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<v Speaker 1>Welcome. This is Rebecca Shore for Radio Eye, and today

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<v Speaker 1>I will be reading from a special edition of Smithsonian Magazine,

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<v Speaker 1>America at 250, The Revolutionary Spark. As a reminder, Radio

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<v Speaker 1>Eye is a reading service intended for people who are

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<v Speaker 1>blind or have other disabilities that make it difficult to

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<v Speaker 1>read printed material. Please join me now for the first

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<v Speaker 1>article titled, In the Early Days of Machine Learning, Massive

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<v Speaker 1>computers said George Harrison was a woman. AI has come

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<v Speaker 1>a long way. A Cornell professor designed a room-sized network

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<v Speaker 1>of sensors that represented a single neuron. He claimed it

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<v Speaker 1>would grow wiser as it gained experience, and it has

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<v Speaker 1>never stopped. By Jenny Rothenberg Gritz Electronic brain teaches itself.

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<v Speaker 1>That was how the New York Times defined the Mark

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<v Speaker 1>I perceptron in a headline on July 13, 1958. Developed

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<v Speaker 1>at Cornell University by psychologist Frank Rosenblatt, who turned 30

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<v Speaker 1>two days before the article appeared, the Perceptron was a

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<v Speaker 1>room-sized grid of 400 light-registering sensors designed to perceive and

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<v Speaker 1>sort images. The idea that a computer could see was

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<v Speaker 1>revolutionary enough, but Rosenblatt also told the Times that the

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<v Speaker 1>machine was designed to, quote, grow wiser, as it gains experience,

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<v Speaker 1>end quote. The perceptron was the first step toward the

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<v Speaker 1>kind of artificial intelligence that's ubiquitous today, where machines learn

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<v Speaker 1>from experience in a way that mimics human brains. Like

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<v Speaker 1>so many other advances of the 1950s, its early history

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<v Speaker 1>now reads like a mid-century science fiction novel. When the

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<v Speaker 1>perceptron debuted, people heard, you can build a brain, it

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<v Speaker 1>can do everything that humans can do, says Killian Weinberger,

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<v Speaker 1>a computer science professor at Cornell who teaches classes on

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<v Speaker 1>machine learning. But scientists had a rudimentary understanding of the

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<v Speaker 1>human brain. They weren't able to study healthy, living gray

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<v Speaker 1>matter using technologies like magnetic resonance imaging, MRI. Instead, they

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<v Speaker 1>relied on indirect approaches, such as dissecting corpses or observing

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<v Speaker 1>the effects of brain lesions on patients' behavior. a theory

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<v Speaker 1>began to emerge. New experiences strengthened the connections between brain cells.

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<v Speaker 1>Once these networks formed, the brain weighed new information differently.

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<v Speaker 1>For instance, after a toddler was told over and over

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<v Speaker 1>that a round object was a ball, the child would

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<v Speaker 1>quickly and intuitively recognize other round objects as balls too.

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<v Speaker 1>Rosenblatt designed the perceptron to mimic this process. His machine

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<v Speaker 1>took in outside information, processed it through circuits, and transmitted

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<v Speaker 1>the resulting answer. Researchers trained the machine by using yes-no

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<v Speaker 1>feedback that updated how it weighed incoming information. Black-and-white footage

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<v Speaker 1>from the mid-1960s shows this type of training in action.

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<v Speaker 1>A researcher sits in front of the giant machine, teaching

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<v Speaker 1>it how to distinguish men from women. and uses two

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<v Speaker 1>simple switches labeled man, woman, and wrong, right. When the

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<v Speaker 1>machine identifies George Harrison of the Beatles as a woman

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<v Speaker 1>based on his shaggy hairstyle, the researcher gives the feedback wrong.

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<v Speaker 1>Through trial and error, the machine will learn that men

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<v Speaker 1>can have long hair too. Everything about this example seems

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<v Speaker 1>quaint today, but the real limitation was that the perceptron

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<v Speaker 1>mimicked a single neuron. One neuron was actually very impressive,

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<v Speaker 1>given the hardware they had at the time, Weinberger says.

