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Move over, silicon switches: There’s a new way to compute

Logic and memory devices, such as the hard drives in computers, now use nanomagnetic mechanisms to store and manipulate information. Unlike silicon transistors, which have fundamental efficiency limitations, they require no energy to maintain their magnetic state: Energy is needed only for reading and writing information.

One method of controlling magnetism uses that transports spin to write information, but this usually involves flowing charge. Because this generates heat and , the costs can be enormous, particularly in the case of large server farms or in applications like artificial intelligence, which require massive amounts of memory. Spin, however, can be transported without a charge with the use of a topological insulator—a material whose interior is insulating but that can support the flow of electrons on its surface.

In a newly published Physical Review Applied paper, researchers from New York University introduce a voltage-controlled topological spin switch (vTOPSS) that requires only electric fields, rather than currents, to switch between two Boolean logic states, greatly reducing the heat generated and energy used. The team is comprised of Shaloo Rakheja, an assistant professor of electrical and at the NYU Tandon School of Engineering, and Andrew D. Kent, an NYU professor of physics and director of the University’s Center for Quantum Phenomena, along Michael E. Flatté, a professor at the University of Iowa.

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A machine has figured out Rubik’s Cube all by itself

Working strategy, by starting at the desired end destination and then looking back, by connecting the dots as they are presented chronologically (in our present) towards the future, a strategic level of thinking now available to machines.


Unlike chess moves, changes to a Rubik’s Cube are hard to evaluate, which is why deep-learning machines haven’t been able to solve the puzzle on their own. Until now.

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Smarter training of neural networks

These days, nearly all the artificial intelligence-based products in our lives rely on “deep neural networks” that automatically learn to process labeled data.

For most organizations and individuals, though, deep learning is tough to break into. To learn well, neural networks normally have to be quite large and need massive datasets. This training process usually requires multiple days of training and expensive graphics processing units (GPUs)—and sometimes even custom-designed hardware.

But what if they don’t actually have to be all that big, after all?

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See Tesla’s Enhanced Summon Pick up a Driver in a Parking Lot

After its release, Tesla owners could instruct their vehicles to autonomously pull in or out of a parking space or garage with the push of a button. They just couldn’t expect the car to make any turns.

In late 2018, Musk began teasing a major update to Summon, which Tesla began rolling out in March — and a newly released video of Enhanced Summon in action shows just how far autonomous tech has come in three years.

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Ducati Is Working on a Futuristic Electric Motorcycle

“The future is electric,” Ducati CEO Claudio Domenicali said during an event in Spain, according to Electrek’s translation, and that the company is “not far from starting series production.”

READ MORE: Ducati CEO confirms ‘The future is electric’, says electric Ducati is coming [Electrek]

More on the bike: BMW’s Self-Driving Motorcycle Could Help Keep Bikers Safe.

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McDonald’s Is Installing AI-Powered Kiosks to Predict Your Order

In the future, your local fast food joint might know your order before you even get to the drive-thru window.

Fast food giant McDonald’s has installed AI-powered kiosks in 700 of its restaurants during an initial trial period. The menus are capable of suggesting menu items that sell best depending on the time of day, the weather, or that are currently trending — think ice cream on hot summer days — as well as add-on items depending on your current order.

It’s a glimpse of a future in which AI does substantial legwork in food service — but also one in which human cashiers could become obsolete.

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Estonia is Building a “Robot Judge” to Help Clear Legal Backlog

The Estonian Ministry of Justice has officially asked Ott Velsberg, the country’s chief data officer, to design a “robot judge” to take care of a backlog of small claims court disputes, Wired reports.

The artificial intelligence-powered “judge” is supposed to analyze legal documents and other relevant information and come to a decision. Though a human judge will have an opportunity to revise those decisions, the project is a striking example of justice by artificial intelligence.

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