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Rashod Bateman productive in Week 2
Ravens WR Rashod Bateman posts team highs in receptions and receiving yards in Week 2
Florida voters won’t see a debate between Jolly and Donalds
Is the debate dead in Florida?
Europe Makes The Science, China Makes The Batteries, But Who Builds The Future?
One in eight electric cars charging in Europe already carries a Chinese badge, while many European brands still rely on Chinese-made batteries. The challenge
[NAW] Champion Focus FNCS Cup Battle Royale : Session 1
Stay focused. Play like a champion. Compete in the Champion Focus FNCS Cup for a chance to earn Champion Focus cosmetic rewards. Put your skills to the test and keep your sights on victory. Good luck and have fun!
Massachusetts' plan to offer postpartum screening home visits sparks online debate
Massachusetts Gov. Maura Healey is investing $2.25 million to send nurses into homes of new parents, sparking a heated government overreach debate.
Email scheme stole thousands from agricultural business
A 44-year-old Decatur woman has been sentenced to 10 years in prison and probation for her role in a business email compromise scheme that stole $158,000 from an agricultural business.
David Jolly declines election debates against Byron Donalds
MIAMI, Fla. (WINK) — Former U.S. Rep. David Jolly, the Democratic nominee for Florida Governor, announced he will not debate Republican nominee Byron Donalds in the general election.Jolly released a
David Jolly declines to debate Byron Donalds in Fort Myers race
MIAMI, Fla. (WINK) — Former U.S. Rep. David Jolly, the Democratic nominee for Florida Governor, announced he will not debate Republican nominee Byron Donalds in the general election.Jolly released a
Health officials seek woman seen handling rabid bat in downtown Minneapolis on Tuesday
Chad Gilbert, New Found Glory’s Founding Guitarist, Dead at 45
Longtime member of Florida pop-punk group revealed in March that he was battling brain cancer
Huawei Pura X View hands-on reveals unusually wide smartphone
Huawei’s Pura X View pairs an unusually wide 16:9.5 OLED display with strong cameras, a 7,000 mAh battery and a design praised for comfortable typing, reading, video and gaming. However, importing the smartphone may not be ideal due to uncertain global software optimization and app compatibility.
The iPhone 18 Pro Max ships to you with a smaller battery than advertised. But it's okay
Your iPhone 18 Pro Max has a new battery feature that limits the capacity. Here's what you need to know.
Crews battle large 3-alarm fire at Rockport business, town water supply affected
Crews are battling a large three-alarm fire at a business in Rockport, Massachusetts.
Why politicians should pay more attention to the polls (reprise)
Welcome to the 231st edition of The Week in Polls (TWIP), a polling newsletter that always welcomes new readers. So please don’t keep TWIP a secret; share it with your friends and colleagues: Share The Week in Polls With all the stories swirling around Reform, JL Partners and political polling, I am finally tearing myself away from talking about the regulation of polling this week - and instead re-running a previous piece reminding us why the solution to problems with polls isn’t simply to ban or ignore them. Rather, we need them to play a vital role in making our politics - and politicians - better. This is followed by summaries of the latest national voting intention polls, seat projections from MRPs and the most recent party leader ratings. Subscribers who pay for the full edition can also read ten insights from the latest polls and analyses, including: A trio of organisations and a pair of professors have been casting their eyes over the Liberal Democrats ahead of the party’s autumn conference; What impact did the summer heatwave have on views on climate change? and Which wins out between chocolate and cheese? If you are not yet a paid subscriber, you can read all ten by starting a free trial now: Get FREE 7-day trial For more polling news as it comes in ahead of next week’s edition, you can also follow The Week in Polls on Bluesky. Picking up on my doubt last week about whether or not 35% of British train travellers have tried to order a takeaway for delivery to a railway station or carriage, thank you to reader Iain, who has been in touch to say he has done just that… in India. Another quick pair of updates, this time on the controversies around Reform and polling. Politico has a further scoop - “Farage aide caught in donor sting attended Egypt retreat with JL Partners” - and Ian Dunt has written about the problems with polling too: “Seeing the response of many polling experts in the