Paddle Ball Quotes

One outer paddles around on his back, spinning a blue ball on his tummy. I could watch them for hours. Because they get it. They get that life is short and you should just forget the crap and have fun.

Dip into the whip and anal bead pool and bathe in it a little. Let’s give our readers wild sex on a silver paddled platter. Let’s dildo up and jump on the gag ball bandwagon.

Ruth was funny. Her bowling was awful; she just sort of paddled up to the line and dropped the ball. Plok.

I almost never like things some people think everyone likes. I do not like peanut butter and jelly sandwiches. I do not like paddling a kayak in the hot sun. I do not like Santa Claus. I do not like it when someone takes out a guitar and everyone has to sing. I do not like standing in a cheering crowd, particularly if the crowd is watching people whose job it is to throw a ball throw a ball. I do not like a picture of a man on a horse. I do not like it when everybody is doing the same thing and someone is standing with a stopwatch waiting to give a prize to the person who finishes doing it first. I do not like hot chocolate and I do not like wearing a shirt or a hat with the name of a place written on it so everyone knows you have been to that place, and I am not a fan of raisins, so I am often frowning at the music in the supermarket.

Virtuality is the cultural perception that material objects are interpenetrated by information patterns. The definition plays off the duality at the heart of the condition of virtuality—materiality on the one hand, information on the other. Normally virtuality is associated with computer simulations that put the body into a feedback loop with a computer-generated image. For example, in virtual Ping-Pong, one swings a paddle wired into a computer, which calculates from the paddle’s momentum and position where the ball would go. Instead of hitting a real ball, the player makes the appropriate motions with the paddle and watches the image of the ball on a computer monitor. Thus the game takes place partly in real life (RL) and partly in virtual reality (VR). Virtual reality technologies are fascinating because they make visually immediate the perception that a world of information exists parallel to the “real” world, the former intersecting the latter at many points and in many ways. Hence the definition’s strategic quality, strategic because it seeks to connect virtual technologies with the sense, pervasive in the late twentieth century, that all material objects are interpenetrated by flows of information, from DNA code to the global reach of the World Wide Web.

As a teenager with morbid proclivities, my only real social outlets in Hawai’i were the gothic and S&M fetish clubs with names like “Flesh” and “The Dungeon” that took place on Saturday nights in warehouses down by the airport. My friends and I, all uniform-wearing private-school girls by day, would tell our parents we were having a sleepover and instead change into black vinyl ball gowns we ordered off the Internet. Then we’d go to the clubs and get tied to iron crosses and publicly flogged amid puffing fog machines. After the clubs closed at two a.m. we’d go into a twenty-four-hour diner called Zippy’s, invariably get called “witches” by some confused late-night patrons, wash off our makeup in the bathroom, and sleep for a few hours in my parents’ car. Since I was also on my school’s competitive outrigger canoe paddling team, the next morning I would have to peel off the vinyl ball gown and paddle in the open ocean for two hours as dolphins leapt majestically next to our boat. Hawai’i is an interesting place to grow up.

Pretend that you’re the paddle and the rubber ball is your feelings. When something bad happens to us, our natural instinct is to try to push the bad feelings away. It’s like we hit the rubber ball as hard as possible to make it vanish, but the harder we hit it, the stronger and faster the ball bounces back. It’s like the ball doesn’t want to leave us. Grief feelings are like that. They need to sit still and be understood. The good news is that if we talk about your feelings, we can make many negative aspects of the ball disappear.

BEACH BALLS AND LONG SHOTS I WAS WATCHING FROM THE ROOF ONE AFTERNOON WHEN A group of roughly sixteen fully armed insurgents emerged from cover. They were wearing full body armor and were heavily geared. (We found out later that they were Tunisians, apparently recruited by one of the militant groups to fight against Americans in Iraq.) Not unusual at all, except for the fact that they were also carrying four very large and colorful beach balls. I couldn’t really believe what I was seeing—they split up into groups and got into the water, four men per beach ball. Then, using the beach balls to keep them afloat, they began paddling across. It was my job not to let that happen, but that didn’t necessarily mean I had to shoot each one of them. Hell, I had to conserve ammo for future engagements. I shot the first beach ball. The four men began flailing for the other three balls. Snap. I shot beach ball number two. It was kind of fun.