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<v Speaker 1>It took a whole room full of equipment and a

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<v Speaker 1>lot of work. Still, the public eventually realized that the

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<v Speaker 1>much-touted electronic brain was less powerful than the brain of

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<v Speaker 1>a mouse. Rosenblatt died in a boating accident in 1971

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<v Speaker 1>at the age of 43. When David Tank began his Ph.D.

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<v Speaker 1>program in physics in at Cornell later that decade, the

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<v Speaker 1>Perceptron and its creator were already the stuff of legend.

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<v Speaker 1>Tank remembers going to a pig roast out in the country,

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<v Speaker 1>where the host took him to a barn and showed

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<v Speaker 1>him an experimental Perceptron machine built in Rosenblatt's lab. It

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<v Speaker 1>had all of these tubes and wires, and it was

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<v Speaker 1>just gathering dust. Around the same time, Tank read Rosenblatt's

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<v Speaker 1>1962 book Principles of Neurodynamics. It was basically the first

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<v Speaker 1>textbook on artificial neural networks, and it's an inspirational book

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<v Speaker 1>in many ways, an absolute classic, says Tank, who became

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<v Speaker 1>a leading AI innovator at Bell Labs and co-founded the

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<v Speaker 1>Princeton Neuroscience Institute. What happened between the Beatles haircut lesson

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<v Speaker 1>and the age of modern AI? For years, it seemed

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<v Speaker 1>as though other forms of machine intelligence would win out.

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<v Speaker 1>Rule-based logic, for instance, used individually coded if-then instructions to

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<v Speaker 1>build an elaborate flowchart. The machine could obey those commands

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<v Speaker 1>to find a solution, but it couldn't learn. Neural networks

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<v Speaker 1>briefly entered the chat again in the late 1980s, when

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<v Speaker 1>researchers collaborated with the U.S. Postal Service to develop zip

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<v Speaker 1>code recognition. A team at Bell Labs, led by Yann LeCun,

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<v Speaker 1>successfully trained machines to recognize different types of handwriting. Instead

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<v Speaker 1>of foreseeing and specifying every possible way a person could

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<v Speaker 1>close the loop of an 8 or angle the line

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<v Speaker 1>of a 7, Lacoon and his colleagues trained their system

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<v Speaker 1>on many examples until it got the hang of human handwriting. Still,

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<v Speaker 1>neural networks weren't able to advance much until computers had

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<v Speaker 1>more storage and bandwidth. A crucial development came through the

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<v Speaker 1>computer games industry in the form of graphics processing units,

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<v Speaker 1>or GPUs, specialized circuits that generate images and videos. These

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<v Speaker 1>networks quickly and accurately performed thousands of calculations at once

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<v Speaker 1>in a way that finally brought truly useful machine learning

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<v Speaker 1>within reach. The other game changer was, of course, the Internet.

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<v Speaker 1>Forget about a lone scientist inputting photos of shaggy-haired musicians,

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<v Speaker 1>AI could now draw on sources ranging from ancient Sanskrit

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<v Speaker 1>scriptures to scientific papers to massive libraries of images and

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<v Speaker 1>videos to endless snarky social media threads. The new form

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<v Speaker 1>of AI could learn an unfathomably large amount about art, science, literature,

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<v Speaker 1>and human nature and weight its results accordingly. When Rosenblatt

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<v Speaker 1>introduced his Perceptron in 1958, He wrote in a research

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<v Speaker 1>paper that he wanted, quote, to understand the capability of

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<v Speaker 1>higher organisms for perceptual recognition, generalization, recall, and thinking, end quote.

