The Language of Food: A Linguist Reads The Menu

The Atlantic has an interesting preview of Dan Jurafsky’s The Language of Food: A Linguist Reads the Menu, coming out in September: 

You needn’t be a linguist to note changes in the language of menus, but Stanford’s Dan Jurafsky has written a book doing just that. In The Language of Food: A Linguist Reads the Menu, Jurafsky describes how he and some colleagues analyzed a database of 6,500 restaurant menus describing 650,000 dishes from across the U.S. Among their findings: fancy restaurants, not surprisingly, use fancier—and longer—words than cheaper restaurants do (think accompaniments and decaffeinated coffee, not sides and decaf). Jurafsky writes that “every increase of one letter in the average length of words describing a dish is associated with an increase of 69 cents in the price of that dish.” Compared with inexpensive restaurants, the expensive ones are “three times less likely to talk about the diner’s choice” (your way, etc.) and “seven times more likely to talk about the chef’s choice.”

Lower-priced restaurants, meanwhile, rely on “linguistic fillers”: subjective words like delicious, flaky, and fluffy. These are the empty calories of menus, less indicative of flavor than of low prices. Cheaper establishments also use terms like ripe and fresh, which Jurafsky calls “status anxiety” words. Thomas Keller’s Per Se, after all, would never use fresh—that much is taken for granted—but Subway would. Per Se does, however, engage in the trendy habit of adding provenance to descriptions of ingredients (Island Creek oysters, Frog Hollow’s peaches). According to Jurafsky, very expensive restaurants “mention the origins of the food more than 15 times as often as inexpensive restaurants.”

Putting this book on my to-read list.

Bill Gates on the Future of College

At the National Association of College and University Business Officers Annual Meeting on July 21, 2014, Bill Gates delivered an address on the “Future of College” in America. A transcription is on Mr. Gates’s blog.

Looking at the individual level of opportunity, do people have equal opportunity? The data we see shows that, unless you’re given the preparation and access to higher education, and unless you have a successful completion of that higher education, your economic opportunity is greatly, greatly reduced. There’s a lot of data recently talking about the premium in salaries for people with four-year college degrees. In 2013, people with four-year college degrees earned 98 percent more per hour, on average, than people without degrees. That differential has gone up a lot. A generation ago, it was only 64 percent.

If you look at the numbers more closely, you will also see that unemployment, partial employment, is primarily in people without four-year degrees. Our economy already is near full employment for people with full year degrees. And, so, the uncertainty, the difficulty, the challenges, faced, if you haven’t been able to get a higher education degree, are very difficult already today. And, with changes coming in the economy, with more automation, more globalization, that divide will become even more stark in the years ahead.

So, if we’re really serious about all lives having equal value, we need to make sure that the higher education system, both access, completion, and excellence, are getting the attention they need.

It is unfortunate that, although the US does quite well in the percentage of kids going into higher education, we’ve actually dropped, quite dramatically, in the percentage who complete higher education. We have, amongst developed countries, the highest dropout rate of kids who start. And, understanding why that happens is very, very important. For many of those kids, that experience is not only financially debilitating, being left with loans that are hard to pay off, but, also, psychologically, very debilitating, that they expected to complete, they tried to complete. And, whether it was math or getting the right courses, or the scheduling, somehow, they weren’t able to do that, which is a huge setback.

Worth the read in entirety.

Why Photography Matters: an Airbnb Case Study

This is a superb read on one of my favorite start-ups, Airbnb, and how the company was able to double its revenues after a critical decision was made: get professional-looking photos of the listings.

At the time, Airbnb was part of Y Combinator. One afternoon, the team was poring over their search results for New York City listings with Paul Graham, trying to figure out what wasn’t working, why they weren’t growing. After spending time on the site using the product, Gebbia had a realization. “We noticed a pattern. There’s some similarity between all these 40 listings. The similarity is that the photos sucked. The photos were not great photos. People were using their camera phones or using their images from classified sites.  It actually wasn’t a surprise that people weren’t booking rooms because you couldn’t even really see what it is that you were paying for.”

