The Hexacoto

Listening to the sound of one hand clapping

Tag: funny

Anyhow Noodles

“What are you making?” you asked, as you walked into the kitchen. “Ugh, you’re using that giant ass wok. It’s such a hassle to wash,” you said.

“Hey, this wok is feeding your ass so don’t complain,” I replied.

“So what are you making? It looks like you’re just randomly throwing things into the wok and frying shit up.”

“That’s right, I’m making ‘Anyhow Noodles.'”

“Anyhow Noodles? What the heck is that?”

“It’s where you randomly throw things into the wok and fry shit up. When you understand cooking enough at my level, you can throw anything into a wok and it’ll turn out fine.”

“So what goes into Anyhow Noodles?”

“You have to have noodles, that’s why it’s ‘Anyhow Noodles’ and not ‘Anyhow Rice,’ right?”

“I can see that…”

“And then, you add in vegetables, meat, brown sauce and you’re done!”

“Wait hold on. Brown sauce?”

“Yes. Brown sauce. It’s sauce that’s brown.”

“And what goes in brown sauce?”

“Brown flavour.”

“That doesn’t even make sense.”

“It does back home. Everyone knows what ‘brown sauce’ is. It’s an established flavour.”

“You’re making shit up. You’re fucking with me.”

“If you don’t believe me, go ask your friend Cassie. She’ll know what ‘brown flavour’ is. All Asians know it.”

……

“Ok I don’t believe it. She told me ‘brown’ is totally a flavour. Her mum makes food with it too, what the fuck. That’s so weird.”

“Well I’m sorry the food you’re eating is weird.”

“Ok then what’s the meat that goes into Anyhow Noodles? ‘Has-legs’? ‘Living-creature?’ ‘Matter???'”

“Don’t be silly. It’s just beef.”

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You ain’t so good, Google Neural Net

Google recently launched an interactive web game to train its neural network to recognise objects. The game, Quick Draw, calls on human users to draw a prompted object within a short period of time and the machine tries to guess what it is based on what it has learned so far from all of the inputs of previous players. Quite ingenious, to crowdsource training a machine learning (ML) program since many people are always looking for an excuse not to do work.

I wanted to test its learning limits. I more or less had a sense of how previous inputs for the prompts would look like, since humans tend to draw objects similarly when under time pressure. I wondered if I drew all of the objects from a different perspective, would the program still recognise it as the object — a task which humans are very capable of?

The answer is: not really.

I experimented with drawing in a sequence that would not be obvious what the object is immediately, but the end product would be discernibly apparent. I experimented with odd and skewed perspectives. Google Neural Net failed most of the time.

screen-shot-2016-11-17-at-3-17-20-pm

I think my mountains were really good! I started with a skewed line to not trigger immediate “mountain” responses from Neural Net and then quickly added half lines but by the time I was done, any human would have seen that these are really good mountains.screen-shot-2016-11-17-at-3-30-52-pm

I thought it was cute that my mouth were interpreted as a bear, an owl and a smiley face. What?? I started with the top line forming the nose, lips, mouth, chin and neck, followed by the back of the head. I filled in details and drew an arrow pointing to the mouth. In Neural Net’s fairness, its creators probably never accounted for it to learn the concept of pointing — a task that I don’t think is too difficult given how far we’ve come along in ML. It seems Neural Net has really only been learning to identify objects by scanning them as a whole.screen-shot-2016-11-17-at-5-23-15-pm

I drew a jagged tooth key, instead of a wedge-end key because I thought it’d be too obvious. By the time I finished the key, Neural Net still hadn’t recognized it. I had some time left and literally drew in the words “KEY” hoping it’d help Neural Net along but noooope. It thought it to be a crocodile. Cute croc though.

Looking at what examples Neural Net uses as its learned base to pass judgment, one sees that humans tend to draw things either profile or head-on, and hence how Neural Net learns to identify objects.

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Come on. My butterfly was clearly the best butterfly all of Neural Net’s learned examples.screen-shot-2016-11-17-at-5-22-35-pm screen-shot-2016-11-17-at-5-22-45-pm

How are some of your examples even mushrooms!? They look more like penises! I declare my mushroom to be mushroomier than your learned examples!

Google Neural Net, it seems you have a long way to go.

