Tag Archives: japan

Wonton font – Wikipedia, the free encyclopedia

Wonton font – Wikipedia, the free encyclopedia.

A wonton font (also known as Chinese font, chopstick font or chop-suey font, type or lettering) is a font with a visual style expressing “Asianness” or “Chineseness”.

Styled to mimic the brush strokes used in Chinese characters, wonton fonts are often used to convey a sense of Orientalism. 

feitclub | It’s a katakana font (named “ゴウラ”) designed to…

feitclub | It’s a katakana font (named “ゴウラ”) designed to….

It’s a katakana font (named “ゴウラ”) designed to look like Olde English fancy print This must be the Japanese equivalent of that “asian” font you see on Chinese takeout boxes (via a friend-of-a-friend on Facebook. hat-tip to artofemilyo)

 

It’s a katakana font (named “ゴウラ”) designed to look like Olde English fancy print

This must be the Japanese equivalent of that “asian” font you see on Chinese takeout boxes

Gate Tower Building – Wikipedia, the free encyclopedia

Gate Tower Building – Wikipedia, the free encyclopedia.

Gate Tower Building (ゲートタワービル gēto tawā biru?) is a 16-story office building in Fukushima-ku, Osaka, Japan. It is notable for the highway that passes through the building. It has been nicknamed “beehive” referencing its appearance as a “bustling place”.

The building has a double core construction, with a circular cross section. The Umeda Exit of the Ikeda Route of the Hanshin Expressway system (when exiting the highway from the direction of Ikeda) passes between the fifth and seventh floors of this building. The highway is the tenant of those floors. The elevator passes through the floors without stopping: floor 4 being followed by floor 8. The floors through which the highway passes consist of elevators, stairways and machinery. The highway does not make contact with the building. It passes through as a bridge, held up by supports next to the building. The highway is surrounded by a structure to protect the building from noise and vibration. The roof has a helipad.

For that reason, the highway laws, city planning laws, city redevelopment laws and building codes were partly revised in 1989 to permit a so-called Multi-Level Road System (立体道路制度 rittai dōro seido?) that allows the unified development of highways and buildings in the same space. This system was originally designed to facilitate the construction of the second Ring Road in the vicinity of Toranomon, Minato-ku, Tokyo, but in the end was not applied there. Instead, the system was put into effect in the construction of the Gate Tower Building, becoming Japan’s first building to have a highway pass through it. Normally, highways are still built underground in these cases, and passing through a building is an extremely rare occurrence.

A Japanese Artist Launches Plants Into Space

A Japanese Artist Launches Plants Into Space.

“Flowers aren’t just beautiful to show on tables,” said Azuma Makoto, a 38-year-old artist based in Tokyo. His latest installation piece, if you could call it that, takes this statement to the extreme. Two botanical objects — “Shiki 1,” a Japanese white pine bonsai suspended from a metal frame, and an untitled arrangement of orchids, hydrangeas, lilies and irises, among other blossoms — were launched into the stratosphere on Tuesday in Black Rock Desert outside Gerlach, Nevada, a site made famous for its hosting of the annual Burning Man festival. ”I wanted to see the movement and beauty of plants and flowers suspended in space,” Makoto explained that morning.

[…]

“The best thing about this project is that space is so foreign to most of us,” says Powell, “so seeing a familiar object like a bouquet of flowers flying above Earth domesticates space, and the idea of traveling into it.”

[…]

He started with an aerial plant tied to a six-rod axis and studiously added peace lilies, poppy seed pods, dahlias, hydrangeas, orchids, bromeliads and a meaty burgundy heliconia. “I am using brightly colored flowers from around the world so that they contrast against the darkness of space,” he said. The scent of the flowers was stronger and more concentrated in the dry desert breeze than in their humid, natural environments, and the launch site was redolent with their perfume. Makoto worked quietly, until the metal rods were covered completely with plants. Then he directed his attention to his bonsai. For this particular project, Makoto chose a 50-year-old pine from his collection of more than 100 specimens, and flew it over from Tokyo in a special box. While readying it for space, he kept it moist and removed a few brown needles with a tweezer.

[…]

Using Styrofoam and a very light metal frame, Powell and his volunteers had created two devices to attach the bonsai and the flowers, which would launch separately. JP’s volunteers and Makoto’s team worked to calibrate still cameras, donated by Fuji Film for this project, and six Go Pro video cameras tied in a ball that would record the trip into the stratosphere and back in 360 degrees. There were two different tracking systems on each device, one a Spot GPS tracker that would help locate the vessel once it fell down back to Earth, and the other that recorded altitude and distance traveled from the launch site. A radio transmitted the data to a computer array in a van. While the crew waited, Makoto took a red carnation, drilled a hole in a crack of the arid, sandy soil and planted it there. It was his nod to the huge red sun that had started to come up.