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<v Speaker 1>His original Mark I machine, now in the Smithsonian's collections,

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<v Speaker 1>is ultimately a testament to the supercomputer inside the human skull,

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<v Speaker 1>with its relentless urge to expand its own powers, maybe

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<v Speaker 1>for worse and maybe for better. and accompanying this article,

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<v Speaker 1>Did You Know? The Past and Future of AI. The

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<v Speaker 1>term artificial intelligence debuted at a Dartmouth conference in 1956,

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<v Speaker 1>shortly before the perceptron appeared. The inner workings of neural

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<v Speaker 1>networks have become so baffling, even to their creators, that

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<v Speaker 1>a new field called explainable AI seeks to uncover the

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<v Speaker 1>processes at work so humans can provide proper oversight. Next,

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<v Speaker 1>a moment of divine inspiration helped Melville Dewey bring obsessive

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<v Speaker 1>order to the infinitely disorganized stacks in the library. The

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<v Speaker 1>Massachusetts student let his mind wander during a Sunday sermon

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<v Speaker 1>and created the decimal-based system that greatly simplified the search

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<v Speaker 1>for any book you were looking for. By Stephen Mim.

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<v Speaker 1>Melville Dewey was a cash-strapped Amherst College student in the

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<v Speaker 1>early 1870s, working at the school library to pay his bills.

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<v Speaker 1>An intense young scholar, Dewey felt at home among the books.

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<v Speaker 1>There was only one problem. They were so disorganized that

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<v Speaker 1>finding a given volume could prove impossible. One spring Sunday

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<v Speaker 1>in 1873, he made a breakthrough. He was sitting in

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<v Speaker 1>the college chapel, listening to a long sermon from the

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<v Speaker 1>college's president. His mind wandered and Thus was born the

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<v Speaker 1>classification system that now bears Dewey's name. His plan sought

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<v Speaker 1>to tame the chaos created by an ever-growing number of books,

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<v Speaker 1>and taught the world how to manage the exponential growth

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<v Speaker 1>of knowledge, that has defined the modern age. Born and

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<v Speaker 1>raised in a devout Baptist family, he internalized his era's

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<v Speaker 1>ethos of religious reform. Though he soon strayed from the church,

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<v Speaker 1>he never abandoned the conviction that the world could be

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<v Speaker 1>made a better, more ordered place. The Amherst Library was

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<v Speaker 1>his guinea pig. Like other libraries around the world, it

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<v Speaker 1>used a makeshift system of classification, lumping books by general

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<v Speaker 1>subject or even by size. As collections grew with astonishing speed,

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<v Speaker 1>after the invention of steam-powered printing presses, reformers sought to

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<v Speaker 1>organize the flow. Dewey found their ideas wanting. After meeting

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<v Speaker 1>the Boston Athenaeum's head librarian, Dewey returned to Amherst and

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<v Speaker 1>lamented in his diary, he puts the books on the

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<v Speaker 1>horse under horse and not under zoology. For months I

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<v Speaker 1>dreamed night and day that there must be somewhere a

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<v Speaker 1>satisfactory solution, he later wrote. Then came that fateful mid-sermon revelation.

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<v Speaker 1>Dewey's system closely mimicked the metric system, with everything built

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<v Speaker 1>around the number 10. There would be 10 major areas

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<v Speaker 1>of knowledge, from basic general works 000 to 099, to

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<v Speaker 1>geography and history 900 to 999. Each could be broken

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<v Speaker 1>down into 10 potential topical subdivisions, with infinite further subdivisions. Here, then,

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<v Speaker 1>was a system that could categorize everything from Aardvark's 599.31

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<v Speaker 1>to Zydeco's 781.62410763. As Dewey wrote in a formal proposal

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<v Speaker 1>published in 1873, the subclasses may be increased in any

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<v Speaker 1>part of the library without limit. Each additional decimal place

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<v Speaker 1>increases the minuteness of classification tenfold. This begat problems. Some

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<v Speaker 1>areas of study grew faster than others, generating ever finer

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<v Speaker 1>distinctions and unwieldy strings of numbers. Others barely changed at all.

