#a phrase my grandma thinks should be its own idiom

[tj-crochets]

Accidentally mixed idioms today and said "wait your damn horses" so work is going well lol

#tj talks about work #hold your horses and wait your turn combined to create: #a phrase my grandma thinks should be its own idiom #just glad I said it to myself and not to a contractor tbh

[topfygad]

Travelmag – An immersion course in Spanish in Puebla, Mexico

I’ve dabbled with studying Spanish for greater than a decade. Mexican cleaning soap operas entertain me. Spanish songs entice me. Ordering tacos and tamales in Espanol makes the consuming doubly delicious. And going to varied Spanish colleges south of the U.S. border make my stays there all of the extra enjoyable. However the one faculty that basically will get severe about its college students mastering Espanol is situated in Puebla, the fourth largest metropolis in Mexico and about 100 km east of Mexico Metropolis. Spending three weeks at Spanish Institute of Puebla taught me an excessive amount of the language with a plentiful combination of tradition and laughter blended into the concoction.

Let me put to relaxation any scary tales about flying out of Tijuana, Mexico. It’s a breeze. Lengthy-term parking might be had for as little as $5 a day, and there’s no visitors jam if you happen to’re dropped off on the U.S. aspect of the airport entrance. Passengers verify in there and easily stroll over a bridge to the Mexican aspect of the airport for the gates. Volaris flies on to Puebla for about half the worth as planes coming from Los Angeles or San Diego to Mexico Metropolis with a bus switch on to Puebla.

My hat’s off to those that decide to stick with a bunch household whereas in Puebla. About half of the scholars on the Institute achieve this. The others, and I’m one among them, desire a tad extra privateness or maybe luxurious and keep at both a resort or an Airbnb. The varsity operates a 3.5 star resort about 4 blocks from the varsity. I selected to remain at El Carmen, an Airbnb boutique resort that labored out completely. The room was charming, had entry to a kitchen, and three entry mixture codes to make sure security and privateness. It additionally didn’t harm that it was kitty-corner from a park, a block away from a church that held live shows, two blocks away from the varsity, had a couple of dozen improbable taco joints inside a block, by no means ran out of sizzling water, and was solely 5 blocks away from the cathedral and zocalo. (For extra info, go to Heroica Puebla de Zaragoza on Airbnb for Puebla, Mexico.)

Nationwide Geographic, with loads of good purpose, acclaimed Spanish Institute of Puebla as a mannequin faculty for educating Spanish. About half of the scholars take small group courses and the others have non-public classes. I opted for the group class. I took a placement examination earlier than coming to the varsity after which one other conversational placement analysis my first morning there. The location was excellent! I used to be matched with two different girls from the states who love tinkering with studying Spanish but certainly are removed from having a deal with on it. Tremendously, I respect that we have been positioned with others with related backgrounds and ages. There was one other class of our identical stage with youthful college students. Reality be instructed, we don’t study a language the identical method and on the identical pace. The varsity acknowledges this and locations its college students nicely.

College students make a pledge to talk solely Espanol whereas on the faculty. College officers plaster the pledge on the entry wall in case one slips. Once I forgot and requested the secretary a query in English, she politely ignored me till I remembered my pledge and plodded away in Spanish. Our instructor was younger, enthusiastic, and affected person. Guadelupe taught us the subjunctive, allow us to speak her into displaying us Spanish motion pictures with Spanish subtitles, sped up our combining verbs with oblique and direct objects, and launched many idioms. My favorites turned out to be “Que te pasa, calabaza?—What’s up, pumpkin?” and “Fresco como una lechuga!—It’s as contemporary as lettuce!” We spent 4 hours within the morning at school with a thirty minute break within the center to regroup and never lose our sanity, had a scrumptious lunch at a selection of two locales, after which met one-on-one our guides for 2 hours to strengthen our classwork, see town’s websites, or grasp one thing new—no matter our needs occurred to be. (For extra info, see https://ift.tt/37FND3l)

All work and no play makes Juan fairly a boring hombre, and Spanish Institute is aware of this nicely. Two or thrice every week they manage excursions: to Mexico Metropolis, Teotihucan, native pyramids and ruins, Cholula for its phenomenal church buildings and ruins, and Tlaxcala for its artisan museum and metropolis murals. I used to be in Puebla for Day of the Lifeless so we visited a city identified for its residents who suffered a loss of life of a member of the family through the previous yr. They opened their houses and hearts to guests to share in recollections of the deceased. We introduced flowers and candles to the altars they set as much as commemorate their expensive ones. Within the close by city heart carnival video games, craft stalls, and firecrackers testified of vivacity as loss of life and life mingled into one.

Whereas in Puebla, I got here to grasp the Spanish phrase for “snigger” fairly nicely. “Reir” means “to snigger,” “reirse” is its reflexive kind, “la risotada” is “a loud snigger,” “risible” is “laughable,” “risa” is “laughter,” and “Que risa! is “What amusing!” An absolute Gotta do whereas in Puebla is attend a lucha, a wrestling match that solely Mexico is aware of how one can do. Purchase a superb seat for Monday night time’s efficiency on the Enviornment so you may see nicely the antics, costumes and grins of the wrestlers. Who is aware of? You would possibly even have one or two of them land in your lap as they’re tossed from the ring. Positively, you’ll “soltar la risa” or in English translation, “Burst out in laughter.”

Visiting nice museums (particularly The Amparo, Biblioteca, and Museo de la Revolucion) will assist provide the wanted strolling train, plus loads of historic info and views of town. You should definitely browse El Parian, an arts and crafts market inside strolling distance of the cathedral. And church buildings, they appear to be on nearly each block of town. Puebla Cathedral took 300 years to finish. To say it’s enormous is an understatement; its bell tower is the tallest in Mexico; its form is of a Latin cross and accommodates 5 naves; it has fourteen chapels, two organs, and quite a few statues of saints and angels made from onyx. One other favourite is The Church of Santo Domingo the place pictures and parts symbolize The Virgin Mary. Talavera pottery and Puebla artistry is sort of synonymous. It’s bought all through the city, however I like to recommend visiting the place the objects are made. I did this one afternoon with my information and loved totally studying of the manufacturing, viewing murals depicting Dante’s Seven Lethal Sins, and shopping for treasures of tile.

Let’s say you wish to do greater than stroll and think about websites so how about horseback using? It proved to be a spotlight for me. Spanish Institute organized for 3 of us to spend a Saturday with horseman Edmundo and his spouse Patricia in Calpan, a fairly city down from the Popocatepetl volcano. We have been picked up on the faculty and drove for about 45 minutes to their beautiful dwelling in Caplan. There we had a scrumptious breakfast, adopted by a couple of hours of knowledgeable instruction by Edmundo. His love for his horses rivals his charisma and his pleasure for sharing his ardour with others. I opted for a reasonably leisurely experience, zig zagging out of trails, riverbanks, and city. Others selected some galloping and some bravo maneuvers. Edmundo videotaped my maneuvering of my horse, Princessa, proving to household and associates again dwelling that I can habla the Espanol and management a horse all on the identical time! Within the late afternoon we visited their neighbors who opened up their dwelling to commemorate Day of the Lifeless, had a scrumptious dinner of mole, and returned again to Puebla early night. (Extra info might be discovered both via Spanish Institute of Puebla or on Airbnb, searching for Patricia and horseback using underneath “Issues to Do.”)

Did I simply point out mole? There is no such thing as a such factor as a foul meal in Puebla. And price? Eating places are insanely low cost! Town’s specialty is mole poblano. To me, improbable is an understatement for mole. The sauce is a mix of about twenty components: chilies, sesame seeds, aniseeds, peppercorn, cloves, thyme, marjoram, bay leaves, cinnamon, hen inventory, fried bread, tomatoes, and, oh sure, did I point out CHOCOLATE?! The chocolate soothes the chilies, and the chilies sharpen the chocolate. In different phrases, it’s to die for! Restaurante Fonda de Santa Clara at 6 Oriente 12 Centro de Puebla would possibly simply must kick you out at closing time if you happen to go there. Andrea is the supervisor; her grandmother bequeathed her this restaurant whereas leaving others to seven different grandchildren. The cooks are all moms as grandma believed {that a} mom’s love transcends into her cooking. I took a cooking class from Andrea, together with a household of three visiting Puebla from Germany. They have been a pleasant group, particularly after they admitted that mole poblano even tops weinersnitzchel. (Extra info might be discovered by stopping by the restaurant or wanting on Airbnb “Issues to Do—Cooking Courses” in Puebla.)

I’ve develop into fairly hooked on having massages wherever I roam. Goa, India, is tough to beat with its number of remedies. Thailand massages knock the knots proper out of you. Filipino massages down on the seaside lull one to sleep with the rhythm of the waves. And the massages in Puebla have their very own distinctive type. Lila is a professional at Mayan massages of the 4 parts. She will mix stretching, bending, and stress-free multi functional session. Her secret is steadiness as she light connects the power between physique and thoughts. Reader beware: you will have a therapeutic massage nearly on daily basis. Actually, she’s simply that improbable at her ability. (If in Puebla, contact her by telephone at 22-25-46-45-47 to arrange an appointment.)

No, I didn’t develop into fluent in Spanish with my three weeks in Puebla. Admittedly, I’ve a really lengthy methods to go if I ever get there. I returned dwelling to Thanksgiving with household after which Christmas with continuous actions so my language immersion has taken a backseat. I’m assured that after the New Yr rolls round, I’ll return to my considerably devoted pupil endeavor. Till then, I’ll simply must cherish my recollections of escuela, amigos, lucha, excursiones, museos, Iglesias, caballos, comida, y masajes. And that’s rather a lot to maintain me feliz!

Copyright © 2019 Bonnie Lynn

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#IFTTT #Cheapr Travels

[smartwebhostingblog]

Autocomplete Presents the Best Version of You

New Post has been published on http://webhostingtop3.com/autocomplete-presents-the-best-version-of-you/

Autocomplete Presents the Best Version of You

Type the phrase “In 2019, I’ll …” and let your smart­phone’s keyboard predict the rest. Depending on what else you’ve typed recently, you might end up with a result like one of these:

In 2019, I’ll let it be a surprise to be honest. In 2019, i’ll be alone. In 2019, I’ll be in the memes of the moment. In 2019, I’ll have to go to get the dog. In 2019 I will rule over the seven kingdoms or my name is not Aegon Targareon [sic].

Many variants on the predictive text meme—which works for both Android and iOS—can be found on social media. Not interested in predicting your 2019? Try writing your villain origin story by following your phone’s suggestions after typing “Foolish heroes! My true plan is …” Test the strength of your personal brand with “You should follow me on Twitter because …” Or launch your political career with “I am running for president with my running mate, @[3rd Twitter Suggestion], because we …”

Gretchen McCulloch is WIRED’s resident linguist. She’s the cocreator of Lingthusiasm, a podcast that’s enthusiastic about linguistics, and her book Because Internet: Understanding the New Rules of Language is coming out in July 2019 from Penguin.

In eight years, we’ve gone from Damn You Autocorrect to treating the strip of three predicted words as a sort of wacky but charming oracle. But when we try to practice divination by algorithm, we’re doing something more than killing a few minutes—we’re exploring the limits of what our devices can and cannot do.

Your phone’s keyboard comes with a basic list of words and sequences of words. That’s what powers the basic language features: autocorrect, where a sequence like “rhe” changes to “the” after you type it, and the suggestion strip just above the letters, which contains both completions (if you type “keyb” it might suggest “keyboard”) and next-word predictions (if you type “predictive” it might suggest “text,” “value,” and “analytics”). It’s this predictions feature that we use to generate amusing and slightly nonsensical strings of text—a function that goes beyond its intended purpose of supplying us with a word or two before we go back to tapping them out letter by letter.

The basic reason we get different results is that, as you use your phone, words or sequences of words that you type get added to your personal word list. “For most users, the on-device dictionary ends up containing local place-names, songs they like, and so on,” says Daan van Esch, a technical program manager of Gboard, Google’s keyboard for Android. Or, in the case of the “Aegon Targareon” example, slightly misspelled Game of Thrones characters.

Another factor that helps us get unique results is a slight bias toward predicting less frequent words. “Suggesting a very common word like ‘and’ might be less helpful because it’s short and easy to type,” van Esch says. “So maybe showing a longer word is actually more useful, even if it’s less frequent.” Of course, a longer word is probably going to be more interesting as meme fodder.

Finally, phones seem to choose different paths from the very beginning. Why are some people getting “I’ll be” while others get “I’ll have” or “I’ll let”? That part is probably not very exciting: The default Android keyboard presumably has slightly different predictions than the default iPhone keyboard, and third-party apps would also have slightly different predictions.

Whatever their provenance, the random juxtaposition of predictive text memes has become fodder for a growing genre of AI humor. Botnik Studios writes goofy songs using souped-up predictive keyboards and a lot of human tweaking. The blog AI Weirdness trains neural nets to do all sorts of ridiculous tasks, such as deciding whether a string of words is more likely to be a name from My Little Pony or a metal band. Darth Vader? 19 percent metal, 81 percent pony. Leia Organa? 96 percent metal, 4 percent pony. (I’m suddenly interpreting Star Wars in quite a new light.)

The combination of the customization and the randomness of the predictive text meme is compelling the way a BuzzFeed quiz or a horoscope is compelling—it gives you a tiny amount of insight into yourself to share, but not so much that you’re baring your soul. It’s also hard to get a truly terrible answer. In both cases, that’s by design.

