#code dasha | Explore Tumblr posts and blogs

batsplat · 7 months ago

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right, by popular demand (a request from @washerdryer), I'm following up this post and just giving a few more details for what you can watch out for to start distinguishing tennis players in your head. how to differentiate the hoards, basically - what makes each tennis player unique. so I've split this up in three basic levels: the numbers, the units, and the shapes

the numbers

so, let's just simplify tennis playstyles as much as it is possible to simplify them, and say we have two types of players: the offensive ones and the defensive ones. the bashers and the pushers. one wants to finish the points on their own racquet, the other one just wants to get the ball back often enough. winning a tennis point is about getting the ball into the court one more time than your opponent. what this means is you can win a point either by putting the ball into a position the opponent can't get it back from, or by waiting until your opponent makes a mistake

when tennis points are coded for purposes of generating stats, point finishes can fall into one of three basic categories:

winner: a ball you hit into the court that the opponent's racquet does not touch, to cleanly win you the point (also includes aces)

unforced errors: a ball you hit that does not make it to your opponent's court, when you could have been expected to make that ball (also includes double faults)

forced errors: a ball you hit that does not make it to your opponent's court, when you have been put under enough duress to 'force' the error

now, you may be wondering how we distinguish between unforced and forced errors, which... it's complicated... it's basically a question of time. if the player had time to reach the ball, if they were in a position on the court where they could hit that ball within a relatively comfortable hitting zone, if they were in a neutral or an offensive position rather than a defensive one, then it's unforced. obviously, this isn't an objective measure, and sometimes whoever is logging in the points is like... either WAY too harsh or far far too generous.... but as a general metric, it's not the worst place to start. now, typically we only get numbers of winners and unforced errors (unless it's a fan-charted match, which we'll get to in a sec), but obviously you can infer the number of forced errors at least. even these basic stats aren't a bad starting point. if someone is playing offensively and taking more risk, it would logically follow that their counts of winners and unforced errors are both higher than for someone playing defensively, right?

let's bring in two players I thought of off the top of my head, and luckily they did not disappoint me here. kasatkina on the left and ostapenko on the right at wimbledon 2021 (this is from flashscore btw):

in the end, penko won this three set match. she won somewhat more points than her opponents - and outperformed her opponent in both service points and return points. what else can these numbers tell us?

well, first of all, penko managed to hit 48 winners vs dasha's *pinches nose* 11. so she tended to play more offensively, or was certainly more effective in doing so. on the flip side, penko hit 48 unforced errors to dasha's 24 - her high risk style inevitably generated more errors than dasha's low risk approach. obviously, in this case that approach took her to victory, despite finishing on double the amount of unforced errors as her opponent. sometimes, the difference between winners and unforced errors is treated as some kind of brute force measure of a match's 'quality' which... I don't love, but of course it's generally a good thing if you're clocking in more winners than unforced errors. dasha ends on (-13) and penko ends on (0), and penko ended up winning the match

what else can we take from this? well, penko came to the net more - and tended to have a very good success rate there. this is a super super rough metric, but I generally feel you want about two thirds success at the net at least, since more often than not you're approaching the net when you're on the offensive and should be winning points. so, y'know, 13 isn't a crazy amount of total net points but it's still fundamentally a job well done. some players don't approach the net at all - and of course it's also reflective of the fact dasha generally wasn't getting herself into positions during the match where she could get to the net. given penko's playstyle, most points will have be conducted on her racquet, where either she bullies around dasha to make an error or she makes an error herself. she's not giving dasha the time to construct rallies in a way that would let dasha gradually navigate herself to the net

and then, of course, there's the most glaring numbers of them all: the serve/return numbers. *pinches nose again* okay. so obviously, the serve is supposed to be a weapon, and especially on grass it is common enough to see 80%, 90% of service points won (if more so on the men's side). these two icons don't believe in that kind of thing, and have even managed to win more points on return than on serve on the most serve-friendly surface. given dasha's impressive returning and her very not impressive serving, I'm guessing this was mainly her fault. there's also a lot of people who will conflate a lot of breaks of serve with a match being 'bad', but those people lack taste. nobody likes a servebot

now, we can add more numbers into the equation. and yes, this is a lot of numbers, but it's all actually quite straightforward, don't run away, we're not going through all of them. this is from ryba vs krej, the wimbledon semi we just had, and is submitted as part of the volunteer-driven match charting project at tennis abstract. what you're seeing are elena's shot types:

so. what you're seeing here is every single shot rybakina hit in that match, and what the result of each and every single one of them was. rybakina hit 257 total shots - of them, 32% ended the point in some way. of those 32%, you get a further breakdown between winners, 11%, forced errors, 8%, and unforced errors, 15%. she hits 133 on the forehand side, and 124 on the backhand - and she was more likely to finish a point on the forehand side than on the backhand side. this is what we would EXPECT to see: for 99% of players, the forehand is a bigger weapon than the backhand. that doesn't mean the forehand is better, and it is often more liable to generating errors, but you can hit the ball harder on that side. the numbers here beyond that are actually a bit quirky... unsurprisingly, rybs was hitting more forehand winners than backhand winners, but in terms of errors the big disparity was in the forced errors tally. now, honestly I don't remember this match enough so this may be bullshit - but just looking at the numbers, my initial guess is that rybs was being forced to run into the forehand corner a lot and krej was extracting errors that way

there's a lot of other details you CAN look at here, but also ryba makes it easy for us by conducting most of her shots from the baseline. 'gs' here stands for 'groundstrokes' so... literally any shot that hits the ground first. she barely went to the net, she wasn't doing much slicing or dropshotting. (I notice the coder made one of her forehand dropshots a forced error, which... I can kinda see how that happens, but to me almost all dropshots are unforced.) some normal volleys, some 'swinging' volleys - also called topspin volleys, which basically looks like your normal groundstroke but without the bit where it touches the ground first