 

Bonus pic from a friend:

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COME ON. In what universe are these trombones?? I’m starting to think people have never seen what a trombone looks like.

Balance Your Chicken

Sometimes, you just gotta lighten up and take a break and create pointless, stupid stuff. I had been on the train, on my phone, extracting bridges from songs for future use on short video clips like these when suddenly the caption “Fried chicken can be part of a balanced diet too!” popped into my head. And as a fan of Cibo Matto, the idea of for this video clip came to fruition.

And I realise I’m no stranger to creating stupid things to make sense of life.

I probably made this back in 2008 or 2009. There were a bunch of other clips from that same filming session that I am not releasing because they’re very cringeworthy.

Reddit Kim

pisai

So I made something, after having been inspired a reddit comment that said that Singaporeans would never waste money buying reddit gold for others. Hence I came up with this idea, for those kiamsiap (stingy) Singaporeans when they don’t want to buy the real thing. (Well it’s not like reddit gold is of any use anyway)

Other ideas included the nose picker projectile flicking the booger, culminating in a giant explosion. But who has time to sit down and draw/animate all that?

Made with 25 stills drawn by mouse using Adobe Photoshop, animated with Premier Pro. Done in one sitting from 8pm to 3am.

The TRUE reason why this blizzard is scary

stonest

#noescape

All Men In North Korea Are Now Reportedly Required to Get the Same Haircut as Kim Jong Un

This is way too funny not to reblog. At least the “undercut” was popular in North Korea before it even hit the States!

How do cows moo in a British accent?

A listener to the podcast “How to Do Everything” named Rachel asked: “How would a person moo in a British accent?” The listener is from Nevada, and professes to moo with an American accent.

What better way to find out than to ask someone close to the source? The kind folks at the show invited Sir Patrick Stewart to answer Rachel’s question, which has been on her mind for a couple of months. Patrick Stewart answers:

It’s not a straightforward, simple answer. Unlike, probably, many other countries, where a cow’s moo is a cow’s moo, in England, you understand, we are dominated by class, by social status, and by location. So, for example, a cow that’s in a field  next to my house in West Oxfordshire would moo in one kind of way, and cow in the field in the semi-industrial town I grew up in in the north of England would moo in another kind of way.

Patrick Stewart then goes on to demonstrate how the different cows would sound at home by bellowing himself. He describes the moo’s of the cows near his home, a long protracted low, as “very conservative.” He goes on to explain why:

You must understand that I live in the constituency of David Cameron, our Prime Minister, who is a Tory (the Conservative Party). And I assume these cows voted for him. I don’t actually vote there, I vote in another place, in London.

If I’m at my home in Yorkshire, where I grew up, and not that there are many fields left where I grew up but I would find one and I would find some cows, what you hear would be something like this: mehhhhhhh. Well, this has all to do with environmental and cultural conditioning.

He emphasises that moos vary by location, and recommends that travellers talk to cows all over the country in any country, because “cows have a great deal to tell us.”

The hosts at the show offered a bit of a culture exchange and offered to show Patrick Stewart what a Nevada cow sounds like, but Stewart suprises them all by saying that his wife is also from Nevada, and he has experience with Nevada cattle, and did his best impression of a Nevada cow. His Nevada cow is high-pitched and nasal, because “that’s the way you people (the hosts) talk. The cows are influenced by how you talk, as you are influenced by the cows.”

The hosts went on to ask, “How a Cockney cow would moo?” Stewart replies:

You understand, Cockney cows are pretty rare these days. I mean, Shakespeare’s days, there were cattle in the middle of London. But nowadays, generally speaking, the city of London doesn’t feel too good about having cattle in Picadilly Circus for example. But I can you an idea of a Cockney cow — I’m old enough to remember when there were Cockney cows.

The resulting impersonation (incowation?) sounds like a mehh-aye! which Stewart describes as “more like a sheep than a cow.” The hosts points out that in Stewart’s walk-through of English cows so far, not only are there different cow accents, it seems that there are also different cow attitudes throughout the country. Stewarts extrapolates:

You are absolutely right. What you just heard just now was an urban cow. All of us who live in big cities, we have to be watchful, we have to be on our guard. We have to be prepared for fight-or-flight at any moment, and it is the same with cattle.

