery Pack Performance Remains A Challenge
Electric cars are currently limited in utility, which means continued government subsidies and high cost, because battery technology has not changed in the last 35 years.
Garmin Approach S72 connects golf performance with health tracking
Starting at $799.99, the S72 pairs swing metrics and green-reading tools with sleep, stress and heart-rate tracking for health-minded golfers.
Sydney Sweeney's controversial ad may work for prediction app Novig
Peak Metrics found the Sydney Sweeney ad campaign for Novig had generated more positive than negative posts online.
Koning Health secures Australian TGA approval for breast CT system
The platform is designed to provide volumetric images to assist clinicians in evaluating breast tissue.
Culturally Relevant Cardiovascular Disease Prevention and Care Strategies
(Feature Impact) Driven by rising rates of obesity, diabetes, high blood pressure and other risk factors, cardiovascular disease has surpassed cancer as the leading cause of death among Hispanic adults in the United States.Hispanic people represent nearly 1 in 5 of the U.S. population and are the nation’s largest ethnic minority group, yet many continue to face barriers to achieving heart health and accessing high-quality healthcare. A new scientific statement published in the American Heart Association’s flagship journal, “Circulation,” revealed how social, economic, cultural and environmental factors contribute to persistent disparities in cardiovascular health, calling for culturally tailored prevention strategies, equitable access to care and greater representation of Hispanic populations in cardiovascular research.“Hispanic populations in the U.S. are incredibly diverse even within their own communities with differences in genetic ancestry, language, cultural traditions and social experiences that can significantly influence cardiovascular health,” said Johanna Contreras, M.D., M.Sc., FAHA, director of the Division of Heart Failure and medical director of the Hispanic Heart Center within the Mount Sinai Health System. “Yet Hispanic people remain underrepresented overall in the research that guides prevention and treatment strategies… Without better representation and more detailed data, we risk overlooking important differences that can help us improve care and save lives.”Hispanic Cardiovascular Health by the NumbersCardiovascular risk factors – obesity (nearly 46%), type 2 diabetes (15.5%) and high blood pressure (approximately 44%) – are prevalent among Hispanic adults and often emerge at younger ages and occur more frequently among Hispanic adults compared with white adults.According to the report, only about 1 in 5 Hispanic adults achieves ideal cardiovascular health as defined by the American Heart Association’s original Life’s Simple 7 metrics. Updated analyses using the Life’s Essential 8 framework demonstrated persistent disparities for heart and brain health, as well as suboptimal dietary quality, sleep patterns and levels of physical activity.Social and Economic Barriers MatterBiology alone does not explain cardiovascular health disparities. The environments where people live, work and age, along with social and economic challenges, impact heart health. In fact, approximately 17% of Hispanics live below the federal poverty threshold, compared with 8.2% of white adults.#placement_976606_0_i{width:100%;max-width:550px;margin:0 auto;}var rnd = window.rnd || Math.floor(Math.random()*10e6);var pid976606 = window.pid976606 || rnd;var plc976606 = window.plc976606 || 0;var abkw = window.abkw || '';var absrc = 'https://ads.empowerlocal.co/adserve/;ID=181918;size=0x0;setID=976606;type=js;sw='+screen.width+';sh='+screen.height+';spr='+window.devicePixelRatio+';kw='+abkw+';pid='+pid976606+';place='+(plc976606++)+';rnd='+rnd+';click=CLICK_MACRO_PLACEHOLDER';var _absrc = absrc.split("type=js"); absrc = _absrc[0] + 'type=js;referrer=' + encodeURIComponent(document.location.href) + _absrc[1];document.write('');“Many Hispanic adults face obstacles that extend far beyond the doctor’s office,” Contreras said. “Limited health insurance coverage, language differences, food insecurity, environmental exposures and concerns related to immigration status can make it more difficult to prevent disease, manage chronic conditions and receive timely treatment.”Contreras emphasized the cultural values and practices of Hispanic people also influence how they perceive their health and healthcare options.“Family plays a central role in many Hispanic communities and can be an extraordinary source of strength, support and resilience,” Contreras said. “At the same time, family members are often called upon to translate medical information, navigate health systems and help make healthcare decisions for loved ones. Those responsibilities can shape how health information is understood and acted upon.”An Action Plan for Improving Hispanic HealthThere are practical opportunities to achieve equitable cardiovascular health and reduce disparities through community engagement, culturally responsive care, inclusive research and policies that address the underlying drivers of health.“Reducing cardiovascular disease among Hispanic populations demands action at every level,” Contreras said, “from improving access to culturally responsive care and expanding research participation to addressing the social and environmental conditions that shape health.”By addressing both medical risk factors and the social conditions that shape health, experts believe there is an important opportunity to reduce disparities and help more people live longer, healthier lives. Learn more at Heart.org.Photo courtesy of Shutterstock
iOS 27.2 Beta Previews New Apple Intelligence Health App
The first beta of iOS 27.2 includes Apple's redesigned Health app, giving developers a chance to try out the features ahead of launch later this year. Apple's developer notes for the feature say the Health app is being tested in this beta, but it won't be in the launch version of iOS 27.2. It will instead come later in the year. The Health app will incorporate Apple Intelligence to turn data and metrics collected by the Apple Watch into personalized guidance.