Graham tossed out a completely non-scalable and non-technical solution to the problem: travel to New York, rent a camera, spend some time with customers listing properties, and replace the amateur photography with beautiful high-resolution pictures. The three-man team grabbed the next flight to New York and upgraded all the amateur photos to beautiful images. There wasn’t any data to back this decision originally. They just went and did it. A week later, the results were in: improving the pictures doubled the weekly revenue to $400 per week. This was the first financial improvement that the company had seen in over eight months. They knew they were onto something.

This was the turning point for the company. Gebbia shared that the team initially believed that everything they did had to be ‘scalable.’ It was only when they gave themselves permission to experiment with non-scalable changes to the business that they climbed out of what they called the ‘trough of sorrow.’

Here’s the takeaway:

Gebbia’s experience with upgrading photographs proved that code alone can’t solve every problem that customers have. While computers are powerful, there’s only so much that software alone can achieve. Silicon Valley entrepreneurs tend to become comfortable in their roles as keyboard jockeys. However, going out to meet customers in the real world is almost always the best way to wrangle their problems and come up with clever solutions. 

Read the rest here.

 

IBM’s SyNAPSE Chip Moves Closer to Brain-Like Computing

This week, scientists at IBM research unveiled a brain-inspired computer and ecosystem. From their press release on the so-called SyNAPSE chip:

Scientists from IBM unveiled the first neurosynaptic computer chip to achieve an unprecedented scale of one million programmable neurons, 256 million programmable synapses and 46 billion synaptic operations per second per watt. At 5.4 billion transistors, this fully functional and production-scale chip is currently one of the largest CMOS chips ever built, yet, while running at biological real time, it consumes a minuscule 70mW—orders of magnitude less power than a modern microprocessor.

MIT Technology Review has a good summary as well:

IBM’s SyNapse chip processes information using a network of just over one million “neurons,” which communicate with one another using electrical spikes—as actual neurons do. The chip uses the same basic components as today’s commercial chips—silicon transistors. But its transistors are configured to mimic the behavior of both neurons and the connections—synapses—between them.

The SyNapse chip breaks with a design known as the Von Neuman architecture that has underpinned computer chips for decades. Although researchers have been experimenting with chips modeled on brains—known as neuromorphic chips—since the late 1980s, until now all have been many times less complex, and not powerful enough to be practical (see “Thinking in Silicon”). Details of the chip were published today in the journal Science.

The new chip is not yet a product, but it is powerful enough to work on real-world problems. In a demonstration at IBM’s Almaden research center, MIT Technology Review saw one recognize cars, people, and bicycles in video of a road intersection. A nearby laptop that had been programed to do the same task processed the footage 100 times slower than real time, and it consumed 100,000 times as much power as the IBM chip. IBM researchers are now experimenting with connecting multiple SyNapse chips together, and they hope to build a supercomputer using thousands.

I think this kind of experimentation is fascinating. You can read more at Science Magazine (subscription required to view full text).

 

College Football in America: Athletics over Academics

This is an unsettling piece in The New York Times on the biggest college football conferences (the SEC, the ACC, the Pacific-12, the Big Ten, and the Big 12) vying to become more autonomous:

This is a portrait of life in the wealthiest districts of college sports.

The denizens of these rarefied quarters, universities like Alabama and Louisiana State, are still institutions of higher education. But athletics have become ever more central to their missions, and their bottom lines, thanks to the juggernaut programs that generate hundreds of millions of dollars a year.

Recruiters fly on private planes, athletes train on top-of-the-line equipment, and teams compete in mammoth stadiums that are the envy of many professional teams. It is not uncommon for a university’s athletic budget to exceed $60 million.

I went to an ACC school that is known for its academic rigor: Georgia Tech. But even there, I felt the athletics often overshadowed academics. Those that attended the university on an athletic scholarship had their priorities in the following order: 1) sports and/or team the athlete was competing for and 2) academics.

The new rules will likely sway the athletics over academics even further. Sad.

What are B Corporations?

Something I learned today: so-called B corporations from this New Yorker piece by James Surowiecki.

B corporations are for-profit companies that pledge to achieve social goals as well as business ones. Their social and environmental performance must be regularly certified by a nonprofit called B Lab, much the way LEED buildings have to be certified by the U.S. Green Building Council. Many B corps are also committed to a specific social mission.

