Adonis Diaries

Archive for the ‘humor’ Category

What Teachers Make?

What Teachers Make
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This is a motherfucking website.

“Good design is as little design as possible”.

Seriously, what the fuck else do you want?

You probably build websites and think your shit is special.

You think your 13 megabyte paralaxative home page is going to get you some fucking Award banner you can glue to the top corner of your site. You think your 40-pound jQuery file and 83 polyfills give IE7 a boner because it finally has box-shadow. Wrong, motherfucker. Let me describe your perfect-ass website:

  • Shit’s lightweight and loads fast
  • Fits on all your shitty screens
  • Looks the same in all your shitty browsers
  • The motherfucker’s accessible to every asshole that visits your site
  • Shit’s legible and gets your fucking point across (if you had one instead of just 5mb pics of hipsters drinking coffee)

Well guess what, motherfucker:

You. Are. Over-designing.

Look at this shit. It’s a motherfucking website. Why the fuck do you need to animate a fucking trendy-ass banner flag when I hover over that useless piece of shit?

You spent hours on it and added 80 kilobytes to your fucking site, and some motherfucker jabbing at it on their iPad with fat sausage fingers will never see that shit. Not to mention blind people will never see that shit, but they don’t see any of your shitty shit.

You never knew it, but this is your perfect website. Here’s why.

It’s fucking lightweight

This entire page weighs less than the gradient-meshed facebook logo on your fucking WordPress site. Did you seriously load 100kb of jQuery UI just so you could animate the fucking background color of a div?

You loaded all 7 fontfaces of a shitty webfont just so you could say “Hi.” at 100px height at the beginning of your site? You piece of shit.

It’s responsive

You dumbass. You thought you needed media queries to be responsive, but no. Responsive means that it responds to whatever motherfucking screensize it’s viewed on. This site doesn’t care if you’re on an iMac or a motherfucking Tamagotchi.

It fucking works

Look at this shit. You can read it … that is, if you can read, motherfucker. It makes sense. It has motherfucking hierarchy. It’s using HTML5 tags so you and your bitch-ass browser know what the fuck’s in this fucking site. That’s semantics, motherfucker.

It has content on the fucking screen. Your site has three bylines and link to your dribbble account, but you spread it over 7 full screens and make me click some bobbing button to show me how cool the jQuery ScrollTo plugin is.

Cross-browser compatibility? Load this motherfucker in IE6. I fucking dare you.

This is a website. Look at it. You’ve never seen one before.

Like the pansy-ass who’s never grown out his beard has no idea what his true natural state is, you have no fucking idea what a website is. All you have ever seen are shitty skeuomorphic bastardizations of what should be text communicating a fucking message. This is a real, naked website. Look at it. It’s fucking beautiful.

Yes, this is fucking satire, you fuck

I’m not actually saying your shitty site should look like this. What I’m saying is that all the problems we have with websites are ones we create ourselves.

Websites aren’t broken by default, they are functional, high-performing, and accessible. You break them. You son-of-a-bitch.

“Good design is as little design as possible.
– some German motherfucker

Note: I have no idea where I got this article or who wrote it

If It Happened There … America’s Annual Festival Pilgrimage Begins

 posted this Nov. 27, 2013
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The long journey home. Photo by Kevork Djansezian/Getty Images

This is the fourth installment of a continuing series in which American events are described using the tropes and tone normally employed by the American media to describe events in other countries.

WASHINGTON, D.C., United States—On Wednesday morning, this normally bustling capital city became a ghost town as most of its residents embarked on the long journey to their home villages for an annual festival of family, food, and questionable historical facts.

Experts say the day is vital for understanding American society and economists are increasingly taking note of its impact on the world economy.

The annual holiday, known as Thanksgiving, celebrates a mythologized moment of peace between America’s early foreign settlers and its native groups—a day that by Americans’ own admission preceded a near genocide of those groups.

Despite its murky origins, the holiday remains a rare institution celebrated almost universally in this ethnically diverse society.