Digital Science appoints Charlesworth as strategic sales partner of Altmetric and Dimensions in China’s scholarly publishing sector
AsiaNet 201874
A resource to help hospitals build the business case for diagnostic stewardship
The Society for Healthcare Epidemiology of America (SHEA) has published a new resource describing how diagnostic stewardship can improve patient outcomes, strengthen hospital quality metrics and reduce ...
AI recommended your brand. Did it get your business right?
Marketers must evaluate the accuracy, context and destination of AI recommendations rather than relying solely on visibility metrics.
Hands-On With the Redesigned Health App in the iOS 27.2 Beta
With the iOS 27.2 beta, Apple is testing the new Health app that it previewed at its September iPhone event. The app has been entirely overhauled, with new Insights and Longevity tabs that give you more information on your health and fitness metrics. Subscribe to the MacRumors YouTube channel for more videos. The Insights tab shows your most recent health data, such as Activity Rings, heart rate, sleep score, and vitals.
Screen protector leak shows iPhone Ultra's asymmetric corners
A leaker with a decent track record has shown what is claimed to be a screen protector for the forthcoming iPhone Ultra, and it shows the device's unusual corners.
Reflections on 15 Years of the “Moneyball” movie
The 2011 movie brought sabermetrics to the mainstream, and changed baseball forever.
Several S&T researchers among top 2% cited scientists in their fields
A total of 94 current and former researchers affiliated with Missouri S&T are among the world’s top 2% most-cited scientists recognized either for their career-long impact or for their 2025 metrics, according to a Stanford University analysis of the Elsevier Data Repository....Continue Reading Several S&T researchers among top 2% cited scientists in their fields
Stop Automating Old Processes. Design New Ones Instead.
Companies are pouring money into AI but often failing to generate enterprise-wide returns because they automate individual tasks rather than redesign the workflows that produce business value. This typically results in one or more of four failures: accelerating tasks rather than value, ignoring unhappy outcomes, overlooking the end-to-end flow of work, or optimizing the wrong metric. To capture AI’s potential, managers need to make three decisions. First, determine what to redesign by identifying the outcome customers value, the constraints AI can remove, and opportunities for learning that compounds over time. Second, decide where human authority should remain, choosing among four modes—Assist, Approve, Audit, and Automate—according to the stakes and reversibility of potential errors. Third, design for the “unhappy path”: specify how the system will recognize uncertainty, escalate exceptions, stop or reverse actions, and learn from corrections. Together, these choices turn isolated AI experiments into reliable, value-producing operating processes.
Cattle ranchers say Trump's push to lower beef prices hurts farmers
On Friday, Trump said the US would allow up to 300,000 metric tons of beef to be imported with no out-of-quota tariff over the next 90 days.