let's quickly bring in what krej was doing:

so, only 23% of shots are point ending, which is what you'd broadly expect - ryba is one of the players with the biggest firepower so she will generally be doing more point ending on her racquet. similarly to ryba, krej has a slight skew to the forehand side, and also has a strong skew towards staying at the baseline. the main thing I'm a teensy bit curious about is how krej ended up with 9 lobs and ryba with only one smash because like?? rybakina is very tall?? but also krej is the prime moonballer on tour, so if that was correctly coded then well done to her lol. the only other thing I wanted to point out is the kind of quirk you can spot through these numbers - krej is one of the big users of the forehand slice in the game, which tends to be an extremely uncommon shot, but she uses 24 times. ryba's 12 also actually feels quite high, but it's also more common to slice when you're getting a slice so that MAY be part of it

tennis has many more numbers that tells you many more things about the matches you're watching - like for instance serve efficacy and how your win % compares on the first serve to the second serve, how often you're getting your first serve in, how often it's an ace, an unreturned serve, a double fault... you'll build up a bit of a frame of reference over time for what counts as 'good' or 'bad' numbers. but, yeah, if one player is hitting a lot of winners and unforced errors and the other one isn't, you can draw some basic conclusions about what kind of player you're watching

the units

okay, so you've got the numbers, which you can also check during matches and will be provided on screen between sets. now we get to the bit where you're actually watching tennis. you basically what to figure out what units, what bits a player's game is composed of. everyone has a serve, everyone has a return, everyone has a forehand and a backhand - but what are they doing with them? how are they using them? where do they tend to win points and where do they tend to lose them? again, part of this will just be about paying attention to what the commentators tell you and try to see if you can spot it for yourself. here are like, some of the basic questions you can watch out for... many you don't need to immediately just spot, but just so you know this is something that is possible to notice:

are they a good server? very tall? good at 'hitting their spots'? do they double fault a lot? can they mix up the spins of their serve - the kick serve (literally kicks up) or slice (slides away from the opponent)? how's their ace rate? how good are they at 'disguising' their serve direction? is it easy to attack their second serve?

how about their return? is there something funky about their return position, are they standing too close or too far away? (most players will be a little bit behind the baseline.) do they change their position depending on whether they're returning first or second serve (typically but not always you'll be closer for the second)? do they get a lot of returns into play? can they attack the second serve? how good are they at 'reading' the opponent's serve?

are they more of an attacking player who attempts to generate their own offence and dominate the point, or a defensive player who is responding to what the opponent is doing and are trying to force them into a mistake? are they a counterpuncher (aka a player who can turn defence into offence)? are they 'aggressive' with their court positioning by standing further forwards? or are they retreating, buying themselves time?

where are they looking to finish points? are they a baseliner and are operating from the back of the court? are they an all courter? are they looking to come in and attack at the net? how's their forecourt game? how are their volleys? do they ever serve and volley (aka immediately follow in the serve to hit the first ball from the net)?

how are their two wings - the forehand and the backhand? how good are they at generating offence from either side? how good are they at defending from either side? is there one side where they're good at hitting 'on the run' shots but not the other? is there one side (typically the forehand) where they can generate more pace but are also more likely to make errors? can they rally consistently from both wins?

what about their variety? now, variety is a bit of a catch all term that describes how many dimensions their game has - but a lot of times it does kinda just mean 'can they slice and volley'. a slice has a different type of spin from your basic ground strokes - especially on the backhand side, it's an important defensive tool, not least to slow the ball down, but can also used offensively. are all the balls they're hitting kinda similar in terms of speed and height and spin? or can they hit their shots flatter, can they change up the spin with slices... can they get forwards and sprinkle in volleys, can they integrate different shots like the dropshot into their game? can they hit high moonballs and find short angles? or is it all just 'see ball bash ball'

how good a mover are they? both in terms of outright speed, up the court and side to side, but also how their balance is, how good they are at anticipating where the opponent will hit the ball, and do on... how flexible are they, can they reach even the unlikeliest balls? how's their endurance? can they defend point after point game after game, or do they eventually falter?

what are they like mentally? do they fold every time they're facing break point? can they actually convert their chances? what are they like at crunch time - late in sets, in tiebreaks, in deciding sets? do they choke away leads? are they clutch under pressure? can they serve out sets and matches?

how do they think they're going to win this match? what's their approach, what's the strategy, what tactics are they deploying, can they adjust these to the match situation? are you watching a player who's thinking their way through rallies, who's following a game plan, or are they just doing whatever?

these aren't questions you need to be engaging with every time you watch a tennis match but, again, they're questions you can ask yourself. not as tricky as it looks!!

the shapes

okay. you get the numbers, you know how the match quite literally is playing out. you've watched the points and can spot what they're actually doing to generate those numbers. now let's go one step further: how are these 'units' being produced? why is it that some serves are better than others? what makes different forehands produce different effects? what makes someone a good mover?

