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The Samsung Galaxy S launch is at all times one of many 12 months’s most anticipated occasions, and the 2026 version may convey some surprises.
We’ve already seen just a few particulars in regards to the Galaxy S26 sequence, together with the Extremely’s dimensions, a doable new identify for the center mannequin, and the potential use of the Exynos 2600 chipset within the two extra reasonably priced fashions. Nevertheless, a brand new report from Korea means that Samsung may also use its homegrown chip within the Extremely mannequin, too. As a substitute of utilizing the Snapdragon 8 Gen 5 within the Galaxy S26 Extremely, as has been customary for a number of generations, Samsung may totally decide to the Exynos 2600 for all of its flagship fashions.
It’s essential to notice that the report isn’t fully convincing, so I counsel taking it with a grain of salt. Nevertheless, it does spotlight an intriguing chance for Samsung and a few potential considerations for patrons.
Don’t wish to miss one of the best from Android Authority?
If the Exynos 2600 is as pacey and punchy as Samsung hopes, it could possibly be a greater choice than the Snapdragon 8 Gen 5, which might sometimes be most well-liked for the Galaxy S26 Extremely. With its rumored 2nm manufacturing course of and NVIDIA’s Xclipse 950 GPU, it might additionally excel in battery life and gaming efficiency. It won’t be a foul transfer if Samsung decides to rely by itself expertise this time.
In the end, the shoppers resolve, and Exynos hasn’t been extremely praised in recent times. Many customers could be hesitant in regards to the absence of a Snapdragon chipset within the flagship Samsung. Whereas it could possibly be a efficiency breakthrough, utilizing Exynos within the Extremely may negatively influence gross sales.
It’s most likely too early to foretell Samsung’s choices, however I’m inquisitive about your ideas on an Exynos-powered Galaxy S26 Extremely. Would this modification your thoughts about shopping for the flagship Samsung, or would it not not have an effect on your determination? Moreover, what are your ideas in regards to the Exynos 2600 in Samsung’s different potential S26 fashions: the S26 Professional and commonplace S26?
Listed below are some extra questions:
What can be your most well-liked chipset for the Galaxy S26 Extremely: the Snapdragon 8 Gen 5, or the Exynos 2600?
What’s your notion of the Exynos chipset line?
What would Samsung have to show so that you can belief Exynos once more?
How essential is a smartphone’s chipset to you in comparison with its different options?
Which chipset would you fairly see within the Samsung Galaxy S26 Extremely?
20 votes
Would you purchase the Galaxy S26 Extremely if it used an Exynos chip?
24 votes
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That is an try at reproducing the evaluation of Part 2.7 of Bayesian Knowledge Evaluation, third version (Gelman et al.), on kidney most cancers charges within the USA within the Nineteen Eighties. I’ve achieved my finest to wash the info from the unique. Andrew wrote a weblog put up to “disillusion [us] in regards to the reproducibility of textbook evaluation”, wherein he refers to this instance. This may then be an try at reillusionment…
Within the information, the columns dc and dc.2 correspond (I believe) to the dying counts attributable to kidney most cancers in every county of the USA, respectively in 1908-84 and 1985-89. The columns pop and pop.2 are some measure of the inhabitants within the counties. It’s not clear to me what the opposite columns characterize.
Easy mannequin
Let be the inhabitants on county , and the variety of kidney most cancers deaths in that county between 1980 and 1989. A easy mannequin is the place is the unknown parameter of curiosity, representing the incidence of kidney most cancers in that county. The utmost chance estimator is .
Specifically, the unique query is to grasp these two maps, which present the counties within the first and final decile for kidney most cancers deaths.
plot_usmap("counties", information=d, values="cancerlow") +
scale_fill_discrete(h.begin = 200,
identify = "Low fee of kidney most cancers deaths")
These maps are suprising, as a result of the counties with the best kidney most cancers dying fee, and people with the bottom, are considerably comparable: principally counties in the midst of the map.
(Additionally, be aware that the info for Alaska are lacking. You may conceal Alaska on the maps by including the parameter embrace = statepop$full[-2] to calls to plot_usmap.)
The rationale for this sample (as defined in BDA3) is that these are counties with a low inhabitants. Certainly, a typical worth for is round . Take a county with a inhabitants of 1000. It’s more likely to don’t have any kidney most cancers deaths, giving and placing it within the first decile. But when it occurs to have a single dying, the estimated fee jumps to (10 occasions the typical fee), placing it within the final decile.
That is hinted at on this histogram of the :
ggplot(information=d, aes(d$thetahat)) +
geom_histogram(bins=30, fill="lightblue") +
labs(x="Estimated kidney most cancers dying fee (most chance)",
y="Variety of counties") +
xlim(c(-1e-5, 5e-4))
Bayesian strategy
When you have ever adopted a Bayesian modelling course, you might be in all probability screaming that this requires a hierarchical mannequin. I agree (and I’m fairly certain the authors of BDA do as effectively), however here’s a extra primary Bayesian strategy. Take a standard distribution for all of the ; I’ll go for and , which is barely vaguer than the prior utilized in BDA. Clearly, it’s best to attempt numerous values of the prior parameters to examine their affect.