last few weeks suggests that they are nervous about what is happening and keen to mitigate against it. Seeing the response of journalists, which has been basically non-existent, suggests the precise opposite.” My usual reminder as well: please do hit reply if you’ve spotted a poll, focus group or new piece of poll-based research that you think should be in contention for coverage in a future edition. Thank you! And with that, on with the show. How politicians get public opinion wrong I have written before about the benefits that come from widespread availability of high-quality political polling. We need more polls and more good coverage of polls. However, what I’ve not dug into before is the research into how accurately politicians estimate public opinion on issues. Thankfully we have academic research to tell us. First, the bad news: We present results from a study of 866 politicians in four countries.1 Politicians were asked to estimate the percentage of public support for various policy proposals. Comparing more than 10,000 estimations with actual levels of public support, we conclude that politicians are quite inaccurate estimators of people’s preferences. They make large errors and even regularly misperceive what a majority of the voters wants. Politicians are hardly better at estimating public preferences than ordinary citizens. Walgrave, S., Jansen, A., Sevenans, J., Soontjens, K., Pilet, J.B., Brack, N., Varone, F., Helfer, L., Vliegenthart, R., van der Meer, T., Breunig, C., Bailer, S., Sheffer, L. & Loewen, P.J. (2023a), “Inaccurate Politicians: Elected Representatives’ Estimations of Public Opinion in Four Countries”, The Journal of Politics, 85(1): 209-222. The bad news is not quite as bad as that makes it sound because, when asked whether the majority of public opinion was for or against various policies, politicians picked the wrong option ‘only’ 29% of the time. However, this included getting it wrong even when public opinion is far from evenly split on an issue: They do not only get it wrong when the public is divided and hard to read (e.g., when there is a 51%:49% distribution). Seventy percent of the misplacements occur for policies with a relatively clear distribution of at least 60% (dis)agreeing citizens. Moreover, the public scored only slightly worse than politicians, picking the wrong option 2.7 out of 8 times on average, compared with 2.3 times for politicians. Turning to the other measure of accuracy (not which side is in the lead but what the percentage support is for each side), politicians on average were 18 percentage points out in their guesses. Again, this was only slightly better than the public, whose error came in at 21 percentage points.2 Further research, using the same mix of countries, gives a little more comfort about how (in)accurate perceptions are: We show that politicians have a better understanding of public opinion when they think the issue matters to voters. Further, when an issue is personally important to politicians they more accurately estimate their party supporters’ opinions. The results confirm that politicians hold more accurate perceptions of voters’ preferences when they think it is important to do so but not necessarily when the issues actually are important to voters. Butler, C., Walgrave, S., Soontjens, K. & Loewen, P.J. (2024), “Politicians are better at estimating public opinion when they think it is more salient”, Party Politics: 1–13. Even so, it’s not a good picture. The remedy for this? Politicians should spend more time reading the polls. So forward this newsletter to someone you know… Share For a more general argument against banning polls, see my 2024 piece. Is “Let Bartlet Be Bartlet” good advice or not? The latest episode of my Political Fictions podcast heads across the Atlantic for a dip into one of the political TV classics: Mark and Cory talk about a giant of American political drama for the first time this week, as they tackle The West Wing. They talk about Let Bartlet Be Bartlet, the nineteenth episode of series one. In it, Mark wonders if The West Wing is actually the epitome of the “Boris Johnson school of politics”, Cory outmanoeuvres Mark into confirming we will record a Christmas Special about Love, Actually and they debate whether the central message of this episode has been misunderstood. Cory’s email newsletter is Paperback Rioter and Mark has a family of email newsletters. Subscribe to our newsletter for some additional bonus content and to get alerted whenever a new episode comes out. Our theme tune is “Monkeys Spinning Monkeys” by Kevin MacLeod/incompetech.com and licensed under the Creative Commons: By Attribution 4.0 License. You can also listen