You know how when you get a new phone and you have to teach it that, no, you aren’t trying to type “duck” and “ducking” all the time? Your keyboard deliberately errs on the conservative side. There are certain words that it just won’t try to complete, even if you get really close. After all, it’s better to accidentally send the word “public” when you meant “pubic” than the other way around.

This goes for sequences of words as well. Just because a sequence is common doesn’t mean it’s a good idea to predict it. “For a while, when you typed ‘I’m going to my Grandma’s,’ GBoard would actually suggest ‘funeral,'” van Esch says. “It’s not wrong, per se. Maybe this is more common than ‘my Grandma’s rave party.’ But at the same time, it’s not something that you want to be reminded about. So it’s better to be a bit careful.”

Users seem to prefer this discretion. Keyboards get roundly criticized when a sexual, morbid, or otherwise disturbing phrase does get predicted. It’s likely that a lot more filtering happens behind the scenes before we even notice it. Janelle Shane, the creator of AI Weirdness, experiences lapses in machine judgment all the time. “Whenever I produce an AI experiment, I’m definitely filtering out offensive content, even when the training data is as innocuous as My Little Pony names. There’s no text-generating algorithm I would trust not to be offensive at some point.”

The true goal of text prediction can’t be as simple as anticipating what a user might want to type. After all, people often type things about sex or death—according to Google Ngrams, “job” is the most common noun after “blow,” and “bucket” is very common after “kick the.” But I experimentally typed these and similar taboo-but-common phrases into my phone’s keyboard, and it never predicted them straightaway. It waited until I’d typed most of the letters of the final word, until I’d definitely committed to the taboo, rather than reminding me of weighty topics when I wasn’t necessarily already thinking about them. With innocuous idioms (like “raining cats and”), the keyboard seemed more proactive about predicting them.

Instead, the goal of text prediction must be to anticipate what the user might want the machine to think they might want to type. For mundane topics, these two goals might seem identical, but their difference shows up as soon as a hint of controversy enters the picture. Predictive text needs to project an aspirational version of a user’s thoughts, a version that avoids subjects like sex and death even though these might be the most important topics to human existence—quite literally the way we enter and leave the world.

We prefer the keyboard to balance raw statistics against our feelings. Sex Death Phone Keyboard is a pretty good name for my future metal band (and a very bad name for my future pony), but I can’t say I’d actually buy a phone that reminds me of my own mortality when I’m composing a grocery list or suggests innuendos when I’m replying to a work email.

The predictive text meme is comforting in a social media world that often leaps from one dismal news cycle to the next. The customizations make us feel seen. The random quirks give our pattern-seeking brains delightful connections. The parts that don’t make sense reassure us of human superiority—the machines can’t be taking over yet if they can’t even write me a decent horoscope! And the topic boundaries prevent the meme from reminding us of our human frailty. The result is a version of ourselves through the verbal equivalent of an Instagram filter, eminently shareable on social media.

More Great WIRED Stories

Tech

[awesomecolorfulcollectorwombat]

Autocomplete Presents the Best Version of You

New Post has been published on http://webhostingtop3.com/autocomplete-presents-the-best-version-of-you/

Autocomplete Presents the Best Version of You

Type the phrase “In 2019, I’ll …” and let your smart­phone’s keyboard predict the rest. Depending on what else you’ve typed recently, you might end up with a result like one of these:

In 2019, I’ll let it be a surprise to be honest. In 2019, i’ll be alone. In 2019, I’ll be in the memes of the moment. In 2019, I’ll have to go to get the dog. In 2019 I will rule over the seven kingdoms or my name is not Aegon Targareon [sic].

Many variants on the predictive text meme—which works for both Android and iOS—can be found on social media. Not interested in predicting your 2019? Try writing your villain origin story by following your phone’s suggestions after typing “Foolish heroes! My true plan is …” Test the strength of your personal brand with “You should follow me on Twitter because …” Or launch your political career with “I am running for president with my running mate, @[3rd Twitter Suggestion], because we …”

Gretchen McCulloch is WIRED’s resident linguist. She’s the cocreator of Lingthusiasm, a podcast that’s enthusiastic about linguistics, and her book Because Internet: Understanding the New Rules of Language is coming out in July 2019 from Penguin.

In eight years, we’ve gone from Damn You Autocorrect to treating the strip of three predicted words as a sort of wacky but charming oracle. But when we try to practice divination by algorithm, we’re doing something more than killing a few minutes—we’re exploring the limits of what our devices can and cannot do.

Your phone’s keyboard comes with a basic list of words and sequences of words. That’s what powers the basic language features: autocorrect, where a sequence like “rhe” changes to “the” after you type it, and the suggestion strip just above the letters, which contains both completions (if you type “keyb” it might suggest “keyboard”) and next-word predictions (if you type “predictive” it might suggest “text,” “value,” and “analytics”). It’s this predictions feature that we use to generate amusing and slightly nonsensical strings of text—a function that goes beyond its intended purpose of supplying us with a word or two before we go back to tapping them out letter by letter.

The basic reason we get different results is that, as you use your phone, words or sequences of words that you type get added to your personal word list. “For most users, the on-device dictionary ends up containing local place-names, songs they like, and so on,” says Daan van Esch, a technical program manager of Gboard, Google’s keyboard for Android. Or, in the case of the “Aegon Targareon” example, slightly misspelled Game of Thrones characters.

Another factor that helps us get unique results is a slight bias toward predicting less frequent words. “Suggesting a very common word like ‘and’ might be less helpful because it’s short and easy to type,” van Esch says. “So maybe showing a longer word is actually more useful, even if it’s less frequent.” Of course, a longer word is probably going to be more interesting as meme fodder.

Finally, phones seem to choose different paths from the very beginning. Why are some people getting “I’ll be” while others get “I’ll have” or “I’ll let”? That part is probably not very exciting: The default Android keyboard presumably has slightly different predictions than the default iPhone keyboard, and third-party apps would also have slightly different predictions.

Whatever their provenance, the random juxtaposition of predictive text memes has become fodder for a growing genre of AI humor. Botnik Studios writes goofy songs using souped-up predictive keyboards and a lot of human tweaking. The blog AI Weirdness trains neural nets to do all sorts of ridiculous tasks, such as deciding whether a string of words is more likely to be a name from My Little Pony or a metal band. Darth Vader? 19 percent metal, 81 percent pony. Leia Organa? 96 percent metal, 4 percent pony. (I’m suddenly interpreting Star Wars in quite a new light.)

The combination of the customization and the randomness of the predictive text meme is compelling the way a BuzzFeed quiz or a horoscope is compelling—it gives you a tiny amount of insight into yourself to share, but not so much that you’re baring your soul. It’s also hard to get a truly terrible answer. In both cases, that’s by design.

You know how when you get a new phone and you have to teach it that, no, you aren’t trying to type “duck” and “ducking” all the time? Your keyboard deliberately errs on the conservative side. There are certain words that it just won’t try to complete, even if you get really close. After all, it’s better to accidentally send the word “public” when you meant “pubic” than the other way around.

This goes for sequences of words as well. Just because a sequence is common doesn’t mean it’s a good idea to predict it. “For a while, when you typed ‘I’m going to my Grandma’s,’ GBoard would actually suggest ‘funeral,'” van Esch says. “It’s not wrong, per se. Maybe this is more common than ‘my Grandma’s rave party.’ But at the same time, it’s not something that you want to be reminded about. So it’s better to be a bit careful.”

Users seem to prefer this discretion. Keyboards get roundly criticized when a sexual, morbid, or otherwise disturbing phrase does get predicted. It’s likely that a lot more filtering happens behind the scenes before we even notice it. Janelle Shane, the creator of AI Weirdness, experiences lapses in machine judgment all the time. “Whenever I produce an AI experiment, I’m definitely filtering out offensive content, even when the training data is as innocuous as My Little Pony names. There’s no text-generating algorithm I would trust not to be offensive at some point.”

The true goal of text prediction can’t be as simple as anticipating what a user might want to type. After all, people often type things about sex or death—according to Google Ngrams, “job” is the most common noun after “blow,” and “bucket” is very common after “kick the.” But I experimentally typed these and similar taboo-but-common phrases into my phone’s keyboard, and it never predicted them straightaway. It waited until I’d typed most of the letters of the final word, until I’d definitely committed to the taboo, rather than reminding me of weighty topics when I wasn’t necessarily already thinking about them. With innocuous idioms (like “raining cats and”), the keyboard seemed more proactive about predicting them.

Instead, the goal of text prediction must be to anticipate what the user might want the machine to think they might want to type. For mundane topics, these two goals might seem identical, but their difference shows up as soon as a hint of controversy enters the picture. Predictive text needs to project an aspirational version of a user’s thoughts, a version that avoids subjects like sex and death even though these might be the most important topics to human existence—quite literally the way we enter and leave the world.

We prefer the keyboard to balance raw statistics against our feelings. Sex Death Phone Keyboard is a pretty good name for my future metal band (and a very bad name for my future pony), but I can’t say I’d actually buy a phone that reminds me of my own mortality when I’m composing a grocery list or suggests innuendos when I’m replying to a work email.

The predictive text meme is comforting in a social media world that often leaps from one dismal news cycle to the next. The customizations make us feel seen. The random quirks give our pattern-seeking brains delightful connections. The parts that don’t make sense reassure us of human superiority—the machines can’t be taking over yet if they can’t even write me a decent horoscope! And the topic boundaries prevent the meme from reminding us of our human frailty. The result is a version of ourselves through the verbal equivalent of an Instagram filter, eminently shareable on social media.

More Great WIRED Stories

Tech

[lazilysillyprince]

Autocomplete Presents the Best Version of You

New Post has been published on http://webhostingtop3.com/autocomplete-presents-the-best-version-of-you/

Autocomplete Presents the Best Version of You

Type the phrase “In 2019, I’ll …” and let your smart­phone’s keyboard predict the rest. Depending on what else you’ve typed recently, you might end up with a result like one of these:

In 2019, I’ll let it be a surprise to be honest. In 2019, i’ll be alone. In 2019, I’ll be in the memes of the moment. In 2019, I’ll have to go to get the dog. In 2019 I will rule over the seven kingdoms or my name is not Aegon Targareon [sic].

Many variants on the predictive text meme—which works for both Android and iOS—can be found on social media. Not interested in predicting your 2019? Try writing your villain origin story by following your phone’s suggestions after typing “Foolish heroes! My true plan is …” Test the strength of your personal brand with “You should follow me on Twitter because …” Or launch your political career with “I am running for president with my running mate, @[3rd Twitter Suggestion], because we …”

Gretchen McCulloch is WIRED’s resident linguist. She’s the cocreator of Lingthusiasm, a podcast that’s enthusiastic about linguistics, and her book Because Internet: Understanding the New Rules of Language is coming out in July 2019 from Penguin.

In eight years, we’ve gone from Damn You Autocorrect to treating the strip of three predicted words as a sort of wacky but charming oracle. But when we try to practice divination by algorithm, we’re doing something more than killing a few minutes—we’re exploring the limits of what our devices can and cannot do.

Your phone’s keyboard comes with a basic list of words and sequences of words. That’s what powers the basic language features: autocorrect, where a sequence like “rhe” changes to “the” after you type it, and the suggestion strip just above the letters, which contains both completions (if you type “keyb” it might suggest “keyboard”) and next-word predictions (if you type “predictive” it might suggest “text,” “value,” and “analytics”). It’s this predictions feature that we use to generate amusing and slightly nonsensical strings of text—a function that goes beyond its intended purpose of supplying us with a word or two before we go back to tapping them out letter by letter.

The basic reason we get different results is that, as you use your phone, words or sequences of words that you type get added to your personal word list. “For most users, the on-device dictionary ends up containing local place-names, songs they like, and so on,” says Daan van Esch, a technical program manager of Gboard, Google’s keyboard for Android. Or, in the case of the “Aegon Targareon” example, slightly misspelled Game of Thrones characters.

Another factor that helps us get unique results is a slight bias toward predicting less frequent words. “Suggesting a very common word like ‘and’ might be less helpful because it’s short and easy to type,” van Esch says. “So maybe showing a longer word is actually more useful, even if it’s less frequent.” Of course, a longer word is probably going to be more interesting as meme fodder.

Finally, phones seem to choose different paths from the very beginning. Why are some people getting “I’ll be” while others get “I’ll have” or “I’ll let”? That part is probably not very exciting: The default Android keyboard presumably has slightly different predictions than the default iPhone keyboard, and third-party apps would also have slightly different predictions.

Whatever their provenance, the random juxtaposition of predictive text memes has become fodder for a growing genre of AI humor. Botnik Studios writes goofy songs using souped-up predictive keyboards and a lot of human tweaking. The blog AI Weirdness trains neural nets to do all sorts of ridiculous tasks, such as deciding whether a string of words is more likely to be a name from My Little Pony or a metal band. Darth Vader? 19 percent metal, 81 percent pony. Leia Organa? 96 percent metal, 4 percent pony. (I’m suddenly interpreting Star Wars in quite a new light.)

The combination of the customization and the randomness of the predictive text meme is compelling the way a BuzzFeed quiz or a horoscope is compelling—it gives you a tiny amount of insight into yourself to share, but not so much that you’re baring your soul. It’s also hard to get a truly terrible answer. In both cases, that’s by design.

You know how when you get a new phone and you have to teach it that, no, you aren’t trying to type “duck” and “ducking” all the time? Your keyboard deliberately errs on the conservative side. There are certain words that it just won’t try to complete, even if you get really close. After all, it’s better to accidentally send the word “public” when you meant “pubic” than the other way around.