The prior is conjugate, so the posterior is . For small counties, the posterior might be extraordinarily near the prior; for bigger counties, the chance will take over.
It’s often a disgrace to make use of solely level estimates, however right here it is going to be enough: allow us to compute the posterior imply of . As a result of the prior has a robust influence on counties with low inhabitants, the histogram seems very totally different:
And the maps of counties within the first and final decile are actually a lot simpler to differentiate; as an example, Florida and New England are closely represented within the final decile. The counties represented listed here are principally populated counties: these are counties for which we’ve got cause to imagine that they’re on the decrease or increased finish for kidney most cancers dying charges.
An necessary caveat: I’m not an knowledgeable on most cancers charges (and I count on a few of the vocabulary I used is ill-chosen), nor do I declare that the info listed here are appropriate (from what I perceive, many changes should be made, however they aren’t detailed in BDA, which explains why the maps are barely totally different). I’m merely posting this as a reproducible instance the place the naïve frequentist and Bayesian estimators differ appreciably, as a result of they deal with pattern dimension in numerous methods. I’ve discovered this instance to be helpful in introductory Bayesian programs, because the distinction is straightforward to understand for college kids who’re new to Bayesian inference.
This video is a part of “Improvements In: RSV,” an editorially unbiased particular report that was produced with monetary assist from MSD, Sanofi and AstraZeneca.
Zachary Rubin: Holy cow, people. We’re getting into RSV season, and for infants, this sickness can flip critical quick. Right here’s what you must know.
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I’m Dr. Zachary Rubin, double board-certified pediatrician and allergist, and each fall I see an increase in RSV circumstances in my clinic. RSV, or respiratory syncytial virus, is the main reason behind toddler hospitalization within the U.S.
At first, RSV would possibly look like only a chilly, but when your child begins respiratory quick, pulling in on the ribs or having bother feeding, it might be extra critical.
The excellent news? We now have instruments to battle again. There are new monoclonal antibody therapies that may assist infants battle off the virus, and pregnant mothers may even get vaccinated to cross antibodies to their infants earlier than beginning.
Remember to wash your arms, keep away from crowded indoor areas or masks up throughout surges, and don’t ignore wheezing or labored respiratory to maintain your self and family members protected throughout this RSV season.
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Should you subscribe to Scientific American, you assist be certain that our protection is centered on significant analysis and discovery; that now we have the assets to report on the selections that threaten labs throughout the U.S.; and that we assist each budding and dealing scientists at a time when the worth of science itself too usually goes unrecognized.
How particular person and neighbourhood socioeconomic disadvantages collectively have an effect on health-related behaviour
Yinjie Zhu
In our research lately printed within the IJE, we discovered that socioeconomically deprived people had been extra more likely to have worse health-related way of life behaviour than their neighbours, even when they lived in neighbourhoods with little general socioeconomic drawback.
We additionally noticed a “double jeopardy” impact: an unhealthier way of life was discovered amongst folks with better particular person drawback residing in deprived neighbourhoods.
Why is way of life behaviour vital to well being?
Unfavorable way of life behaviours — equivalent to unhealthy weight loss plan, smoking, inadequate bodily exercise and alcohol misuse – may end up in persistent ailments, equivalent to weight problems and diabetes, and are related to decrease life expectancy and better mortality. Modifying these behaviours can deal with a variety of ailments. Nonetheless, neighbourhood socioeconomic standing is equally vital for well being and wellbeing.
How is socioeconomic drawback associated to way of life behaviour?
Socioeconomic drawback normally exists at two ecological ranges: particular person and neighbourhood. Particular person drawback is commonly influenced by training and earnings, whereas the neighbourhood serves as a platform for well being assets and the unfold of sure well being beliefs and social norms.
In our research, utilizing the Lifelines cohort and Biobank of 77,244 members residing within the northern Netherlands, we estimated socioeconomic drawback on the particular person and neighbourhood ranges. Neighbourhood drawback was based mostly on earnings and social safety advantages, whereas particular person drawback moreover thought of training and unemployment.
We investigated the joint impact and interrelation of those disadvantages on health-related way of life behaviours (weight loss plan high quality, smoking, alcohol consumption, hours of sleep, hours of watching TV and bodily exercise). These behaviours had been summed to create a life-style threat index, with the next index representing an unhealthier way of life.
What’s the “double jeopardy” impact?
Merely put, in our research, folks with the unhealthiest existence had the best ranges of each particular person and neighbourhood disadvantages. Nonetheless, the impression of particular person drawback was stronger in additional deprived neighbourhoods.
People who find themselves much less individually deprived will likely be extra resilient and proof against their neighbourhood drawback as a result of they’re extra more likely to entry well being assets, have the next degree of self-perceived management and have better information of the best way to keep away from unhealthy way of life behaviour.
What’s the lesson for coverage makers?
The double jeopardy impact can present sensible steering to coverage makers and public well being practitioners. It tells us that practising an unhealthy way of life will depend on each particular person and neighbourhood disadvantages. This requires built-in public insurance policies specializing in, and interesting with, folks’s environment in addition to the folks themselves.