now, obviously, this is like. a massive topic, and I'm not going to give an intro to tennis technique here. but what you really want to do, especially at the start, is spot variance. the photos I included at the top of this post are all from players with techniques that immediately jump out at you for being WEIRD. snigur's forehand looks weird (it's like she's swinging a pan). delbonis' serve looks weird (bizarrely high ball toss). norrie's backhand looks weird (like he's trying to stab someone). obviously, to some extent you can only do this through brute force watching tennis to give yourself a kind of internal, instinctual understanding of what the 'average' shot looks like... but you can also kickstart this process

the thing is, right, you can say that all technique is very complicated, but at the end of the day what it boils down to is you have the bit that happens before they hit the ball, the bit where they're hitting the ball, and the bit after they're hitting the ball. usually, what tennis viewers are responding to when they're watching the sport is some kind of flash aesthetic judgement of that racquet motion. is it a 'short' or a 'long' motion? you can be super concise and compressed with your motion, and only quickly slash at the ball in a direct path, or you can draw a massive loop with your arm like you're simulating a windmill where, after yanking it in a bunch of directions, eventually you make contact with the ball... where is the racquet at the point of contact? generally speaking it should be in front of the body, though how close or far it is can vary quite a lot. and where does the racquet go afterwards?

let's bring in a straightforward example, and check out the forehand techniques of the two most recent women's slam champs - krej on the left and iga on the right

at point of contact, krej has her arm completely extended, while iga's elbow is bent. both are entirely acceptable way of hitting your forehand!! it obviously means both need to move differently to the ball to make sure it's at their preferred distance

if you look at iga's arm, you may also notice all the... bits are kinda pointing in different ways? what you might notice if you watch her a bit is that she draws quite the loop with her forehand, and that a lot of her arm seems to be moving a lot during the stroke. the underlying 'reason' for that is she has quite an extreme forehand grip (called the 'western' grip) which means that the way she holds her racquet essentially requires her to twist around her wrist to make contact with it. so, what's the benefit? why are you doing weird shit with your wrist while hitting the ball? well, iga's forehand also has a lot of topspin - the sharp wrist movement applies an intensive amount of spin to the ball that makes it fly high over the net and bounce high on the other side of the court. it's a very spin-intensive forehand grip - she WHIPS the racquet up to make that ball rotate a shit ton

now, obviously you don't need to get all that just looking at a clip of a player hitting a shot. it's more just... stuff to start paying attention to. how much they're using their arms. how much they're bending their knees. where their racquet is in relation to their body when they hit it. how big the steps they're taking are to get across the court

in conclusion

in conclusion. have fun watching the matches!!

#//#tennis #this is supposed to be an intro guide but (not to be rude) you do feel like a lot of long term fans still can't spot some of this stuff lol #so it's not mandatory. I just think tennis is fundamentally more interesting if you treat it as a puzzle. what's the story of a match #also the quirkier the technique the better

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fixedfour · 6 months ago

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Any explanation for the buzzed blonde look 😅

omg! 🤭 I saw that he said he was just bored

but

the moment i saw his new hair (first of all, I actually gasped), i couldn't help but think that that was so purva ashadha coded of him lol!

literally saw this the same day he cut his hair and, yes! exactly!

It’s giving Mulan, it’s giving: bringing honor to the family lol!

again, if this is true and he’s going through a new supportive dasha—

babes we could really go to the Super Bowl🧎🏻‍♀️

but also, the day we all saw that one tweet from his stylist, Kyle, the "I did it" text, that day the moon was literally in Leo! It could have 100% been an impulsive decision, he has Mars in Leo so a moon transit over Mars can make one just a touch reckless lol! and Leo = hair of course lol! 💛

also can I just add— the Cody Rhodes comparisons killed me a little bit because Cody Rhodes is actually ALSO a Scorpio/Jyeshta moon! The girls are not lying!

#astrology

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piratewithvigor · 1 year ago

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AEW Roster Organized By Age (& events, for context)