to our episode on Apple Podcasts, Spotify, the web or YouTube. Elsewhere from me… [ A Lord's Eye View How to fix the problem of money in our politics Welcome to my latest update on work in the House of Lords. This time I am taking a look at how our political system is regulated, and the protections we need to keep democracy safe from becoming simply a contest to see who has the biggest bank account… Read more 5 days ago · 3 likes · 2 comments · Mark Pack ](https://lordseyeview.substack.com/p/how-to-fix-the-problem-of-money-in?utm_source=substack&utm_campaign=post_embed&utm_medium=web&embedding_publication_id=1269283) If you spot a factual error… Borrowing an idea from Stuart Ritchie and others, if you spot a factual error in an edition of this newsletter, I will give you a free 12-month subscription to the paid-for version (or an extra 12 months on your existing one). Factual errors qualify, but grammatical errors or disagreements over interpretation do not, and my decision is final. Messages about both of those are always welcome, though. Voting intention and leadership ratings Here are the latest voting intention polls from different pollsters. It is all pretty static at the moment, with a small and consistent Labour lead in nearly all the polls. The table is also online here, along with explanations about what is included. It is updated regularly throughout the week as new polls are released. Next are the seat projections from MRPs, also sorted by fieldwork dates, listing those which are based on dedicated fieldwork (rather than models based on averages of other polls). Because such MRPs are published infrequently, some of the entries below are quite old. Finally, here is a summary of leadership ratings, with a graph from PollCheck: Detailed numbers from the latest polls are online here, and both that and the graph are updated regularly throughout the week as new data comes out. For historical figures on both voting intention and leader approval stretching back to the 1930s, including Parliamentary by-election polls, see PollBase. Catch up on the previous two editions [ ](https://theweekinpolls.substack.com/p/a-crisis-point-for-political-polling) [ A crisis point for political polling Sep 13 ](https://theweekinpolls.substack.com/p/a-crisis-point-for-political-polling) [ Read full story ](https://theweekinpolls.substack.com/p/a-crisis-point-for-political-polling) [ ](https://theweekinpolls.substack.com/p/extra-questions-about-the-polls-in) [ Extra questions about the polls in Reform’s funding scandal Sep 6 ](https://theweekinpolls.substack.com/p/extra-questions-about-the-polls-in) [ Read full story ](https://theweekinpolls.substack.com/p/extra-questions-about-the-polls-in) My privacy policy and other legal information are available here. Links to purchase books or other items are usually affiliate links which pay a commission for each sale. Quotes from social media messages are occasionally lightly edited for punctuation and clarity. If you are subscribed to other email lists of mine, please note that unsubscribing from this one will not automatically remove you from the others. If you wish to be removed from all my lists, simply reply to this email to let me know. A quintet of Lib Dem polling analyses, and 9 other polling insights you shouldn’t miss The following ten findings from the most recent polls and analyses are only for subscribers who pay for the full edition, but you can sign up for a free trial to read them straight away. Ahead of the start of Liberal Democrat conference, we have a trio of organisations and a pair of professors with pieces out about Ed Davey’s party:
Nicolas Cage, 62, Reveals Striking White Hair and Beard Transformation With Wife Riko Shibata, 31
Nicolas Cage, 62, Reveals Striking White Hair and Beard Transformation With Wife Riko Shibata, 31
Look at that full white beard!
Business People: Julie Batliner named president at Padilla
ADVERTISING/PUBLIC RELATIONS Padilla, a Minneapolis-based public relations firm, announced that it has named Julie Batliner president, succeeding Matt Kucharski, who will transition to a planned retirement at the end of 2026. Kucharski…
Shula Bowl | Florida Atlantic edges FIU behind defense, special teams
The Owls defeated the Panthers 16-10 in a gritty, defensive battle that was the lowest scoring game in the 24-year series.
A bitter battle is brewing in one of Washington state’s last swing districts
Democrats are looking to scoop up more legislative seats this November in Battle Ground and other chunks of Southwestern Washington as they edge toward a supermajority in Olympia — a shift that would give them broad power to pass legislation or redraw the state’s voting maps.
