Steve Lohr

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The Deep Learning defeat of a human Go champion has coincided with AI research booming in the U.S. like never before, with millions being thrown at freshly minted Ph.D.s in the field and small startups announcing the very immodest goal of “capturing all human knowledge.” Everyone is making a big bet on the sector’s future, and, of course, almost all will go bust. The competition, however, will lead to progress. 

The opening of a NYT article by John Markoff and Steve Lohr:

SAN FRANCISCO — The resounding win by a Google artificial intelligence program over a champion in the complex board game Go this month was a statement — not so much to professional game players as to Google’s competitors.

Many of the tech industry’s biggest companies, like Amazon, Google, IBM and Microsoft, are jockeying to become the go-to company for A.I. In the industry’s lingo, the companies are engaged in a “platform war.”

A platform, in technology, is essentially a piece of software that other companies build on and that consumers cannot do without. Become the platform and huge profits will follow. Microsoft dominated personal computers because its Windows software became the center of the consumer software world. Google has come to dominate the Internet through its ubiquitous search bar.

If true believers in A.I. are correct that this long-promised technology is ready for the mainstream, the company that controls A.I. could steer the tech industry for years to come.

“Whoever wins this race will dominate the next stage of the information age,” said Pedro Domingos, a machine learning specialist and the author of The Master Algorithm, a 2015 book that contends that A.I. and big-data technology will remake the world.•

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Daniel Kahneman has taught us that people who feel observed behave more morally. Further proof: An excerpt from “Surveillance Changes Behavior,” Steve Lohr’s New York Times article about the shift in employee behavior when bars and restaurants watch them via monitoring software:

“Most of the restaurant industry pays its servers low wages and they depend on tips. Employee turnover is high. In that environment, a certain amount of theft has long been regarded as a normal part of the business.

Unethical behavior runs the gamut. There is even a how-to book on the subject, published in 2004, How To Burn Down the House: The Infamous Waiter and Bartender’s Scam Bible by Two Bourbon Street Waiters. A simple example is a bartender’s not charging for a round of drinks, and urging the customers to ‘take care of me’ — with a large tip. Other tactics are more elaborate.

But monitoring software is now available to track all transactions and detect suspicious patterns. In the new study, the tracking software was NCR’s Restaurant Guard product, and NCR provided the data. The software is intentionally set so that a restaurant manager gets only an electronic theft alert in cases that seem to clearly be misconduct. Otherwise, a manager might be mired in time-consuming detective work instead of running the restaurant.

The savings from the theft alerts themselves were modest, $108 a week per restaurant. However, after installing the monitoring software, the revenue per restaurant increased by an average of $2,982 a week, or about 7 percent.

The impact, the researchers say, came not from firing workers engaged in theft, but mostly from their changed behavior. Knowing they were being monitored, the servers not only pulled back on any unethical practices, but also channeled their efforts into, say, prompting customers to have that dessert or a second beer, raising revenue for the restaurant and tips for themselves.”

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From a Steve Lohr New York Times article about computer-written articles proliferating online thanks to new software, like that created by the good people at Narrative Science:

“The company’s software takes data, like that from sports statistics, company financial reports and housing starts and sales, and turns it into articles. For years, programmers have experimented with software that wrote such articles, typically for sports events, but these efforts had a formulaic, fill-in-the-blank style. They read as if a machine wrote them.

But Narrative Science is based on more than a decade of research, led by two of the company’s founders, Kris Hammond and Larry Birnbaum, co-directors of theIntelligent Information Laboratory at Northwestern University, which holds a stake in the company. And the articles produced by Narrative Science are different.

‘I thought it was magic,’ says Roger Lee, a general partner of Battery Ventures, which led a $6 million investment in the company earlier this year. ‘It’s as if a human wrote it.'”

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"High-resolution, low-cost cameras are proliferating." (Image by Leonid Dzhepko.)

An article by Steve Lohr in the New York Times looks at the positives and negatives involved in the coming proliferation of cameras that can recognize objects, gestures, situations and even faces. An excerpt:

“High-resolution, low-cost cameras are proliferating, found in products like smartphones and laptop computers. The cost of storing images is dropping, and new software algorithms for mining, matching and scrutinizing the flood of visual data are progressing swiftly.

A computer-vision system can watch a hospital room and remind doctors and nurses to wash their hands, or warn of restless patients who are in danger of falling out of bed. It can, through a computer-equipped mirror, read a man’s face to detect his heart rate and other vital signs. It can analyze a woman’s expressions as she watches a movie trailer or shops online, and help marketers tailor their offerings accordingly. Computer vision can also be used at shopping malls, schoolyards, subway platforms, office complexes and stadiums.

All of which could be helpful — or alarming.

‘Machines will definitely be able to observe us and understand us better,’ said Hartmut Neven, a computer scientist and vision expert at Google. ‘Where that leads is uncertain.’”

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