Breeding is of utmost important in humans, as it is in cattle. How would a well-bred cow sound like?

We had a Prime Minister many, many years ago called Alec Douglas-Home (pronounced hyoom) and one of the wonderful things about Alec Douglas-Home — including his name by the way, and you’d think that his name is probably spelled “H-double O-M-E” or “H-U-M-L” or something like that, his name was actually spelled “H-O-M-E” — home, but it was pronounced “hume,” and we do that mostly to confuse Americans, like Leicester Square and Lye-cester.

Anyway, the thing about Alec Douglas-Home was that he didn’t move his lips when he talked, (unintelligible mumble because Stewart is mimicking talking without his lips but the words sounds like: “and here’s an example, this is how he always talks. He didn’t actually move the lips.”) Because moving your lips is terribly bad taste. So, if Alec Douglas-Home had cattle, and I’m sure he did; he must have been a landowner because I think he was actually Scottish, his cows would mooed something like this: hrmmmmmm. Very refined, very sophisticated, very cultured. These cows had gone to Eton or Harrow (prestigious boarding schools), or at least the cow equivalent.

There you go, how British cows moo, and like humans, how they speak is also  affected by social ecownomics.

I’ll see myself out now.

Listen to the full podcast here, if not for the knowledge, then at least to hear Sir Patrick Steward moo like a cow!

An order of Chinese puns, stuffed with conspiracies

It’s an interesting day when the president of China eating lunch sparks off a wave of conspiracy theories.

Chinese President Xi Jinping got in the queue with the lunch crowd and bought six steamed buns filled with pork and spring onions, a bowl of stir-fried liver, and a plate of vegetables, for a cost of 21 yuan.

On Weibo, some were marvelling at how the President himself was getting in the line, paid for the food himself, carried the trays himself, and obtained the food himself. Others wondered if his public obtaining of food had any symbolic meaning.

The New York Times reports:

While photos of the presidential lunch fill pages of Weibo, China’s Twitter-like social media site, users are trying to “crack the code” of the three simple food items for signals regarding the president’s anti-corruption campaign.

According to one theory, the name of the steamed bun shop, “Qingfeng,” which means “celebrating the harvest” but sounds like the Chinese words for “clear wind” and evokes an honest government official who never takes bribes, suggests the qualities Mr. Xi wants all government officials to uphold as a standard.

Another says the stir-fried pig liver means that any government officials who demonstrate pig-like greed will be “fried,” which can mean to be fired in Chinese.

The green vegetables Mr. Xi ordered, called “jiecai,” sound like the Chinese phrase “beware of wealth” — a possible warning to all officials to resist the temptation of financial gain.

The translucent filling of fatty pork and spring onion signifies transparency. And it is no coincidence, says one theory, that the meal cost 21 renminbi, the sum of three times seven. This is because the Chinese saying “It doesn’t matter if three times seven is 21” means that whatever is going to happen is going to happen.

“President Xi is saying government officials must stay clean and transparent, otherwise they will all get fired!” concludes this theory.

“If you are a corrupt official, the president will finish you like he did his lunch!” said another Weibo user.

So basically, the essence of Chinese conspiracy theories lie in… puns? Wow.

Which is not that surprising, given that the language is full of homophones.

Neither rain nor snow shall keep the one wheel from ruling them all

15348[1]Some two weeks ago, Utah had a snowstorm, and the picture above was circulating around the internet. Where cars skidded and crash, that lone unicyclist calm rolled on.

So did NYC.

a_560x375[1]A unicyclist was seen rolling through SoHo last night in winter storm Hercules, like a boss.

Unicyclists: Clearly the master race

 

 

Simple witty animal comics

I wish there were a simpler way to reblog things from Tumblr on Wordspace, but for now, I’ll just have to manually put pictures and stuff up.

Amongst the comics out there, it is usually the simpler ones that I appreciate the most, usually with a simple line of text. Those that require just a little bit of thinking: the comic artist puts in a little effort, just as the readers do.

A friend shared a Tumblr belonging to Liz Climo, an animator for The Simpsons. But where The Simpsons rely on in-your-face humour, Climo’s Tumblr relies on subtle wit revolving around animals, usually something to do with the physical properties of the animals themselves.

Here are some of my favourites:

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