During the holiday, more than 38.4 million Americans will make the long pilgrimage home, traveling an average of 214 miles over congested highways, often in inclement weather.

The more prosperous citizens will frequently opt for the nation’s airways, suffering through a series of flight delays and missed airline connections thanks to the country’s decaying transportation infrastructure and residual fears of foreign terrorist attacks.

Once home, the holiday’s traditions encourage Americans to consume massive quantities of food centered around the turkey, a flightless, and some would say tasteless bird , native to the American continent.

All in all, 46 million of these animals will be slaughtered for the feast, nearly 20% of those raised each year.

The average American will consume an almost unbelievable 4,500 calories, despite ongoing warnings about dangerous obesity rates nationally.

Virtually the only break from the eating comes when Americans gather around the television to watch a special presentation of football, the country’s most popular sport.

If the brutal violence of the game seems at odds with the holiday’s emphasis on thanks and good will, no one seems to mind.

Though rooted in America’s ancient history, the celebration of Thanksgiving today also reflects the transforming values of American society.

One relatively recent tradition is the head of state’s public “pardoning” of a turkey—a sop to animal rights activists made somewhat moot by the fact that the country’s president simply dines on a different turkey.

To outsiders, it can also seem like a somewhat macabre gesture since the United States is one of the last developed countries to employ the death penalty for humans.

Traditionally, the Friday and weekend following Thanksgiving have been set aside for another American institution—intense consumer activity and bargain shopping.

(The availability of deeply discounted goods is increasingly beginning even sooner, sometime on the holiday itself, angering some purists.)

More than $59 billion will be spent over these days, though the exact figure will be watched closely by economists looking for clues about the country’s national mood and economic well-being.

The event is known as “Black Friday,” though contrary to popular belief, this is not due to the injuries and deaths that periodically occur during retail stampedes.

In recent years, some experts have questioned whether the hidden costs of the Thanksgiving holiday have become excessive;

whether the celebration is worth its massive environmental impact and the increased health risks due to traffic accidents and overeating.

Still, the majority of the population holds fast to these pastimes.

For them, they are part of a rare, quintessentially American tradition in a modernizing society that finds itself increasingly under the influence of the outside world.

Traditional Russian Wedding Pictures

January 31st, 2014

Also check out these stunning galleries:
Life in Russia

Read more athttp://www.sadanduseless.com/2014/01/traditional-russian-wedding-pictures/#uDDYvAgAdADzpW61.99

Refreshing your memory? This huge rock that sits on your chest…?

Unless you keep diaries, detailed and transparent diaries, recollecting events of your life is like digging around a bad big rock in order to dislodge it.

Most of the time, you are playing the archaeologist, digging carefully and very slowly in order not to disturb the chronological story and get to the context of the event and the various external factors that played catalyst to the event…

More often than not, it is the collateral emotions that surface, more horrific than what you initially asked for.

And your mind takes a tangent and lead your memory to paths that you completely have forgotten.

It is Not that you are rediscovering the events and emotions: They are basically false what you recollected.

Events and emotions that have been created and developed through the years, and never the kind of refresher kinds.

Altered events and emotions that are within the “feeling of what happened“.

And who cares about the actual facts and the detailed occurrences: You are after “hidden emotions” that you believe were truer and more candid and represent “Who you are…”?

Wrong. You don’t want to really know and feel how you were as a child, this brute and egomaniac child, this uncultured and half cooked mankind…

Can you teach a computer to be funny?

The reverse is already more than funny

Note: Good humor requires vast general knowledge: A rare ingredient. Hard to accumulate a vast data-base for categorizing humor and performing statistical analysis

Nov 2, 2017 

Here’s one example of a machine-generated joke: “Why did the chicken cross the road? To see the punchline.”

Learn about the work that scientists are doing to make AI more LOL.

When it comes to predicting advances in AI, the popular imagination tends to fixate on the most dystopian scenarios: as in, If our machines get so smart, someday they’ll rise up against humanity and take over the world.

But what if all our machines wanted to do was crack some jokes?