For instance, a public coverage aiming to extend bodily exercise might contain constructing extra sports activities amenities and enlarging the neighbourhood’s playground space, in addition to organising sports activities actions and disseminating well being details about bodily exercise to folks residing within the neighbourhood.
Furthermore, future public well being initiatives ought to take into account offering extra well being assets, and enabling higher entry to them, in addition to growing social alternatives, equivalent to training and cultural actions, for socioeconomically deprived neighbourhoods, whereas additionally focusing on particular person behaviour. Solely then can we work in direction of attaining a wholesome way of life for all and mitigate society’s persistent well being inequalities.
Learn extra:
Zhu Y, Duan M-J, Riphagen IJ, et al. Separate and mixed results of particular person and neighbourhood socio-economic drawback on health-related way of life threat components: a multilevel evaluation. Int J Epidemiol 2021; 24 April. doi: 10.1093/ije/dyab079.
Yinjie Zhu holds a Grasp’s diploma in diet and rural improvement from Ghent College and is a PhD candidate within the Division of Inner Medication (Division of Nephrology) on the College Medical Centre Groningen, The Netherlands. She is keen on how socioeconomic standing impacts way of life, dietary standing and well being outcomes in a basic inhabitants.
Duflo et al (2008) describe this in additional element:
“Because the covariates for use should be chosen upfront with the intention to keep away from specification looking out and knowledge mining, they can be utilized to stratify (or block) the pattern with the intention to enhance the precision of estimates. This system (¯rst proposed by Fisher (1926)) includes dividing the pattern into teams sharing the identical or related values of sure observable traits. The randomization ensures that therapy and management teams might be related in expectation. However stratification is used to make sure that alongside necessary observable dimensions that is additionally true in apply within the pattern….blocking is extra environment friendly than controlling ex publish for these variables, because it ensures an equal proportion of handled and untreated unit inside every block and subsequently minimizes variance.”
In addition they elaborate on blocking if you find yourself focused on subgroup evaluation:
“Other than decreasing variance, an necessary cause to undertake a stratified design is when the researchers have an interest within the impact of this system on particular subgroups. If one is within the impact of this system on a sub-group, the experiment will need to have sufficient energy for this subgroup (every sub-group constitutes in some sense a definite experiment). Stratification in accordance with these subgroups then make sure that the ratio between therapy and management items is decided by the experimenter in every sub-group, and might subsequently be chosen optimally. It’s also an assurance for the reader that the sub-group evaluation was deliberate upfront.”
Dijkman et al (2009) focus on subgroup evaluation in blocked or stratified designs in additional element:
“When stratification of randomization relies on subgroup variables, it’s extra doubtless that therapy assignments inside subgroups are balanced, making every subgroup a small trial. As a result of randomization makes it doubtless for the subgroups to be related in all facets besides therapy, legitimate inferences about therapy efficacy inside subgroups are prone to be drawn. In publish hoc subgroup analyses, the subgroups are sometimes incomparable as a result of no stratified randomization is carried out. Moreover, stratified randomization is fascinating because it forces researchers to outline subgroups earlier than the beginning of the examine.”
Each of those accounts appear very a lot in step with one another by way of serious about randomization inside subgroups making a mini trial the place causal inferences could be drawn. However I feel the important thing factor to contemplate is they’re referring to comparisons made WITHIN sub teams and never essentially BETWEEN subgroups.
Gerber and Inexperienced focus on this in one in all their chapters on evaluation of block randomized experiments :
“No matter whether or not one controls for blocks utilizing weighted regression or regression with indicators for blocks, they key precept is to match therapy and management topics inside blocks, not between blocks.”
After we begin to evaluate therapy and management items BETWEEN blocks or subgroups we’re primarily decoding covariates and this can’t be finished with a causal interpretation. Inexperienced and Gerber focus on an instance associated to variations within the efficiency of Hindu vs. Muslim colleges.
“it might simply be that faith is a marker for a bunch of unmeasured attributes which can be correlated with instructional outcomes. The set of covariates included in an experimental evaluation needn’t be an entire record of things that have an effect on outcomes: the truth that some elements are ignored or poorly measured isn’t a supply of bias when the purpose is to measure the typical therapy impact of the random intervention. Omitted variables and mismeasurement, nonetheless, can result in sever bias if the purpose is to attract causal inferences concerning the results of covariates. Causal interpretation of the covariates encounters all the threats to inference related to evaluation of observational knowledge.”
In different phrases, these sorts of comparisons face the the identical challenges associated to decoding management variables in a regression in an observational setting (see Keele, 2020).
However why would not randomization inside faith enable us to make causal statements about these comparisons? Let’s take into consideration a special instance. Suppose we wished to measure therapy results for some form of instructional intervention and we have been focused on subgroup variations within the end result between private and non-private excessive colleges. We might randomly assign therapies and controls throughout the public faculty inhabitants and do the identical throughout the non-public faculty inhabitants. We all know total therapy results could be unbiased as a result of the college sort could be completely balanced (as a substitute of balanced simply on common in a totally random design) and we’d count on all different necessary confounders to be balanced between therapies and controls on common.
We additionally know that throughout the group of personal colleges the therapy and controls ought to at the very least on common be balanced for sure confounders (median family earnings, trainer’s schooling/coaching/expertise, and maybe an unobservable confounder associated to pupil motivation).