There are now more than a thousand B corps in the U.S., including Patagonia, Etsy, and Seventh Generation. And in the past four years twenty-seven states have passed laws allowing companies to incorporate themselves as “benefit corporations”—which are similar to B corps but not identical. The commitments that these companies are making aren’t just rhetorical. Whereas a regular business can abandon altruistic policies when times get tough, a benefit corporation can’t. Shareholders can sue its directors for not carrying out the company’s social mission, just as they can sue directors of traditional companies for violating their fiduciary duty.

Examples of B corps in America include Patagonia, Etsy, Seventh Generation, and Warby Parker.

A very nice conclusion to the piece:

The rise of B corps is a reminder that the idea that corporations should be only lean, mean, profit-maximizing machines isn’t dictated by the inherent nature of capitalism, let alone by human nature. As individuals, we try to make our work not just profitable but also meaningful. It may be time for more companies to do the same.

Why Are Americans So Bad at Math?

The New York Times has a noteworthy piece on why math education is so poor in the United States. Borrowing examples from how math is taught in Japan, the article outlines how different initiatives to reform math education in America have failed (and why they are likely to continue to fail). Worth the read.

It wasn’t the first time that Americans had dreamed up a better way to teach math and then failed to implement it. The same pattern played out in the 1960s, when schools gripped by a post-Sputnik inferiority complex unveiled an ambitious “new math,” only to find, a few years later, that nothing actually changed. In fact, efforts to introduce a better way of teaching math stretch back to the 1800s. The story is the same every time: a big, excited push, followed by mass confusion and then a return to conventional practices.

The new math of the ‘60s, the new new math of the ‘80s and today’s Common Core math all stem from the idea that the traditional way of teaching math simply does not work. As a nation, we suffer from an ailment that John Allen Paulos, a Temple University math professor and an author, calls innumeracy — the mathematical equivalent of not being able to read. On national tests, nearly two-thirds of fourth graders and eighth graders are not proficient in math. More than half of fourth graders taking the 2013 National Assessment of Educational Progress could not accurately read the temperature on a neatly drawn thermometer.

I hadn’t heard of this parable/story before, but it is quite the embarrassment:

One of the most vivid arithmetic failings displayed by Americans occurred in the early 1980s, when the A&W restaurant chain released a new hamburger to rival the McDonald’s Quarter Pounder. With a third-pound of beef, the A&W burger had more meat than the Quarter Pounder; in taste tests, customers preferred A&W’s burger. And it was less expensive. A lavish A&W television and radio marketing campaign cited these benefits. Yet instead of leaping at the great value, customers snubbed it.

Only when the company held customer focus groups did it become clear why. The Third Pounder presented the American public with a test in fractions. And we failed. Misunderstanding the value of one-third, customers believed they were being overcharged. Why, they asked the researchers, should they pay the same amount for a third of a pound of meat as they did for a quarter-pound of meat at McDonald’s. The “4” in “¼,” larger than the “3” in “⅓,” led them astray.

Maybe we need to develop more system-wide efforts to showcase teaching styles to observers, like they do in Japan:

In Japan, teachers had always depended on jugyokenkyu, which translates literally as “lesson study,” a set of practices that Japanese teachers use to hone their craft. A teacher first plans lessons, then teaches in front of an audience of students and other teachers along with at least one university observer. Then the observers talk with the teacher about what has just taken place. Each public lesson poses a hypothesis, a new idea about how to help children learn. And each discussion offers a chance to determine whether it worked. Without jugyokenkyu, it was no wonder the American teachers’ work fell short of the model set by their best thinkers.

What else matters? That teachers embrace new teaching styles, and persevere:

Most policies aimed at improving teaching conceive of the job not as a craft that needs to be taught but as a natural-born talent that teachers either decide to muster or don’t possess. Instead of acknowledging that changes like the new math are something teachers must learn over time, we mandate them as “standards” that teachers are expected to simply “adopt.” We shouldn’t be surprised, then, that their students don’t improve.

Here, too, the Japanese experience is telling. The teachers I met in Tokyo had changed not just their ideas about math; they also changed their whole conception of what it means to be a teacher. “The term ‘teaching’ came to mean something totally different to me,” a teacher named Hideto Hirayama told me through a translator. It was more sophisticated, more challenging — and more rewarding. “The moment that a child changes, the moment that he understands something, is amazing, and this transition happens right before your eyes,” he said. “It seems like my heart stops every day.”

Worth reading in entirety here.