That is the dream of computational humorists — machine learning researchers dedicated to creating funny computers.

One such enthusiast is Vinith Misra (TED@IBM Talk: Machines need an algorithm for humor: Here’s what it looks like), a data scientist at Netflix (and consultant to HBO’s Silicon Valley) who wants to see a bit more whimsy in technology.

While there’s intrinsic value in cracking the code for humor, this research also holds practical importance.

As machines occupy larger and larger chunks of our lives, Misra sees a need to imbue circuitry with personality. We’ve all experienced the frustration caused by a dropped phone call or a crashed program.

Your computer isn’t a sympathetic audience during these trials and tribulations; at times like these, levity can go a long way in improving our relationship with technology.

So, how do you program a computer for laughs? “Humor is one of the most non-computational things,” Misra says. In other words, there’s no formula for funny-ness.

While you can learn how to bake a cake or build a chair from a set of instructions, there’s no recipe for crafting a great joke. But if we want to imbue our machines with wit, we need to find some kind of a recipe; after all, computers are unflinching rule-followers. This is the great quagmire of computational humor.

To do this, you have to pick apart what makes a particular joke funny. (Like in linguistic?)

Then you need to turn your ideas into rules and codify them into algorithms. However, humor is kind of like pornography … you know it when you see it. (Humor is Not just words: it is gestures, silences, faces, postures, vast general knowledge…)

A joke told by British comedian Lee Dawson exemplifies the difficulties of deconstructing jokes, according to Misra. It goes: “My mother-in-law fell down a wishing well the other day. I was surprised — I had no idea that they worked!” 

It’s not so easy to pick out why this joke works (and some mothers-in-law would argue it does not work at all). For starters, there’s a certain amount of societal context that goes with understanding why a mother-in-law going down a well is funny. (Now, what’s a wishing well?)

Does this mean that creating a joke-telling computer would require the uploading and analyzing of an entire culture’s worth of knowledge and experience?

Some researchers have been experimenting with a different approach.

Abhinav Moudgil, a graduate student at the International Institute for Information Technology in Hyderabad, India, works primarily in the field of computer vision but explores his interest in computational humor in his spare time.

Moudgil has been working with a recurrent neural network, a popular type of statistical model. The distinction between neural networks and older, rule-based models could be compared to the difference between showing and telling.

With rule-based algorithms, most of the legwork is done by the coders; they put in a great deal of labor and energy up-front, writing specific directions for the program that tells it what to do. The system is highly constrained, and it produces a set of similarly structured jokes. The results are decent but closer to what kids — not adults — might find hilarious.

Here are two examples:

“What is the difference between a mute glove and a silent cat? One is a cute mitten and the other is a mute kitten.”

“What do you call a strange market? A bizarre bazaar.”

With neural networks, data does the heavy lifting; you can show a program what to generate by feeding it a data-set of hundreds of thousands of examples. The network picks out patterns and emulates them when it generates text. (This is the same way computers “learn” how to recognize particular images.)

Of course, neural networks don’t see like humans do. Networks analyze data inputs, whether pictures or text, as strings of numbers, and comb through these strings to detect patterns. The number of times your network analyzes the dataset — called iterations — is incredibly important: too few iterations, and the network won’t pick up enough patterns; too many, and the network will pick out superfluous patterns.

For instance, if you want your network to recognize flamingos but you made it iterate on a set of flamingo pictures for too long, it would probably get better at recognizing that particular set of pictures rather than flamingos in general.

Moudgil created a dataset of 231,657 short jokes culled from the far corners of the Internet.

He fed it to his network, which analyzed the jokes letter by letter. Because the network operates on a character level, it didn’t analyze the wordplay of the jokes; instead, it picked up on the probabilities of certain letters appearing after other letters and then generated jokes along similar lines.

So, because many of the jokes in the training set were in the form “What do you call…” or “Why did the…”, the letter “w” had a high probability of being followed by “h”, the letter pair “wh” had high probabilities of being followed by “y” or “a,” and the letter sequence “wha” was almost certainly followed by “t.”