Lets say the identical factor about comparisons WITHIN the subgroup of public colleges. However there isn’t any cause to imagine that the handled college students in non-public colleges could be similar to the handled college students in public colleges as a result of there isn’t any cause to count on that necessary confounders could be balanced when making the comparisons.
Assume we’re taking a look at variations in first semester school GPA. Possibly throughout the non-public subgroup we discover that handled handled college students on common have a primary semester school GPA that’s .25 factors greater the comparable management group. However throughout the public faculty subgroup, this variations was solely .10. We are able to say that there’s a distinction in outcomes of .15 factors between teams however can we are saying that is causal? Is the distinction actually associated to highschool sort or is faculty sort actually a proxy for earnings, trainer high quality, or motivation? If we elevated motivation or earnings within the public colleges would that make up the distinction? We would do higher if our design initially stratified on all of those necessary confounders like earnings and trainer schooling. Then we might evaluate college students in each private and non-private colleges with related household incomes and academics of comparable credentials. However…there isn’t any cause to imagine that pupil motivation could be balanced. We will not block or stratify on an unobservable confounder. Once more, as Gerber and Inexperienced state, we discover ourselves in a world that borders between experimental and non-experimental strategies. Merely, the subgroups outlined by any specific covariate that itself isn’t or can’t be randomly assigned might have totally different potential outcomes. What we are able to say from these outcomes is that faculty sort predicts the end result however doesn’t essentially trigger it.
Gerber and Inexperienced expound on this concept:
“Subgroup evaluation needs to be considered exploratory or descriptive evaluation….if the purpose is just to foretell when therapy results might be giant, the researcher needn’t have a accurately specified causal mannequin that explains therapy results (see to elucidate or predict)….noticing that therapy results are usually giant in some teams and absent from others can present necessary clues about why therapies work. However resist the temptation to assume subgroup variations set up the causal impact of randomly various one’s subgroup attributes.”
References
Dijkman B, Kooistra B, Bhandari M; Proof-Primarily based Surgical procedure Working Group. Tips on how to work with a subgroup evaluation. Can J Surg. 2009;52(6):515-522.
Duflo, Esther, Rachel Glennerster, and Michael Kremer. 2008. “Utilizing Randomization in Improvement Economics Analysis: A Toolkit.” T. Schultz and John Strauss, eds., Handbook of Improvement Economics. Vol. 4. Amsterdam and New York: North Holland.
Gerber, Alan S., and Donald P. Inexperienced. 2012. Discipline Experiments: Design, Evaluation, and Interpretation. New York: W.W. Norton
Keele, L., Stevenson, R., & Elwert, F. (2020). The causal interpretation of estimated associations in regression fashions. Political Science Analysis and Strategies, 8(1), 1-13. doi:10.1017/psrm.2019.31
After I first began messing round with code, rounded corners required 5 background photos or an picture sprite probably created in Photoshop, so when border-radius got here onto the scene, I bear in mind everyone pondering that it was the most effective factor ever. Internet designs had been very sq. on the time, so to have border-radius was tremendous cool, and it saved us plenty of time, too.
Chris’ border-radius article from 2009, which on the time of writing is 16 years outdated (wait, how outdated am I?!), consists of vendor prefixes for older net browsers, together with “outdated Konqueror browsers” (-khtml-border-radius). What a time to be alive!
We’re a lot much less enthusiastic about rounded corners these days. In truth, sharp corners have made a comeback and are simply as standard now, as are squircles (square-ish circles or circle-y squares, take your decide), which is precisely what the corner-shape CSS property permits us to create (along with many different cool UI results that I’ll be strolling you thru in the present day).
On the time of writing, solely Chrome 139 and above helps corner-shape, which have to be used with the border-radius property or/and any of the associated particular person properties (i.e., border-top-left-radius, border-top-right-radius, border-bottom-right-radius, and border-bottom-left-radius):
Within the instance above, it’s as simple as utilizing corner-shape: bevel for the snipped corners impact after which border-bottom-right-radius: 16px for the scale.
We will do the identical factor and it actually works with a cyberpunk aesthetic:
Slanted sections utilizing corner-shape: bevel
Slanted sections is a visible impact that’s much more standard, in all probability not going wherever, and once more, helps components to look so much much less just like the containers that they’re.
Earlier than we dive in although, it’s necessary to understand that every border radii has two semi-major axes, a horizontal axis and a vertical axis, with a ‘level’ (to make use of vector terminology) on every axis. Within the instance above, each are set to 16px, so each factors transfer alongside their respective axis by that quantity, away from their nook after all, after which the beveled line is drawn between them. Within the slanted part instance under, nevertheless, we have to provide a special level worth for every axis, like this:
The primary level strikes alongside 100% of the horizontal axis whereas the second level travels 50px of the vertical axis, after which the beveled line is drawn between them, creating the slant that you simply see above.
By the way in which, having totally different values for every axis and border radius is precisely how these cool border radius blobs are made.