Source: Smackdown Hotel

Jan 3 1952 - Jim Ross

Feb 8 1952 - Elizabeth II crowned

May 30 1955 - Jake Roberts

Nov 3 1957 - Laika becomes first animal in space

Nov 7 1957 - Tony Schiavone

May 13 1958 - Velcro is patented

Sep 20 1958 - Arn Anderson

Mar 20 1959 - Sting

Jun 12 1963 - Jerry Lynn

Jul 1 1963 - ZIP codes are introduced in the US

Oct 13 1963 - Don Callis

Nov 11 1963 - Daddy Ass

Apr 14 1967 - Jeff Jarrett

May 9 1967 - Kevin Kelly

Oct 11 1967 - Taz

Dec 6 1967 - First successful heart transplant

May 10 1968 - William Regal

Oct 30 1968 - Luther

Apr 10 1969 - Dustin Rhodes

Jul 16 1969 - Apollo 11 lands the first people on the moon

Mar 24 1970 - Christopher Daniels

Nov 9 1970 - Chris Jericho

Dec 18 1970 - Rob Van Dam

Apr 3 1971 - Alex Marvez

Jun 12 1971 - Mark Henry

Feb 8 1972 - Paul Wight

Oct 12 1972 - Karen Jarrett

Nov 29 1972 - Atari releases Pong

Oct 30 1973 - Adam Copeland

Nov 30 1973 - Christian Cage

Jan 1 1974 - Jim Ross starts his career in wrestling

Sep 23 1974 - Matt Hardy

Oct 8 1975 - Michael Nakazawa

Jan 23 1976 - Nigel McGuinness

May 8 1976 - First roller coaster with a loop in it opens

Oct 4 1976 - Emi Sakura

Feb 28 1977 - Lance Archer

Aug 31 1977 - Jeff Hardy

Nov 9 1977 - Alex Abrahantes

Dec 12 1977 - The Butcher

Mar 17 1979 - Samoa Joe

Aug 1 1979 - Prince Nana

Oct 3 1979 - Johnny TV

Dec 29 1979 - Justin Roberts

May 6 1980 - Colt Cabana

Jun 2 1980 - The Blade

Jul 16 1980 - Excalibur

Nov 17 1980 - Mercedes Martinez

Dec 27 1980 - Claudio Castagnoli

Feb 19 1981 - Shawn Spears

May 22 1981 - Bryan Danielson

Aug 1 1981 - MTV debuts

Dec 12 1981 - Eddie Kingston

Apr 7 1982 - Sonjay Dutt

May 21 1982 - Kota Ibushi

Aug 3 1982 - Nyla Rose

Oct 10 1982 - Tony Khan

Dec 3 1982 - Jake Hager

Mar 1 1983 - Mark Sterling

Mar 19 1983 - Matt Sydal

Apr 1 1983 - Scorpio Sky

Jul 26 1983 - Roderick Strong

Oct 16 1983 - Kenny Omega

Dec 7 1983 - Matt Menard

Jan 26 1984 - JD Drake

Feb 2 1984 - Brian Cage

Feb 17 1984 - Jimmy Jacobs

Feb 23 1984 - Serpentico

Mar 20 1984 - Angelo Parker

May 4 1984 - Orange Cassidy

Jun 30 1984 - Dax Harwood

Jul 1 1984 - PG13 rating is invented

Sep 19 1984 - Renee Paquette

Nov 4 1984 - Ryan Nemeth

Nov 8 1984 - Keith Lee

Dec 26 1984 - Pat Buck

Dec 29 1984 - Anthony Henry

Jan 17 1985 - Mark Briscoe

Feb 13 1985 - Truth Magnum

Feb 26 1985 - Penta El Zero Miedo

Mar 13 1985 - Matt Jackson

Mar 19 1985 - Luchasaurus

Mar 20 1985 - Matt Taven

Mar 23 1985 - CJ

Mar 31 1985 - First Wrestlemania

May 16 1985 - Mike Bennett

May 19 1985 - Malakai Black

Apr 20 1985 - Jay Lethal

Jul 15 1985 - QT Marshall

Aug 6 1985 - Tony Nese

Sep 9 1985 - The Bunny

Dec 7 1985 - Jon Moxley

Dec 25 1985 - Miro

Jan 24 1986 - Vincent

Feb 5 1986 - Madison Rayne

Feb 19 1986 - Shawn Dean

Feb 21 1986 - The first Zelda game is released

Mar 2 1986 - Bishop Kaun

Mar 4 1986 - Dalton Castle

Apr 8 1986 - Big Bill

Apr 22 1986 - Chuck Taylor

Jun 15 1986 - Cezar Bononi

Jun 29 1986 - Serena Deeb

Jul 22 1986 - Thunder Rosa

Aug 21 1986 - Pac

Oct 22 1986 - Taya Valkyrie

Jan 13 1987 - Ian Riccaboni

Feb 4 1987 - Aaron Solo

Mar 1 1987 - Kyle O'Reilly

Mar 7 1987 - Angelico

Mar 10 1987 - Alex Reynolds

Mar 17 1987 - Brody King

Mar 30 1987 - Trent Beretta

May 17 1987 - Cash Wheeler

Apr 21 1987 - Dutch

Jun 18 1987 - Brandon Cutler

Jul 20 1987 - Evil Uno

Sep 5 1987 - AR Fox

Jan 19 1988 - Wardlow

Mar 20 1988 - Josh Woods

Apr 14 1988 - Marina Shafir

Apr 17 1988 - Dasha Gonzalez

Jun 11 1988 - Hikaru Shida

Jul 18 1988 - RJ City

Aug 23 1988 - Metalik

Aug 28 1988 - EJ Nduka

Aug 31 1988 - Athena

Sep 26 1988 - Buddy Matthews

Sep 29 1988 - Rush

Nov 24 1988 - Anthony Ogogo

Jan 25 1989 - Stu Grayson

Apr 10 1989 - Juice Robinson

Apr 11 1989 - Ari Daivari

Jun 14 1989 - Peter Avalon

Jul 5 1989 - Adam Cole

Jul 27 1989 - Nick Jackson

Jul 31 1989 - Max Caster

Sep 20 1989 - Ethan Page

Nov 3 1989 - Andrade El Idolo

Dec 17 1989 - The Simpsons premiers

Aug 17 1990 - Danhausen

Aug 20 1990 - Mark Davis

Sep 30 1990 - Swerve Strickland

Nov 12 1990 - Stokely Hathaway

Dec 18 1990 - Anthony Bowens

Dec 30 1990 - Rey Fenix

Jan 9 1991 - Ruby Soho

Jan 23 1991 - Powerhouse Hobbs

Jan 30 1991 - Toa Liona

Feb 4 1991 - Mike Santana

Apr 22 1991 - Nick Comoroto

Apr 23 1991 - Dr Britt Baker DMD

May 18 1991 - Colten Gunn

Jun 4 1991 - John Silver

Jul 14 1991 - Diamante

Jul 21 1991 - Adam Page

Aug 23 1991 - World Wide Web starts up

Sep 27 1991 - Ortiz

Nov 22 1991 - Brandon

Nov 22 1991 - Brent

Jan 15 1992 - Preston Vance

Apr 7 1992 - Abadon

May 19 1992 - Kip Sabian

Jun 3 1992 - Red Velvet

Aug 17 1992 - Saraya

Sep 14 1992 - Penelope Ford

Sep 15 1992 - Dralistico

Oct 9 1992 - Jay White

Dec 27 1992 - Yuka Sakazaki

Jan 7 1993 - Darby Allin

Jul 28 1993 - Sammy Guevara

Jan 25 1994 - Willow Nightingale

Feb 21 1994 - Ricky Starks

Mar 26 1994 - Paige Vanzant

Apr 12 1994 - Marq Quen

Jun 6 1994 - Lee Moriarty

Aug 26 1994 - Austin Gunn

Sep 16 1994 - Kiera Hogan

Apr 17 1995 - Bandido

Apr 23 1995 - Jamie Hayter

May 29 1995 - Konosuka Takeshita

Jun 6 1995 - Tay Melo

Aug 7 1995 - Kris Statlander

