Auto industry will spend $25 billion on autonomous tech by 2020

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A new study suggests that annual spending on autonomous-driving technology could hit $25 billion by the end of the decade.

Continue reading Auto industry will spend $25 billion on autonomous tech by 2020

Auto industry will spend $25 billion on autonomous tech by 2020 originally appeared on Autoblog on Thu, 07 Jul 2016 09:59:00 EDT. Please see our terms for use of feeds.

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Handheld Tool Is Like Shazam for Fonts and OMG We Need It

Visual inspiration can strike anywhere, but you might not be in front of your computer when it does. The color of a piece of fruit, the typeface on a book of matches—the best you can do to capture these moments is take a photo and reference it later.

That’s not the worst solution, but Fiona O’Leary has a better idea. For her graduation project at the Royal College of Art, O’Leary developed a handy, handheld tool she calls Spector that captures typefaces and colors in the real world, and then transfers them directly to InDesign.

Full disclosure: Spector is a prototype. A working prototype, but a prototype, nonetheless. You can’t buy it, and while O’Leary is interested in commercializing it, she’s in no rush. There’s no whizbang Spector website or neatly manicured Kickstarter campaign; for now, it’s a smart, charming idea that creates an eminently practical bridge between physical and digital media—which is exactly why it caught our eye.

O’Leary describes Spector as a “physical eyedropper.” We like to think of it as Shazam for colors. Or maybe a Poké Ball for fonts. But we digress. Here’s how it works: Place Spector over a piece of media and depress the button on top. A camera inside photographs the sample, and an algorithm translates the image into information about the shape of the typeface, or the color’s CMYK/RGB values. Spector beams that information to a font or color database, which IDs the sample. If your computer is nearby, a custom plugin ports the font or color information to InDesign, where highlighted text or projects will automatically change to the typeface or color of your real-world sample. No computer? No problem. Spector can store up to 20 font samples, so you can transfer them to your computer later.

Spector was born out of personal frustration. “When you design for print on screen, it never looks like how it’s going to print,” says O’Leary, who has a background in graphic design. It’s hard to get a sense of scale, typesetting can be deceiving, and color values don’t always translate from screen to page. “If you’re going to design for print on screen you should start with print,” she says.

Spector currently recognizes seven typefaces that it accesses through a font database, including Apercu, Bureau Grot, Canela, and Founders Grotesk, and O’Leary is working to integrate it with a larger font database. The tool can also translate type size (up to 48 point), kerning and leading, by analyzing the white space between the lines and letters.

The one major drawback to Spector, if it ever gets made, is its potential for facilitating theft. Typeface piracy is a surprisingly big, and messy, problem, and a device like Spector would probably complicate things further. Just one example: Spector would certainly make it easier to identify typefaces from the real world, but those typefaces could still require a paid license to own or use.

O’Leary recognizes piracy as a potential setback for Spector, though she notes that there’s always been an element of creative poaching in graphic design. (She’s not wrong; the line dividing plagiarism from inspiration is notoriously vague, across all fields of design.) Plus, she adds, in testing, most people have used Spector as an educational tool. Best case scenario, she says, designers would use Spector first and foremost as a tool for discovery. And who can argue with making discovery easier?

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Data Mining Reveals the Six Basic Emotional Arcs of Storytelling

Back in 1995, Kurt Vonnegut gave a lecture in which he described his theory about the shapes of stories. In the process, he plotted several examples on a blackboard. “There is no reason why the simple shapes of stories can’t be fed into computers,” he said. “They are beautiful shapes.” The video is available on YouTube.

Vonnegut was representing in graphical form an idea that writers have explored for centuries—that stories follow emotional arcs, that these arcs can have different shapes, and that some shapes are better suited to storytelling than others.

Vonnegut mapped out several arcs in his lecture. These include the simple arc encapsulating “man falls into hole, man gets out of hole” and the more complex one of “boy meets girl, boy loses girl, boy gets girl.”

