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Russian Police Arrested a Robot. So, Who Gets Punished When an AI Breaks the Law?

#artificialintelligence

Meet Promobot IR77, an artificial intelligence (AI) designed to have face-to-face interactions with humans. It looks cute, but this Russian-made robot had recently been "arrested," after making rounds in a political rally, recording voters' opinions about a candidate's team. It sounds fairly harmless, but Promobot seemed to have made enough trouble to make the local authorities ask policemen to apprehend and detain the robot. "Police asked to remove the robot away from the crowded area, and even tried to handcuff him," the Promobot spokesperson said. This isn't the first time that Promobot got itself in a fair amount of mischief--it's run away from its home laboratory before, twice. The mad run for freedom ended with a battery-drained robot blocking thickening traffic in the street; the programmers were left scratching their heads.


Video Friday: One-Legged Hopper, Mini Humanoid, and Robot Heads

IEEE Spectrum Robotics

Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We'll also be posting a weekly calendar of upcoming robotics events for the next two months; here's what we have so far (send us your events!): Let us know if you have suggestions for next week, and enjoy today's videos. "Current and previous single-legged hopping robots are energetically tethered and lack portability. Here, we present the design and control of an untethered, energetically autonomous single-legged hopping robot. The thrust-producing mechanism of the robot's leg is an actuated prismatic joint, called a linear elastic actuator in parallel (LEAP). The LEAP mechanism comprises a voice coil actuator in parallel with two compression springs, which gives our robot passive compliance. An actuated gimbal hip joint is realized by two standard servomotors. To control the robot, we adapt Raibert's hopping controller, and find we can maintain balance roughly in-place for up to approx. If you have a robot that runs ROS and makes maps, you've likely been using GMapping, which gives you very GMapping-y results. Google has just released its own open source ROS-based real-time 2D/3D SLAM library called Cartographer, and it already has support for PR2, TurtleBot, Revo LDS (aka Neato's lidar), and even TRI's HSR: POW! For more details, read this 2016 ICRA paper. "Toyota Motor Corporation plans to launch sales of its compact and cuddlesome'Kirobo Mini' communication partner through Toyota vehicle dealers across Japan in 2017.


Intelligence is not Artificial: Why the Singularity is not Coming any Time Soon And Other Meditations on the Post-Human Condition and the Future of Intelligence: piero scaruffi: 9780976553199: Amazon.com: Books

@machinelearnbot

Piero Scaruffi is a cognitive scientist who has lectured in three continents and published several books on Artificial Intelligence and Cognitive Science, the latest one being "Thinking about Thought" (2014). He pioneered Internet applications in the early 1980s and the use of the World-Wide Web for cultural purposes in the mid 1990s. His poetry has been awarded several national prizes in Italy and the USA. His latest book of poems and meditations is "Synthesis" (2009). As a music historian, he has published ten books, the latest ones being "A History of Rock and Dance Music" (2009) and "A History of Jazz Music" (2007).


We're getting closer to clothing made entirely by robots

#artificialintelligence

When it comes to stitching together complex garments, dexterous human hands are still far superior to rigid robot arms. Much of the garment production process is already automated, from picking cotton to spinning yarn to cutting clothes. Some specialist machines can even sew buttons or pockets. However, no commercial robot had been able to piece together all the different materials to create an entire item of clothing, like a pair of jeans or a t-shirt. But last month, Jonathan Zornow, founder and sole employee of Seattle-based startup Sewbo, claimed a breakthrough: He says he overcame a common hurdle to clothing automation--the challenge of working with weak, flexible fabrics--and successfully used an industrial robot to sew together a t-shirt.


Dream: Difference between revisions - Wikipedia, the free encyclopedia

#artificialintelligence

A dream is a succession of images, ideas, emotions, and sensations that usually occurs involuntarily in the mind during certain stages of sleep.[1] The content and purpose of dreams are not definitively understood, though they have been a topic of scientific speculation, as well as a subject of philosophical and religious interest, throughout recorded history. The scientific study of dreams is called oneirology.[2] Dreams mainly occur in the rapid-eye movement (REM) stage of sleep--when brain activity is high and resembles that of being awake. REM sleep is revealed by continuous movements of the eyes during sleep. At times, dreams may occur during other stages of sleep. However, these dreams tend to be much less vivid or memorable.[3] The length of a dream can vary; they may last for a few seconds, or approximately 20–30 minutes.[3] People are more likely to remember the dream if they are awakened during the REM phase. The average person has three to five dreams per night, and some may have up to seven;[4] however, most dreams are immediately or quickly forgotten.[5] Dreams tend to last longer as the night progresses. During a full eight-hour night sleep, most dreams occur in the typical two hours of REM.[6] In modern times, dreams have been seen as a connection to the unconscious mind. They range from normal and ordinary to overly surreal and bizarre. Dreams can have varying natures, such as being frightening, exciting, magical, melancholic, adventurous, or sexual. The events in dreams are generally outside the control of the dreamer, with the exception of lucid dreaming, where the dreamer is self-aware.[7]


