Shadow Lessons: The Unexpected Journey of an Inner City Art Teacher

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For years Mr. In , he was mentioned in a federal criminal complaint as an unindicted co-conspirator who had helped a prominent New York gallery owner falsify documents associated with Cambodian artifacts so that they would be easier to sell on the international art market.

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But this is the first time that he has been formally charged. Geoffrey S. Berman, the United States attorney in Manhattan, said Mr. Davis said. Prosecutors describe Mr. Latchford as having provided invoices that misrepresented identifying details of artifacts, such as age or country of origin, to United States Customs and Border Protection in order to hide the fact that they were looted.

He is also accused of directing others to create false provenance documents for him. In previous interviews, Mr. Many thought it made the most sense to build machines that reasoned according to rules and logic, making their inner workings transparent to anyone who cared to examine some code. Others felt that intelligence would more easily emerge if machines took inspiration from biology, and learned by observing and experiencing.

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This meant turning computer programming on its head. Instead of a programmer writing the commands to solve a problem, the program generates its own algorithm based on example data and a desired output. Then the computerization of many industries and the emergence of large data sets renewed interest. That inspired the development of more powerful machine-learning techniques, especially new versions of one known as the artificial neural network. By the s, neural networks could automatically digitize handwritten characters. It has given computers extraordinary powers, like the ability to recognize spoken words almost as well as a person could, a skill too complex to code into the machine by hand.

Deep learning has transformed computer vision and dramatically improved machine translation.

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It is now being used to guide all sorts of key decisions in medicine, finance, manufacturing—and beyond. The workings of any machine-learning technology are inherently more opaque, even to computer scientists, than a hand-coded system. This is not to say that all future AI techniques will be equally unknowable. But by its nature, deep learning is a particularly dark black box. The neurons in the first layer each receive an input, like the intensity of a pixel in an image, and then perform a calculation before outputting a new signal.

These outputs are fed, in a complex web, to the neurons in the next layer, and so on, until an overall output is produced. Plus, there is a process known as back-propagation that tweaks the calculations of individual neurons in a way that lets the network learn to produce a desired output.

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The many layers in a deep network enable it to recognize things at different levels of abstraction. In a system designed to recognize dogs, for instance, the lower layers recognize simple things like outlines or color; higher layers recognize more complex stuff like fur or eyes; and the topmost layer identifies it all as a dog.


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The same approach can be applied, roughly speaking, to other inputs that lead a machine to teach itself: the sounds that make up words in speech, the letters and words that create sentences in text, or the steering-wheel movements required for driving.

In , researchers at Google modified a deep-learning-based image recognition algorithm so that instead of spotting objects in photos, it would generate or modify them. By effectively running the algorithm in reverse, they could discover the features the program uses to recognize, say, a bird or building. The resulting images , produced by a project known as Deep Dream, showed grotesque, alien-like animals emerging from clouds and plants, and hallucinatory pagodas blooming across forests and mountain ranges. But the images also hinted at how different deep learning is from human perception, in that it might make something out of an artifact that we would know to ignore.

Google researchers noted that when its algorithm generated images of a dumbbell, it also generated a human arm holding it. The machine had concluded that an arm was part of the thing. Further progress has been made using ideas borrowed from neuroscience and cognitive science. A team led by Jeff Clune, an assistant professor at the University of Wyoming, has employed the AI equivalent of optical illusions to test deep neural networks. His tool targets any neuron in the middle of the network and searches for the image that activates it the most.

It is the interplay of calculations inside a deep neural network that is crucial to higher-level pattern recognition and complex decision-making, but those calculations are a quagmire of mathematical functions and variables.


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In the office next to Jaakkola is Regina Barzilay, an MIT professor who is determined to apply machine learning to medicine. For the duration of the residency I explored the richness of drawing, working out its many challenges on over-sized paper. The gestural quality that is most inherent to drawing, as well as its repetitive nature brings me to a most zen-like calmness, an inner stillness, akin to going for a good, long run.

Edmundo Fernandez. My work scales from the personal to the public, from intimate rituals to large-scale adventurous social events.

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I use social dynamics and human behaviour as mediums of play and invention to connect people's bodies to greater ideas, employing drawing as a way to communicate story and action for social reality. Francisca Yanez.

My focus is often on the image field, using the most apposite materials and marks to create a certain sense of time or place, often grounded by an ambiguous character, who might be repeated across multiple images in a series. My work investigates the nature of time, personal memory and loss in relation to place and landscape. The emerging marks are minute and measured, enormous, fluid, aggressive, meditative: a lexicon of individual marks mapping the simultaneous complexities of an inner landscape and the land we inhabit.

Several drawings are layered over the surfaces - paper, walls, floors and windows and recorded using a digital camera resulting in an animation which is a mere residue of the process. Akin to what we do with our landscapes, etching and marking into them, every place a palimpsest of memories and past forces. We are our memories, or the erasures of. Our bodies remember things that our minds forget. My work is a desperate attempt to reconnect, lest I fail to find any meaning, and hope. Sometimes, they describe an interior frame of mind or mood and other times I consciously strive for a larger, more global perspective and commentary.

Either way, my subjects function as personifications of specific and generalised anxieties about the contemporary world. Drawing offers an immediacy and materiality intrinsic to their meaning. Through the sensory experiences of material and environment, I react to physical space and participate with the audience. I explore the relationship between a body and the traces it leaves on a surface, such as paper or a floor.

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The dust of found objects and graphite pencils mark memories of a temporary presence, an expression of identity in a site-specific place. There I am standing in a stream of images, with a strong desire to make events from the inner stage visible — traces of impressions, traces of experiences, fragments of memories, emotions never expressed, quiet questions, reflections. In a fuzzy patch of the wall, or the uncertain contours of bark. I paint constructed landscapes that piece together scenes of conflict, abandonment and disarray.

Split-level scenes from little lifeboats cracked in half, fractured piers, scaffolding, to huddled shapes trying to escape or hide. I am questioning my own pervasive feeling of helplessness. Using boat shapes is an immediate connection to a slow, archaic, and maybe timeless means of transport.

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My painted worlds explore uncertainty and hardship, using water as a way for me to destabilize the ground and suggest a constant state of fluctuation. Mariam Stephan www. Inspiration is triggered by an emotional response, be it an incidental landscape, natures role as a sculptor, or chance discovery. This has resulted in a body of work represented by drawing, printmaking and painting. David McSweeney. During a residency in Italy, I abandoned oil paints and canvas, and began experimenting with fluid water based paints.