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<v Speaker 1>Dewey doesn't seem to have anticipated these flaws. He continued

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<v Speaker 1>to hone his classifications at Amherst and in 1883 became

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<v Speaker 1>chief librarian at Columbia University, where he organized the collection

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<v Speaker 1>under his schemes. Other U.S. libraries copied the system, as

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<v Speaker 1>did many overseas. In 1900, a prominent British librarian concluded

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<v Speaker 1>that the Dewey decimal system was, quote, by far the

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<v Speaker 1>most widely used and influential of all the classification systems.

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<v Speaker 1>Its decimal numbers have attained an international significance, end quote.

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<v Speaker 1>Dewey established the world's first library school at Columbia in 1887.

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<v Speaker 1>and encouraged women to join the profession. But women librarians

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<v Speaker 1>alleged that he'd made unwanted sexual advances. He died in 1931,

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<v Speaker 1>but not before the allegations caught up to him. And

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<v Speaker 1>in 2019, the American Library Association stripped his name from

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<v Speaker 1>its highest award, citing his sexual harassment as well as

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<v Speaker 1>his prejudice against Jewish people, African Americans, or other minorities.

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<v Speaker 1>These revelations, and the coming obsolescence of brick-and-mortar libraries, diminish

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<v Speaker 1>Dewey's stature. Yet his legacy as an apostle of the

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<v Speaker 1>information economy remains. Confronting the prospect of a near-infinite expansion

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<v Speaker 1>of knowledge, his system anticipated a place for everything, and

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<v Speaker 1>put everything in its place. And accompanying this article, fun fact.

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<v Speaker 1>Melville Dewey's doomed quest for a phonetic English. Dewey was

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<v Speaker 1>obsessed with simplifying and increasing efficiency, including in spelling. Dewey

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<v Speaker 1>became a zealous spelling reformer, including a phonetic approach to

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<v Speaker 1>English orthography that did away with unnecessary consonants, non-intuitive diphthongs,

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<v Speaker 1>and other bugbears of the language. To take one example,

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<v Speaker 1>the man born as Melville Dewey began to write his

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<v Speaker 1>name as M-E-L-V-I-L-D-U-I. The Dewey, D-U-I approach to spelling did

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<v Speaker 1>not catch on. Next. After the concept of peaceful disobedience

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<v Speaker 1>was established in America, it traveled around the world before

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<v Speaker 1>taking hold. Force may subdue, but love gains. The Quaker

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<v Speaker 1>practice of conscientious objection evolved through Thoreau, Tolstoy and Gandhi

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<v Speaker 1>before becoming the hallmark of the civil rights movement by

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<v Speaker 1>Jeff McGregor. The 1955-56 bus boycott in Montgomery, Alabama was

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<v Speaker 1>won by the simple act of refusal led in part

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<v Speaker 1>by Martin Luther King Jr., an American pastor convinced that

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<v Speaker 1>love was the only answer to hate. His commitment to

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<v Speaker 1>non-violent protest became the standard for the rest of the

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<v Speaker 1>century and At the same time, he was drawing on

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<v Speaker 1>a tradition that predates the establishment of the Republic. Long

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<v Speaker 1>before the states united, American Quakers in Pennsylvania, what founder

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<v Speaker 1>William Penn called a holy experiment, had espoused conscientious objection, pacifism,

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<v Speaker 1>and a peaceful refusal to do wrong. As Penn wrote

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<v Speaker 1>in 1682, force may subdue, but love gains, and he

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<v Speaker 1>that forgives first wins the laurel. In the century after

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<v Speaker 1>the Revolution, perhaps the most famous American proponent of civil

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<v Speaker 1>resistance was Henry David Thoreau. After spending a single night

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<v Speaker 1>in jail in Concord, Massachusetts, for refusing to pay his

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<v Speaker 1>poll tax, he produced one of America's foundational texts, his

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<v Speaker 1>1849 essay, On the Duty of Civil Disobedience. It is

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<v Speaker 1>not desirable to cultivate a respect for the law so

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<v Speaker 1>much as for the right, Thoreau wrote. He endorsed such

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<v Speaker 1>tactics as the march and protest, which later became the walkout,

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<v Speaker 1>the sit-in, the boycott, the courageous and active willingness to

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<v Speaker 1>suffer punishment, even violence, in order to shame the state,

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<v Speaker 1>change the law, or raise the public's consciousness. But sometimes

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<v Speaker 1>ideas need to travel the world before they take hold.

