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Mocking AI Panic

Turing anticipated many of today’s worries about super-smart machines threatening mankind

3 min read
Illustration: Chad Hagen
Illustration: Chad Hagen

Many people today are concerned by the prospect of out-of-control artificial intelligence. Some call it “killer AI,” “evil AI,” or “malevolent AI.” Billionaires throw money at the “existential risks” posed by ultraintelligent machines: In January, Elon Musk, creator of PayPal and CEO of SpaceX and Tesla Motors, donated US $10 million to the Future of Life Institute, in Cambridge, Mass., which is “focusing on potential risks from the development of human-level artificial intelligence.” Other new research institutes with apocalyptic names explore the dangers of “singularity” scenarios, and Google has recently formed a hush-hush AI ethics board.

Actually, history is repeating itself. In the mid-1940s, public reaction to reports of the new “electronic brains” was fearful. Newspapers announced that “the controlled monster” (a room-size vacuum-tube computer) could rapidly become “the monster in control,” reducing people to “degenerate serfs.” Humans would “perish, victims of their own brain products.”

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Video Friday: Humanoid Soccer

Your weekly selection of awesome robot videos

4 min read
Humans and human-size humanoid robots stand together on an indoor soccer field at the beginning of a game

Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion.

CoRL 2022: 14–18 December 2022, AUCKLAND, NEW ZEALAND
ICRA 2023: 29 May–2 June 2023, LONDON

Enjoy today’s videos!

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Computing With Chemicals Makes Faster, Leaner AI

Battery-inspired artificial synapses are gaining ground

5 min read
Array of devices on a chip

This analog electrochemical memory (ECRAM) array provides a prototype for artificial synapses in AI training.

IBM research

How far away could an artificial brain be? Perhaps a very long way off still, but a working analogue to the essential element of the brain’s networks, the synapse, appears closer at hand now.

That’s because a device that draws inspiration from batteries now appears surprisingly well suited to run artificial neural networks. Called electrochemical RAM (ECRAM), it is giving traditional transistor-based AI an unexpected run for its money—and is quickly moving toward the head of the pack in the race to develop the perfect artificial synapse. Researchers recently reported a string of advances at this week’s IEEE International Electron Device Meeting (IEDM 2022) and elsewhere, including ECRAM devices that use less energy, hold memory longer, and take up less space.

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