Oct 19 1995 - Toni Storm

Nov 13 1995 - Boulder

Nov 13 1995 - Bronson

Nov 22 1995 - Toy Story is released

Dec 10 1995 - Satnam Singh

Mar 15 1996 - MJF

Aug 11 1996 - Lexy Nair

Oct 26 1996 - Wheeler Yuta

Apr 29 1997 - El Hijo Del Vikingo

Jun 4 1997 - Riho

Jun 15 1997 - Jack Perry

Jul 10 1997 - Isiah Kassidy

Oct 27 1997 - Leyla Hirsch

Dec 13 1997 - Lee Johnson

Mar 9 1998 - Parker Boudreaux

Jul 15 1998 - Anna Jay

Aug 4 1998 - Mariah May

Sep 7 1998 - Daniel Garcia

Dec 15 1998 - Komander

Dec 24 1998 - Kyle Fletcher

May 4 1999 - Hook

Sep 20 1999 - Darius Martin

Oct 2 1999 - Skye Blue

Mar 3 2001 - Dante Martin

Mar 23 2001 - WWF buys WCW

Nov 8 2001 - Julia Hart

Oct 13 2004 - Billie Starkz

Jul 10 2005 - Nick Wayne

Jan 17 2012 - Negative One

#it is now law that whoever's name is higher gets to call whoever's name is lower an infant #or a child #or a baby #as is law whenever you're older than anyone #also if anyone is missing SDH didn't have their birthday #i think I just wanted to roast JR for being old as fuck #AEW #please appreciate this it took days and now I have like 90 tabs open #of wikipedia articles that I want to read after doing the research here

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thesinglesjukebox · 8 months ago

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MIRANDA LAMBERT - "WRANGLERS"

youtube

Use promo code "JUKEBOX" at checkout to get 20% off your first pair of jeans...

[5.36]

Alfred Soto: She didn't write a note or a word for this, and I can tell. It's as if someone typed "Gunpowder and Lead" and "Mama's Broken Heart" into ChatGPT and out came "Wranglers." The brawny production hinders: every rote syllable gets punched up. [4]

Aaron Bergstrom: Miranda Lambert knows her way around a great revenge song, so I have no idea how something as bloodless as "Wranglers" made it past quality control. This sounds like if "Kerosene" was taken over by a hedge fund. [4]

Nortey Dowuona: Someone needs to get Audra Mae on the record on how long Wranglers take to burn. We would all learn a great deal. I mean, they're jeans, how long do they -- wait. [10]

Ian Mathers: See, other jeans burn like this [crowd goes "ooooh"] but Wranglers burn like this [crowd loses it, uproarious laughter]. Wranglers be burnin', amirite folks? [crowd goes absolutely feral with joy, rips up seats, destroys stadium] [6]

Katherine St. Asaph: As a bar, "Wranglers take forever to burn" sounds badass until you think about it -- so you're what, waiting around your no-good ex's house for a couple hours watching yourself fail to commit arson? As a piece of maybe-product placement, it's no "Wrangler butts drive the cowgirls nuts." [5]

Jacob Sujin Kuppermann: Just as schlocky as Chris Stapleton's take on prestige-country RAWK; just as charming, too -- you get the sense that Lambert knows she could do a little better than replicating the feel of "The Chain" for the Taylor Sheridan aesthetic universe, but she's clearly having fun. The drums unfortunately sound like Stadium Arcadium-era Red Hot Chili Peppers, but everything else is gorgeously-wrought in the way that Lambert's best singles sound: it's not subtle and brilliant in the way that "Bluebird" or "Vice" were, but even unsubtle Lambert can be an exceedingly good time. [7]

Wayne Weizhen Zhang: The way that the chorus descends -- as if engulfed by flames and consumed by vitriol -- is satisfying as hell. This one is for your inner pyro. [7]

Taylor Alatorre: One of the purposes of a song like "Wranglers," even if Lambert will deny this, is to demonstrate how much more "real" its performer is than Nashville newcomers like, for instance, Dasha. Which is fine on its own: gatekeeping, in forms both benign and ugly, has been a country tradition since it was still being called "hillbilly music," and it makes more sense to police the authentic in a genre whose very name embeds it in the soil. Lambert certainly sounds more comfortable tossing around the signifiers of battle-scarred, woman-scorned country than Dasha does -- maybe too comfortable, if all the instant "Kerosene" comparisons are any indication. But there's one fatal flaw that "Wranglers" shares with "Austin," and it's the intended wham line in the chorus that serves only to douse the narrative in the cold waters of an anti-climax. Steer your mind away from the familiar abstractions of vengeance and female autonomy, and actually picture what Lambert is asking us to picture here: does a pile of faded blue jeans burning in the desert sun for half an hour longer than expected really sound all that satisfying to observe? Why write a revenge fantasy where it can be assumed that the revenger is impatiently checking her watch every few minutes, waiting for the fantasy to be over already? [3]

Jonathan Bradley: A far cry from “Kerosene” or “Gunpowder and Lead,” what’s supposed to be a barn-burner turns out to be a damp squib due to a muddy mix that chokes the guitar in indistinct haze, taking Lambert’s own voice with it. Soggy kindling results in little heat and so much smoke you can’t make out much of anything at all. [4]