Entertainment Stars Jeon Won-ju, Go Ji-yong, Han So-hee Spark Controversies
Entertainment Stars Jeon Won-ju, Go Ji-yong, Han So-hee Spark Controversies Weekly roundup includes fee disputes, backlash, custody battle, and verbal misstep
Dolly Parton Carries This Shocking Home Item ‘Non-Stop' While Touring
Miley Cyrus questions Dolly Parton's mobile tub: "When are you taking the bath on the highway?".
iOS 27 Battery Drain & Overheating? Here’s How to Fix It
Fix iOS 27 battery drain and overheating by identifying power-hungry background processes. Check your battery usage by app to stop the excessive drain today.
Wolverine developer Insomniac denies using generative AI after fans spot strange restroom sign
Insomniac denies using generative AI on Marvel's Wolverine after fans spotted a strange bathroom sign, blaming a "UV map bug" instead.
Fast food from the US and China catches on in both countries
China and the United States are divided on many issues, from tariffs to Taiwan.
Trump and sons invest heavily in AI economy as he resists calls for slowdown
Trump’s decisions as president on one of the most consequential policy debates of his administration could affect the value of his personal investments.
Offense Carries Guardians To Another Win
It was a beautiful offensive performance from the Guardians today. The bats appear to be heating up at the right time. The Guardians scored 12 runs on 15 hits and 3 home runs. Angel Martinez went 4-5 with two home runs and is up to a .255 AVG with an OPS of .759 on the […]
Defender Ng predicts big wins to come for Cardiff
Cardiff City defender Perry Ng says he expects the club to "batter some teams" moving forward as the Bluebirds finally put an end to their winless run.
Michael Vick notches first Division I win, more to come?
Michael Vick secured his first Division I victory in resounding fashion with a blowout win over Hampton in this year’s Battle of the Bay. Last year’s matchup was a high-scoring affair that stayed close throughout and saw Hampton ultimately emerge victorious. But in Vick’s second year leading the Spartans, they looked way more potent offensively and […] The post Michael Vick notches first Division I win, more to come? appeared first on ClutchPoints.
Ranked: Top 3 Hardest Sports In Thailand
From striking to acrobatics to endurance, discover what makes these sports so challenging.
Furbank to miss opener
GEORGE Furbank suffered a nightmare start to his new life at Harlequins after he was forced off a minute into his club debut on Friday night. Furbank, who joined the London club from Northampton over the summer, is likely to miss his new club’s Premiership opener against Bath on Friday after he was caught by […] The post Furbank to miss opener appeared first on The Rugby Paper .
Don’t rule Ford out of England
■By BEN JAYCOCK ANTHONY Watson believes England fans would be “ridiculously foolish” to write George Ford out of the battle for the No.10 jersey at next year’s World Cup. Ford was included among the 25 players handed enhanced EPS contracts by Steve Borthwick and Watson is far from surprised to see the 105-cap fly-half remain […] The post Don’t rule Ford out of England – Watson appeared first on The Rugby Paper .
Is social media giving you health anxiety? Here's how to combat it
LONDON - Do you ever find yourself caught in a health advice doomscrolling session on TikTok late at...
Is social media giving you health anxiety? Here's how to combat it
LONDON - Do you ever find yourself caught in a health advice doomscrolling session on TikTok late at...
Latest batch of Nintendo Switch backwards compatibility fixes for Switch 2
Nintendo has been striving to get all third party Nintendo Switch games up and running and compatible with the Nintendo Switch 2. The company has been working with third party developers to ensure any…
Saturday Night Open Thread: Can’t Stand *Pats
Come and join this merry band of Steelers’ faithful for some lively debate about our Steelers, good food, music, and the merits of the odd cold beverage.
The Worst Seed The Cubs Can Get In The Postseason
A three-way deadlock atop the Wild Card standings forces Chicago into a high-stakes sprint. With postseason odds secured, the North Siders must now battle for crucial seeding.
Nintendo has issued new batch of Switch 1 backwards compatibility fixes for Switch 2
Nintendo has now released new Switch 1 backwards compatibility fixes for Switch 2, and here's the full list.
Buccaneers Battle Browns With Season at Early Crossroads
Buccaneers look to bounce back against the Browns and avoid their first 0-2 start under Todd Bowles.
