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This past spring, Google began feeding its natural language algorithm thousands of romance novels in an effort to humanize its “conversational tone.” The move did so much to fire the collective comic imagination that the ensuing hilarity muffled any serious commentary on its symbolic importance. The jokes, as they say, practically wrote themselves.
Of course, all old technologies were once new. People were at one point genuinely concerned about things we take for granted as perfectly harmless now. In the later decades of the 19th century it was thought that the telephone would induce deafness and that sulphurous vapours were asphyxiating passengers on the London Underground. These then-new advancements were replacing older still technologies that had themselves occasioned similar anxieties on their introduction.
Text is surprisingly resilient. It's cheap, it's flexible, it's discreet. Human brains process it absurdly well considering there's nothing really built-in for it. Plenty of people can deal with text better than they can spoken language, whether as a matter of preference or necessity. And it's endlessly computable -- you can search it, code it. You can use text to make it do other things.
From Facebook is wrong, text is deathless
In “Scenarios,” a special edition from 1995, the guest editor Douglas Coupland took it upon himself to compile a “reverse time capsule,” which he deemed “not a capsule directed to the future, but rather to the citizens of 1975.” What artifacts, he asked, “might surprise them most about the direction taken by the next 20 years?” Included in the capsule—alongside non-tech items such as a chunk of the Berlin Wall, Prozac, and a Japanese luxury sedan—were a laptop (“more power in your lap than MIT’s biggest mainframe”), an Apple MessagePad (“hand-held devices are replacing secretaries”), and a cellular phone. Scanning my apartment, I can spot progeny of all three. One suspects that, were we to engineer our own reverse time capsule today and ship it back to the citizens of 1995, they might not be all that surprised by the direction we’ve taken. They might think they’d seen this future already—in the pages of Wired.
From On Reading Issues of Wired from 1993 to 1995 - The New Yorker
This autonomous robotic shelf-scanning (AuRoSS) platform scans RFID tags on the books and produces a report. In the morning, the human librarians can check the results and can easily see which books are in the wrong spot and where they belong. There's still a need for human labor, but it's far less time-consuming than manually searching every shelf for misplaced titles.
From Robotic librarians hit the books
This page has two main purposes:
To present a new method, the “Möbius method”, for printing and reading double-sided, loose-leaf documents.
To collect and summarize concise explanations of the pros and cons of different methods for printing and reading loose-leaf documents, including single-sided, standard double-sided, and Möbius double-sided. (If you know of other methods, or have anything to add, please contact me!)
From How to print things | blog :: Brent -> [String]
In the case of language and culture, big data showed up in a big way in 2011, when Google released its Ngrams tool. Announced with fanfare in the journal Science, Google Ngrams allowed users to search for short phrases in Google’s database of scanned books—about 4 percent of all books ever published!—and see how the frequency of those phrases has shifted over time. The paper’s authors heralded the advent of “culturomics,” the study of culture based on reams of data and, since then, Google Ngrams has been, well, largely an endless source of entertainment—but also a goldmine for linguists, psychologists, and sociologists. They’ve scoured its millions of books to show that, for instance, yes, Americans are becoming more individualistic; that we’re “forgetting our past faster with each passing year”; and that moral ideals are disappearing from our cultural consciousness.
From How Big Data Creates False Confidence - Facts So Romantic - Nautilus
Don’t miss these amazing speakers at this important LITA preconference to the ALA Annual 2016 conference in Orlando FL.
Digital Privacy and Security: Keeping You And Your Library Safe and Secure In A Post-Snowden World
Friday June 24, 2016, 1:00 – 4:00 pm
Presenters: Blake Carver, LYRASIS and Jessamyn West, Library Technologist at Open Library
From LITA ALA Annual Precon: Digital Privacy – LITA Blog
Google BigQuery Public Datasets
A public dataset is any dataset that is stored in BigQuery and made available to the general public. This page lists a special group of public datasets that Google BigQuery hosts for you to access and integrate into your applications. Google pays for the storage of these data sets and provides public access to the data via BigQuery. You pay only for the queries that you perform on the data (the first 1 TB per month is free, subject to query pricing details). It includes the GDELT HathiTrust and Internet Archive Book Data. This dataset contains 3.5 million digitized books stretching back two centuries, encompassing the complete English-language public domain collections of the Internet Archive (1.3M volumes) and HathiTrust (2.2 million volumes).
From Google BigQuery Public Datasets — Google Cloud Platform
We tend to think of memory as a purely mental phenomenon, something ethereal that goes on inside our minds. That’s a misperception. Scientists are discovering that our senses and even our emotions play important roles in recollection and remembrance. Memory seems to have emerged in animals as a way to navigate and make sense of the world, and the faculty remains tightly tied to the physical body and its material surroundings. Just taking a walk can help unlock memory’s archives, studies have shown.
From When our culture’s past is lost in the cloud - The Washington Post