This goes for sequences of words as well. Just because a sequence is common doesn’t mean it’s a good idea to predict it. “For a while, when you typed ‘I’m going to my Grandma’s,’ GBoard would actually suggest ‘funeral,'” van Esch says. “It’s not wrong, per se. Maybe this is more common than ‘my Grandma’s rave party.’ But at the same time, it’s not something that you want to be reminded about. So it’s better to be a bit careful.”

Users seem to prefer this discretion. Keyboards get roundly criticized when a sexual, morbid, or otherwise disturbing phrase does get predicted. It’s likely that a lot more filtering happens behind the scenes before we even notice it. Janelle Shane, the creator of AI Weirdness, experiences lapses in machine judgment all the time. “Whenever I produce an AI experiment, I’m definitely filtering out offensive content, even when the training data is as innocuous as My Little Pony names. There’s no text-generating algorithm I would trust not to be offensive at some point.”

The true goal of text prediction can’t be as simple as anticipating what a user might want to type. After all, people often type things about sex or death—according to Google Ngrams, “job” is the most common noun after “blow,” and “bucket” is very common after “kick the.” But I experimentally typed these and similar taboo-but-common phrases into my phone’s keyboard, and it never predicted them straightaway. It waited until I’d typed most of the letters of the final word, until I’d definitely committed to the taboo, rather than reminding me of weighty topics when I wasn’t necessarily already thinking about them. With innocuous idioms (like “raining cats and”), the keyboard seemed more proactive about predicting them.

Instead, the goal of text prediction must be to anticipate what the user might want the machine to think they might want to type. For mundane topics, these two goals might seem identical, but their difference shows up as soon as a hint of controversy enters the picture. Predictive text needs to project an aspirational version of a user’s thoughts, a version that avoids subjects like sex and death even though these might be the most important topics to human existence—quite literally the way we enter and leave the world.

We prefer the keyboard to balance raw statistics against our feelings. Sex Death Phone Keyboard is a pretty good name for my future metal band (and a very bad name for my future pony), but I can’t say I’d actually buy a phone that reminds me of my own mortality when I’m composing a grocery list or suggests innuendos when I’m replying to a work email.

The predictive text meme is comforting in a social media world that often leaps from one dismal news cycle to the next. The customizations make us feel seen. The random quirks give our pattern-seeking brains delightful connections. The parts that don’t make sense reassure us of human superiority—the machines can’t be taking over yet if they can’t even write me a decent horoscope! And the topic boundaries prevent the meme from reminding us of our human frailty. The result is a version of ourselves through the verbal equivalent of an Instagram filter, eminently shareable on social media.

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Autocomplete Presents the Best Version of You

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Autocomplete Presents the Best Version of You

Type the phrase “In 2019, I’ll …” and let your smart­phone’s keyboard predict the rest. Depending on what else you’ve typed recently, you might end up with a result like one of these:

In 2019, I’ll let it be a surprise to be honest. In 2019, i’ll be alone. In 2019, I’ll be in the memes of the moment. In 2019, I’ll have to go to get the dog. In 2019 I will rule over the seven kingdoms or my name is not Aegon Targareon [sic].

Many variants on the predictive text meme—which works for both Android and iOS—can be found on social media. Not interested in predicting your 2019? Try writing your villain origin story by following your phone’s suggestions after typing “Foolish heroes! My true plan is …” Test the strength of your personal brand with “You should follow me on Twitter because …” Or launch your political career with “I am running for president with my running mate, @[3rd Twitter Suggestion], because we …”

Gretchen McCulloch is WIRED’s resident linguist. She’s the cocreator of Lingthusiasm, a podcast that’s enthusiastic about linguistics, and her book Because Internet: Understanding the New Rules of Language is coming out in July 2019 from Penguin.

In eight years, we’ve gone from Damn You Autocorrect to treating the strip of three predicted words as a sort of wacky but charming oracle. But when we try to practice divination by algorithm, we’re doing something more than killing a few minutes—we’re exploring the limits of what our devices can and cannot do.

Your phone’s keyboard comes with a basic list of words and sequences of words. That’s what powers the basic language features: autocorrect, where a sequence like “rhe” changes to “the” after you type it, and the suggestion strip just above the letters, which contains both completions (if you type “keyb” it might suggest “keyboard”) and next-word predictions (if you type “predictive” it might suggest “text,” “value,” and “analytics”). It’s this predictions feature that we use to generate amusing and slightly nonsensical strings of text—a function that goes beyond its intended purpose of supplying us with a word or two before we go back to tapping them out letter by letter.

The basic reason we get different results is that, as you use your phone, words or sequences of words that you type get added to your personal word list. “For most users, the on-device dictionary ends up containing local place-names, songs they like, and so on,” says Daan van Esch, a technical program manager of Gboard, Google’s keyboard for Android. Or, in the case of the “Aegon Targareon” example, slightly misspelled Game of Thrones characters.

Another factor that helps us get unique results is a slight bias toward predicting less frequent words. “Suggesting a very common word like ‘and’ might be less helpful because it’s short and easy to type,” van Esch says. “So maybe showing a longer word is actually more useful, even if it’s less frequent.” Of course, a longer word is probably going to be more interesting as meme fodder.

Finally, phones seem to choose different paths from the very beginning. Why are some people getting “I’ll be” while others get “I’ll have” or “I’ll let”? That part is probably not very exciting: The default Android keyboard presumably has slightly different predictions than the default iPhone keyboard, and third-party apps would also have slightly different predictions.

Whatever their provenance, the random juxtaposition of predictive text memes has become fodder for a growing genre of AI humor. Botnik Studios writes goofy songs using souped-up predictive keyboards and a lot of human tweaking. The blog AI Weirdness trains neural nets to do all sorts of ridiculous tasks, such as deciding whether a string of words is more likely to be a name from My Little Pony or a metal band. Darth Vader? 19 percent metal, 81 percent pony. Leia Organa? 96 percent metal, 4 percent pony. (I’m suddenly interpreting Star Wars in quite a new light.)

The combination of the customization and the randomness of the predictive text meme is compelling the way a BuzzFeed quiz or a horoscope is compelling—it gives you a tiny amount of insight into yourself to share, but not so much that you’re baring your soul. It’s also hard to get a truly terrible answer. In both cases, that’s by design.

You know how when you get a new phone and you have to teach it that, no, you aren’t trying to type “duck” and “ducking” all the time? Your keyboard deliberately errs on the conservative side. There are certain words that it just won’t try to complete, even if you get really close. After all, it’s better to accidentally send the word “public” when you meant “pubic” than the other way around.

This goes for sequences of words as well. Just because a sequence is common doesn’t mean it’s a good idea to predict it. “For a while, when you typed ‘I’m going to my Grandma’s,’ GBoard would actually suggest ‘funeral,'” van Esch says. “It’s not wrong, per se. Maybe this is more common than ‘my Grandma’s rave party.’ But at the same time, it’s not something that you want to be reminded about. So it’s better to be a bit careful.”

Users seem to prefer this discretion. Keyboards get roundly criticized when a sexual, morbid, or otherwise disturbing phrase does get predicted. It’s likely that a lot more filtering happens behind the scenes before we even notice it. Janelle Shane, the creator of AI Weirdness, experiences lapses in machine judgment all the time. “Whenever I produce an AI experiment, I’m definitely filtering out offensive content, even when the training data is as innocuous as My Little Pony names. There’s no text-generating algorithm I would trust not to be offensive at some point.”

The true goal of text prediction can’t be as simple as anticipating what a user might want to type. After all, people often type things about sex or death—according to Google Ngrams, “job” is the most common noun after “blow,” and “bucket” is very common after “kick the.” But I experimentally typed these and similar taboo-but-common phrases into my phone’s keyboard, and it never predicted them straightaway. It waited until I’d typed most of the letters of the final word, until I’d definitely committed to the taboo, rather than reminding me of weighty topics when I wasn’t necessarily already thinking about them. With innocuous idioms (like “raining cats and”), the keyboard seemed more proactive about predicting them.

Instead, the goal of text prediction must be to anticipate what the user might want the machine to think they might want to type. For mundane topics, these two goals might seem identical, but their difference shows up as soon as a hint of controversy enters the picture. Predictive text needs to project an aspirational version of a user’s thoughts, a version that avoids subjects like sex and death even though these might be the most important topics to human existence—quite literally the way we enter and leave the world.

We prefer the keyboard to balance raw statistics against our feelings. Sex Death Phone Keyboard is a pretty good name for my future metal band (and a very bad name for my future pony), but I can’t say I’d actually buy a phone that reminds me of my own mortality when I’m composing a grocery list or suggests innuendos when I’m replying to a work email.

The predictive text meme is comforting in a social media world that often leaps from one dismal news cycle to the next. The customizations make us feel seen. The random quirks give our pattern-seeking brains delightful connections. The parts that don’t make sense reassure us of human superiority—the machines can’t be taking over yet if they can’t even write me a decent horoscope! And the topic boundaries prevent the meme from reminding us of our human frailty. The result is a version of ourselves through the verbal equivalent of an Instagram filter, eminently shareable on social media.

More Great WIRED Stories

Tech

[topfygad]

Travelmag – An immersion course in Spanish in Puebla, Mexico

I’ve dabbled with studying Spanish for greater than a decade. Mexican cleaning soap operas entertain me. Spanish songs entice me. Ordering tacos and tamales in Espanol makes the consuming doubly delicious. And going to varied Spanish colleges south of the U.S. border make my stays there all of the extra enjoyable. However the one faculty that basically will get severe about its college students mastering Espanol is situated in Puebla, the fourth largest metropolis in Mexico and about 100 km east of Mexico Metropolis. Spending three weeks at Spanish Institute of Puebla taught me an excessive amount of the language with a plentiful combination of tradition and laughter blended into the concoction.

Let me put to relaxation any scary tales about flying out of Tijuana, Mexico. It’s a breeze. Lengthy-term parking might be had for as little as $5 a day, and there’s no visitors jam if you happen to’re dropped off on the U.S. aspect of the airport entrance. Passengers verify in there and easily stroll over a bridge to the Mexican aspect of the airport for the gates. Volaris flies on to Puebla for about half the worth as planes coming from Los Angeles or San Diego to Mexico Metropolis with a bus switch on to Puebla.

My hat’s off to those that decide to stick with a bunch household whereas in Puebla. About half of the scholars on the Institute achieve this. The others, and I’m one among them, desire a tad extra privateness or maybe luxurious and keep at both a resort or an Airbnb. The varsity operates a 3.5 star resort about 4 blocks from the varsity. I selected to remain at El Carmen, an Airbnb boutique resort that labored out completely. The room was charming, had entry to a kitchen, and three entry mixture codes to make sure security and privateness. It additionally didn’t harm that it was kitty-corner from a park, a block away from a church that held live shows, two blocks away from the varsity, had a couple of dozen improbable taco joints inside a block, by no means ran out of sizzling water, and was solely 5 blocks away from the cathedral and zocalo. (For extra info, go to Heroica Puebla de Zaragoza on Airbnb for Puebla, Mexico.)

Nationwide Geographic, with loads of good purpose, acclaimed Spanish Institute of Puebla as a mannequin faculty for educating Spanish. About half of the scholars take small group courses and the others have non-public classes. I opted for the group class. I took a placement examination earlier than coming to the varsity after which one other conversational placement analysis my first morning there. The location was excellent! I used to be matched with two different girls from the states who love tinkering with studying Spanish but certainly are removed from having a deal with on it. Tremendously, I respect that we have been positioned with others with related backgrounds and ages. There was one other class of our identical stage with youthful college students. Reality be instructed, we don’t study a language the identical method and on the identical pace. The varsity acknowledges this and locations its college students nicely.

College students make a pledge to talk solely Espanol whereas on the faculty. College officers plaster the pledge on the entry wall in case one slips. Once I forgot and requested the secretary a query in English, she politely ignored me till I remembered my pledge and plodded away in Spanish. Our instructor was younger, enthusiastic, and affected person. Guadelupe taught us the subjunctive, allow us to speak her into displaying us Spanish motion pictures with Spanish subtitles, sped up our combining verbs with oblique and direct objects, and launched many idioms. My favorites turned out to be “Que te pasa, calabaza?—What’s up, pumpkin?” and “Fresco como una lechuga!—It’s as contemporary as lettuce!” We spent 4 hours within the morning at school with a thirty minute break within the center to regroup and never lose our sanity, had a scrumptious lunch at a selection of two locales, after which met one-on-one our guides for 2 hours to strengthen our classwork, see town’s websites, or grasp one thing new—no matter our needs occurred to be. (For extra info, see https://ift.tt/37FND3l)

All work and no play makes Juan fairly a boring hombre, and Spanish Institute is aware of this nicely. Two or thrice every week they manage excursions: to Mexico Metropolis, Teotihucan, native pyramids and ruins, Cholula for its phenomenal church buildings and ruins, and Tlaxcala for its artisan museum and metropolis murals. I used to be in Puebla for Day of the Lifeless so we visited a city identified for its residents who suffered a loss of life of a member of the family through the previous yr. They opened their houses and hearts to guests to share in recollections of the deceased. We introduced flowers and candles to the altars they set as much as commemorate their expensive ones. Within the close by city heart carnival video games, craft stalls, and firecrackers testified of vivacity as loss of life and life mingled into one.