DeepMind soon published their method and shared their code, explaining that it used a very simple yet powerful idea called deep reinforcement learning.2 Basic reinforcement learning is a classic machine learning technique inspired by behaviorist psychology, where getting a positive reward increases your tendency to do something again and vice versa. Just like a dog learns to do tricks when this increases the likelihood of its getting encouragement or a snack from its owner soon, DeepMind’s AI learned to move the paddle to catch the ball because this increased the likelihood of its getting more points soon.

When Diana finally felt ready, they went back to the shelter in Dennis and found a medium-sized mutt, a cheerful fellow with bushy brown fur and eyes like bright black buttons. He seemed to be the result of the union between a corgi and some kind of terrier, and, like Willa, he'd been abandoned, tied up underneath a bridge, starving, with his fur full of mats and burrs and every kind of bug. Diana and Michael brought him home. They brushed the remaining dirt and twigs and burrs out of his coat, and fed him kibble soaked in chicken broth, and tossed a tennis ball for him to fetch. Eventually, his favorite thing became sitting in the prow of a kayak with his back paws on the base of the boat and his front paws on its top, gazing out across the water as Diana paddled.

A ball gag, a bag of zip ties, and a paddle that says SLUT across it. A choker that reads whore.

Pickleball is a sport most people have never heard of but is a big deal in Florida's retirement communities. It is a geriatric version of tennis played with Ping-Pong paddles and a Whiffle Ball on a court similar to a badminton court... Jeff Laughlin, a North Carolina sportswriter, visited a pickleball match and reported that "the absurdity of the name can only be rivaled by the absurdity of the sport itself." Because the rackets are pretty lightweight and the Whiffle Ball is, well, a Whiffle Ball, no on can hit the ball hard enough to get it past an opposing player. The result is a game featuring "long, arduous volleys" that seem to end mainly once someone gets tired of swinging the racket or it's time for lunch. Laughlin characterizes the sport as "incredibly easy and boring," but to aficionados, apparently, it is a great way to work up a thirst for an afternoon martini.

Kyle strained his eyes to the horizon while they paddled swiftly through the fog.

To illustrate this relation, think of a game of table tennis. As the ball hits the table, it will bounce up and down. When we restrain the upward bounce by holding the paddle parallel to the table at a small height, the ball will bounce up and down at a faster rate between paddle and table. If the paddle, the table, and the ball were perfectly elastic, the ball would not lose any energy in the process. The closer to the table we hold the paddle, the more precisely we fix the location of the ball-but at the expense of having it move faster and faster. If we removed both paddle and table in one instant, we would not be able to predict the direction in which the ball moves-up or down. We simply don't know in which direction the very rapidly bouncing ball was moving at the very instant of removal. Consequently, we might say that this process just prior to the removal of table and paddle fixes the location while failing to give us any good information on the velocity; it makes the velocity uncertain. What distinguishes this macroscopic process from the quantum mechanical uncertainty relation is that in principle we can calculate the velocity of the ball at every instant from the initial conditions (how the bounce started) and the boundary conditions (the relative positions of table and paddle). In principle, macroscopic motion is free of uncertainties.

Kahnawake August 1704 Temperature 75 degrees It was worth going into the water just to get away from Ruth’s nagging. Mercy waded in, appalled by how cold it was. Snow Walker towed her around for a minute and then let go. At first Mercy couldn’t take two strokes without having to stand up and reassure herself that there was a bottom, but soon she could swim ten, and then twenty, strokes. Joseph, who had been swimming with the boys, paddled over to admire her new skill. Snow Walker coaxed them to put their heads under the water and swim like fish. Mercy loved it. Wiping river water from her eyes and laughing, she shouted, “Come on in, Joanna!” In front of Snow Walker, she spoke Mohawk. “It feels so cool and slippery inside the water.” Joanna shook her head. “I can’t see where I’m going on land. I don’t want to be blind in water over my head.” “Ruth!” yelled Joseph, in English so she’d answer. “Try it. I won’t pull you under by the toes. I promise.” “Savages swim,” said Ruth. “English people walk or ride horses.” By now, Mercy had flung her tunic onto the grass and was as bare as everybody else. When Ruth scolded, Mercy ducked under the water and stayed there until the yelling was over. “Just wait till you get out, Mercy,” said Ruth. “The mosquitos are going to feast on your wet bare skin.” Mercy translated for Snow Walker, who said, “No, no. We grease to keep the mosquitos away.” Joseph, of course, had been greasing for weeks, but so far Mercy had not submitted. Ruth, unwilling to see Mercy slather bear fat over her nakedness, stalked away. “Good,” said Snow Walker, giggling. “The fire is out. We are safe now.” Mercy was startled. “I never heard you use her old name.” “I don’t call her Let the Sky In,” explained Snow Walker. “She would let nothing in but storms.” Snow Walker’s not such a fence post after all, thought Mercy. “Snow Walker, why have they given Ruth such a fine new name?” “I don’t know. One day at a feast, the story will be told.” “They’ll have to gag Ruth before they tell it,” said Joseph. “She hates her new name even more than she hated her old one.” They got out of the water, racing in circles to dry off, and then Snow Walker rubbed bear grease all over Mercy. “I can’t see you from here, Munnonock,” said Joanna, “but I can smell you.” “Want some?” said Mercy, planning to attack with a scoop of bear grease, but Joanna left for the safety of the cornfields and her mother. Snow Walker went back in to join a water ball team.

