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Putting their own twist on robots that amble through complicated landscapes, the Stanford Student Robotics club’s Extreme Mobility team has developed a four-legged robot that is not only capable of performing acrobatic tricks and traversing challenging terrain but is also designed with reproducibility in mind. Anyone who wants their own version of the robot, dubbed Stanford Doggo, can consult comprehensive plans, code and a supply list that the students have made freely available online.

“We had seen these other quadruped robots used in research, but they weren’t something that you could bring into your own lab and use for your own projects,” said Nathan Kau, ‘20, a major and lead for Extreme Mobility. “We wanted Stanford Doggo to be this open source that you could build yourself on a relatively small budget.”

Whereas other similar robots can cost tens or hundreds of thousands of dollars and require customized parts, the Extreme Mobility students estimate the cost of Stanford Doggo at less than $3,000—including manufacturing and shipping costs—and nearly all the components can be bought as-is online. They hope the accessibility of these resources inspires a community of Stanford Doggo makers and researchers who develop innovative and meaningful spinoffs from their work.

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An algorithm developed by Brown University computer scientists enables robots to put pen to paper, writing words using stroke patterns similar to human handwriting. It’s a step, the researchers say, toward robots that are able to communicate more fluently with human co-workers and collaborators.

“Just by looking at a target image of a word or sketch, the robot can reproduce each stroke as one continuous action,” said Atsunobu Kotani, an undergraduate student at Brown who led the algorithm’s development. “That makes it hard for people to distinguish if it was written by the robot or actually written by a human.”

The algorithm makes use of deep learning networks that analyze images of handwritten words or sketches and can deduce the likely series of pen strokes that created them. The robot can then reproduce the words or sketches using the pen strokes it learned. In a paper to be presented at this month’s International Conference on Robotics and Automation, the researchers demonstrate a robot that was able to write “hello” in 10 languages that employ different character sets. The robot was also able to reproduce rough sketches, including one of the Mona Lisa.

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In a terrifying breakthrough similar to the metal morphing villain in Terminator 2, scientists at the University of Sussex and Swansea University have discovered a way to apply electrical charges to liquid metal and coax it into 3D shapes such as letters and even a heart.

This discovery has been called an “extremely promising” new kind of material that can be programmed to alter its shape.

Yutaka Tokuda, the Research Associate, working on this project at the University of Sussex, says: “This is a new class of programmable materials in a liquid state which can dynamically transform from a simple droplet shape to many other complex geometry in a controllable manner.

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There are about half a dozen other technological approaches to quantum computing vying for preeminence these days. The ion trap method differs from the most popular approach—the silicon chip-based “superconducting qubit”—preferred by the likes of IBM, Google, Intel, and other tech giants. Honeywell, the industrial conglomerate, is one of the few companies pursuing the ion trap approach along with IonQ.

“Quantum computers can potentially solve many of the problems we have today,” Chapman told Fortune on a call. He listed off potential areas of impact, such as drug discovery, energy, logistics, materials science, and A.I. techniques. “How would you not want to be part of that?”

“This is a once-in-a-generation type opportunity,” said Andrew Schoen, a principal at New Enterprise Associates, IonQ’s first backer. “We view this as a chance to build the next Intel.”

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Being an entrepreneur means being willing to take some risks. But Richard Browning doesn’t just put money on the line for his company — he risks his own life.

In 2017, Browning founded Gravity Industries. And since then, he’s served as the chief test pilot for the company’s flagship product, an Iron Man-style jet suit.

In a newly released video, Browning dons the latest version of the suit to fly over a lush green landscape — demonstrating how a concept once relegated to sci-fi is now an incredible reality.

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They have successfully test-fired 3D-printed combustion chambers made from multiple materials.

The news: By combining their manufacturing and testing capabilities, small-satellite launcher Virgin Orbit and NASA created a rocket combustion chamber that was 3D-printed from multiple metals. A combustion chamber is the container where all the propellants get mixed up and ignite—so it must be able to cope with extreme heat and force. The test part that used the chamber generated more than 2,000 pounds of thrust in a series of 60-second test fires. You can watch a video of the test firing here.

Why are chambers a challenge? Because it has to withstand so much, it must be designed to a very high standard, meaning the part is expensive and time consuming to make.

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The idea of “liquid silicon” conjures images from a Terminator film. Fittingly, it is a nascent ’80s computing concept brought to life with modern fabrication techniques, with the potential to alter the course of the future for computer hardware.

“Liquid Si,” with its delicate layers of mono-crystalline silicon and stacked transistors, have real-world implications in the post-Moore semiconductor landscape.

Building unified computer hardware that incorporates system memory, I/O logic, and disk storage into the same module represents a long-standing goal for microchip architects, and attainment is closer now than ever. Using a process called monolithic 3D integration, modern fabrication machines can execute chip designs with silicon and semiconductor circuitry layered on the bottom, solid-state memory arrays on top, and a dense metal-to-metal bus sandwiched in between.

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