Whereas in Puebla, I got here to grasp the Spanish phrase for “snigger” fairly nicely. “Reir” means “to snigger,” “reirse” is its reflexive kind, “la risotada” is “a loud snigger,” “risible” is “laughable,” “risa” is “laughter,” and “Que risa! is “What amusing!” An absolute Gotta do whereas in Puebla is attend a lucha, a wrestling match that solely Mexico is aware of how one can do. Purchase a superb seat for Monday night time’s efficiency on the Enviornment so you may see nicely the antics, costumes and grins of the wrestlers. Who is aware of? You would possibly even have one or two of them land in your lap as they’re tossed from the ring. Positively, you’ll “soltar la risa” or in English translation, “Burst out in laughter.”

Visiting nice museums (particularly The Amparo, Biblioteca, and Museo de la Revolucion) will assist provide the wanted strolling train, plus loads of historic info and views of town. You should definitely browse El Parian, an arts and crafts market inside strolling distance of the cathedral. And church buildings, they appear to be on nearly each block of town. Puebla Cathedral took 300 years to finish. To say it’s enormous is an understatement; its bell tower is the tallest in Mexico; its form is of a Latin cross and accommodates 5 naves; it has fourteen chapels, two organs, and quite a few statues of saints and angels made from onyx. One other favourite is The Church of Santo Domingo the place pictures and parts symbolize The Virgin Mary. Talavera pottery and Puebla artistry is sort of synonymous. It’s bought all through the city, however I like to recommend visiting the place the objects are made. I did this one afternoon with my information and loved totally studying of the manufacturing, viewing murals depicting Dante’s Seven Lethal Sins, and shopping for treasures of tile.

Let’s say you wish to do greater than stroll and think about websites so how about horseback using? It proved to be a spotlight for me. Spanish Institute organized for 3 of us to spend a Saturday with horseman Edmundo and his spouse Patricia in Calpan, a fairly city down from the Popocatepetl volcano. We have been picked up on the faculty and drove for about 45 minutes to their beautiful dwelling in Caplan. There we had a scrumptious breakfast, adopted by a couple of hours of knowledgeable instruction by Edmundo. His love for his horses rivals his charisma and his pleasure for sharing his ardour with others. I opted for a reasonably leisurely experience, zig zagging out of trails, riverbanks, and city. Others selected some galloping and some bravo maneuvers. Edmundo videotaped my maneuvering of my horse, Princessa, proving to household and associates again dwelling that I can habla the Espanol and management a horse all on the identical time! Within the late afternoon we visited their neighbors who opened up their dwelling to commemorate Day of the Lifeless, had a scrumptious dinner of mole, and returned again to Puebla early night. (Extra info might be discovered both via Spanish Institute of Puebla or on Airbnb, searching for Patricia and horseback using underneath “Issues to Do.”)

Did I simply point out mole? There is no such thing as a such factor as a foul meal in Puebla. And price? Eating places are insanely low cost! Town’s specialty is mole poblano. To me, improbable is an understatement for mole. The sauce is a mix of about twenty components: chilies, sesame seeds, aniseeds, peppercorn, cloves, thyme, marjoram, bay leaves, cinnamon, hen inventory, fried bread, tomatoes, and, oh sure, did I point out CHOCOLATE?! The chocolate soothes the chilies, and the chilies sharpen the chocolate. In different phrases, it’s to die for! Restaurante Fonda de Santa Clara at 6 Oriente 12 Centro de Puebla would possibly simply must kick you out at closing time if you happen to go there. Andrea is the supervisor; her grandmother bequeathed her this restaurant whereas leaving others to seven different grandchildren. The cooks are all moms as grandma believed {that a} mom’s love transcends into her cooking. I took a cooking class from Andrea, together with a household of three visiting Puebla from Germany. They have been a pleasant group, particularly after they admitted that mole poblano even tops weinersnitzchel. (Extra info might be discovered by stopping by the restaurant or wanting on Airbnb “Issues to Do—Cooking Courses” in Puebla.)

I’ve develop into fairly hooked on having massages wherever I roam. Goa, India, is tough to beat with its number of remedies. Thailand massages knock the knots proper out of you. Filipino massages down on the seaside lull one to sleep with the rhythm of the waves. And the massages in Puebla have their very own distinctive type. Lila is a professional at Mayan massages of the 4 parts. She will mix stretching, bending, and stress-free multi functional session. Her secret is steadiness as she light connects the power between physique and thoughts. Reader beware: you will have a therapeutic massage nearly on daily basis. Actually, she’s simply that improbable at her ability. (If in Puebla, contact her by telephone at 22-25-46-45-47 to arrange an appointment.)

No, I didn’t develop into fluent in Spanish with my three weeks in Puebla. Admittedly, I’ve a really lengthy methods to go if I ever get there. I returned dwelling to Thanksgiving with household after which Christmas with continuous actions so my language immersion has taken a backseat. I’m assured that after the New Yr rolls round, I’ll return to my considerably devoted pupil endeavor. Till then, I’ll simply must cherish my recollections of escuela, amigos, lucha, excursiones, museos, Iglesias, caballos, comida, y masajes. And that’s rather a lot to maintain me feliz!

Copyright © 2019 Bonnie Lynn

from Cheapr Travels https://ift.tt/2SZsVrg via https://ift.tt/2NIqXKN

[topfygad]

Travelmag – An immersion course in Spanish in Puebla, Mexico

I’ve dabbled with studying Spanish for greater than a decade. Mexican cleaning soap operas entertain me. Spanish songs entice me. Ordering tacos and tamales in Espanol makes the consuming doubly delicious. And going to varied Spanish colleges south of the U.S. border make my stays there all of the extra enjoyable. However the one faculty that basically will get severe about its college students mastering Espanol is situated in Puebla, the fourth largest metropolis in Mexico and about 100 km east of Mexico Metropolis. Spending three weeks at Spanish Institute of Puebla taught me an excessive amount of the language with a plentiful combination of tradition and laughter blended into the concoction.

Let me put to relaxation any scary tales about flying out of Tijuana, Mexico. It’s a breeze. Lengthy-term parking might be had for as little as $5 a day, and there’s no visitors jam if you happen to’re dropped off on the U.S. aspect of the airport entrance. Passengers verify in there and easily stroll over a bridge to the Mexican aspect of the airport for the gates. Volaris flies on to Puebla for about half the worth as planes coming from Los Angeles or San Diego to Mexico Metropolis with a bus switch on to Puebla.

My hat’s off to those that decide to stick with a bunch household whereas in Puebla. About half of the scholars on the Institute achieve this. The others, and I’m one among them, desire a tad extra privateness or maybe luxurious and keep at both a resort or an Airbnb. The varsity operates a 3.5 star resort about 4 blocks from the varsity. I selected to remain at El Carmen, an Airbnb boutique resort that labored out completely. The room was charming, had entry to a kitchen, and three entry mixture codes to make sure security and privateness. It additionally didn’t harm that it was kitty-corner from a park, a block away from a church that held live shows, two blocks away from the varsity, had a couple of dozen improbable taco joints inside a block, by no means ran out of sizzling water, and was solely 5 blocks away from the cathedral and zocalo. (For extra info, go to Heroica Puebla de Zaragoza on Airbnb for Puebla, Mexico.)

Nationwide Geographic, with loads of good purpose, acclaimed Spanish Institute of Puebla as a mannequin faculty for educating Spanish. About half of the scholars take small group courses and the others have non-public classes. I opted for the group class. I took a placement examination earlier than coming to the varsity after which one other conversational placement analysis my first morning there. The location was excellent! I used to be matched with two different girls from the states who love tinkering with studying Spanish but certainly are removed from having a deal with on it. Tremendously, I respect that we have been positioned with others with related backgrounds and ages. There was one other class of our identical stage with youthful college students. Reality be instructed, we don’t study a language the identical method and on the identical pace. The varsity acknowledges this and locations its college students nicely.

College students make a pledge to talk solely Espanol whereas on the faculty. College officers plaster the pledge on the entry wall in case one slips. Once I forgot and requested the secretary a query in English, she politely ignored me till I remembered my pledge and plodded away in Spanish. Our instructor was younger, enthusiastic, and affected person. Guadelupe taught us the subjunctive, allow us to speak her into displaying us Spanish motion pictures with Spanish subtitles, sped up our combining verbs with oblique and direct objects, and launched many idioms. My favorites turned out to be “Que te pasa, calabaza?—What’s up, pumpkin?” and “Fresco como una lechuga!—It’s as contemporary as lettuce!” We spent 4 hours within the morning at school with a thirty minute break within the center to regroup and never lose our sanity, had a scrumptious lunch at a selection of two locales, after which met one-on-one our guides for 2 hours to strengthen our classwork, see town’s websites, or grasp one thing new—no matter our needs occurred to be. (For extra info, see https://ift.tt/37FND3l)

All work and no play makes Juan fairly a boring hombre, and Spanish Institute is aware of this nicely. Two or thrice every week they manage excursions: to Mexico Metropolis, Teotihucan, native pyramids and ruins, Cholula for its phenomenal church buildings and ruins, and Tlaxcala for its artisan museum and metropolis murals. I used to be in Puebla for Day of the Lifeless so we visited a city identified for its residents who suffered a loss of life of a member of the family through the previous yr. They opened their houses and hearts to guests to share in recollections of the deceased. We introduced flowers and candles to the altars they set as much as commemorate their expensive ones. Within the close by city heart carnival video games, craft stalls, and firecrackers testified of vivacity as loss of life and life mingled into one.

Whereas in Puebla, I got here to grasp the Spanish phrase for “snigger” fairly nicely. “Reir” means “to snigger,” “reirse” is its reflexive kind, “la risotada” is “a loud snigger,” “risible” is “laughable,” “risa” is “laughter,” and “Que risa! is “What amusing!” An absolute Gotta do whereas in Puebla is attend a lucha, a wrestling match that solely Mexico is aware of how one can do. Purchase a superb seat for Monday night time’s efficiency on the Enviornment so you may see nicely the antics, costumes and grins of the wrestlers. Who is aware of? You would possibly even have one or two of them land in your lap as they’re tossed from the ring. Positively, you’ll “soltar la risa” or in English translation, “Burst out in laughter.”

Visiting nice museums (particularly The Amparo, Biblioteca, and Museo de la Revolucion) will assist provide the wanted strolling train, plus loads of historic info and views of town. You should definitely browse El Parian, an arts and crafts market inside strolling distance of the cathedral. And church buildings, they appear to be on nearly each block of town. Puebla Cathedral took 300 years to finish. To say it’s enormous is an understatement; its bell tower is the tallest in Mexico; its form is of a Latin cross and accommodates 5 naves; it has fourteen chapels, two organs, and quite a few statues of saints and angels made from onyx. One other favourite is The Church of Santo Domingo the place pictures and parts symbolize The Virgin Mary. Talavera pottery and Puebla artistry is sort of synonymous. It’s bought all through the city, however I like to recommend visiting the place the objects are made. I did this one afternoon with my information and loved totally studying of the manufacturing, viewing murals depicting Dante’s Seven Lethal Sins, and shopping for treasures of tile.

Let’s say you wish to do greater than stroll and think about websites so how about horseback using? It proved to be a spotlight for me. Spanish Institute organized for 3 of us to spend a Saturday with horseman Edmundo and his spouse Patricia in Calpan, a fairly city down from the Popocatepetl volcano. We have been picked up on the faculty and drove for about 45 minutes to their beautiful dwelling in Caplan. There we had a scrumptious breakfast, adopted by a couple of hours of knowledgeable instruction by Edmundo. His love for his horses rivals his charisma and his pleasure for sharing his ardour with others. I opted for a reasonably leisurely experience, zig zagging out of trails, riverbanks, and city. Others selected some galloping and some bravo maneuvers. Edmundo videotaped my maneuvering of my horse, Princessa, proving to household and associates again dwelling that I can habla the Espanol and management a horse all on the identical time! Within the late afternoon we visited their neighbors who opened up their dwelling to commemorate Day of the Lifeless, had a scrumptious dinner of mole, and returned again to Puebla early night. (Extra info might be discovered both via Spanish Institute of Puebla or on Airbnb, searching for Patricia and horseback using underneath “Issues to Do.”)

Did I simply point out mole? There is no such thing as a such factor as a foul meal in Puebla. And price? Eating places are insanely low cost! Town’s specialty is mole poblano. To me, improbable is an understatement for mole. The sauce is a mix of about twenty components: chilies, sesame seeds, aniseeds, peppercorn, cloves, thyme, marjoram, bay leaves, cinnamon, hen inventory, fried bread, tomatoes, and, oh sure, did I point out CHOCOLATE?! The chocolate soothes the chilies, and the chilies sharpen the chocolate. In different phrases, it’s to die for! Restaurante Fonda de Santa Clara at 6 Oriente 12 Centro de Puebla would possibly simply must kick you out at closing time if you happen to go there. Andrea is the supervisor; her grandmother bequeathed her this restaurant whereas leaving others to seven different grandchildren. The cooks are all moms as grandma believed {that a} mom’s love transcends into her cooking. I took a cooking class from Andrea, together with a household of three visiting Puebla from Germany. They have been a pleasant group, particularly after they admitted that mole poblano even tops weinersnitzchel. (Extra info might be discovered by stopping by the restaurant or wanting on Airbnb “Issues to Do—Cooking Courses” in Puebla.)

I’ve develop into fairly hooked on having massages wherever I roam. Goa, India, is tough to beat with its number of remedies. Thailand massages knock the knots proper out of you. Filipino massages down on the seaside lull one to sleep with the rhythm of the waves. And the massages in Puebla have their very own distinctive type. Lila is a professional at Mayan massages of the 4 parts. She will mix stretching, bending, and stress-free multi functional session. Her secret is steadiness as she light connects the power between physique and thoughts. Reader beware: you will have a therapeutic massage nearly on daily basis. Actually, she’s simply that improbable at her ability. (If in Puebla, contact her by telephone at 22-25-46-45-47 to arrange an appointment.)