There were the twins, faces vacant with concentration as they walloped small red balls attached to paddles. Pat-a-pat-a-pat-a-pat-a-pat-a-pat-a-pat-a-pat-a . . . They’d been jai-alai-ing all this time. Despite himself, Dexter smiled.

Rob Petrie, trying to write a novel, found himself with writer’s block and decided to go to a mountain cabin alone, to get some work done. He needed space, freedom from disturbance. The only scene Amos could remember was toward the end: the wooden crate on the cabin floor overflowing with discarded sheets of paper; Rob wearing a cowboy hat, smacking a ball on a string against a paddle over and over. Rob didn’t put on the cowboy hat or pick up the paddleball at the beginning—oh, no. He tried hour after hour to get something written. The cowboy hat came on by degrees.

There are moments in life when you collide with something that sends you careening down a path from which you can never return. We are ping-pong balls, paddled about by fate and coincidence, doing our best to wrestle back some agency from the forces that move our lives. On our deathbeds, our last thoughts a faint echo: what if, what if, what if.

MABEL’S CHOCOLATE CHIP PUDDING COOKIES Servings: 15 cookies INGREDIENTS • 2 ¼ cups (281g) all purpose flour spooned and leveled • 1 teaspoon baking soda • ½ teaspoon salt • 1 cup (2 sticks; 227g) unsalted butter, softened to room temperature (vegan butter works too) • ¾ cup (150g) light brown sugar packed • ¼ cup (50g) granulated sugar • 1 (3.4-ounce) package instant vanilla pudding mix • 2 large eggs room temperature • 1 teaspoon vanilla extract • 2 cups semi-sweet chocolate chips INSTRUCTIONS • Preheat the oven to 350 degrees F. Line a cookie sheet with parchment paper and set aside. • In a medium bowl, whisk together flour, baking soda and salt and set aside. • In a separate bowl with a hand mixer, or in the bowl of a stand mixer fitted with the paddle attachment, cream the butter, brown sugar, and white sugar on high speed until light and creamy, at least 3 minutes. Do not skip this step.  • Add the dry pudding mix, vanilla and eggs and beat on high for 2-3 minutes, until light and fluffy. • Slowly add half of the dry ingredients to the wet ingredients and turn the mixer on low speed to start so the flour doesn't get everywhere. Turn the mixer up to high speed and mix until combined. Add the rest of the dry ingredients and repeat until dough is just combined. Stir in the chocolate chips with a rubber spatula until incorporated. • Use a large cookie scoop or ¼ cup measuring cup to drop the cookie dough balls onto the prepared baking sheet. Bake for 10-12 minutes, or until slightly golden and just set on the top. Allow to cool on the baking sheet for two minutes then transfer to a baking rack to cool completely.

There was that word again—“perfect.” It was a word that held a lot of charge for me. For years, when someone described me or my life that way, I’d reject or deflect the characterization. “I don’t know what perfect even means,” I’d say. The word felt crass. I never wanted anyone to notice my quest for perfection or to call me out for it. I’d always try to be like a duck: seeming to glide across the water effortlessly but frantically paddling my feet beneath the surface in order to stay afloat. I’d worked so hard to keep everyone happy, to do right by everyone, to never let the ball drop. I was always the first to volunteer, the first to deny my own needs to ensure someone else’s comfort. But where had that gotten me? All that running had left me ragged—“nice but not real,” as Gigi had said. I didn’t want to model that for my daughters. I’d never want them to feel they couldn’t truly be themselves.