Galaxy S27 Pro and S27 Ultra reportedly getting major battery upgrade
Samsung’s Galaxy S27 Ultra and S27 Pro are expected to get major battery upgrades, with certification records pointing to typical capacities of about 5,700mAh and 5,200mAh, respectively. This would mark the most significant battery upgrade since the S20.
Nearly 3 in 4 Americans are battling the same exhausting health problem, CDC reveals
More than seven in 10 U.S. adults experienced fatigue during a three-month period, according to a 2024 CDC survey of roughly 27,000 people. T
Nearly 3 in 4 Americans are battling the same exhausting health problem, CDC reveals
More than seven in 10 U.S. adults experienced fatigue during a three-month period, according to a 2024 CDC survey of roughly 27,000 people. T
Nearly 3 in 4 Americans are battling the same exhausting health problem, CDC reveals
More than seven in 10 U.S. adults experienced fatigue during a three-month period, according to a 2024 CDC survey of roughly 27,000 people. T
Nearly 3 in 4 Americans are battling the same exhausting health problem, CDC reveals
More than seven in 10 U.S. adults experienced fatigue during a three-month period, according to a 2024 CDC survey of roughly 27,000 people. T
Health department warns of increased Asian tiger mosquito activity
Evanston Health and Human Services and the North Shore Mosquito Abatement District (NSMAD) continue to see increased biting mosquito reports, largely
Here's how Apple circumvented the battery shipping restrictions for iPhone 18 Pro Max
Learn about this simple software trick that regulators hate. If you've been following the smartphone trends in recent years, you've probably noticed that...
The race to build a pandemic-proof world
Six years after COVID-19 killed millions, battered health systems, disrupted lives and brought the global economy to a virtual standstill, the world is still grappling with how we can prepare better for the next pandemic.
Democratic Gov. Katie Hobbs leans into a GOP-friendly message in battleground Arizona
Even as the political environment favors her party, Hobbs is focused on the middle as she seeks a second term in a state Trump won in 2024.
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!
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Engrams Embedding Entendre: Codesign for Efficient DRAM/SSD Offloading
Engram extends standard token embeddings with learned multi-token lookups. Recurring local patterns retrieve vectors directly, reducing the need to reconstruct them through attention and feed-forward layers. With Engram model architecture optimization, it allows for lower HBM capacity to be needed for models at the same quality. This does not mean there won’t be an insane demand for HBM but it just means that model architecture will continue to innovate around constraints. This model architecture design is naturally codesigned for parameter offloading: each token accesses a few embedding rows whose addresses depend on token IDs, not hidden states. The runtime can prefetch those rows from host DRAM while earlier layers compute, keeping the table outside HBM without transferring entire weight matrices. Our Memory model contains our latest estimates of quarter by quarter HBM, DRAM, & NAND supply and demand. Offloading frees HBM for model weights and KV cache, potentially supporting larger batches or more concurrent sessions. When DRAM becomes the next constraint, NVMe offers another tier. Recommendation systems already cache frequently or recently accessed embedding rows in faster memory while backing colder rows with SSDs. After NVIDIA roadmap had to change due to massively despec’ing Rubin Ultra from 1024GB to now ~200GB of HBM per chip, model architecture optimizations like emgram maybe helpful. Our DeepSeek-V4.1-Flash configuration uses roughly 189 GiB of memory for Engram. We replace it with a memory-mapped (mmap) file and measure serving performance with offload to SSD. Later on in our report, we will show our Engram offloading experiments along with the official InferenceX agentic inference serving results on Engram models like DeepSeekv4.1 Flash across all 6 NVIDIA GPU SKUs along with MI355X. Unsurprisingly, the CUDA Moat is still mogging MI355X on the ultra popular DeepSeekV4.1 Flash model. We also show how even on high capacity HBM SKUs, offloading emgrams to DRAM could result in even better performance for most of the pareto than keeping the emgram in HBM. Our benchmark has been widely reproduced, validated and/or supported by almost every major buyer of compute from Google Cloud to Microsoft Azure to Oracle, to Meta and many more. Furthermore, it has the support of the ML community including