No, I didn’t develop into fluent in Spanish with my three weeks in Puebla. Admittedly, I’ve a really lengthy methods to go if I ever get there. I returned dwelling to Thanksgiving with household after which Christmas with continuous actions so my language immersion has taken a backseat. I’m assured that after the New Yr rolls round, I’ll return to my considerably devoted pupil endeavor. Till then, I’ll simply must cherish my recollections of escuela, amigos, lucha, excursiones, museos, Iglesias, caballos, comida, y masajes. And that’s rather a lot to maintain me feliz!

Copyright © 2019 Bonnie Lynn

source http://cheaprtravels.com/travelmag-an-immersion-course-in-spanish-in-puebla-mexico/

[smartwebhostingblog]

Autocomplete Presents the Best Version of You

New Post has been published on http://webhostingtop3.com/autocomplete-presents-the-best-version-of-you/

Autocomplete Presents the Best Version of You

Type the phrase “In 2019, I’ll …” and let your smart­phone’s keyboard predict the rest. Depending on what else you’ve typed recently, you might end up with a result like one of these:

In 2019, I’ll let it be a surprise to be honest. In 2019, i’ll be alone. In 2019, I’ll be in the memes of the moment. In 2019, I’ll have to go to get the dog. In 2019 I will rule over the seven kingdoms or my name is not Aegon Targareon [sic].

Many variants on the predictive text meme—which works for both Android and iOS—can be found on social media. Not interested in predicting your 2019? Try writing your villain origin story by following your phone’s suggestions after typing “Foolish heroes! My true plan is …” Test the strength of your personal brand with “You should follow me on Twitter because …” Or launch your political career with “I am running for president with my running mate, @[3rd Twitter Suggestion], because we …”

Gretchen McCulloch is WIRED’s resident linguist. She’s the cocreator of Lingthusiasm, a podcast that’s enthusiastic about linguistics, and her book Because Internet: Understanding the New Rules of Language is coming out in July 2019 from Penguin.

In eight years, we’ve gone from Damn You Autocorrect to treating the strip of three predicted words as a sort of wacky but charming oracle. But when we try to practice divination by algorithm, we’re doing something more than killing a few minutes—we’re exploring the limits of what our devices can and cannot do.

Your phone’s keyboard comes with a basic list of words and sequences of words. That’s what powers the basic language features: autocorrect, where a sequence like “rhe” changes to “the” after you type it, and the suggestion strip just above the letters, which contains both completions (if you type “keyb” it might suggest “keyboard”) and next-word predictions (if you type “predictive” it might suggest “text,” “value,” and “analytics”). It’s this predictions feature that we use to generate amusing and slightly nonsensical strings of text—a function that goes beyond its intended purpose of supplying us with a word or two before we go back to tapping them out letter by letter.

The basic reason we get different results is that, as you use your phone, words or sequences of words that you type get added to your personal word list. “For most users, the on-device dictionary ends up containing local place-names, songs they like, and so on,” says Daan van Esch, a technical program manager of Gboard, Google’s keyboard for Android. Or, in the case of the “Aegon Targareon” example, slightly misspelled Game of Thrones characters.

Another factor that helps us get unique results is a slight bias toward predicting less frequent words. “Suggesting a very common word like ‘and’ might be less helpful because it’s short and easy to type,” van Esch says. “So maybe showing a longer word is actually more useful, even if it’s less frequent.” Of course, a longer word is probably going to be more interesting as meme fodder.

Finally, phones seem to choose different paths from the very beginning. Why are some people getting “I’ll be” while others get “I’ll have” or “I’ll let”? That part is probably not very exciting: The default Android keyboard presumably has slightly different predictions than the default iPhone keyboard, and third-party apps would also have slightly different predictions.

Whatever their provenance, the random juxtaposition of predictive text memes has become fodder for a growing genre of AI humor. Botnik Studios writes goofy songs using souped-up predictive keyboards and a lot of human tweaking. The blog AI Weirdness trains neural nets to do all sorts of ridiculous tasks, such as deciding whether a string of words is more likely to be a name from My Little Pony or a metal band. Darth Vader? 19 percent metal, 81 percent pony. Leia Organa? 96 percent metal, 4 percent pony. (I’m suddenly interpreting Star Wars in quite a new light.)

The combination of the customization and the randomness of the predictive text meme is compelling the way a BuzzFeed quiz or a horoscope is compelling—it gives you a tiny amount of insight into yourself to share, but not so much that you’re baring your soul. It’s also hard to get a truly terrible answer. In both cases, that’s by design.

You know how when you get a new phone and you have to teach it that, no, you aren’t trying to type “duck” and “ducking” all the time? Your keyboard deliberately errs on the conservative side. There are certain words that it just won’t try to complete, even if you get really close. After all, it’s better to accidentally send the word “public” when you meant “pubic” than the other way around.

This goes for sequences of words as well. Just because a sequence is common doesn’t mean it’s a good idea to predict it. “For a while, when you typed ‘I’m going to my Grandma’s,’ GBoard would actually suggest ‘funeral,'” van Esch says. “It’s not wrong, per se. Maybe this is more common than ‘my Grandma’s rave party.’ But at the same time, it’s not something that you want to be reminded about. So it’s better to be a bit careful.”

Users seem to prefer this discretion. Keyboards get roundly criticized when a sexual, morbid, or otherwise disturbing phrase does get predicted. It’s likely that a lot more filtering happens behind the scenes before we even notice it. Janelle Shane, the creator of AI Weirdness, experiences lapses in machine judgment all the time. “Whenever I produce an AI experiment, I’m definitely filtering out offensive content, even when the training data is as innocuous as My Little Pony names. There’s no text-generating algorithm I would trust not to be offensive at some point.”

The true goal of text prediction can’t be as simple as anticipating what a user might want to type. After all, people often type things about sex or death—according to Google Ngrams, “job” is the most common noun after “blow,” and “bucket” is very common after “kick the.” But I experimentally typed these and similar taboo-but-common phrases into my phone’s keyboard, and it never predicted them straightaway. It waited until I’d typed most of the letters of the final word, until I’d definitely committed to the taboo, rather than reminding me of weighty topics when I wasn’t necessarily already thinking about them. With innocuous idioms (like “raining cats and”), the keyboard seemed more proactive about predicting them.

Instead, the goal of text prediction must be to anticipate what the user might want the machine to think they might want to type. For mundane topics, these two goals might seem identical, but their difference shows up as soon as a hint of controversy enters the picture. Predictive text needs to project an aspirational version of a user’s thoughts, a version that avoids subjects like sex and death even though these might be the most important topics to human existence—quite literally the way we enter and leave the world.

We prefer the keyboard to balance raw statistics against our feelings. Sex Death Phone Keyboard is a pretty good name for my future metal band (and a very bad name for my future pony), but I can’t say I’d actually buy a phone that reminds me of my own mortality when I’m composing a grocery list or suggests innuendos when I’m replying to a work email.

The predictive text meme is comforting in a social media world that often leaps from one dismal news cycle to the next. The customizations make us feel seen. The random quirks give our pattern-seeking brains delightful connections. The parts that don’t make sense reassure us of human superiority—the machines can’t be taking over yet if they can’t even write me a decent horoscope! And the topic boundaries prevent the meme from reminding us of our human frailty. The result is a version of ourselves through the verbal equivalent of an Instagram filter, eminently shareable on social media.

More Great WIRED Stories

Tech

[smartwebhostingblog]

Autocomplete Presents the Best Version of You

New Post has been published on http://webhostingtop3.com/autocomplete-presents-the-best-version-of-you/

Autocomplete Presents the Best Version of You

Type the phrase “In 2019, I’ll …” and let your smart­phone’s keyboard predict the rest. Depending on what else you’ve typed recently, you might end up with a result like one of these:

In 2019, I’ll let it be a surprise to be honest. In 2019, i’ll be alone. In 2019, I’ll be in the memes of the moment. In 2019, I’ll have to go to get the dog. In 2019 I will rule over the seven kingdoms or my name is not Aegon Targareon [sic].

Many variants on the predictive text meme—which works for both Android and iOS—can be found on social media. Not interested in predicting your 2019? Try writing your villain origin story by following your phone’s suggestions after typing “Foolish heroes! My true plan is …” Test the strength of your personal brand with “You should follow me on Twitter because …” Or launch your political career with “I am running for president with my running mate, @[3rd Twitter Suggestion], because we …”

Gretchen McCulloch is WIRED’s resident linguist. She’s the cocreator of Lingthusiasm, a podcast that’s enthusiastic about linguistics, and her book Because Internet: Understanding the New Rules of Language is coming out in July 2019 from Penguin.

In eight years, we’ve gone from Damn You Autocorrect to treating the strip of three predicted words as a sort of wacky but charming oracle. But when we try to practice divination by algorithm, we’re doing something more than killing a few minutes—we’re exploring the limits of what our devices can and cannot do.

Your phone’s keyboard comes with a basic list of words and sequences of words. That’s what powers the basic language features: autocorrect, where a sequence like “rhe” changes to “the” after you type it, and the suggestion strip just above the letters, which contains both completions (if you type “keyb” it might suggest “keyboard”) and next-word predictions (if you type “predictive” it might suggest “text,” “value,” and “analytics”). It’s this predictions feature that we use to generate amusing and slightly nonsensical strings of text—a function that goes beyond its intended purpose of supplying us with a word or two before we go back to tapping them out letter by letter.

The basic reason we get different results is that, as you use your phone, words or sequences of words that you type get added to your personal word list. “For most users, the on-device dictionary ends up containing local place-names, songs they like, and so on,” says Daan van Esch, a technical program manager of Gboard, Google’s keyboard for Android. Or, in the case of the “Aegon Targareon” example, slightly misspelled Game of Thrones characters.

Another factor that helps us get unique results is a slight bias toward predicting less frequent words. “Suggesting a very common word like ‘and’ might be less helpful because it’s short and easy to type,” van Esch says. “So maybe showing a longer word is actually more useful, even if it’s less frequent.” Of course, a longer word is probably going to be more interesting as meme fodder.

Finally, phones seem to choose different paths from the very beginning. Why are some people getting “I’ll be” while others get “I’ll have” or “I’ll let”? That part is probably not very exciting: The default Android keyboard presumably has slightly different predictions than the default iPhone keyboard, and third-party apps would also have slightly different predictions.

Whatever their provenance, the random juxtaposition of predictive text memes has become fodder for a growing genre of AI humor. Botnik Studios writes goofy songs using souped-up predictive keyboards and a lot of human tweaking. The blog AI Weirdness trains neural nets to do all sorts of ridiculous tasks, such as deciding whether a string of words is more likely to be a name from My Little Pony or a metal band. Darth Vader? 19 percent metal, 81 percent pony. Leia Organa? 96 percent metal, 4 percent pony. (I’m suddenly interpreting Star Wars in quite a new light.)

The combination of the customization and the randomness of the predictive text meme is compelling the way a BuzzFeed quiz or a horoscope is compelling—it gives you a tiny amount of insight into yourself to share, but not so much that you’re baring your soul. It’s also hard to get a truly terrible answer. In both cases, that’s by design.

You know how when you get a new phone and you have to teach it that, no, you aren’t trying to type “duck” and “ducking” all the time? Your keyboard deliberately errs on the conservative side. There are certain words that it just won’t try to complete, even if you get really close. After all, it’s better to accidentally send the word “public” when you meant “pubic” than the other way around.

This goes for sequences of words as well. Just because a sequence is common doesn’t mean it’s a good idea to predict it. “For a while, when you typed ‘I’m going to my Grandma’s,’ GBoard would actually suggest ‘funeral,'” van Esch says. “It’s not wrong, per se. Maybe this is more common than ‘my Grandma’s rave party.’ But at the same time, it’s not something that you want to be reminded about. So it’s better to be a bit careful.”

Users seem to prefer this discretion. Keyboards get roundly criticized when a sexual, morbid, or otherwise disturbing phrase does get predicted. It’s likely that a lot more filtering happens behind the scenes before we even notice it. Janelle Shane, the creator of AI Weirdness, experiences lapses in machine judgment all the time. “Whenever I produce an AI experiment, I’m definitely filtering out offensive content, even when the training data is as innocuous as My Little Pony names. There’s no text-generating algorithm I would trust not to be offensive at some point.”

The true goal of text prediction can’t be as simple as anticipating what a user might want to type. After all, people often type things about sex or death—according to Google Ngrams, “job” is the most common noun after “blow,” and “bucket” is very common after “kick the.” But I experimentally typed these and similar taboo-but-common phrases into my phone’s keyboard, and it never predicted them straightaway. It waited until I’d typed most of the letters of the final word, until I’d definitely committed to the taboo, rather than reminding me of weighty topics when I wasn’t necessarily already thinking about them. With innocuous idioms (like “raining cats and”), the keyboard seemed more proactive about predicting them.

Instead, the goal of text prediction must be to anticipate what the user might want the machine to think they might want to type. For mundane topics, these two goals might seem identical, but their difference shows up as soon as a hint of controversy enters the picture. Predictive text needs to project an aspirational version of a user’s thoughts, a version that avoids subjects like sex and death even though these might be the most important topics to human existence—quite literally the way we enter and leave the world.