Once Marcelino reached the river, he wheeled around and drilled the ball to a little six-year-old who’d lost one sandal and was struggling with his belt. For a few glorious moments, Little One-Shoe was leading his team and loving it, hopping on one bare foot while grappling to keep his skirt from falling off. That’s when I began to glimpse the real genius of the rarájipari. Because of gnarly trails and back-and-forth laps, the game is endlessly and instantly self-handicapping; the ball ricocheted around as if it were coming off a pinball paddle, allowing the slower kids to catch up whenever Marcelino had to root it out of a crevice. The playing field levels the playing field, so everyone is challenged and no one is left out.

DeepMind soon published their method and shared their code, explaining that it used a very simple yet powerful idea called deep reinforcement learning.2 Basic reinforcement learning is a classic machine learning technique inspired by behaviorist psychology, where getting a positive reward increases your tendency to do something again and vice versa. Just like a dog learns to do tricks when this increases the likelihood of its getting encouragement or a snack from its owner soon, DeepMind’s AI learned to move the paddle to catch the ball because this increased the likelihood of its getting more points soon. DeepMind combined this idea with deep learning: they trained a deep neural net, as in the previous chapter, to predict how many points would on average be gained by pressing each of the allowed keys on the keyboard, and then the AI selected whatever key the neural net rated as most promising given the current state of the game.

According to his former sound engineer David Z, Prince once played ping-pong with Michael Jackson in a recording studio and trash-talked the music legend for playing the game “like Helen Keller.” “You want me to slam it?” Prince taunted Jacko, according to Z. “Michael dropped his paddle and held his hands up in front of his face so the ball wouldn’t hit him,” Z recalled. “Michael walked out . . . and Prince started strutting and said, ‘Did you see that? He played like Helen Keller.’” It was no secret, Prince was extremely competitive.4

Sideshows in wooden shacks, peanuts and popcorn, rag-throated barkers, hot babies spilling out of tired arms, petty swindles, puerile divisions, a wooden elephant, a Ferris Wheel, an observation tower, hot sands, squalling children, bathers indecently fat or inhumanly lean shrieking in a crowded and dirty ocean, sweaty citizens, pickpockets picking empty pockets, lung-testers, noisome bicyclists, merry-go-rounds, weight-pounding machines, punching machines, “one-baby-down-one-cigar!” – ring throwing at ugly canes, ball throwing at coons, “guess your weight!” – tintype tents, dusty clam chowder served by toughs in maculate aprons, reliques of old picnics, a captive balloon, squalling babies covered with prickly heat, drooling sots and boozy women with their hair in strings, a boardwalk fetid with sweaty citizens, museums with snake-charmers who could charm nothing else, pretzels, fly-haunted pyramids of mucilaginous pies, shrieking babies with pins sticking in them, spanked by weary mothers and sworn at by jaded fathers, lemonade where overfed flies commit suicide, only to be disinterred by unmanicured thumbs, nigrescent bananas, heel-marked orange peelings, fractured chicken bones, shooting galleries snapping and banging and smelly of powder, saloon odious with old beer slops and inebriates, umbrellas on the sand where gap-toothed bicyclists grin at fat beauties of enormous hip, little girls and boys with bony legs all hives and scratches paddling in the surf-lather with dripping drawers and fife-like shrieks, gaily bedight nymphs proud of their shapes and dawdling about in wet bathing suits that keep no secrets, poor mewling babies that really need to go home, dance halls where flat-headed youths and women with plackets agape spiel slowly in a death-clutch, German bands whose music sounds like horses with the heaves, the steeplechase, where men and women straddle the same hobbyhorse and slide yelling down the ringing grooves of small change, rancid sandwiches, sticky candies made of adulterated sweets and dye, more clam chowder, banging, bumping cars on creaking trestles filled with yowling couples, tangle-faced babies howling toward apoplexy, dusty shoes, obsolete linen, draggle skirts, sweat, fatigue, felicity – that is the Coney Island of long memory.

Adrian gazed past Susie and out at her beautiful garden. He saw ghosts of old afternoons out there, the shadowy echoes of small children, the shrieks of dips in icy paddling pools, the twang and thwack of a ball going round a swing-ball post, half-melted snowmen, barbecue parties that went on into the early hours, failed attempts at handstands, the sand that had sat year after year getting filthy in a plastic trough full of dead leaves and broken toys. Its energy was all still there, hiding among the manicured bushes and shrubs.