from vLLM, LMCache, SGLang, PyTorch, Huggingface and the support of major labs like OpenAI, MiniMax, ZAI, Qwen, Moonshot Kimi, etc. Star the InferenceX GitHub repository if you find the open-source benchmark and data useful!. InferenceX is the only inference benchmark in the world to have TPUv7, Jalapeño, Nvidia Rubin NVL72, AMD, and soon, SambaNova and Trainium. Due to how realistic AgentX scenario is to real world agentic inference workloads, AMD has committed to collaborating on MI455X UALoE72 too. DeepSeek did not release the original paper’s two trained Engram models. We replicated its setup on fineweb-edu using the released code and training hyperparameters, at an estimated 6E18 FLOPs per run. We observed the same U-shape scaling: Engram improved performance over pure MoE baselines. We also reproduced DeepSeek’s results, where earlier-layer representations with Engram resembled those of later layers. Like the original Engram paper, it is possible to probe Engram’s gate scores to see what n-grams DeepSeek-V4.1-Flash makes the most use of. Our gate scan finds names, code fragments, relational phrasing, and boilerplate. These examples prioritize interesting-ness over gate strength. One unexpected result was Wright : Ace Attorney. These examples suggest learned memory optimizes the training objective, not a judgment of which facts deserve storage. Licenses, bibliography fragments, API scaffolding, and website furniture can provide prediction shortcuts, so the value of additional Engram capacity may depend on what survives data preparation. This does not show that table capacity is “wasted”: the evaluation-corpus scan establishes neither training exposure nor the capacity occupied by each category. For offloading, strong gates do not identify cache-hot rows. Low gates do not automatically save reads either: computing the gate requires the retrieved key and undoes the performance gain of a fused kernel. Skipping reads would require a separate usefulness predictor before retrieval. In the original paper’s inference-time ablation, factual-knowledge benchmarks retained just 29–44% of their original performance, while reading comprehension retained 81–93%. This is due to the training–inference mismatch. The resulting degradation therefore measures this trained model’s dependence on Engram, not the performance difference between models trained with and without it. In our ablations, suppressing Engram worsens token likelihood across all evaluated domains, especially encyclopedia text and several code corpora. Surprisingly, GSM8K accuracy stays within measured run-to-run variation and removing Engram has no effect. Engram is not a detachable dictionary beside an unchanged MoE. Removing it changes downstream features and expert selection. We tested whether rerouting hurts or compensates by holding tokens fixed in a teacher-forced experiment on CRUXEval, a code-reasoning benchmark of small Python functions where the model predicts a function’s output from its code and an input, and scoring the reference answer. Removing Engram raised answer loss from 0.2848 to 0.3093 bits/token. Forcing the ablated model to use the original Engram-on expert choices made it worse still, at 0.3375 bits/token. Rerouting partially compensates for the missing memory. Memory features and expert selection work together, rather than following a clean “memory stores facts; experts reason” division. On the same CRUXeval, removing Engram during either phase reduced accuracy and increased generated tokens; removing it throughout produced the largest changes. Keeping Engram for prefill leads to more correct answers than keeping for decode likely due to semantically richer KV cache transferred to decode workers, allowing it to mitigate some of the performance loss. Engram’s table is large, but each lookup is small. DeepSeek-V4.1-Flash requests 24 rows at each of two Engram layers, about 12.4 KiB per processed token position across the model, or 3.1 KiB per GPU when split across four GPUs. Currently as of Day 7 since Model Release, MI355X is still 2-4x worse performance per dollar compared to B200 even when normalized by Mi355X’s lower TCO. Our full total cost of ownership breakdown comes from our AI Cloud TCO Model along with monthly market surveys of over 100+ gpu clouds & gpu cloud customers. On the Day 0 release of DeepSeekv4.1 Flash, NVIDIA vLLM works out of the box with zero issues across all 6 SKUs: H100, H200, B200, B300, GB200, GB300! This was thanks to the amazing work by the NVIDIA & Interact teams! In comparison, AMD vLLM did not work on day 0 for DeepSeekv4.1 Flash.Source: SemiAnalysis InferenceX AMD’s vLLM documentation points to using