Sale tags utilizing corner-shape: spherical bevel bevel spherical
You’ve see these sale tags on nearly each e-commerce web site, both as photos or with rounded corners and never the sharp half (different methods simply aren’t definitely worth the bother). However now we are able to carve out the right form utilizing two various kinds of corner-shape without delay, in addition to an entire set of border radius values:
You’ll want corner-shape: spherical bevel bevel spherical to begin off. The order flows clockwise, ranging from the top-left, as follows:
top-left
top-right
bottom-right
bottom-left
Similar to with border-radius. You can omit some values, inflicting them to be inferred from different values, however each the inference logic and ensuing worth syntax lack readability, so I’d simply keep away from this, particularly since we’re about to discover a extra advanced border-radius:
Left of the ahead slash (/) we have now the horizontal-axis values of every nook within the order talked about above, and on the proper of the /, the vertical-axis values. So, to be clear, the primary and fifth values correspond to the identical nook, as do the second and sixth, and so forth. You’ll be able to unpack the shorthand if it’s simpler to learn:
Up till now, we’ve probably not wanted to totally perceive the border radius syntax. However now that we have now corner-shape, it’s undoubtedly price doing so.
As for the precise values, 16px corresponds to the spherical corners (this one’s simple to grasp) whereas the 48px 50% values are for the bevel ones, which means that the corners are ‘drawn’ from 48px horizontally to 50% vertically, which is why and the way they head into some extent.
Relating to borders — sure, the sharp components would look nicer in the event that they had been barely rounded, however utilizing borders and defines on these components yields unpredictable (however I think supposed) outcomes because of how browsers draw the corners, which sucks.
Arrow crumbs utilizing the identical methodology
Yep, identical factor.
We primarily have a grid row with adverse margins, however as a result of we are able to’t create ‘inset’ arrows or use borders/outlines, we have now to create an impact the place the pretend borders of sure arrows bleed into the following. That is performed by nesting the very same form within the arrows after which making use of one thing to the impact of padding-right: 3px, the place 3px is the worth of the would-be border. The code feedback under ought to clarify it in additional element (the whole code in the Pen is sort of fascinating, although):
ol {
/* Clip n’ spherical */
overflow: clip;
border-radius: 16px;
li {
/* Arrow colour */
background: hsl(270 100% 30%);
/* Reverses the z-indexes, making the arrows stack */
/* Outcome: 2, 1, 0, ... (sibling-x requires Chrome 138+) */
z-index: calc((sibling-index() * -1) + sibling-count());
&:not(:last-child) {
/* Arrow width */
padding-right: 3px;
/* Arrow form */
corner-shape: bevel;
border-radius: 0 32px 32px 0 / 0 50% 50% 0;
/* Pull the following one into this one */
margin-right: -32px;
}
a {
/* Similar form */
corner-shape: inherit;
border-radius: inherit;
/* Overlay background */
background: hsl(270 100% 50%);
}
}
}
Tooltips utilizing corner-shape: scoop
To create this tooltip fashion, I’ve used a popover, anchor positioning (to place the caret relative to the tooltip), and corner-shape: scoop. The caret form is identical because the arrow form used within the examples above, so be at liberty to modify scoop to bevel for those who desire the basic triangle tooltips.
A fast walkthrough:
Don’t eat yellow snow
#tooltip {
/* Outline anchor */
anchor-name: --tooltip;
/* Vital reset */
margin: 0;
/* Heart vertically */
align-self: anchor-center;
/* Pin to proper aspect + 15 */
left: calc(anchor(proper) + 15px);
&::after {
/* Create caret */
content material: "";
width: 5px;
peak: 10px;
corner-shape: scoop;
border-top-left-radius: 100% 50%;
border-bottom-left-radius: 100% 50%;
/* Anchor to tooltip */
position-anchor: --tooltip;
/* Heart vertically */
align-self: anchor-center;
/* Pin to left aspect */
proper: anchor(left);
/* Popovers have this already (required in any other case) */
place: mounted;
}
}
Should you’d reasonably these had been hover-triggered, the upcoming Curiosity Invoker API is what you’re searching for.
Life like highlighting utilizing corner-shape: squircle bevel
The component, used for semantic highlighting, defaults with a yellow background, but it surely doesn’t precisely create a highlighter impact. By including the next two strains of CSS, which admittedly I found by experimenting with fully random values, we are able to make it look extra like a hand-waved spotlight:
We will additionally use squircle by itself to create these fancy-rounded app icons, or use them on buttons/playing cards/kind controls/and so on. for those who assume the ‘outdated’ border radius is beginning to look a bit stale:
Hand-drawn containers utilizing the identical methodology
Similar factor, solely bigger. Type of appears like a hand-drawn field?
Notched border radii are ugly and I gained’t hear in any other case. I don’t assume you’ll need to use them to create a visible impact, however I’ve discovered that they’re helpful for background clipping for those who set the irrelevant axis to 50% and the axis of the aspect that you simply need to clip by the quantity that you simply need to clip it by. So for those who needed to clip 30px off the background from the left for instance, you’d select 30px for the horizontal axes and 50% for the vertical axes (for the -left-radius properties solely, after all).
So, corner-shape is definitely a helluva lot of enjoyable. It definitely has extra makes use of than I anticipated, and little question with some experimentation you’ll provide you with some extra. With that in thoughts, I’ll go away it to you CSS-Tricksters to fiddle with (bear in mind although, you’ll have to be utilizing Chrome 139 or greater).