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<v Speaker 1>In the late 19th century, Russian author Leo Tolstoy drew

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<v Speaker 1>deep inspiration from Thoreau, American Mennonites, and Quakers, and in

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<v Speaker 1>his 1893 book, The Kingdom of God is Within You,

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<v Speaker 1>argued persuasively for the virtues of nonviolent disobedience. Quoting from

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<v Speaker 1>the Sermon on the Mount, Tolstoy took the love and

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<v Speaker 1>conscience propounded in the Gospels as the path to the

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<v Speaker 1>highest good. Not long after, in South Africa, A young

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<v Speaker 1>Mohandas K. Gandhi read Tolstoy and refined his own ideas

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<v Speaker 1>about peace and moral refusal. King read Gandhi reading Tolstoy

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<v Speaker 1>reading Thoreau. And one of King's closest advisors, Bayard Rustin,

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<v Speaker 1>a quiet giant of the American civil rights movement, was

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<v Speaker 1>raised a Quaker. So civil rights protests joined American history's

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<v Speaker 1>long line of marches for abolition, suffrage, temperance, labor. Active

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<v Speaker 1>nonviolence is a protester's brave appeal to our better angels.

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<v Speaker 1>Our First Amendment guarantees us the right to organize and

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<v Speaker 1>to disagree and to refuse, especially contra our own government. Now,

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<v Speaker 1>as then, these are the rules of common conscience, of

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<v Speaker 1>moral conduct, and of love. And with this article, Did

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<v Speaker 1>You Know? Inside the Civilian Public Service Programs. During World

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<v Speaker 1>War II, the United States built a parallel army out

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<v Speaker 1>of conscientious objectors. Many Quakers, Mennonites, and other pacifist groups

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<v Speaker 1>joined the CPS rather than the army, fulfilling a range

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<v Speaker 1>of non-violent patriotic duties. Some spent years as fire watchers

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<v Speaker 1>in the American West. Others had agricultural roles. Some served

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<v Speaker 1>in domestic mental hospitals, yet others took part in sometimes

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<v Speaker 1>controversial experiments. These non-violent Americans of conscience were still often

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<v Speaker 1>required to wear uniforms. Next, five advances that helped turn

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<v Speaker 1>a night out at the movies into the all-enveloping experience

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<v Speaker 1>it has become. The power of film is often in

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<v Speaker 1>its ability to feel larger than life. moviemakers have been

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<v Speaker 1>developing ways to accentuate that aspect for more than a century.

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<v Speaker 1>By John Semley. The Close-Up. American cinema arguably owes The

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<v Speaker 1>Close-Up to controversial filmmaker D. W. Griffith, a director perhaps

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<v Speaker 1>best known today as the racist auteur behind Birth of

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<v Speaker 1>a Nation. In his 1912 short film Friends, Griffith moves

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<v Speaker 1>his camera from standard medium shots of the era to

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<v Speaker 1>tighter crop on his star, Mary Pickford, whose character is

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<v Speaker 1>torn between two suitors. The close shot of Pickford's stony

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<v Speaker 1>expression intimately conveys the character's ambivalence about her final decision.

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<v Speaker 1>The Vitaphone. The Vitaphone debuted in 1926, allowing sound recorded

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<v Speaker 1>on vinyl platters to play simultaneously with the projected image

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<v Speaker 1>in movie theaters. Developed by engineers at Western Electric, the

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<v Speaker 1>Vitaphone was deployed to astonishing effect in that year's Don Juan,

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<v Speaker 1>starring John Barrymore. A reviewer hailed the technology as a, quote,

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<v Speaker 1>marvelous modern synchronizer of sound and action, end quote. It

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<v Speaker 1>would usher in the era of sound motion pictures, or talkies.

