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Electronics on Paper

Paper electronics could pave the way to a new generation of cheap, flexible gadgets

12 min read
02PaperElectronicsSteckl
Photo: Adam Zocco/Andrew J. Steckl/University of Cincinnati

You wake up with a heavy head. Was it the half dozen glasses of champagne last night or are you getting sick? In your bathroom is a little strip of paper that can tell you for sure. You place it on your tongue and after a few seconds, you pull it back to see the bad news: There’s a small green dot next to the word “flu.” When you fish your doctor’s business card out of your wallet, you notice it looks different from the last time you looked at it. The phone number for his office was originally black. Now it’s displayed in blinking red letters, a sign that the number was changed recently.

The electronics in this scenario are not far off; in fact the basic technological breakthroughs needed to make them work have all been achieved in the past few years. At the moment the costs are still too high for them to be used in things like business cards or package labels, but remarkable advances in materials science and simpler fabrication methods are setting the stage for a whole new breed of cheap, bendable, disposable, and perhaps even recyclable electronics. And some of the most exciting work in this field is happening with paper.

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Meta’s AI Takes an Unsupervised Step Forward

In the quest for human-level intelligent AI, Meta is betting on self-supervised learning

6 min read
A collection of 8 sets of images. In each, the left most image is partially obscured, yet recognizable as the blurry version (center) and the sharp version on the right.

Meta AI’s masked auto-encoder for computer vision was trained on images that were mostly obscured [left]. Yet its reconstructions [center] were remarkably close to the original images [right].

Meta

Meta’s chief AI scientist, Yann LeCun, doesn’t lose sight of his far-off goal, even when talking about concrete steps in the here and now. “We want to build intelligent machines that learn like animals and humans,” LeCun tells IEEE Spectrum in an interview.

Today’s concrete step is a series of papers from Meta, the company formerly known as Facebook, on a type of self-supervised learning (SSL) for AI systems. SSL stands in contrast to supervised learning, in which an AI system learns from a labeled data set (the labels serve as the teacher who provides the correct answers when the AI system checks its work). LeCun has often spoken about his strong belief that SSL is a necessary prerequisite for AI systems that can build “world models” and can therefore begin to gain humanlike faculties such as reason, common sense, and the ability to transfer skills and knowledge from one context to another. The new papers show how a self-supervised system called a masked auto-encoder (MAE) learned to reconstruct images, video, and even audio from very patchy and incomplete data. While MAEs are not a new idea, Meta has extended the work to new domains.

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Landsat Proved the Power of Remote Sensing

The Earth-imaging satellites have amassed a half-century of data on crops, borders, and war zones

6 min read
A satellite image shows vegetation in red tones and urban and rocky areas in grays and whites.

The first image captured on 25 July 1972 by the first Landsat satellite shows the Dallas-Fort Worth area.

Robert Simmon/USGS/NASA

On 18 September 1969, U.S. President Richard Nixon addressed the General Assembly of the United Nations. It was a difficult time in global politics, and much of his speech focused on the war in Vietnam, disputes in the Middle East, and strategic arms control. Toward the end, though, the speech took a curious and hopeful turn, as Nixon rhapsodized about the unifying potential of international cooperation in space exploration. As an example, he noted the United States was in the process of developing new satellites to survey Earth’s natural resources.

Three years later, on 23 July 1972, NASA launched what would be the first Earth Resources Technology Satellite (ERTS). It gave scientists, land managers, policymakers, and others an unprecedented view of their planet. The program has since launched eight more satellites. Renamed the Landsat program in 1975, it is now celebrating its 50th anniversary of imaging the Earth.

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Improved Dynamic Range for Pulse Detection

Achieving an unprecedented combination of dynamic range and sampling rate for pulse data acquisition

1 min read

Join Teledyne SP Devices for an introduction to our Pulse Detection Range eXtension (PDRX) technology. It achieves a dynamic range equivalent to 16-bit analog-to-digital converters (ADCs) while exceeding the sampling rate supported by commercially available devices. It is ideal for pulse capture in applications such as mass spectrometry. Register now for this free webinar!

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