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The Newest AI-Enabled Weapon: ‘Deep-Faking’ Photos of the Earth | RealClearDefense.

This robot works wonders in logistics as it can autonomously locate, grasp and place boxes onto pallets via BostonDynamics.

A new self-healing electronic skin could improve water-resistant touchscreens and soft robots. And reduce waste, too.

But in “The Matrix,” the landmark of liquid-action sci-fi released 20 years ago today, the artificial intelligence comes at us in a uniquely teasing, forward-tilting, who’s-that-in-the-mirror way. The movie is about a computer-company office drone, played with pinpoint charisma by Keanu Reeves, who gets tugged out of his existence by a rebel underground that unplugs him from the Matrix.

The term “artificial intelligence” was coined in 1956, but one way or another it has been the subject of just about every great science-fiction movie, from “Metropolis” to “Frankenstein,” from the paranoid fables of the ’50s (about brainy robots and aliens with giant noggins who were like “advanced” versions of ourselves) to “2001: A Space Odyssey,” in which HAL, the computer who talks like a wounded therapy patient, displays the anger and ego of a jilted human being. And by the late ’70s and early ’80s, the Machines Who Could Think were really taking over. “Alien” featured a technologically evolved monster with the metallic jaws, the helmet head, and the relentlessness of a demonic thresher, the most sympathetic character in “Blade Runner” was a replicant, and “The Terminator” gave us a dystopia ruled by the machines, featuring a weaponized badass who was the ultimate programmed destroyer.

I ask not for the children’s safety in mind, but rather the robot’s.

“Artificial intelligence will never get jokes like humans do.”

WASHINGTON (AP) — A robot walks into a bar. It goes CLANG.

Alexa and Siri can tell jokes mined from a humor database, but they just don’t get them.

Continue reading “No AI in humor: R2-D2 walks into a bar, doesn’t get the joke” »

Summary: Machine learning significantly improves the accuracy of predicting premature deaths, from all causes, in a middle-aged population compared with more traditional models. Source: University.

Neuroscience News

The Quantum Flagship was first announced in 2016, and on 29 October, the commission announced the first batch of fund recipients. The 20 international consortia, each of which includes public research institutions as well as industry, will receive a total of €132 million over 3 years for technology-demonstration projects.

One of the most ambitious EU ‘Flagship’ schemes yet has picked 20 projects, aiming to turn weird physics into useful products.

Artificial neural networks are the heart of machine learning algorithms and artificial intelligence. Historically, the simplest implementation of an artificial neuron traces back to the classical Rosenblatt’s “perceptron”, but its long term practical applications may be hindered by the fast scaling up of computational complexity, especially relevant for the training of multilayered perceptron networks. Here we introduce a quantum information-based algorithm implementing the quantum computer version of a binary-valued perceptron, which shows exponential advantage in storage resources over alternative realizations. We experimentally test a few qubits version of this model on an actual small-scale quantum processor, which gives answers consistent with the expected results. We show that this quantum model of a perceptron can be trained in a hybrid quantum-classical scheme employing a modified version of the perceptron update rule and used as an elementary nonlinear classifier of simple patterns, as a first step towards practical quantum neural networks efficiently implemented on near-term quantum processing hardware.