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Seeing Double

Someday, chips might be made with X-rays. Until then, double-patterning lithography will be the only game in town

14 min read
Illustration by Emily Cooper
Illustration: Emily Cooper

In 1971, Intel astounded the world with its 4004 microprocessor, whose 2300 transistors could execute 60 000 instructions per second. Today, the 820 million transistors of an Intel Core 2 Extreme chip can process nearly 72 billion instructions per second.

Such an improvement is the inevitable result of several decades of Moore’s Law, which refers to the semiconductor industry’s ability to double, every 18 to 24 months, the number of transistors on an integrated circuit. But the chips haven’t seen a commensurate six-orders-of-magnitude cost increase, and that’s because chip manufacturers have had to make those transistors not only smaller but cheaper. In 1963, a transistor cost US $10. That transistor corresponded to half a storage bit and cost as much as an automobile tire at the time. Today flash memory costs $25 for 8 gigabytes, or 64 x 230 bits—enough storage to encode the text of all the books in a small-town library, or more than a 100-word-per-minute typist could type in his lifetime. And it will be cheaper still by the time you read this article.

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Paying Tribute to 1997 IEEE President Charles K. Alexander

The Life Fellow was a professor at Cleveland State University

4 min read
portrait of man smiling against a light background
The Alexander Family

Charles K. Alexander, 1997 IEEE president, died on 17 October at the age of 79.

The active volunteer held many high-level positions throughout the organization, including 1991–1992 IEEE Region 2 director. He was also the 1993 vice president of the IEEE United States Activities Board (now IEEE-USA).

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Robot Learns Human Trick for Not Falling Over

Humanoid limbs are useful for more than just manipulation

3 min read
A black and white humanoid robot with a malfunctioning leg supports itself with one arm against a wall

This article is part of our exclusive IEEE Journal Watch series in partnership with IEEE Xplore.

Humanoid robots are a lot more capable than they used to be, but for most of them, falling over is still borderline catastrophic. Understandably, the focus has been on getting humanoid robots to succeed at things as opposed to getting robots to tolerate (or recover from) failing at things, but sometimes, failure is inevitable because stuff happens that’s outside your control. Earthquakes, accidentally clumsy grad students, tornadoes, deliberately malicious grad students—the list goes on.

When humans lose their balance, the go-to strategy is a highly effective one: use whatever happens to be nearby to keep from falling over. While for humans this approach is instinctive, it’s a hard problem for robots, involving perception, semantic understanding, motion planning, and careful force control, all executed under aggressive time constraints. In a paper published earlier this year in IEEE Robotics and Automation Letters, researchers at Inria in France show some early work getting a TALOS humanoid robot to use a nearby wall to successfully keep itself from taking a tumble.

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Fourth Generation Digitizers With Easy-to-Use API

Learn about the latest generation high-performance data acquisition boards from Teledyne

1 min read

In this webinar, we explain the design principles and operation of our fourth-generation digitizers with a focus on the application programming interface (API).

Register now for this free webinar!

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