Your Business Probably Has More Data Than Insight by Nathan Tayloe
Most businesses know more about themselves than they ever have. Leaders have access to financial reports, sales pipelines, customer data, employee metrics, website analytics, and dashboards for almost every part of the organization. CRMs track every stage of the sales process. Marketing platforms report results in real time. AI can analyze and summarize enormous amounts of information in seconds. Yet I've sat in plenty of meetings where all of that information is available, and some of the most important questions are still surprisingly difficult to answer. What's actually working? Why are customers choosing us? Where are we losing opportunities? What should we do differently? Having the data and understanding what it means are two very different things. More Information Doesn't Always Create More Clarity Over the past decade, businesses have invested heavily in visibility, and that's a good thing. We can understand performance with a level of detail that would have been unimaginable not long ago. But there's an unintended consequence. The easier something becomes to measure, the easier it is to assume it must be important. Website traffic goes up, so that looks positive. Leads increase, so marketing appears to be working. Sales activity climbs, so the pipeline looks healthy. Maybe. The numbers tell us what happened. Understanding why it happened, whether it matters, and what we should do next still requires judgment. Not Everything That Matters Fits on a Dashboard Consider a customer who ultimately contacts your company through Google. The data may attribute that lead to search. What it may not show is that the customer heard about you from a colleague six months earlier, saw your company mentioned in an industry publication, followed one of your employees on LinkedIn, and read several reviews before finally searching for your company. Google may have produced the click. It didn't necessarily create the decision. This happens throughout a business. Some of the things that matter most are difficult to reduce to a single metric: Why your best customers stay Why talented employees choose your company Why a prospect trusts one provider over another Why one service is gaining momentum while another isn't Why the market perceives your business the way it does Data can help answer those questions, but it needs context. Better Decisions Start With Better Questions One of the easiest traps for leaders is starting with the information in front of them rather than the decision they're trying to make. Instead of opening a dashboard and asking, "What does the data show?" it can be more useful to start with a different set of questions: What are we trying to understand? What decision are we trying to make? What would we need to know to make that decision confidently? That changes the role of data. Instead of looking at every number available and searching for meaning, you're using information to understand something specific about the business. Information Still Requires Judgment More sophisticated analytics and AI will continue to give leaders access to better information, faster. That's valuable, but I don't think it reduces the importance of experience and judgment. If anything, it increases it. Someone still has to decide which numbers deserve attention, which patterns matter, what context might be missing, and when the data isn't telling the whole story. The goal isn't to know more about your business simply because you can. It's to understand your business well enough to make better decisions. Good data can tell you what happened. Good leadership has to decide what it means. — Learn more about how we help organizations turn business, customer, and marketing insights into smarter strategies at tayloegray.com, or reach out directly at nathan@tayloegray.com.
Xiaohong Chen named the Koopmans Professor of Economics
Chen, who has made fundamental contributions to econometric methods, joined the Yale faculty in 2007.
Florida's College Football Playoff Odds Skyrocket After 3-0 Start
Surging metrics give the Gators a fighting chance in a crowded SEC. With a crucial Ole Miss showdown looming, Gainesville braces for a gauntlet that could define their season.
Digital Science appoints Charlesworth as strategic sales partner of Altmetric and Dimensions in China’s scholarly publishing sector
Digital Science has appointed Charlesworth as its strategic sales partner of Altmetric and Dimensions in China’s scholarly publishing sector. This collaboration aims to support the growing demand for research data and information across this rapidly developing market.
Peoples Could Become Rangers’ Future Setup Man for Latz
Armed with a 96-mph heater and elite contact suppression, Ben Peoples possesses the raw velocity and metrics to anchor a dominant late-inning bridge for the Texas Rangers.
How Much Of Qualcomm Stock Rides On One Business?
Phone chip revenue is the central metric to watch at Qualcomm (QCOM). Handset chips generated $5.1 billion in fiscal Q3 2026, accounting for more than half of the company's $9.9 billion in revenue. Total revenue fell 4.0% from a year earlier, and a segment that makes up more than half of sales deserves close attention.
Six Flags Entertainment plunges 14% after fatal roller coaster incident
Six Flags (FUN) stock plunges 14% to a 52-week low after a fatal coaster incident and ride closures; see key metrics, risks, and what’s next—read now.
Hiyd is a health tracker that attaches to the watch you already wear
Former Apple engineers figured out how to get a biometric sensor to attach to your watch without any magnets or adhesives.
Padres’ Potential Game 4 Starter Comes Back from Paternity List
Walker Buehler has spent the season being one of the San Diego Padres' most valuable starting pitchers. That might not be immediately apparent from the overlying statistics, but the metrics under the surface show a different picture. San Diego will be all hands on deck after dropping both games to the Milwaukee Brewers at American …
Nobel Prize for “Asymmetric Synthesis”
Every year, the first week in October, I eagerly await the announcement of the Nobel Prize in Chemistry. If Louis Pasteur were alive today, he would be thrilled with the 2026 honour being bestowed on
Alex Rodriguez completely misunderstands ‘Moneyball’ while praising Milwaukee Brewers
In 2003, “Moneyball” took MLB by storm. The book, which chronicles how the 2002 Oakland Athletics won 103 games using a data-driven approach, became the template for how baseball would be played for decades to come. Many of that Athletics team’s core “sabermetrics” tenets still drive strategy in MLB today: prioritizing on-base percentage over batting…
French, Japanese scientists share Nobel Prize in Chemistry
Henri B. Kagan and Kenso Soai won the Nobel Prize in chemistry Wednesday for their discovery of non-linear effects and autocatalysis in asymmetric organic synthesis.