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<v Speaker 1>Cinema scope. In the 1950s, home TVs were stealing audiences

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<v Speaker 1>from cinemas. The response, developed in part by Bausch and Lohm,

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<v Speaker 1>was to make movies bigger. Using unique lenses fashioned for

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<v Speaker 1>both film cameras and and theater projectors, filmmakers captured panoramic

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<v Speaker 1>scenes on 35mm film, and the projected image was about

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<v Speaker 1>twice the width of the previous standards. Spectacles like Bridge

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<v Speaker 1>on the River Kwai, 1957, lured audiences back into theaters.

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<v Speaker 1>MTV Editing The first music videos appeared on MTV in 1981.

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<v Speaker 1>These promotional works, marked by flashy graphics and rapid-fire jump

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<v Speaker 1>cuts between short shots, influenced movies. The sense of energy

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<v Speaker 1>increased at the expense of old-fashioned virtues like continuity. Within

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<v Speaker 1>a couple of years, films like Flashdance, 1983, and Top Gun, 1986,

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<v Speaker 1>incorporated these speedy new rhythms, creating a visual language that

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<v Speaker 1>would come to dominate pop culture. And finally, computer-generated imagery.

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<v Speaker 1>By the 1990s, blockbusters like Terminator 2, Judgment Day, 1991,

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<v Speaker 1>and Jurassic Park, 1993, were using computer technology to make

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<v Speaker 1>robots and prehistoric dinosaurs seem lifelike. By the release of

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<v Speaker 1>Toy Story, 1995, whole movies could be produced inside computers.

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<v Speaker 1>Cinematic special effects became slicker and more realistic. It was

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<v Speaker 1>a revolution on par with the introduction of talkies. And

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<v Speaker 1>with this article, did you know the return of VistaVision? VistaVision,

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<v Speaker 1>a high-resolution film format, was developed by Paramount Pictures in

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<v Speaker 1>the 1950s. White Christmas was the first movie shot in

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<v Speaker 1>VistaVision to hit theaters. The film negative is twice as

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<v Speaker 1>large as regular film, giving directors the chance to create richer,

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<v Speaker 1>and more detailed images. It fell out of favor within

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<v Speaker 1>a decade and was only sparingly used for specific special effects.

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<v Speaker 1>In recent years, auteur directors such as Brady Corbett, Paul

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<v Speaker 1>Thomas Anderson, and Yorgos Lanthimos have resuscitated the format for

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<v Speaker 1>their Oscar-nominated films, sparking a resurgence of interest in film

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<v Speaker 1>during the digital age. Next When patent protections couldn't keep

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<v Speaker 1>pace with ingenuity in the colonies, one inventive woman took

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<v Speaker 1>her case to Britain. Sybilla Wrighton Masters devised a novel

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<v Speaker 1>way to work with grains available to her in Philadelphia.

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<v Speaker 1>A long journey led to the first patent issued to

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<v Speaker 1>an American, though it went to her husband. By Lucia J.

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<v Speaker 1>Graves In the late 17th century, colonists in North America

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<v Speaker 1>faced a new problem. How to Process Maize, a new

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<v Speaker 1>world staple, using mills designed for softer European grains. Sibylla

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<v Speaker 1>Wrighton Masters, a Philadelphia mother of four, devised a solution.

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<v Speaker 1>Born circa 1676 and raised in Burlington Township, West Jersey,

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<v Speaker 1>Sibylla married the prosperous merchant Thomas Masters in the early

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<v Speaker 1>1690s and moved to Philadelphia. After observing the way indigenous

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<v Speaker 1>communities pounded maize with wooden pestles, she conceived a machine

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<v Speaker 1>that produced coarse kernels used for making hominy meal, a

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<v Speaker 1>staple at the time, and similar to what we now

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<v Speaker 1>call grits. While some colonies granted exclusive privileges for inventions,

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<v Speaker 1>Pennsylvania was still young and did not yet issue patents,

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<v Speaker 1>so masters set sail for Britain in 1712 to seek

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<v Speaker 1>legal protection for her designs. I have been at great