As a parting present, I go away you with this very cool however fully ineffective CSS Tie Fighter, made with corner-shape and anchor positioning:
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Excessive scalability: AI-first companies can scale with out linear will increase in manpower.
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For founders, positioning as an AI-native firm is about being investable.
What’s subsequent for AI and startups?
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AI-native industries: Solely new markets like AI remedy apps or AI-driven farming will emerge.
Regulation frameworks: Governments will implement stricter compliance for AI ethics, requiring startups to be extra clear.
AI + human collaboration: Probably the most profitable startups gained’t change people with AI however design hybrid workflows.
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The startups that develop would be the ones that see AI as a device for constructing sustainable, future-ready companies.
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Formally generally known as Physarum polycephalum, slime mildew is neither plant, animal, nor fungus however a single-celled organism older than dinosaurs. When looking for meals, it extends tentacle-like projections in a number of instructions concurrently. It then doubles down on essentially the most environment friendly paths that result in meals whereas abandoning much less productive routes. This course of creates optimized networks that stability effectivity with resilience—a sought-after high quality in transportation and infrastructure programs.
The organism’s potential to search out the shortest path between a number of factors whereas sustaining backup connections has made it a favourite amongst researchers finding out community design. Most famously, in 2010 researchers at Hokkaido College reported outcomes from an experiment wherein they dumped a blob of slime mildew onto an in depth map of Tokyo’s railway system, marking main stations with oat flakes. At first the brainless organism engulfed all the map. Days later, it had pruned itself again, abandoning solely essentially the most environment friendly pathways. The outcome intently mirrored Tokyo’s precise rail community.
Since then, researchers worldwide have used slime mildew to resolve mazes and even map the darkish matter holding the universe collectively. Specialists throughout Mexico, Nice Britain, and the Iberian peninsula have tasked the organism with redesigning their roadways—although few of those experiments have translated into real-world upgrades.
Traditionally, researchers working with the organism would print a bodily map and add slime mildew onto it. However Kay believes that Mireta’s method, which replicates slime mildew’s pathway-building with out requiring precise organisms, might assist resolve extra complicated issues. Slime mildew is seen to the bare eye, so Kay’s crew studied how the blobs behave within the lab, specializing in the important thing behaviors that make these organisms so good at creating environment friendly networks. Then they translated these behaviors right into a algorithm that turned an algorithm.
Some consultants aren’t satisfied. In response to Geoff Boeing, an affiliate professor on the College of Southern California’s Division of City Planning and Spatial Evaluation, such algorithms don’t deal with “the messy realities of getting into a room with a bunch of stakeholders and co-visioning a future for his or her group.” Fashionable city planning issues, he says, aren’t solely technical points: “It’s not that we don’t know how one can make infrastructure networks environment friendly, resilient, linked—it’s that it’s politically difficult to take action.”
Reminiscence defines us in so some ways, nevertheless it’s not precisely what we expect it’s.
We are likely to think about reminiscence virtually like a submitting cupboard — a devoted report of the previous we will pull from when wanted. However in keeping with new analysis, reminiscence is much less about storing info and extra about shaping the story of our lives. It helps us make sense of the current and assemble which means out of chaos.
Dr. Charan Ranganath is a neuroscientist at College of California Davis, and the writer of Why We Bear in mind: Unlocking Reminiscence’s Energy to Maintain on to What Issues. His work has reworked how scientists perceive the thoughts’s most mysterious operate. I invited him onto The Grey Space to speak about why forgetting is as important as remembering, how emotion shapes what we recall, why trauma lingers, and the way collective reminiscence can bind — or divide — whole societies.
As at all times, there’s rather more within the full podcast, so hear and comply with The Grey Space on Apple Podcasts, Spotify, Pandora, or wherever you discover podcasts. New episodes drop each Monday.
This interview has been edited for size and readability.
You write that an important message from reminiscence science isn’t “bear in mind extra.” So what’s reminiscence for?
It’s not a vault that shops each expertise. Reminiscence is a useful resource we draw on to know what’s taking place now, to plan, and to anticipate the longer term.
When individuals say, “I’ve a nasty reminiscence,” what do you assume they’re misunderstanding?
If somebody really had a “unhealthy reminiscence,” as in clinically impaired, they couldn’t operate independently. I’ve examined sufferers like that. What most individuals imply is, “I can’t at all times recall what I would like, after I need.” Usually these are high-functioning individuals who count on to recollect every part. That expectation is the mismatch.
However absolutely some recollections are “higher” than others…or is “higher/worse” the flawed body?
That’s the error. Folks conflate “extra” with “higher.” Take extremely superior autobiographical reminiscence: Some of us can let you know what they ate on March 7, 2011, who received a recreation, what the climate was. You may assume they’ve an important reminiscence. However they don’t study a brand new language quicker than anybody else. And lots of report it’s a burden; they will’t cease replaying minor damaging moments. Some even name it a curse. So “extra” isn’t essentially “higher.”