Mark Sinker: A pop song is after all no more than a cluster of commodities circulating within a set of interlinked markets -- so how is a Brit listener my age (me) still faintly rattled when said song’s burden is a straight-up major brand-name placement? As if that’s somehow not allowed (or anyway not really cricket). Blame the BBC’s straight-up long-term ban on any hint of advertising in anything they broadcast, and the penumbras of ideology beneath and alongside that ban, the smoke and the steel shaping my inner mind: it’s like The Who never Sold Out; like the late Nick Kamen kept his laundrette Levis on to Marvin’s “Grapevine,” like Sigue Sigue Sputnik never sold literal ad-space slots on their first LP (for L’Oréal, EMI, i-D magazine and more); it’s like Run DMC went barefoot. I escaped it enough that Vybz Kartel, Gaza Slim and Popcaan excitedly hymning their nice new furry suede shoes is one of my all-time favourite Jukebox entries. Sadly this is no “Clarks”: after a misleading Morricone lens-flare it slumps quickly into charred serge and claggy ash. No ethical immolation under capitalism! [5]

Michael Hong: If this is Miranda's attempt at returning to being the shit-talker and the fire starter, well, it sounds like she's got her kindling stacked too neatly and forgotten her matchbook at home. [4]

[Read, comment and vote on The Singles Jukebox]

#miranda lambert #music #country #country music #music writing #music reviews #music criticism #the singles jukebox #Youtube

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blessed1neha · 2 years ago

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MAHADASHA and PAST KARMAS

MAHADASHA and PAST KARMAS (This special post was written in a spiritual attitude, thus it has a divine touch. In order to fully grasp this piece, please take your time and read it twice or three times in a relaxed state. Today, we'll talk about some fascinating facts concerning the Dasha system. But first, let's comprehend a little KARMA theory. Why were we born into a certain family? The distribution of past KARMA from previous life or lives was appropriate for that family's environment, according to the answer. Why are we born under the Mesh, Vrushabha, Mithun, and other astrological signs? This is directly related to our prior birth as well.There is a connection to a prior life when you are born in a certain star or nakshatra. Our KARMA is distributed by the MOON. Our MANAS or ASTRAL BODY is continued from countless prior births, and the SUN is the SOUL or witness.Throughout our journey from conception to death, our ASTRAL BODY, or, or a coded language, records all of the good or ill DEEDS we perform with our physical body and powerfully create with our lower Mind. After passing away, our ASTRAL BODY is divided and rests in the ASTRAL PLANE while we wait for the right family and setting in which to enjoy or suffer the results of our KARMA. ( मनु स्मृति ) We will now concentrate on Nakshatras. The zodiac has a total of 27 Nakshatras. AADHAN Group, KARMA Group, and BIRTH Group. These 27 Nakshatras are the possible birth constellations. Our Rishis believe that a person can live for a maximum of 120 years, and they divide this lifespan into nine Nakshatras starting with the birth Nakshatra using the Vimshottari dasha system.Let's now discuss in more depth. Our BIRTH Nakshatra is the one in which we are born. This nakshatra degree is closely related to our OLD birth. In a certain Mahadasha, Antardasha, and Pratyantar dasha on earth, we were born and took our first breath. Along with the Antar dasha Lord or Sub Lord, the Birth Nakshatra Lord or Main dasha Lord is the MAIN controller of our life journey on this Earth planet. They are BOTH given the responsibility of giving birth at a specific time. Our MAIN god is the Dasha Lord. These two planets will leave a lasting impression on our minds for the duration of our lives.Also owned by the same MAIN god or planet are the nakshatras for the tenth (KARMA) and nineteenth (AADHAN).For instance, the Moon is your BIRTH planet or deity if you were born in Rohini. Hasta (KARMA) and Shravan (AADHAN) are likewise owned by the same moon.If we live 120 years, our trip on Earth begins in the birth nakshatra and finishes in the ninth nakshatra. However, as the seventh Nakshatra is known as Naidhan or Death Nakshatra, death typically occurs during this dasha. Most people pass away during their seventh Dasha.As we have mentioned, the 10th is a KARMA Nakshatra and the 19th is an AADHAN Nakshatra. What does this imply? Each of the three groups is connected to the others.When we begin our lives from the Birth Group Nakshatra, we receive both the good and terrible results of our prior karma within the first nine Dasha Antardashas. The dashas and antardashas of the BIRTH Group are being carried out in accordance with our prior karma, which is why we are experiencing all the positive possibilities, environments, happiness, and sorrows along the way.However, 9 Nakshatras of the second KARMA Group, which spans from the tenth to the eighteenth Nakshatras, are also active at the same time. Once the fruits of the first Group are released and we are set free from our karmic obligations, this Group decodes all previous karma from the ASTRAL BODY. Past-life cassettes or CDs are KARMA Group. This Group controls the BIRTH Group and determines how the dashas will play out.The 3rd AADHAN Group is also functioning at the same moment, and everything we think, desire, and do with our physical bodies is recorded there beginning with the 19th AADHAN Nakshatra in a pictorial form but in a coded language on the ASTRAL BODY of our this new Birth.Let's go into further detail about this. Let's say you were born under the Rohini Nakshatra and are currently in the Mars Venus dasha. indicates that you are traversing Mrugshirsha Nakshatra. What happens next? According to your Karma, which was recorded in the Chitra Nakshatra of the KARMA Group, you are either enjoying or suffering during this time, and anything you desire or do, whether good or evil, will be recorded in the Dhanishtha Nakshatra of the AADHAN Group.If your wife decides to divorce you due to excessive fighting during the Mars-Venus dasha in Mrigshirsha, it means that you caused excessive suffering to your husband or wife during the Mars-Venus dasha in Chitra Nakshatra in a previous birth, and that karma was recorded at that time, giving you the same result in this birth.In a similar vein, anything you are feeling or doing physically during the Mars-Venus stellium will only result in the stellium during the next birth when Dhanishtha Nakshatra is triggered in a birth group.The KARMA theory is this. Every dasha antardasha transmits joy or suffering that was chronicled in a previous existence in the Karma Group Nakshatra. Because our entire life's path is preserved in our ASTRAL BODY, the outcomes of the Dasha Antardasha are not as uniform as they are in books. The birth chart is created by fate based on our karmas, and all of the planets carry the weight of our past deeds and produce results in accordance with their dashas. Everything has been planned out.I want to add one more item to this. Jupiter, also known as Brihaspati, is intimately connected to God and possesses the 5th and 9th aspects, allowing him to observe both other groups when he is in one group during transit.As a result, Jupiter has the ability to use the benevolent forces that are solely within his control, such as,,,,, and, to lessen the severity of the bad karmas that are active at a given dasha.