His network generated a lot of jokes — some terrible, some awful and some okay. Here’s a sample:

“I think hard work is the reason they hate me.”

“Why can’t Dracula be true? Because there are too many cheetahs.”

“Why did the cowboy buy the frog? Because he didn’t have any brains.”

Why did the chicken cross the road? To see the punchline.”

Some read more like Zen koans than jokes. 

That’s because Moudgil trained his network with many different kinds of humor. While his efforts won’t get him a comedy writing gig, he considers them to be promising. He plans to continue his work, and he’s also made his dataset public to encourage others to experiment as well.

He wants the machine learning community to know that, he says, “a neural net is a way to do humor research.”

On his next project, Moudgil will try to eliminate nonsensical results by training the network on a large set of English sentences before he trains it on a joke dataset. That way, the network will have integrated grammar into its joke construction and should generate much less gibberish.

Other efforts have focused on replicating a particular comedian’s style. He Ren and Quan Yang of Stanford University trained a neural network to imitate the humor of Conan O’Brien.

Their model generated these one-liners:

“Apple is teaming up with Playboy in the self-driving office.”

“New research finds that Osama Bin Laden was arrested for President on a Southwest Airlines flight.”

Yes, the results read a bit more like drunk Conan than real Conan. Ren and Yang estimate only 12% of the jokes were funny (based on human ratings), and some of the funny jokes only generated laughs because they were so nonsensical.

These efforts show there’s clearly a lot of work to be done before researchers can say they’ve successfully engineered humor.

“They’re an effective illustration of the state of computational humor today, which is both promising in the long term and discouraging in the short term,” says Misra.

Yet if we ever want to build AI that simulates human-style intelligence, we’ll need to figure out how to code for funny. And when we finally do, this could turn our human fears of a machine uprising into something we can all laugh about.

A few stories of regret?

There was a French girl student in my class of Physics/Chemistry at the university. We spent 2 years in that program and I don’t recall I have ever talked to her.

She was slim, slightly red-headed, hair cut a la garcon, rather flat-chested and elegant in her sober attire and wore the same flat shoes. I think she was pretty. It would have taken a forceful determination from any girl then to take the initiative and lead me to utter a few sentences.

Another regret. She occasionally paid her grandmother visits, from the other part of the continent. I occasionally wrote her letters in the name of her mentally handicapped grand mother.

One of the letter included a convoluted sentence that she picked up as a confession of love. And it was.
A couple of weeks later she showed up. She went jogging and rubbed her feet with lotion. She then asked me to go for a walk. She wanted a verbal confirmation.

I was in a rot with my PhD dissertation and lacked the spirit for such kinds of conversation. I couldn’t master enough craziness to blurt out: ” I find you a lovely, natural and compassionate woman. Take me with you…”
I didn’t see her again: I moved out to another old lady house whose son wanted someone to live with.

Another regret. It was winter of 1976. A Friday, and about 8:30 pm.  Alone, I am to watch a foreign movie, shown by the University Film Club at the Microbiology department.

She showed up with her girlfriend. She is blonde, blue/green eyed, not tall, not skinny.For my candid eyes, just the perfect beauty. I cowered. I should have made haste, join her, and say: “Fair lady, have a good look at my face.

A couple of days later, returning from the library at midnight, I saw her “studying” with my roommate. I had to piss badly and as I emerged, she was gone.

Another regret: When I first saw her I was mesmerized. She was wearing boots and a white shirt and looked gorgeous and stunning. I had to meet her in West Hollywood to convey her sister salutation who had a Lebanese boyfriend. She kept asking me about my friend, as if I was a mere messenger. She never knew that she made me walk on air the entire encounter

Note 1: I barely recollect a regret Not involving a beautiful girl whom I failed to engage with. The first lesson in classrooms for adolescent of both sex should be “how to engage a girl you think you like” and save a lifetime of accumulated regrets.

Note 2: You may read a detailed account of these regrets and much more in my category Auto-biography


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