So in my case, I’d say that I’ve a considerably bizarre and annoying reminiscence. I can bear in mind complete chunks of sure books or random trivia, however then I routinely neglect faces and names — issues I really wish to bear in mind. Why?
There are two massive points. First, competitors. Reminiscences compete with one another. If my desk is piled excessive with near-identical papers, it’s laborious to seek out one. Faces are like that: Most have two eyes, a nostril, a mouth; they’re extremely comparable. Names are additionally comparable, and the mapping between a face and a reputation is unfair. “Baker” used to confer with somebody who baked bread; now it doesn’t. So that you’ve obtained comparable inputs and an arbitrary hyperlink. That’s interference.
The opposite difficulty has to do with consideration. Once you meet somebody, your consideration is break up: noise, small discuss, your personal self-consciousness. If the identify doesn’t get a clear “write-in,” retrieval later is shaky. It’s not which you could’t bear in mind names; it’s that the identify was by no means strongly encoded within the first place.
Are you able to give us sensible hacks so we cease embarrassing ourselves at events?
I’ll offer you three fast ones and a pair bonuses:
Make a significant hyperlink. Create a mediator between a facial function and the identify – “Nosy Neil,” “Sinatra-eyes Sam.” Foolish is sweet; weird sticks. You’ll usually bear in mind the act of inventing the hyperlink.
Take a look at your self instantly. Thirty seconds or a minute into the dialog, quietly retrieve the identify. In the event you can’t, ask once more — “Sorry, what was your identify?” That speedy suggestions after a retrieval try is highly effective.
Add distinctive info. A bit extra data helps if it suits collectively. Career, hometown, a enjoyable truth. It offers the identify/face a novel slot.
How does reminiscence change with age? What declines and what holds?
Separate episodic from semantic reminiscence. Semantic is info and data — historical past, vocabulary, experience. Episodic is remembering a particular occasion in time, like the place you set your keys, particulars from a dialog, the distinctive texture of a day.
With getting older, it’s largely episodic reminiscence — forgetfulness, names, particulars — that declines. Semantic reminiscence usually stays strong, even grows. One other piece: retrieval management. Older adults usually know the actor’s identify however can’t pull it up; correct nouns are infamous. That’s tied to government operate within the prefrontal cortex, which steadily declines beginning round 30. It’s not simply storing recollections; it’s regulating consideration and utilizing methods. That’s what slips.
Give me concrete examples of episodic versus semantic in on a regular basis life.
Semantic: you understand what a mortgage is, the principles of baseball, your occupation’s jargon. Episodic: the primary home you toured, the place you parked at the moment, the particular at-bat the place your child hit a double. When individuals say, “My reminiscence is getting worse,” they normally imply, “My episodic reminiscence is much less dependable within the second,” not “I’ve misplaced my data of the world.”
So the throughline is: Reminiscence isn’t free. You must set an intention.
Precisely. Ask: What do I wish to bear in mind from this? In case your objective is to recollect names, begin with that intention and deploy the technique. In the event you assume recollections “come at no cost,” you’ll be upset.
There are research displaying the happiness we get from our selections is set much less by what we skilled and extra by what we bear in mind. Why is that?
As a result of we neglect most particulars shortly. Traditional findings present you’ll be able to lose round 60 p.c of newly realized particulars inside an hour. What stays are beginnings, endings, highs, and lows — the components most helpful for future selections. The “remembering self,” not the “experiencing self,” usually drives satisfaction later.
Are you able to give an instance of how that performs out?
Take into consideration a trip. The experiencing self has 100 small moments — ready in strains, one nice sundown, one unhealthy dinner. The remembering self condenses [it all] to a spotlight reel: the proper swim on the finish (peak), the journey nightmare (low), the final evening’s dinner (ending). That compressed story — greater than the uncooked sum of moments — drives whether or not you say, “That journey was wonderful; let’s return.”
That means the tales we inform ourselves actually matter. We’re continuously updating recollections — they’re not etched in stone — so possibly we will intentionally bear in mind the “proper” issues and be happier.
Reminiscence is extra like a portray than {a photograph}. Van Gogh’s church is recognizably that church, nevertheless it’s additionally his perspective: what he emphasised, what he overlooked, the place he stood, the sunshine he selected. Each time we bear in mind, we create a recent portray — identical occasion, completely different vantage level. That’s why a horrible expertise can change into, later, a comic story. The info don’t vanish; our relationship to them adjustments.
What about trauma? These recollections can really feel not possible to shake. How are traumatic recollections completely different? Are they completely different in any respect?
Emotionally important occasions get biochemical precedence…There’s additionally a distinction between particulars and the visceral punch — that surge of worry or ache. [These memories] depend on partly completely different techniques. What makes trauma really feel “photographic” is normally the emotion, not good element. The objective isn’t to neglect. You wish to bear in mind with out the punch. You wish to preserve the knowledge that retains you protected, with out reliving the risk. Sleep will help “de-charge” recollections; typically it doesn’t, and that’s the place PTSD arises {and professional} care issues.
Music appears to have a particular energy over reminiscence. Why does a tragic track cue unhappy recollections, and a cheerful track cue pleased ones?