Vonnegut is not alone in attempting to categorize stories into types, although he was probably the first to do it in graphical form. Aristotle was at it over 2,000 years before him, and many others have followed in his footsteps.

However, there is little agreement on the number of different emotional arcs that arise in stories or their shape. Estimates vary from three basic patterns to more than 30. But there is little in the way of scientific evidence to favor one number over another.

Today, that changes thanks to the work of Andrew Reagan at the Computational Story Lab at the University of Vermont in Burlington and a few pals. These guys have used sentiment analysis to map the emotional arcs of over 1,700 stories and then used data-mining techniques to reveal the most common arcs. “We find a set of six core trajectories which form the building blocks of complex narratives,” they say.

Their method is straightforward. The idea behind sentiment analysis is that words have a positive or negative emotional impact. So words can be a measure of the emotional valence of the text and how it changes from moment to moment. So measuring the shape of the story arc is simply a question of assessing the emotional polarity of a story at each instant and how it changes.

Reagan and co do this by analyzing the emotional polarity of “word windows” and sliding these windows through the text to build up a picture of how the emotional valence changes. They performed this task on over 1,700 English works of fiction that had each been downloaded from the Project Gutenberg website more than 150 times.

Finally, they used a variety of data-mining techniques to tease apart the different emotional arcs present in these stories.

The results make for interesting reading. Reagan and co say that their techniques all point to the existence of six basic emotional arcs that form the building blocks of more complex stories. They are also able to identify the stories that are the best examples of each arc.

The six basic emotional arcs are these:

A steady, ongoing rise in emotional valence, as in a rags-to-riches story such as Alice’s Adventures Underground by Lewis Carroll. A steady ongoing fall in emotional valence, as in a tragedy such as Romeo and Juliet. A fall then a rise, such as the man-in-a-hole story, discussed by Vonnegut. A rise then a fall, such as the Greek myth of Icarus. Rise-fall-rise, such as Cinderella. Fall-rise-fall, such as Oedipus.

Finally, the team looks at the correlation between the emotional arc and the number of story downloads to see which types of arc are most popular. It turns out the most popular are stories that follow the Icarus and Oedipus arcs and stories that follow more complex arcs that use the basic building blocks in sequence. In particular, the team says the most popular are stories involving two sequential man-in-hole arcs and a Cinderella arc followed by a tragedy.

Of course, many books follow more complex arcs at more fine-grained resolution. Reagan and co’s method does not capture the changes in emotional polarity that occur on the level of paragraphs, for example. But instead, it captures the much broader emotional arcs involved in storytelling. Their story arcs are available here.

That’s interesting work that provides empirical evidence for the existence of basic story arcs for the first time. It also provides an important insight into the nature of storytelling and its appeal to the human psyche.

It also sets the scene for the more ambitious work. Reagan and co look mainly at works of fiction in English. It would be interesting to see how emotional arcs vary according to language or culture, how they have varied over time and also how factual books compare.

Vonnegut famously outlined his theory of story shapes in his master’s thesis in anthropology at the University of Chicago. It was summarily rejected, in Vonnegut’s words, “because it was so simple, and looked like too much fun.” Today he would surely be amused but unsurprised.

Ref: http://ift.tt/28XePxa: The Emotional Arcs of Stories Are Dominated by Six Basic Shapes

 

 

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Data Mining Novels Reveals the Six Basic Emotional Arcs of Storytelling

Back in 1995, Kurt Vonnegut gave a lecture in which he described his theory about the shapes of stories. In the process, he plotted several examples on a blackboard. “There is no reason why the simple shapes of stories can’t be fed into computers,” he said. “They are beautiful shapes.” The video is available on YouTube.

Vonnegut was representing in graphical form an idea that writers have explored for centuries—that stories follow emotional arcs, that these arcs can have different shapes and that some shapes are better suited to storytelling than others.

Vonnegut mapped out several arcs in his lecture. These include the simple arc encapsulating “man falls into hole, man gets out of hole” and the more complex one of “boy meets girl, boy loses girl, boy gets girl.”