vllm/vllm-openai-rocm:deepseekv41-flash-0909, but from hour 0 of the model release to hour 23, AMD has not publicly released the image. AMD claims, “SPEED IS THE MOAT,” yet it has still not released it by the 23rd hour. We wish that, going forward, the AMD team has a better process for hour 0 model releases. Eventually when they did publicly release for “day 0” image support, performance-wise, it is currently up to 14.8x worse perf per dollar than H200 and up to 42x worse perf per dollar than B200/B300. The power of the CUDA MOAT is NVIDIA’s collaboration with its massive 6 million-developer community ecosystem including most of the vLLM & SGLang & Tokenspeed maintainers which means that CUDA is optimized on day 0. Overall, AMD did make significant improvements but the performance per dollar is still currently 2-4x worse than B200. AgentX Engram DRAM Offloading Improving Performance The HBM and DRAM offload use the same GPU kernel to select and dequantize rows. With HBM, it reads GPU memory; with Unified Virtual Addressing (UVA), it reads pinned host memory directly. Both support full decode graphs. Moving the table into HBM accelerates only the sparse lookup, leaving decoder computation and communication unchanged, resulting in little overall benefit while consuming memory otherwise available to KV cache. Another benefit of Engram offloaded to DRAM which means you can reduce the communication overhead by using less HBM GPUs per replica. For example, when enabling Engram offloading on B300, we are able to switch from TP4 to now TP2 which improves the pareto curve by up to 1.6x. When iso-model quality, less HBM is required as the engrams could be offloaded to host DRAM. Thus HBM bandwidth matters way more than HBM capacity. For inference workloads where memory bandwidth matters the most, 4-hi HBM provides the best $/bandwidth and therefore lowest cost per token. If China continues to make more and more revolutionary model architecture innovations, soon it could potentially 0Hi HBM stacks. [ ](https://newsletter.semianalysis.com/p/long-live-the-short-king-why-4-hi) [ Long Live the Short King: Why 4-hi HBM Wins ](https://newsletter.semianalysis.com/p/long-live-the-short-king-why-4-hi) Myron Xie, Bryan Shan, and 3 others · Sep 13 [ Read full story ](https://newsletter.semianalysis.com/p/long-live-the-short-king-why-4-hi) Moreover, on B300 and week-0 stack, moving the Engram table back to HBM did not improve results and stay within run-to-run variance. This is a result of the work optimizing DRAM offload, such as async, and overlap. SSD Offloading On B200, we created a unoptimized vLLM fork and stored the Engram tables in memory-mapped files on local SSDs. File backing lets the OS reclaim table pages when other applications need RAM. Pages already cached in memory can be served without reading the SSD again. Furthermore, note that we were unable to turn on GDS The unoptimized SSD implementation changes how rows reach the GPU. It copies row IDs to the CPU, deduplicates them, gathers the requested rows into pinned buffers, copies those rows back to the GPU and dequantizes them. This work runs between segments of the GPU execution graph. Native UVA performs row selection and dequantization directly on the GPU, avoiding the CPU round trip. A warm filesystem cache removes physical SSD reads, but leaves the coordination, row gathering and transfers. This is why a file already cached in RAM can still perform worse than a pinned DRAM table. The comparison measures the whole serving path; it does not separate the time spent on each of these operations. B200 DRAM dominates both measured SSD serving curves in total tokens per dollar and P90 interactivity. Near 125 tokens/s/user, DRAM delivers 121 million total tokens per dollar versus 52 million for SSD. For production serving, SSD offloading is likely not worth the tradeoff. On the B200 configurations we measured, SSD offloading loses on both measures: every observed SSD point has a DRAM alternative that delivers higher P90 interactivity and more total tokens per dollar. The only points where Cheaper storage does not automatically produce a cheaper inference service. Moving Engram to SSD leaves the same four expensive GPUs and the rest of the server in place. Reclaiming RAM only creates an economic benefit if it enables a cheaper server configuration or additional useful capacity. The current unoptimized path provides neither benefit, and the filesystem cache still consumes RAM when table pages are resident. Next we will look at the mechanisms and specific implementation of ngrams from DeepSeekv4.1 Flash, LongCat, Qwen3.8 Flash Next.
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