[…]

Away 101 went to 91,800 feet, traveling up for 100 minutes until the helium balloon burst. It fell for 40 minutes; two parachutes in baskets opened automatically when there was enough air in the atmosphere to soften impact. Away 100, which held the arrangement, made it up to 87,000 feet. Both devices were retrieved about five miles from the launch site. The bonsai and flowers, though, were never found.

 

The Mystery of Go, the Ancient Game That Computers Still Can’t Win | Enterprise | WIRED

The Mystery of Go, the Ancient Game That Computers Still Can’t Win | Enterprise | WIRED.

Remi Coulom (left) plays against Norimoto Yoda in Tokyo. Photo: Takashi Osato/WIRED

Crazy Stone and Nomitan are locked in a game of Go, the Eastern version of chess. On each screen, you can see a Go board — a grid of 19 lines by 19 lines — filling up with black and white playing pieces, each placed at the intersection of two lines. If Crazy Stone can win and advance to the finals, it will earn the right play one of the best human Go players in Japan. No machine has ever beaten a top human Go player — at least not without a huge head-start. Even if it does advance to the man-machine match, Crazy Stone has no chance of changing this, but Coulom wants to see how far his creation has come.

[…]

In 1994, machines took the checkers crown, when a program called Chinook beat the top human. Then, three years later, they topped the chess world, IBM’s Deep Blue supercomputer besting world champion Garry Kasparov. Now, computers match or surpass top humans in a wide variety of games: Othello, Scrabble, backgammon, poker, even Jeopardy. But not Go. It’s the one classic game where wetware still dominates hardware.

Invented over 2500 years ago in China, Go is a pastime beloved by emperors and generals, intellectuals and child prodigies. Like chess, it’s a deterministic perfect information game — a game where no information is hidden from either player, and there are no built-in elements of chance, such as dice.1 And like chess, it’s a two-person war game. Play begins with an empty board, where players alternate the placement of black and white stones, attempting to surround territory while avoiding capture by the enemy. That may seem simpler than chess, but it’s not. When Deep Blue was busy beating Kasparov, the best Go programs couldn’t even challenge a decent amateur. And despite huge computing advances in the years since — Kasparov would probably lose to your home computer — the automation of expert-level Go remains one of AI’s greatest unsolved riddles.

[…]

The challenge is daunting. In 1994, machines took the checkers crown, when a program called Chinook beat the top human. Then, three years later, they topped the chess world, IBM’s Deep Blue supercomputer besting world champion Garry Kasparov. Now, computers match or surpass top humans in a wide variety of games: Othello, Scrabble, backgammon, poker, even Jeopardy. But not Go. It’s the one classic game where wetware still dominates hardware.

Invented over 2500 years ago in China, Go is a pastime beloved by emperors and generals, intellectuals and child prodigies. Like chess, it’s a deterministic perfect information game — a game where no information is hidden from either player, and there are no built-in elements of chance, such as dice.1 And like chess, it’s a two-person war game. Play begins with an empty board, where players alternate the placement of black and white stones, attempting to surround territory while avoiding capture by the enemy. That may seem simpler than chess, but it’s not. When Deep Blue was busy beating Kasparov, the best Go programs couldn’t even challenge a decent amateur. And despite huge computing advances in the years since — Kasparov would probably lose to your home computer — the automation of expert-level Go remains one of AI’s greatest unsolved riddles.

[…]

… games of Go are often so complex that only extremely high-level players can understand how they’re progressing.

[…]

‘THERE IS CHESS IN THE WESTERN WORLD, BUT GO IS INCOMPARABLY MORE SUBTLE AND INTELLECTUAL.’

This is not for lack of trying on the part of programmers, who have worked on Go alongside chess for the last fifty years, with substantially less success. The first chess programs were written in the early fifties, one by Turing himself. By the 1970s, they were quite good. But as late as 1962, despite the game’s popularity among programmers, only two people had succeeded at publishing Go programs, neither of which was implemented or tested against humans.

Finally, in 1968, computer game theory genius Alfred Zobrist authored the first Go program capable of beating an absolute beginner. It was a promising first step, but notwithstanding enormous amounts of time, effort, brilliance, and quantum leaps in processing power, programs remained incapable of beating accomplished amateurs for the next four decades.

To understand this, think about Go in relation to chess. At the beginning of a chess game, White has twenty possible moves. After that, Black also has twenty possible moves. Once both sides have played, there are 400 possible board positions. Go, by contrast, begins with an empty board, where Black has 361 possible opening moves, one at every intersection of the 19 by 19 grid. White can follow with 360 moves. That makes for 129,960 possible board positions after just the first round of moves.

The rate at which possible positions increase is directly related to a game’s “branching factor,” or the average number of moves available on any given turn. Chess’s branching factor is 35. Go’s is 250. Games with high branching factors make classic search algorithms like minimax extremely costly. Minimax creates a search tree that evaluates possible moves by simulating all possible games that might follow, and then it chooses the move that minimizes the opponent’s best-case scenario. Improvements on the algorithm — such as alpha-beta search and null-move — can prune the chess game tree, identifying which moves deserve more attention and facilitating faster and deeper searches. But what works for chess — and checkers and Othello — does not work for Go.