We prefer the keyboard to balance raw statistics against our feelings. Sex Death Phone Keyboard is a pretty good name for my future metal band (and a very bad name for my future pony), but I can’t say I’d actually buy a phone that reminds me of my own mortality when I’m composing a grocery list or suggests innuendos when I’m replying to a work email.

The predictive text meme is comforting in a social media world that often leaps from one dismal news cycle to the next. The customizations make us feel seen. The random quirks give our pattern-seeking brains delightful connections. The parts that don’t make sense reassure us of human superiority—the machines can’t be taking over yet if they can’t even write me a decent horoscope! And the topic boundaries prevent the meme from reminding us of our human frailty. The result is a version of ourselves through the verbal equivalent of an Instagram filter, eminently shareable on social media.

More Great WIRED Stories

Tech

[awesomecolorfulcollectorwombat]

Autocomplete Presents the Best Version of You

New Post has been published on http://webhostingtop3.com/autocomplete-presents-the-best-version-of-you/

Autocomplete Presents the Best Version of You

Type the phrase “In 2019, I’ll …” and let your smart­phone’s keyboard predict the rest. Depending on what else you’ve typed recently, you might end up with a result like one of these:

In 2019, I’ll let it be a surprise to be honest. In 2019, i’ll be alone. In 2019, I’ll be in the memes of the moment. In 2019, I’ll have to go to get the dog. In 2019 I will rule over the seven kingdoms or my name is not Aegon Targareon [sic].

Many variants on the predictive text meme—which works for both Android and iOS—can be found on social media. Not interested in predicting your 2019? Try writing your villain origin story by following your phone’s suggestions after typing “Foolish heroes! My true plan is …” Test the strength of your personal brand with “You should follow me on Twitter because …” Or launch your political career with “I am running for president with my running mate, @[3rd Twitter Suggestion], because we …”

Gretchen McCulloch is WIRED’s resident linguist. She’s the cocreator of Lingthusiasm, a podcast that’s enthusiastic about linguistics, and her book Because Internet: Understanding the New Rules of Language is coming out in July 2019 from Penguin.

In eight years, we’ve gone from Damn You Autocorrect to treating the strip of three predicted words as a sort of wacky but charming oracle. But when we try to practice divination by algorithm, we’re doing something more than killing a few minutes—we’re exploring the limits of what our devices can and cannot do.

Your phone’s keyboard comes with a basic list of words and sequences of words. That’s what powers the basic language features: autocorrect, where a sequence like “rhe” changes to “the” after you type it, and the suggestion strip just above the letters, which contains both completions (if you type “keyb” it might suggest “keyboard”) and next-word predictions (if you type “predictive” it might suggest “text,” “value,” and “analytics”). It’s this predictions feature that we use to generate amusing and slightly nonsensical strings of text—a function that goes beyond its intended purpose of supplying us with a word or two before we go back to tapping them out letter by letter.

The basic reason we get different results is that, as you use your phone, words or sequences of words that you type get added to your personal word list. “For most users, the on-device dictionary ends up containing local place-names, songs they like, and so on,” says Daan van Esch, a technical program manager of Gboard, Google’s keyboard for Android. Or, in the case of the “Aegon Targareon” example, slightly misspelled Game of Thrones characters.

Another factor that helps us get unique results is a slight bias toward predicting less frequent words. “Suggesting a very common word like ‘and’ might be less helpful because it’s short and easy to type,” van Esch says. “So maybe showing a longer word is actually more useful, even if it’s less frequent.” Of course, a longer word is probably going to be more interesting as meme fodder.

Finally, phones seem to choose different paths from the very beginning. Why are some people getting “I’ll be” while others get “I’ll have” or “I’ll let”? That part is probably not very exciting: The default Android keyboard presumably has slightly different predictions than the default iPhone keyboard, and third-party apps would also have slightly different predictions.

Whatever their provenance, the random juxtaposition of predictive text memes has become fodder for a growing genre of AI humor. Botnik Studios writes goofy songs using souped-up predictive keyboards and a lot of human tweaking. The blog AI Weirdness trains neural nets to do all sorts of ridiculous tasks, such as deciding whether a string of words is more likely to be a name from My Little Pony or a metal band. Darth Vader? 19 percent metal, 81 percent pony. Leia Organa? 96 percent metal, 4 percent pony. (I’m suddenly interpreting Star Wars in quite a new light.)

The combination of the customization and the randomness of the predictive text meme is compelling the way a BuzzFeed quiz or a horoscope is compelling—it gives you a tiny amount of insight into yourself to share, but not so much that you’re baring your soul. It’s also hard to get a truly terrible answer. In both cases, that’s by design.

You know how when you get a new phone and you have to teach it that, no, you aren’t trying to type “duck” and “ducking” all the time? Your keyboard deliberately errs on the conservative side. There are certain words that it just won’t try to complete, even if you get really close. After all, it’s better to accidentally send the word “public” when you meant “pubic” than the other way around.

This goes for sequences of words as well. Just because a sequence is common doesn’t mean it’s a good idea to predict it. “For a while, when you typed ‘I’m going to my Grandma’s,’ GBoard would actually suggest ‘funeral,'” van Esch says. “It’s not wrong, per se. Maybe this is more common than ‘my Grandma’s rave party.’ But at the same time, it’s not something that you want to be reminded about. So it’s better to be a bit careful.”

Users seem to prefer this discretion. Keyboards get roundly criticized when a sexual, morbid, or otherwise disturbing phrase does get predicted. It’s likely that a lot more filtering happens behind the scenes before we even notice it. Janelle Shane, the creator of AI Weirdness, experiences lapses in machine judgment all the time. “Whenever I produce an AI experiment, I’m definitely filtering out offensive content, even when the training data is as innocuous as My Little Pony names. There’s no text-generating algorithm I would trust not to be offensive at some point.”

The true goal of text prediction can’t be as simple as anticipating what a user might want to type. After all, people often type things about sex or death—according to Google Ngrams, “job” is the most common noun after “blow,” and “bucket” is very common after “kick the.” But I experimentally typed these and similar taboo-but-common phrases into my phone’s keyboard, and it never predicted them straightaway. It waited until I’d typed most of the letters of the final word, until I’d definitely committed to the taboo, rather than reminding me of weighty topics when I wasn’t necessarily already thinking about them. With innocuous idioms (like “raining cats and”), the keyboard seemed more proactive about predicting them.

Instead, the goal of text prediction must be to anticipate what the user might want the machine to think they might want to type. For mundane topics, these two goals might seem identical, but their difference shows up as soon as a hint of controversy enters the picture. Predictive text needs to project an aspirational version of a user’s thoughts, a version that avoids subjects like sex and death even though these might be the most important topics to human existence—quite literally the way we enter and leave the world.

We prefer the keyboard to balance raw statistics against our feelings. Sex Death Phone Keyboard is a pretty good name for my future metal band (and a very bad name for my future pony), but I can’t say I’d actually buy a phone that reminds me of my own mortality when I’m composing a grocery list or suggests innuendos when I’m replying to a work email.

The predictive text meme is comforting in a social media world that often leaps from one dismal news cycle to the next. The customizations make us feel seen. The random quirks give our pattern-seeking brains delightful connections. The parts that don’t make sense reassure us of human superiority—the machines can’t be taking over yet if they can’t even write me a decent horoscope! And the topic boundaries prevent the meme from reminding us of our human frailty. The result is a version of ourselves through the verbal equivalent of an Instagram filter, eminently shareable on social media.

More Great WIRED Stories

Tech

[awesomecolorfulcollectorwombat]

Autocomplete Presents the Best Version of You

New Post has been published on http://webhostingtop3.com/autocomplete-presents-the-best-version-of-you/

Autocomplete Presents the Best Version of You

Type the phrase “In 2019, I’ll …” and let your smart­phone’s keyboard predict the rest. Depending on what else you’ve typed recently, you might end up with a result like one of these:

In 2019, I’ll let it be a surprise to be honest. In 2019, i’ll be alone. In 2019, I’ll be in the memes of the moment. In 2019, I’ll have to go to get the dog. In 2019 I will rule over the seven kingdoms or my name is not Aegon Targareon [sic].

Many variants on the predictive text meme—which works for both Android and iOS—can be found on social media. Not interested in predicting your 2019? Try writing your villain origin story by following your phone’s suggestions after typing “Foolish heroes! My true plan is …” Test the strength of your personal brand with “You should follow me on Twitter because …” Or launch your political career with “I am running for president with my running mate, @[3rd Twitter Suggestion], because we …”

Gretchen McCulloch is WIRED’s resident linguist. She’s the cocreator of Lingthusiasm, a podcast that’s enthusiastic about linguistics, and her book Because Internet: Understanding the New Rules of Language is coming out in July 2019 from Penguin.

In eight years, we’ve gone from Damn You Autocorrect to treating the strip of three predicted words as a sort of wacky but charming oracle. But when we try to practice divination by algorithm, we’re doing something more than killing a few minutes—we’re exploring the limits of what our devices can and cannot do.

Your phone’s keyboard comes with a basic list of words and sequences of words. That’s what powers the basic language features: autocorrect, where a sequence like “rhe” changes to “the” after you type it, and the suggestion strip just above the letters, which contains both completions (if you type “keyb” it might suggest “keyboard”) and next-word predictions (if you type “predictive” it might suggest “text,” “value,” and “analytics”). It’s this predictions feature that we use to generate amusing and slightly nonsensical strings of text—a function that goes beyond its intended purpose of supplying us with a word or two before we go back to tapping them out letter by letter.

The basic reason we get different results is that, as you use your phone, words or sequences of words that you type get added to your personal word list. “For most users, the on-device dictionary ends up containing local place-names, songs they like, and so on,” says Daan van Esch, a technical program manager of Gboard, Google’s keyboard for Android. Or, in the case of the “Aegon Targareon” example, slightly misspelled Game of Thrones characters.

Another factor that helps us get unique results is a slight bias toward predicting less frequent words. “Suggesting a very common word like ‘and’ might be less helpful because it’s short and easy to type,” van Esch says. “So maybe showing a longer word is actually more useful, even if it’s less frequent.” Of course, a longer word is probably going to be more interesting as meme fodder.

Finally, phones seem to choose different paths from the very beginning. Why are some people getting “I’ll be” while others get “I’ll have” or “I’ll let”? That part is probably not very exciting: The default Android keyboard presumably has slightly different predictions than the default iPhone keyboard, and third-party apps would also have slightly different predictions.

Whatever their provenance, the random juxtaposition of predictive text memes has become fodder for a growing genre of AI humor. Botnik Studios writes goofy songs using souped-up predictive keyboards and a lot of human tweaking. The blog AI Weirdness trains neural nets to do all sorts of ridiculous tasks, such as deciding whether a string of words is more likely to be a name from My Little Pony or a metal band. Darth Vader? 19 percent metal, 81 percent pony. Leia Organa? 96 percent metal, 4 percent pony. (I’m suddenly interpreting Star Wars in quite a new light.)

The combination of the customization and the randomness of the predictive text meme is compelling the way a BuzzFeed quiz or a horoscope is compelling—it gives you a tiny amount of insight into yourself to share, but not so much that you’re baring your soul. It’s also hard to get a truly terrible answer. In both cases, that’s by design.

You know how when you get a new phone and you have to teach it that, no, you aren’t trying to type “duck” and “ducking” all the time? Your keyboard deliberately errs on the conservative side. There are certain words that it just won’t try to complete, even if you get really close. After all, it’s better to accidentally send the word “public” when you meant “pubic” than the other way around.

This goes for sequences of words as well. Just because a sequence is common doesn’t mean it’s a good idea to predict it. “For a while, when you typed ‘I’m going to my Grandma’s,’ GBoard would actually suggest ‘funeral,'” van Esch says. “It’s not wrong, per se. Maybe this is more common than ‘my Grandma’s rave party.’ But at the same time, it’s not something that you want to be reminded about. So it’s better to be a bit careful.”

Users seem to prefer this discretion. Keyboards get roundly criticized when a sexual, morbid, or otherwise disturbing phrase does get predicted. It’s likely that a lot more filtering happens behind the scenes before we even notice it. Janelle Shane, the creator of AI Weirdness, experiences lapses in machine judgment all the time. “Whenever I produce an AI experiment, I’m definitely filtering out offensive content, even when the training data is as innocuous as My Little Pony names. There’s no text-generating algorithm I would trust not to be offensive at some point.”

The true goal of text prediction can’t be as simple as anticipating what a user might want to type. After all, people often type things about sex or death—according to Google Ngrams, “job” is the most common noun after “blow,” and “bucket” is very common after “kick the.” But I experimentally typed these and similar taboo-but-common phrases into my phone’s keyboard, and it never predicted them straightaway. It waited until I’d typed most of the letters of the final word, until I’d definitely committed to the taboo, rather than reminding me of weighty topics when I wasn’t necessarily already thinking about them. With innocuous idioms (like “raining cats and”), the keyboard seemed more proactive about predicting them.

Instead, the goal of text prediction must be to anticipate what the user might want the machine to think they might want to type. For mundane topics, these two goals might seem identical, but their difference shows up as soon as a hint of controversy enters the picture. Predictive text needs to project an aspirational version of a user’s thoughts, a version that avoids subjects like sex and death even though these might be the most important topics to human existence—quite literally the way we enter and leave the world.

We prefer the keyboard to balance raw statistics against our feelings. Sex Death Phone Keyboard is a pretty good name for my future metal band (and a very bad name for my future pony), but I can’t say I’d actually buy a phone that reminds me of my own mortality when I’m composing a grocery list or suggests innuendos when I’m replying to a work email.