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justamonkeyonautopilot · 5 months ago

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Can't remember if it was last year or the year before I did this or both. But yesterday on my way to work I saw that Apple has already shared their Replay 2024 list. So I'm going to post it here to see if it has changed any by December. As once again I'm curious. I also noticed through this that some of the songs listed on here I have only listened to once so I have no clue how they generate these lists. Some I understand they're on there from the dance show back in February because I'd play them on repeat to practice.

Here we go then:

Texas Hold 'Em - Beyonce

Anatomy - Kenzie

Feminine Rage - Peggy

The Code - Nemo

A Bar Song (Tipsy) - Shaboozey

Stick Season - Noah Kahan

Marameo - Alessandra

I Choose Violence - Jax

Houdini - Eminem

Austin (Boots Stop Workin') - Dasha

90s Kids - Jax

The Me I Was - Kenzie

Sos - Soap

Heather On The Hill - Nathan Evans

Seventeen - Marina and The Diamonds

Born This Way - Lady Gaga

Get the Party Started - P!nk

Disconnect - Becky Hill & Chase & Status

Attention - Todrick Hall

As Long As You're There - Stuart Matthew Price (Carrie Hope Fletcher and Oliver Ormson)

Hayloft II - Mother Mother

Someone You Loved - Lewis Capaldi

Sail - Awolnation

A Song For Chelsea - Jax

Where Do All The Good Kids Go? - Maddie Zahm

Lost On You - LP

Naughty - Matilda Movie Soundtrack

Beautiful Things - Benson Boone

Anybody Have A Map? - Dear Evan Hansen

Something Just Like This - The Chainsmokers & Coldplay

Join Us For A Bite - JT Music

Kang Kang Kang (DJ) - Half Ton Brothers

The Gambler - Kenny Rogers

Dance With Me Tonight - Olly Murs

Ob-La-Di, Ob-La-Da - The Beatles

Gangsta's Paradise - Coolio

Whistle (While You Work It) - Katy Tiz

Ava - Natalie Jane

Airplanes - B.o.B.

Found A Way - Drake Bell

I Just Can't Wait To Be King - The Lion King

Freedom - Pharrell Williams

Like My Father - Jax

Girl In The Mirror - Megan Moroney

W.I.T.C.H. - Devon Cole

The Room Where It Happened - Hamilton

Proud Mary - Tina Turner

I'm Gonna Be (500 Miles) - The Proclaimers

You'll Be Back - Hamilton

Youngblood - 5 Seconds of Summer

Wasn't Expecting That - Jamie Lawson

Hit The Road Jack - 2WEI & Bri Bryant

I Say No - Heathers

Bang Bang - Jessie J, Ariana Grande & Nicki Minaj

I Got Up - Overnight Lows

Pretty Devil - Alessandra

Working For The Company - Willy Moon

We On Top - Photronique & Shari Short

Pretty Little Black-Eyed Suzie - Guy Mitchell

21 Reasons - Nathan Dawe

Stargazing - Myles Smith

Below The Surface - Griffinilla

Kiss An Angel Good Morning - Charley Pride

Barry and Freda - Victoria Wood

Circle The Drain - Katy Perry

I Kind of Relate - Drake Bell

Helium - Sia

Teir Abhaile Riu - Celtic Woman

Bring Him Home - Ramin Karimloo

One Day More - The 2020 Les Miserables Staged Concert Company

I'm Not Here To Make Friends - Sam Smith

Dark Horse - Katy Perry

Don't Forget - Demi Lovato

It's Goin' Down - Descendants

I Do Not Hook Up - Kelly Clarkson

Break The Ice - Britney Spears

Candyman - Christina Aguilera

Vampire - Olivia Rodrigo

Hey Mama - David Guetta

Karma - JoJo Siwa

Beat Again - JLS

I Think I'm In Love - Kat Dahlia

Diva - Beyonce

Paint The Town Red - Doja Cat

We No Speak Americano - Yolanda Be Cool & DCUP

Boyfriend - Alphabeat

Get Stupid - Aston Merrygold

I Put A Spell On You - Annie Lennox

Let Me Down Slowly - Alex Benjamin

Can't Be Tamed - Miley Cyrus

They Just Keep Moving The Line - Carrie Hope Fletcher

Kings & Queens - Ava Max

Achy Breaky Heart - Billy Ray Cyrus

She Likes - Forever the Sickest Kids

Boyfriend - Dove Cameron

The Hanging Tree - Rachel Zegler

Hound Dog - Elvis Presley

42nd Street - 42nd Street

La Vecinita - Don Omar

You Matter To Me - Carrie Hope Fletcher

(After going through them again, I genuinely don't remember listening to half of them anytime recently - it's not that I don't listen to music either I have a playlist I play in the car when I'm driving and the songs off that aren't on this list)

#Personal #Music #Apple Replay #2024

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govindhtech · 6 months ago

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AI Act EU First Regulation On Artificial Intelligence

EU AI Act

What the AI Act EU has already altered for companies

The AI Act of the European Union went into effect on August 1. Among the first artificial intelligence legislation to be implemented in one of the biggest marketplaces in the world is the AI Act EU.