Vonnegut is not alone in attempting to categorize stories into types, although he was probably the first to do it in graphical form. Aristotle was at it over 2000 years before him and many others have followed in his footsteps.

However, there is little agreement on the number of different emotional arcs that arise in stories or their shape. Estimates vary from three basic patterns to more than 30. But there is little in the way of scientific evidence to favor one number over another.

Today, that changes thanks to the work of Andrew Reagan at the Computational Story Lab at the University of Vermont in Burlington and a few pals. These guys have used sentiment analysis to map the emotional arcs of over 1,700 stories and then used data-mining techniques to reveal the most common arcs. “We find a set of six core trajectories which form the building blocks of complex narratives,” they say.

Their method is straightforward. The idea behind sentiment analysis is that words have a positive or negative emotional impact. So words can be a measure of the emotional valence of the text and how it changes from moment to moment. So measuring the shape of the story arc is simply a question of assessing the emotional polarity of a story at each instant and how it changes.

Reagan and co do this by analyzing the emotional polarity of “word windows” and sliding these windows through the text to build up a picture of how the emotional valence changes. They performed this task on over 1,700 English works of fiction that had each been downloaded from the Project Gutenberg website more than 150 times.

Finally, they used a variety of data-mining techniques to tease apart the different emotional arcs present in these stories.

The results make for interesting reading. Reagan and co say that their data mining techniques all point to the existence of six basic emotional arcs that form the building blocks of more complex stories. They are also able to identify the stories that are the best examples of each arc.

The six basic emotional arcs are these:

A steady, ongoing rise in emotional valence as in a rags-to-riches story such as Alice’s Adventures Underground by Lewis Carroll. A steady ongoing fall in emotional valence as in a tragedy such as Romeo and Juliet. A fall then a rise, such as the man-in-a-hole story, discussed by Vonnegut. A rise then a fall, such as the Greek myth of Icarus. Rise-fall-rise, such as Cinderella. Fall-rise-fall, such as Oedipus.

Finally, the team looks at the correlation between the emotional arc and the number of story downloads to see which types of arc are most popular. It turns out the most popular are stories that follow the Icarus and Oedipus arcs and stories that follow more complex arcs that use the basic building blocks in sequence. In particular, the team says the most popular are stories involving two sequential man-in-hole arcs and a Cinderella arc followed by a tragedy.

Of course, many books follow more complex arcs at more fine grained resolution. Reagan and co’s method does not capture the changes in emotional polarity that occur on the level of paragraphs, for example. But instead, it captures the much broader emotional arcs involved in storytelling. Their story arcs are available here.

That’s interesting work that provides empirical evidence for the existence of basic story arcs for the first time. It also provides an important insight into the nature of storytelling and its appeal to the human psyche.

It also sets the scene for the more ambitious work. Reagan and co look mainly at works of fiction in English. It would be interesting to see how emotional arcs vary according to language or culture, how they have varied over time and also how factual books compare.

Vonnegut famously outlined his theory of story shapes in his master’s thesis in anthropology at the University of Chicago. It was summarily rejected, in Vonnegut’s words, “because it was so simple, and looked like too much fun." Today he would surely be amused but unsurprised.

Ref: http://ift.tt/28XePxa: The Emotional Arcs of Stories Are Dominated by Six Basic Shapes

 

 

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Samsung Introduces World’s First UFS 1.0 Card Extension Standard – Cards Now Hitting 530 MB/s

Samsung Introduces World’s First Universal Flash Storage (UFS) Removable Memory Card Line-up, Offering up to 256-Gigabyte (GB) Capacity   SEOUL, Korea – July 7, 2016 – Samsung Electronics Co., Ltd., the world leader in advanced memory technology, today unveiled the industry’s first removable memory cards based on the JEDEC Universal Flash Storage (UFS) 1.0 Card Extension Standard*, …more

The post Samsung Introduces World’s First UFS 1.0 Card Extension Standard – Cards Now Hitting 530 MB/s appeared first on Legit Reviews.

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