The predictive text meme is comforting in a social media world that often leaps from one dismal news cycle to the next. The customizations make us feel seen. The random quirks give our pattern-seeking brains delightful connections. The parts that don’t make sense reassure us of human superiority—the machines can’t be taking over yet if they can’t even write me a decent horoscope! And the topic boundaries prevent the meme from reminding us of our human frailty. The result is a version of ourselves through the verbal equivalent of an Instagram filter, eminently shareable on social media.

More Great WIRED Stories

Tech

[lazilysillyprince]

Autocomplete Presents the Best Version of You

New Post has been published on http://webhostingtop3.com/autocomplete-presents-the-best-version-of-you/

Autocomplete Presents the Best Version of You

Type the phrase “In 2019, I’ll …” and let your smart­phone’s keyboard predict the rest. Depending on what else you’ve typed recently, you might end up with a result like one of these:

In 2019, I’ll let it be a surprise to be honest. In 2019, i’ll be alone. In 2019, I’ll be in the memes of the moment. In 2019, I’ll have to go to get the dog. In 2019 I will rule over the seven kingdoms or my name is not Aegon Targareon [sic].

Many variants on the predictive text meme—which works for both Android and iOS—can be found on social media. Not interested in predicting your 2019? Try writing your villain origin story by following your phone’s suggestions after typing “Foolish heroes! My true plan is …” Test the strength of your personal brand with “You should follow me on Twitter because …” Or launch your political career with “I am running for president with my running mate, @[3rd Twitter Suggestion], because we …”

Gretchen McCulloch is WIRED’s resident linguist. She’s the cocreator of Lingthusiasm, a podcast that’s enthusiastic about linguistics, and her book Because Internet: Understanding the New Rules of Language is coming out in July 2019 from Penguin.

In eight years, we’ve gone from Damn You Autocorrect to treating the strip of three predicted words as a sort of wacky but charming oracle. But when we try to practice divination by algorithm, we’re doing something more than killing a few minutes—we’re exploring the limits of what our devices can and cannot do.

Your phone’s keyboard comes with a basic list of words and sequences of words. That’s what powers the basic language features: autocorrect, where a sequence like “rhe” changes to “the” after you type it, and the suggestion strip just above the letters, which contains both completions (if you type “keyb” it might suggest “keyboard”) and next-word predictions (if you type “predictive” it might suggest “text,” “value,” and “analytics”). It’s this predictions feature that we use to generate amusing and slightly nonsensical strings of text—a function that goes beyond its intended purpose of supplying us with a word or two before we go back to tapping them out letter by letter.

The basic reason we get different results is that, as you use your phone, words or sequences of words that you type get added to your personal word list. “For most users, the on-device dictionary ends up containing local place-names, songs they like, and so on,” says Daan van Esch, a technical program manager of Gboard, Google’s keyboard for Android. Or, in the case of the “Aegon Targareon” example, slightly misspelled Game of Thrones characters.

Another factor that helps us get unique results is a slight bias toward predicting less frequent words. “Suggesting a very common word like ‘and’ might be less helpful because it’s short and easy to type,” van Esch says. “So maybe showing a longer word is actually more useful, even if it’s less frequent.” Of course, a longer word is probably going to be more interesting as meme fodder.

Finally, phones seem to choose different paths from the very beginning. Why are some people getting “I’ll be” while others get “I’ll have” or “I’ll let”? That part is probably not very exciting: The default Android keyboard presumably has slightly different predictions than the default iPhone keyboard, and third-party apps would also have slightly different predictions.

Whatever their provenance, the random juxtaposition of predictive text memes has become fodder for a growing genre of AI humor. Botnik Studios writes goofy songs using souped-up predictive keyboards and a lot of human tweaking. The blog AI Weirdness trains neural nets to do all sorts of ridiculous tasks, such as deciding whether a string of words is more likely to be a name from My Little Pony or a metal band. Darth Vader? 19 percent metal, 81 percent pony. Leia Organa? 96 percent metal, 4 percent pony. (I’m suddenly interpreting Star Wars in quite a new light.)

The combination of the customization and the randomness of the predictive text meme is compelling the way a BuzzFeed quiz or a horoscope is compelling—it gives you a tiny amount of insight into yourself to share, but not so much that you’re baring your soul. It’s also hard to get a truly terrible answer. In both cases, that’s by design.

You know how when you get a new phone and you have to teach it that, no, you aren’t trying to type “duck” and “ducking” all the time? Your keyboard deliberately errs on the conservative side. There are certain words that it just won’t try to complete, even if you get really close. After all, it’s better to accidentally send the word “public” when you meant “pubic” than the other way around.

This goes for sequences of words as well. Just because a sequence is common doesn’t mean it’s a good idea to predict it. “For a while, when you typed ‘I’m going to my Grandma’s,’ GBoard would actually suggest ‘funeral,'” van Esch says. “It’s not wrong, per se. Maybe this is more common than ‘my Grandma’s rave party.’ But at the same time, it’s not something that you want to be reminded about. So it’s better to be a bit careful.”

Users seem to prefer this discretion. Keyboards get roundly criticized when a sexual, morbid, or otherwise disturbing phrase does get predicted. It’s likely that a lot more filtering happens behind the scenes before we even notice it. Janelle Shane, the creator of AI Weirdness, experiences lapses in machine judgment all the time. “Whenever I produce an AI experiment, I’m definitely filtering out offensive content, even when the training data is as innocuous as My Little Pony names. There’s no text-generating algorithm I would trust not to be offensive at some point.”

The true goal of text prediction can’t be as simple as anticipating what a user might want to type. After all, people often type things about sex or death—according to Google Ngrams, “job” is the most common noun after “blow,” and “bucket” is very common after “kick the.” But I experimentally typed these and similar taboo-but-common phrases into my phone’s keyboard, and it never predicted them straightaway. It waited until I’d typed most of the letters of the final word, until I’d definitely committed to the taboo, rather than reminding me of weighty topics when I wasn’t necessarily already thinking about them. With innocuous idioms (like “raining cats and”), the keyboard seemed more proactive about predicting them.

Instead, the goal of text prediction must be to anticipate what the user might want the machine to think they might want to type. For mundane topics, these two goals might seem identical, but their difference shows up as soon as a hint of controversy enters the picture. Predictive text needs to project an aspirational version of a user’s thoughts, a version that avoids subjects like sex and death even though these might be the most important topics to human existence—quite literally the way we enter and leave the world.

We prefer the keyboard to balance raw statistics against our feelings. Sex Death Phone Keyboard is a pretty good name for my future metal band (and a very bad name for my future pony), but I can’t say I’d actually buy a phone that reminds me of my own mortality when I’m composing a grocery list or suggests innuendos when I’m replying to a work email.

The predictive text meme is comforting in a social media world that often leaps from one dismal news cycle to the next. The customizations make us feel seen. The random quirks give our pattern-seeking brains delightful connections. The parts that don’t make sense reassure us of human superiority—the machines can’t be taking over yet if they can’t even write me a decent horoscope! And the topic boundaries prevent the meme from reminding us of our human frailty. The result is a version of ourselves through the verbal equivalent of an Instagram filter, eminently shareable on social media.

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Tech

[lazilysillyprince]

Autocomplete Presents the Best Version of You

New Post has been published on http://webhostingtop3.com/autocomplete-presents-the-best-version-of-you/

Autocomplete Presents the Best Version of You

Type the phrase “In 2019, I’ll …” and let your smart­phone’s keyboard predict the rest. Depending on what else you’ve typed recently, you might end up with a result like one of these:

In 2019, I’ll let it be a surprise to be honest. In 2019, i’ll be alone. In 2019, I’ll be in the memes of the moment. In 2019, I’ll have to go to get the dog. In 2019 I will rule over the seven kingdoms or my name is not Aegon Targareon [sic].

Many variants on the predictive text meme—which works for both Android and iOS—can be found on social media. Not interested in predicting your 2019? Try writing your villain origin story by following your phone’s suggestions after typing “Foolish heroes! My true plan is …” Test the strength of your personal brand with “You should follow me on Twitter because …” Or launch your political career with “I am running for president with my running mate, @[3rd Twitter Suggestion], because we …”

Gretchen McCulloch is WIRED’s resident linguist. She’s the cocreator of Lingthusiasm, a podcast that’s enthusiastic about linguistics, and her book Because Internet: Understanding the New Rules of Language is coming out in July 2019 from Penguin.

In eight years, we’ve gone from Damn You Autocorrect to treating the strip of three predicted words as a sort of wacky but charming oracle. But when we try to practice divination by algorithm, we’re doing something more than killing a few minutes—we’re exploring the limits of what our devices can and cannot do.

Your phone’s keyboard comes with a basic list of words and sequences of words. That’s what powers the basic language features: autocorrect, where a sequence like “rhe” changes to “the” after you type it, and the suggestion strip just above the letters, which contains both completions (if you type “keyb” it might suggest “keyboard”) and next-word predictions (if you type “predictive” it might suggest “text,” “value,” and “analytics”). It’s this predictions feature that we use to generate amusing and slightly nonsensical strings of text—a function that goes beyond its intended purpose of supplying us with a word or two before we go back to tapping them out letter by letter.

The basic reason we get different results is that, as you use your phone, words or sequences of words that you type get added to your personal word list. “For most users, the on-device dictionary ends up containing local place-names, songs they like, and so on,” says Daan van Esch, a technical program manager of Gboard, Google’s keyboard for Android. Or, in the case of the “Aegon Targareon” example, slightly misspelled Game of Thrones characters.

Another factor that helps us get unique results is a slight bias toward predicting less frequent words. “Suggesting a very common word like ‘and’ might be less helpful because it’s short and easy to type,” van Esch says. “So maybe showing a longer word is actually more useful, even if it’s less frequent.” Of course, a longer word is probably going to be more interesting as meme fodder.

Finally, phones seem to choose different paths from the very beginning. Why are some people getting “I’ll be” while others get “I’ll have” or “I’ll let”? That part is probably not very exciting: The default Android keyboard presumably has slightly different predictions than the default iPhone keyboard, and third-party apps would also have slightly different predictions.

Whatever their provenance, the random juxtaposition of predictive text memes has become fodder for a growing genre of AI humor. Botnik Studios writes goofy songs using souped-up predictive keyboards and a lot of human tweaking. The blog AI Weirdness trains neural nets to do all sorts of ridiculous tasks, such as deciding whether a string of words is more likely to be a name from My Little Pony or a metal band. Darth Vader? 19 percent metal, 81 percent pony. Leia Organa? 96 percent metal, 4 percent pony. (I’m suddenly interpreting Star Wars in quite a new light.)

The combination of the customization and the randomness of the predictive text meme is compelling the way a BuzzFeed quiz or a horoscope is compelling—it gives you a tiny amount of insight into yourself to share, but not so much that you’re baring your soul. It’s also hard to get a truly terrible answer. In both cases, that’s by design.

You know how when you get a new phone and you have to teach it that, no, you aren’t trying to type “duck” and “ducking” all the time? Your keyboard deliberately errs on the conservative side. There are certain words that it just won’t try to complete, even if you get really close. After all, it’s better to accidentally send the word “public” when you meant “pubic” than the other way around.

This goes for sequences of words as well. Just because a sequence is common doesn’t mean it’s a good idea to predict it. “For a while, when you typed ‘I’m going to my Grandma’s,’ GBoard would actually suggest ‘funeral,'” van Esch says. “It’s not wrong, per se. Maybe this is more common than ‘my Grandma’s rave party.’ But at the same time, it’s not something that you want to be reminded about. So it’s better to be a bit careful.”

Users seem to prefer this discretion. Keyboards get roundly criticized when a sexual, morbid, or otherwise disturbing phrase does get predicted. It’s likely that a lot more filtering happens behind the scenes before we even notice it. Janelle Shane, the creator of AI Weirdness, experiences lapses in machine judgment all the time. “Whenever I produce an AI experiment, I’m definitely filtering out offensive content, even when the training data is as innocuous as My Little Pony names. There’s no text-generating algorithm I would trust not to be offensive at some point.”

The true goal of text prediction can’t be as simple as anticipating what a user might want to type. After all, people often type things about sex or death—according to Google Ngrams, “job” is the most common noun after “blow,” and “bucket” is very common after “kick the.” But I experimentally typed these and similar taboo-but-common phrases into my phone’s keyboard, and it never predicted them straightaway. It waited until I’d typed most of the letters of the final word, until I’d definitely committed to the taboo, rather than reminding me of weighty topics when I wasn’t necessarily already thinking about them. With innocuous idioms (like “raining cats and”), the keyboard seemed more proactive about predicting them.

Instead, the goal of text prediction must be to anticipate what the user might want the machine to think they might want to type. For mundane topics, these two goals might seem identical, but their difference shows up as soon as a hint of controversy enters the picture. Predictive text needs to project an aspirational version of a user’s thoughts, a version that avoids subjects like sex and death even though these might be the most important topics to human existence—quite literally the way we enter and leave the world.

We prefer the keyboard to balance raw statistics against our feelings. Sex Death Phone Keyboard is a pretty good name for my future metal band (and a very bad name for my future pony), but I can’t say I’d actually buy a phone that reminds me of my own mortality when I’m composing a grocery list or suggests innuendos when I’m replying to a work email.

The predictive text meme is comforting in a social media world that often leaps from one dismal news cycle to the next. The customizations make us feel seen. The random quirks give our pattern-seeking brains delightful connections. The parts that don’t make sense reassure us of human superiority—the machines can’t be taking over yet if they can’t even write me a decent horoscope! And the topic boundaries prevent the meme from reminding us of our human frailty. The result is a version of ourselves through the verbal equivalent of an Instagram filter, eminently shareable on social media.