Episodic recollections are organized by context — place, time, inside state. Emotion is a part of that context. In the event you’re unhappy now, you’re successfully looking the “unhappy” wing of the library. Music is a potent emotional cue, and it’s tied to id throughout time. We decide music that matches who we’re at completely different phases of life, so it turns into a automobile to revisit who we have been.
You write about reminiscence shaping id, and the way our “self” is a story stitched collectively via reminiscence. Is the self only a reminiscence system holding a narrative collectively?
In some methods, sure. We now have schemas — blueprints for weddings, basketball video games, restaurant scripts — and we’ve self-schemas: tales about who we’re. Once we bear in mind, we don’t simply listing particulars; we sew causes and results: I felt indignant, so I left. Or: She left due to an emergency. These causal hyperlinks are how we make sense of the previous and plan the longer term. The self-schema organizes these hyperlinks throughout time.
If somebody loses their recollections, can they nonetheless be themselves?
Folks with dense amnesia can retain a skinny sense of self — preferences, traits — however there’s usually a flatness. With out episodic reminiscence, there’s little skill to “mentally time journey” — to enliven who you have been or might be. Many amnesic sufferers are “caught” at an earlier age internally; they appear within the mirror and don’t acknowledge the older face. The self can persist, nevertheless it turns into emptier with out the episodic wellspring.
Do political actions do the identical factor — sew collective reminiscence right into a collective id?
Completely. Households have a shared story; nations do too. Once we inform one another these tales, everybody’s reminiscence adjustments — yours, mine, ours. That’s highly effective for transmitting knowledge, and harmful as a result of reminiscence is selective and malleable. Authoritarian regimes know this: change the statues, rewrite the textbooks, prohibit archives, and also you reshape id by reshaping reminiscence.
As we change into extra segregated culturally and informationally, we find yourself with completely different recollections of the identical occasions. That feels fairly unsustainable.
It’s one of many largest threats I see, particularly as AI ramps up scale and velocity. We used to share a restricted set of fact-checked sources. That was imperfect, but additionally constraining. Now it’s simple to consider no matter feels good. Lengthy-form podcasts, Substacks, YouTube — “let all of it air and the reality will emerge” — doesn’t account for a way reminiscence works. We bear in mind what suits our prior beliefs and emotional states, and we neglect base-rate statistics as a result of “nothing occurred” isn’t memorable. Vivid anecdotes drive causal beliefs; numbers don’t.
How does that play out with misinformation?
Two methods. First, salience bias: The vivid story of a vaccine aspect impact outweighs 100,000 uneventful vaccinations. Second, social reinforcement: When a higher-status voice in a gaggle asserts a assured — however flawed — element, it spreads like a social contagion. Folks bear in mind the confidently expressed model later. The repair isn’t one magical supply of reality, it’s cultivating habits that counteract reminiscence’s weaknesses: a number of sources, wait-time earlier than sharing, express uncertainty, and publicity to disconfirming proof.
How malleable is collective reminiscence? Can a rustic rewrite its story as a person can?
Collective reminiscence magnifies the strengths and weaknesses of particular person reminiscence. That’s unhealthy information and excellent news. The unhealthy information is that it’s simple to steer with easy, repeated narratives. The excellent news is that teams can even change course in the event that they construct norms for cross-checking, embody numerous views, and preserve an audit path of sources. That slows the “contagion” impact and creates a richer, extra correct shared story.
So which comes first: recollections or beliefs? Do recollections type beliefs, or do beliefs curate recollections?
Each. We construct beliefs from what we’ve heard, achieved, and remembered. And beliefs filter what we will retrieve and the way we reconstruct it. Folks are likely to recall their previous extra positively than it was and bear in mind themselves extra favorably. Scale that as much as a nation and also you get, “We have been nice; we have been wronged; we have to be nice once more.” The narrative selects the recollections, and the recollections entrench the narrative.
There’s a query right here about reminiscence and forgiveness. Do we’ve to neglect to maneuver on — individually and socially? Or is that value too excessive?
“Forgiving will not be forgetting; forgiving is remembering with out ache.” That line captures it. Fact and reconciliation processes will help — or re-traumatize — relying on how the remembering occurs. Simply dredging up the previous doesn’t heal. The work is to vary your relationship to the reminiscence: retain the knowledge, cut back the toxicity. That’s true in remedy and in society.
What does “altering your relationship” appear to be in apply?
There are a number of components we see throughout approaches. You’ll be able to contextualize causes. Understanding why one thing occurred doesn’t excuse it, however it may possibly cut back the sense of current risk. You’ll be able to have completely different vantage factors; telling the story from a future self, or from a compassionate narrator, shifts emphasis. You’ll be able to add new which means. Extracting what you realized or the way it formed your values rewires the “why this issues” tag. And you’ll goal for protected retrievals. Recalling in protected contexts, then returning to the current, teaches your mind the reminiscence will not be the occasion.
I’d add two issues. First, the intention precept: reminiscence isn’t free, simple, or absolute. Determine what issues earlier than the second — names at a celebration, particulars of a household journey, concepts from a e-book — and use methods accordingly. Second, I’d like to make a plug for science. If we wish progress on Alzheimer’s, trauma, studying, then we’d like sustained assist for analysis. Name your representatives, specific your assist, make your voice heard. These small actions matter.