[…]

“A lot of people peak out at a certain level of amateur and never get any stronger,” David Fotland explains. Fotland, an early computer Go innovator, also worked as chief engineer of Hewlett Packard’s PA-RISC processor in the 70s, and tested the system with his Go program. “There’s some kind of mental leap that has to happen to get you past that block, and the programs ran into the same issue. The issue is being able to look at the whole board, not the just the local fights.”

[…]

Coulom had exchanged ideas with a fellow academic named Bruno Bouzy, who believed that the secret to computer Go might lie in a search algorithm known as Monte Carlo. Developed in 1950 to model nuclear explosions, Monte Carlo replaces an exhaustive search with a statistical sampling of fewer possibilities. The approach made sense for Go. Rather than having to search every branch of the game tree, Monte Carlo would play out a series of random games from each possible move, and then deduce the value of the move from an analysis of the results.

[…]

Black and white stones continue to fill the board, beautiful as always, forming what is technically known as a percolated fractal.

[…]

Coulom plays down the Electric Sage Battle. “The real competition is program against program,” he told me during one early phone interview. “When my opponent is a programmer, we are doing the same thing. We can talk to each other. But when I play against a professional and he explains the moves to me, it is too high level. I can’t understand, and he can’t understand what I am doing. The Densei-sen — it is good for publicity. I am not so interested in that.”

[…]

According to University of Sydney cognitive scientist and complex systems theorist Michael Harré, professional Go players behave in ways that are incredibly hard to predict. In a recent study, Harré analyzed Go players of various strengths, focusing on the predictability of their moves given a specific local configuration of stones. “The result was totally unexpected,” he says. “Moves became steadily more predictable until players reached near-professional level. But at that point, moves started getting less predictable, and we don’t know why. Our best guess is that information from the rest of the board started influencing decision-making in a unique way.”

[…]

…no programmers think of their creations as “intelligent.” “The game of Go is spectacularly challenging,” says Coulom, “but there is nothing to do with making a human intelligence.” In other words, Watson and Crazy Stone are not beings. They are solutions to specific problems. That’s why its inaccurate to say that IBM Watson will be used to fight cancer, unless playing Jeopardy helps reduce tumors. Developing Watson might have led to insights that help create an artificial diagnostician, but that diagnostician isn’t Watson, just as MCTS programs used in hospital planning are not Crazy Stone.

The public relations folks at IBM paint a different picture, and so does the press. Anthropomorphized algorithms make for a better story. Deep Blue and Watson can be pitted against humans in highly produced man-machine battles, and IBM becomes the gatekeeper of a new era in artificial intelligence. Caught between atheism and a crippling fear of death, Ray Kurzweil and other futurists feed this mischaracterization by trumpeting the impending technological apotheosis of humanity, their breathless idiocy echoing through popular media. “The Brain’s Last Stand,” read the cover of Newsweek after Kasparov’s defeat. But in truth, these machines are nowhere close to mimicking the brain, and their creators admit as much.

Many Go players see the game as the final bastion of human dominance over computers. This view, which tacitly accepts the existence of a battle of intellects between humans and machines, is deeply misguided. In fact, computers can’t “win” at anything, not until they can experience real joy in victory and sadness in defeat, a programming challenge that makes Go look like tic-tac-toe. Computer Go matches aren’t the brain’s last stand. Rather, they help show just how far machines have to go before achieving something akin to true human intelligence. Until that day comes, perhaps it’s best to view the Densei-sen as programmers do. “It is fun for me,” says Coulom, “but that’s all.”

A Virtuoso Robot Band Whose Guitarist Has 78 Fingers | Underwire | WIRED

A Virtuoso Robot Band Whose Guitarist Has 78 Fingers | Underwire | WIRED.

Meet the Z-Machines, a band made entirely of robots. There’s Mach, a 78-fingered guitarist; Ashura, a 22-armed drummer; and Cosmo, a robot that plays keyboards with lasers.
[…]

When a team of University of Tokyo roboticists created the Z-Machines last year, it asked several artists to develop music the robots could be programmed to play, and the U.K.-based electronic composer was among them. His submission was a song called “Sad Robot Goes Funny,” but after it was finished Squarepusher (aka Tom Jenkinson) wasn’t done with his droid friends. He ended up writing an entire EP of material for the ‘bots called, appropriately, Music for Robots, which was released last week.

The idea, Jenkinson says, was to find out if robots can play music that is engaging emotionally, even as they pull off feats of instrumentation human hands never could. “The robot guitar player for example can play much faster than a human ever could, but there is no amplitude control,” Jenkinson says. “In the same way that you do when you write music for a human performer, these attributes have to be borne in mind—and a particular range of musical possibilities corresponds to those attributes. Consequently, in this project familiar instruments are used in ways which till now have been impossible.”