What changes can businesses expect?

Describe the EU AI Act

The first significant market to establish new AI regulations is the European Union (EU). As stated by EU authorities, “the goal is to establish the EU as a worldwide Centre for reliable AI.”

What is the EU AI Act

Using a risk-based methodology, the AI Act groups applications depending on how likely they are to endanger people’s safety and basic rights. Rules for general-purpose AI (GPAI) models, criteria for developing and implementing particular high-risk AI systems, and a ban on specific AI practices that are judged to pose unacceptable risk are some of the most significant clauses.

Known as the “minimal risk” category, AI systems that do not fit into any of the risk categories outlined in the AI Act EU are exempt from its restrictions, however some may still need to adhere to other applicable laws and transparency standards.

According to Bruno Massot, Vice President, Assistant General Counsel, and Head of Legal at IBM Europe, “it is a form of regulatory pragmatism that aims to adapt constraints with the level of risk.”

Certain AI applications that pose a threat to people’ rights will be prohibited under these new regulations. Predictive policing, emotion recognition in the workplace and classroom, untargeted facial picture scraping from the internet or CCTV footage to build facial recognition databases, and biometric categorization systems based on sensitive features are some examples.

European Union AI Act

On April 22, the European Parliament passed the AI Act EU, and on May 21, the EU Member States did the same. The law went into effect on August 1st, after several clauses were gradually implemented. It was first published in the European Union’s Official Journal on July 12th.

EU Act On AI

The timeline for the EU AI Act will move extremely quickly

Everything is not surprising, even though everything is happening quite quickly. It’s long been known about the drafts. Given how swiftly technology is developing, it’s also critical to move quickly, according to Massot.

Sixth month: Prohibitions against AI techniques go into effect. Codes of practice come into effect in month nine. General-purpose AI regulations, including governance, take effect in month twelve. The high-risk AI system regulations will go into force after 24 months. In conclusion, the regulations pertaining to AI systems that are either products or safety components of products subject to special EU legislation will come into effect 36 months following the laws’ introduction.

The EU AI Act

Which actions ought firms to take?

Dasha Simons, Managing Consultant, Trustworthy AI at IBM, notes that “there is a sense of urgency.” “Somethings taking two or three years to prepare could appear excessive. However, it’s not that lengthy if you’re a global or multinational company with numerous AI systems located all over the world.

Where should they begin then? According to Simons, the first stage is to decide which regulations will be relevant to your company.

The AI Act EU lays out distinct guidelines and terminology for importers, providers, and delayers. You will have to adhere to distinct regulations based on your company’s function, according to Simons. Are you purchasing models and merely giving them a new name without altering the model itself? Or are you really adjusting the model quite a little bit? Essentially, this is the initial phase.

The second stage would be to ascertain which AI systems are in operation at your company and the degrees of risk attached to each one.

“Knowing where you want to focus at first is important,” says Simons.” Many businesses have no idea what kind of AI models and systems they have in development or in production.”

Businesses can identify their priorities by completing this assessment, which evaluates the high-risk systems after the prohibited ones.

“This will assist in identifying the procedures that must be implemented when new AI systems are introduced, and ensure that compliance with the AI Act EU is done proactively rather than reactively.”

According to Simons, the rules specify that companies must use AI strategically and that the C-suite must actively participate in this discussion.

You require technical know-how; in addition, it can be helpful to have a Chief Privacy Officer with experience implementing GDPR. While it’s important to have that knowledge available, Simons also believes that the C-level should establish accountability and strategy.

What effects will the EU AI Act have on companies?

The EU aims to set a global AI development standard. The GDPR of 2018 gave the EU a comprehensive data privacy and security law.

Parliamentarian Dragos Tudor ache, the AI Act’s main negotiator, called it “the first regulation in the world that is laying a clear roadmap on a safe and human-centric development” at a news conference.

Regarding the use of AI, numerous policies are being adopted globally

“Because it would be difficult [for businesses] to develop different systems with diverging restraints, consistency is important,” adds Massot.

An interesting development will be the requirement for organizations and enterprises operating in the EU to teach their users or workers about AI, according to Hans-Petter Dalen, IBM’s EMEA Business Leader for Watson and embeddable AI.

It’s interesting to note that there is a section on AI literacy in the AI Act EU. Hence, in order to use AI in the EU single market, any business or organization must provide a specific degree of education to both its users and workers. According to Dalen, “raising the fundamental understanding of what AI is is a very desirable thing. They don’t know what the level is yet.

“HR systems, which can currently screen resumes and suggest applicants, are one example in that regard. There are seven crucial requirements that must be met in order to proceed with that high-risk use case. Are you knowledgeable enough about artificial intelligence (AI) as the person purchasing that program to know what questions to ask about the algorithms? asks Dalen.

EU AI Act High Risk

The technological criteria that the AI Act will mandate remain mostly undetermined

The regulation itself lays out seven very loosely worded standards that must be met in order to comply with high-risk use scenarios. Ten requests for technical standards have been generated by those seven requirements, and two European standard decision organizations are currently working on developing those requests, says Dalen.

They anticipate that putting the technical standards into practice will be the quickest and least expensive way to achieve conformity, as they will provide us with clarity on the actual requirements from the regulation.”