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<v Speaker 1>trouble and expense and have ventured my life across the seas,

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<v Speaker 1>she wrote in her 1713 patent application. I have left

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<v Speaker 1>my country, my family, and all your comforts of life

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<v Speaker 1>for the good of the public. Married women could not

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<v Speaker 1>legally hold patents in their own name, neither in the

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<v Speaker 1>colonies nor in England, so Master's patent was issued to

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<v Speaker 1>her husband in 1715, specifying that the invention had been quote,

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<v Speaker 1>found out by Sibylla, his wife. Historians consider her the

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<v Speaker 1>first American colonist to secure an English patent, despite the

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<v Speaker 1>legal hurdles. While in London, Sibylla opened a shop selling

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<v Speaker 1>hats and bonnets made using a second innovation, a method

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<v Speaker 1>for preparing and weaving fibers from plants such as straw

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<v Speaker 1>and palmetto. In 1716, patent number 403 was issued to

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<v Speaker 1>Thomas for the weaving process. The same year, Masters returned

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<v Speaker 1>to Philadelphia, where her corn processing technology was used at

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<v Speaker 1>a mill established by her husband. Although the product never

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<v Speaker 1>sold well in England, it found some success in the colonies.

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<v Speaker 1>More significant was Masters' progression from observation to innovation and commercialization,

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<v Speaker 1>securing her a place in the canon of American invention.

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<v Speaker 1>And with this article, Did You Know?, a fashion entrepreneur.

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<v Speaker 1>Sybilla Wrighton Masters wasn't just an inventor. She was also

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<v Speaker 1>a fashion entrepreneur. In 1716, she obtained a further patent,

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<v Speaker 1>also under her husband's name, for a method of making

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<v Speaker 1>novel hats from palmetto leaves. From a shop she opened

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<v Speaker 1>in London, she sold the hats to some fanfare before

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<v Speaker 1>she and her husband returned to the States. And finally,

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<v Speaker 1>Because of a mathematician from rural Virginia's work on global positioning,

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<v Speaker 1>you have no excuse for getting lost. Gladys West had

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<v Speaker 1>an insatiable thirst for knowledge. She used computers, radars, and

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<v Speaker 1>satellites to make calculations that led to the GPS technology

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<v Speaker 1>that allows us to pinpoint any spot on the globe,

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<v Speaker 1>by Jenny Rothenberg Gritz. When mathematician Gladys Mae West died

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<v Speaker 1>this year at 95, she was celebrated for her work

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<v Speaker 1>on global positioning and Satellite Mapping. We didn't know exactly

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<v Speaker 1>where it was going because we worked for the military,

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<v Speaker 1>where everything is secret, West once recalled. As a child

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<v Speaker 1>in segregated rural Virginia, West attended what she described as

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<v Speaker 1>the stereotypical little one-room schoolhouse with rusty, decrepit furniture, sometimes

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<v Speaker 1>leaky ceilings, and always hand-me-down books. She won a scholarship

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<v Speaker 1>to Virginia State College, propelling her toward 42 years of

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<v Speaker 1>mapping and for the U.S. Navy. In the 1960s, she

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<v Speaker 1>helped train a computer to do 5 billion calculations to

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<v Speaker 1>measure the movement of Pluto. In the 70s, she began

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<v Speaker 1>using radar and satellite data to calculate the Earth's curvature,

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<v Speaker 1>accounting for ice levels, ocean currents, gravity, and tides. Her

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<v Speaker 1>work helped scientists create the precise model used by GPS

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<v Speaker 1>to pinpoint any location on the planet. After her retirement

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<v Speaker 1>in 1998, West went on to earn a Ph.D. in

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<v Speaker 1>public administration. I still had an insatiable thirst for knowledge,

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<v Speaker 1>she wrote in her memoir. I always had this sense

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<v Speaker 1>that there was more to accomplish. This concludes readings from

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<v Speaker 1>the Smithsonian Magazine for today. Your reader has been Rebecca Shore.

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<v Speaker 1>Thank you for listening, and have a great day.