More Great WIRED Stories

Tech

[hostingnewsfeed]

Autocomplete Presents the Best Version of You

New Post has been published on http://webhostingtop3.com/autocomplete-presents-the-best-version-of-you/

Autocomplete Presents the Best Version of You

Type the phrase “In 2019, I’ll …” and let your smart­phone’s keyboard predict the rest. Depending on what else you’ve typed recently, you might end up with a result like one of these:

In 2019, I’ll let it be a surprise to be honest. In 2019, i’ll be alone. In 2019, I’ll be in the memes of the moment. In 2019, I’ll have to go to get the dog. In 2019 I will rule over the seven kingdoms or my name is not Aegon Targareon [sic].

Many variants on the predictive text meme—which works for both Android and iOS—can be found on social media. Not interested in predicting your 2019? Try writing your villain origin story by following your phone’s suggestions after typing “Foolish heroes! My true plan is …” Test the strength of your personal brand with “You should follow me on Twitter because …” Or launch your political career with “I am running for president with my running mate, @[3rd Twitter Suggestion], because we …”

Gretchen McCulloch is WIRED’s resident linguist. She’s the cocreator of Lingthusiasm, a podcast that’s enthusiastic about linguistics, and her book Because Internet: Understanding the New Rules of Language is coming out in July 2019 from Penguin.

In eight years, we’ve gone from Damn You Autocorrect to treating the strip of three predicted words as a sort of wacky but charming oracle. But when we try to practice divination by algorithm, we’re doing something more than killing a few minutes—we’re exploring the limits of what our devices can and cannot do.

Your phone’s keyboard comes with a basic list of words and sequences of words. That’s what powers the basic language features: autocorrect, where a sequence like “rhe” changes to “the” after you type it, and the suggestion strip just above the letters, which contains both completions (if you type “keyb” it might suggest “keyboard”) and next-word predictions (if you type “predictive” it might suggest “text,” “value,” and “analytics”). It’s this predictions feature that we use to generate amusing and slightly nonsensical strings of text—a function that goes beyond its intended purpose of supplying us with a word or two before we go back to tapping them out letter by letter.

The basic reason we get different results is that, as you use your phone, words or sequences of words that you type get added to your personal word list. “For most users, the on-device dictionary ends up containing local place-names, songs they like, and so on,” says Daan van Esch, a technical program manager of Gboard, Google’s keyboard for Android. Or, in the case of the “Aegon Targareon” example, slightly misspelled Game of Thrones characters.

Another factor that helps us get unique results is a slight bias toward predicting less frequent words. “Suggesting a very common word like ‘and’ might be less helpful because it’s short and easy to type,” van Esch says. “So maybe showing a longer word is actually more useful, even if it’s less frequent.” Of course, a longer word is probably going to be more interesting as meme fodder.

Finally, phones seem to choose different paths from the very beginning. Why are some people getting “I’ll be” while others get “I’ll have” or “I’ll let”? That part is probably not very exciting: The default Android keyboard presumably has slightly different predictions than the default iPhone keyboard, and third-party apps would also have slightly different predictions.

Whatever their provenance, the random juxtaposition of predictive text memes has become fodder for a growing genre of AI humor. Botnik Studios writes goofy songs using souped-up predictive keyboards and a lot of human tweaking. The blog AI Weirdness trains neural nets to do all sorts of ridiculous tasks, such as deciding whether a string of words is more likely to be a name from My Little Pony or a metal band. Darth Vader? 19 percent metal, 81 percent pony. Leia Organa? 96 percent metal, 4 percent pony. (I’m suddenly interpreting Star Wars in quite a new light.)

The combination of the customization and the randomness of the predictive text meme is compelling the way a BuzzFeed quiz or a horoscope is compelling—it gives you a tiny amount of insight into yourself to share, but not so much that you’re baring your soul. It’s also hard to get a truly terrible answer. In both cases, that’s by design.

You know how when you get a new phone and you have to teach it that, no, you aren’t trying to type “duck” and “ducking” all the time? Your keyboard deliberately errs on the conservative side. There are certain words that it just won’t try to complete, even if you get really close. After all, it’s better to accidentally send the word “public” when you meant “pubic” than the other way around.

This goes for sequences of words as well. Just because a sequence is common doesn’t mean it’s a good idea to predict it. “For a while, when you typed ‘I’m going to my Grandma’s,’ GBoard would actually suggest ‘funeral,'” van Esch says. “It’s not wrong, per se. Maybe this is more common than ‘my Grandma’s rave party.’ But at the same time, it’s not something that you want to be reminded about. So it’s better to be a bit careful.”

Users seem to prefer this discretion. Keyboards get roundly criticized when a sexual, morbid, or otherwise disturbing phrase does get predicted. It’s likely that a lot more filtering happens behind the scenes before we even notice it. Janelle Shane, the creator of AI Weirdness, experiences lapses in machine judgment all the time. “Whenever I produce an AI experiment, I’m definitely filtering out offensive content, even when the training data is as innocuous as My Little Pony names. There’s no text-generating algorithm I would trust not to be offensive at some point.”

The true goal of text prediction can’t be as simple as anticipating what a user might want to type. After all, people often type things about sex or death—according to Google Ngrams, “job” is the most common noun after “blow,” and “bucket” is very common after “kick the.” But I experimentally typed these and similar taboo-but-common phrases into my phone’s keyboard, and it never predicted them straightaway. It waited until I’d typed most of the letters of the final word, until I’d definitely committed to the taboo, rather than reminding me of weighty topics when I wasn’t necessarily already thinking about them. With innocuous idioms (like “raining cats and”), the keyboard seemed more proactive about predicting them.

Instead, the goal of text prediction must be to anticipate what the user might want the machine to think they might want to type. For mundane topics, these two goals might seem identical, but their difference shows up as soon as a hint of controversy enters the picture. Predictive text needs to project an aspirational version of a user’s thoughts, a version that avoids subjects like sex and death even though these might be the most important topics to human existence—quite literally the way we enter and leave the world.

We prefer the keyboard to balance raw statistics against our feelings. Sex Death Phone Keyboard is a pretty good name for my future metal band (and a very bad name for my future pony), but I can’t say I’d actually buy a phone that reminds me of my own mortality when I’m composing a grocery list or suggests innuendos when I’m replying to a work email.

The predictive text meme is comforting in a social media world that often leaps from one dismal news cycle to the next. The customizations make us feel seen. The random quirks give our pattern-seeking brains delightful connections. The parts that don’t make sense reassure us of human superiority—the machines can’t be taking over yet if they can’t even write me a decent horoscope! And the topic boundaries prevent the meme from reminding us of our human frailty. The result is a version of ourselves through the verbal equivalent of an Instagram filter, eminently shareable on social media.

More Great WIRED Stories

Tech

[hostingnewsfeed]

Autocomplete Presents the Best Version of You

New Post has been published on http://webhostingtop3.com/autocomplete-presents-the-best-version-of-you/

Autocomplete Presents the Best Version of You

Type the phrase “In 2019, I’ll …” and let your smart­phone’s keyboard predict the rest. Depending on what else you’ve typed recently, you might end up with a result like one of these:

In 2019, I’ll let it be a surprise to be honest. In 2019, i’ll be alone. In 2019, I’ll be in the memes of the moment. In 2019, I’ll have to go to get the dog. In 2019 I will rule over the seven kingdoms or my name is not Aegon Targareon [sic].

Many variants on the predictive text meme—which works for both Android and iOS—can be found on social media. Not interested in predicting your 2019? Try writing your villain origin story by following your phone’s suggestions after typing “Foolish heroes! My true plan is …” Test the strength of your personal brand with “You should follow me on Twitter because …” Or launch your political career with “I am running for president with my running mate, @[3rd Twitter Suggestion], because we …”

Gretchen McCulloch is WIRED’s resident linguist. She’s the cocreator of Lingthusiasm, a podcast that’s enthusiastic about linguistics, and her book Because Internet: Understanding the New Rules of Language is coming out in July 2019 from Penguin.

In eight years, we’ve gone from Damn You Autocorrect to treating the strip of three predicted words as a sort of wacky but charming oracle. But when we try to practice divination by algorithm, we’re doing something more than killing a few minutes—we’re exploring the limits of what our devices can and cannot do.

Your phone’s keyboard comes with a basic list of words and sequences of words. That’s what powers the basic language features: autocorrect, where a sequence like “rhe” changes to “the” after you type it, and the suggestion strip just above the letters, which contains both completions (if you type “keyb” it might suggest “keyboard”) and next-word predictions (if you type “predictive” it might suggest “text,” “value,” and “analytics”). It’s this predictions feature that we use to generate amusing and slightly nonsensical strings of text—a function that goes beyond its intended purpose of supplying us with a word or two before we go back to tapping them out letter by letter.

The basic reason we get different results is that, as you use your phone, words or sequences of words that you type get added to your personal word list. “For most users, the on-device dictionary ends up containing local place-names, songs they like, and so on,” says Daan van Esch, a technical program manager of Gboard, Google’s keyboard for Android. Or, in the case of the “Aegon Targareon” example, slightly misspelled Game of Thrones characters.

Another factor that helps us get unique results is a slight bias toward predicting less frequent words. “Suggesting a very common word like ‘and’ might be less helpful because it’s short and easy to type,” van Esch says. “So maybe showing a longer word is actually more useful, even if it’s less frequent.” Of course, a longer word is probably going to be more interesting as meme fodder.

Finally, phones seem to choose different paths from the very beginning. Why are some people getting “I’ll be” while others get “I’ll have” or “I’ll let”? That part is probably not very exciting: The default Android keyboard presumably has slightly different predictions than the default iPhone keyboard, and third-party apps would also have slightly different predictions.

Whatever their provenance, the random juxtaposition of predictive text memes has become fodder for a growing genre of AI humor. Botnik Studios writes goofy songs using souped-up predictive keyboards and a lot of human tweaking. The blog AI Weirdness trains neural nets to do all sorts of ridiculous tasks, such as deciding whether a string of words is more likely to be a name from My Little Pony or a metal band. Darth Vader? 19 percent metal, 81 percent pony. Leia Organa? 96 percent metal, 4 percent pony. (I’m suddenly interpreting Star Wars in quite a new light.)

The combination of the customization and the randomness of the predictive text meme is compelling the way a BuzzFeed quiz or a horoscope is compelling—it gives you a tiny amount of insight into yourself to share, but not so much that you’re baring your soul. It’s also hard to get a truly terrible answer. In both cases, that’s by design.

You know how when you get a new phone and you have to teach it that, no, you aren’t trying to type “duck” and “ducking” all the time? Your keyboard deliberately errs on the conservative side. There are certain words that it just won’t try to complete, even if you get really close. After all, it’s better to accidentally send the word “public” when you meant “pubic” than the other way around.

This goes for sequences of words as well. Just because a sequence is common doesn’t mean it’s a good idea to predict it. “For a while, when you typed ‘I’m going to my Grandma’s,’ GBoard would actually suggest ‘funeral,'” van Esch says. “It’s not wrong, per se. Maybe this is more common than ‘my Grandma’s rave party.’ But at the same time, it’s not something that you want to be reminded about. So it’s better to be a bit careful.”

Users seem to prefer this discretion. Keyboards get roundly criticized when a sexual, morbid, or otherwise disturbing phrase does get predicted. It’s likely that a lot more filtering happens behind the scenes before we even notice it. Janelle Shane, the creator of AI Weirdness, experiences lapses in machine judgment all the time. “Whenever I produce an AI experiment, I’m definitely filtering out offensive content, even when the training data is as innocuous as My Little Pony names. There’s no text-generating algorithm I would trust not to be offensive at some point.”

The true goal of text prediction can’t be as simple as anticipating what a user might want to type. After all, people often type things about sex or death—according to Google Ngrams, “job” is the most common noun after “blow,” and “bucket” is very common after “kick the.” But I experimentally typed these and similar taboo-but-common phrases into my phone’s keyboard, and it never predicted them straightaway. It waited until I’d typed most of the letters of the final word, until I’d definitely committed to the taboo, rather than reminding me of weighty topics when I wasn’t necessarily already thinking about them. With innocuous idioms (like “raining cats and”), the keyboard seemed more proactive about predicting them.

Instead, the goal of text prediction must be to anticipate what the user might want the machine to think they might want to type. For mundane topics, these two goals might seem identical, but their difference shows up as soon as a hint of controversy enters the picture. Predictive text needs to project an aspirational version of a user’s thoughts, a version that avoids subjects like sex and death even though these might be the most important topics to human existence—quite literally the way we enter and leave the world.

We prefer the keyboard to balance raw statistics against our feelings. Sex Death Phone Keyboard is a pretty good name for my future metal band (and a very bad name for my future pony), but I can’t say I’d actually buy a phone that reminds me of my own mortality when I’m composing a grocery list or suggests innuendos when I’m replying to a work email.

The predictive text meme is comforting in a social media world that often leaps from one dismal news cycle to the next. The customizations make us feel seen. The random quirks give our pattern-seeking brains delightful connections. The parts that don’t make sense reassure us of human superiority—the machines can’t be taking over yet if they can’t even write me a decent horoscope! And the topic boundaries prevent the meme from reminding us of our human frailty. The result is a version of ourselves through the verbal equivalent of an Instagram filter, eminently shareable on social media.

More Great WIRED Stories

Tech