Dream: Difference between revisions - Wikipedia, the free encyclopedia

#artificialintelligence

A dream is a succession of images, ideas, emotions, and sensations that usually occurs involuntarily in the mind during certain stages of sleep.[1] The content and purpose of dreams are not definitively understood, though they have been a topic of scientific speculation, as well as a subject of philosophical and religious interest, throughout recorded history. The scientific study of dreams is called oneirology.[2] Dreams mainly occur in the rapid-eye movement (REM) stage of sleep--when brain activity is high and resembles that of being awake. REM sleep is revealed by continuous movements of the eyes during sleep. At times, dreams may occur during other stages of sleep. However, these dreams tend to be much less vivid or memorable.[3] The length of a dream can vary; they may last for a few seconds, or approximately 20–30 minutes.[3] People are more likely to remember the dream if they are awakened during the REM phase. The average person has three to five dreams per night, and some may have up to seven;[4] however, most dreams are immediately or quickly forgotten.[5] Dreams tend to last longer as the night progresses. During a full eight-hour night sleep, most dreams occur in the typical two hours of REM.[6] In modern times, dreams have been seen as a connection to the unconscious mind. They range from normal and ordinary to overly surreal and bizarre. Dreams can have varying natures, such as being frightening, exciting, magical, melancholic, adventurous, or sexual. The events in dreams are generally outside the control of the dreamer, with the exception of lucid dreaming, where the dreamer is self-aware.[7]


Dream: Difference between revisions - Wikipedia, the free encyclopedia

#artificialintelligence

A dream is a succession of images, ideas, emotions, and sensations that usually occurs involuntarily in the mind during certain stages of sleep.[1] The content and purpose of dreams are not definitively understood, though they have been a topic of scientific speculation, as well as a subject of philosophical and religious interest, throughout recorded history. The scientific study of dreams is called oneirology.[2] Dreams mainly occur in the rapid-eye movement (REM) stage of sleep--when brain activity is high and resembles that of being awake. REM sleep is revealed by continuous movements of the eyes during sleep. At times, dreams may occur during other stages of sleep. However, these dreams tend to be much less vivid or memorable.[3] The length of a dream can vary; they may last for a few seconds, or approximately 20–30 minutes.[3] People are more likely to remember the dream if they are awakened during the REM phase. The average person has three to five dreams per night, and some may have up to seven;[4] however, most dreams are immediately or quickly forgotten.[5] Dreams tend to last longer as the night progresses. During a full eight-hour night sleep, most dreams occur in the typical two hours of REM.[6] In modern times, dreams have been seen as a connection to the unconscious mind. They range from normal and ordinary to overly surreal and bizarre. Dreams can have varying natures, such as being frightening, exciting, magical, melancholic, adventurous, or sexual. The events in dreams are generally outside the control of the dreamer, with the exception of lucid dreaming, where the dreamer is self-aware.[7]


IBM invests 200 million in Watson IoT AI business

#artificialintelligence

The venerable 105-year-old IBM may be a global company, but while it has operated important labs and offices overseas, its business units have always been headquartered in the U.S. Until December of last year, that is, when it opened the new global headquarters for the IBM Watson Internet of Things (IoT) unit in Munich, Germany. Now, faced with dramatically increasing global demand for Watson IoT solutions and services, Big Blue is doubling down on that investment. On Tuesday, IBM announced a 200 million investment in the Watson IoT headquarters, marking one of the company's largest investments in Europe in its history. The investment is part of the 3 billion IBM has earmarked to bring Watson cognitive computing to IoT. IBM says the move is a response to escalating demand from customers who are looking to transform their operations using a combination of IoT and artificial intelligence technologies.


Africa trying out drones to deliver medicines, blood but hurdles, fears abound

The Japan Times

JOHANNESBURG – At first, the drone took some explaining. Anxious villagers buzzed with rumors of a new blood-sucking thing that would fly above their homes. The truth was more practical: A United Nations project would explore whether a small unmanned aerial vehicle, or UAV, could deliver HIV test samples more efficiently than land transport in rural Malawi. Once understanding dawned and work began, young students and their teachers would spill out of the nearby school, cheering, each time they heard the drone approaching. "It was very exciting," UNICEF official Judith Sherman said. As drones quickly pick up momentum around the world in everything from military strikes to pizza delivery, Africa, the continent with some of the most entrenched humanitarian crises, hopes the technology will bring progress.


Optimal spectral transportation with application to music transcription

arXiv.org Machine Learning

Many spectral unmixing methods rely on the non-negative decomposition of spectral data onto a dictionary of spectral templates. In particular, state-of-the-art music transcription systems decompose the spectrogram of the input signal onto a dictionary of representative note spectra. The typical measures of fit used to quantify the adequacy of the decomposition compare the data and template entries frequency-wise. As such, small displacements of energy from a frequency bin to another as well as variations of timber can disproportionally harm the fit. We address these issues by means of optimal transportation and propose a new measure of fit that treats the frequency distributions of energy holistically as opposed to frequency-wise. Building on the harmonic nature of sound, the new measure is invariant to shifts of energy to harmonically-related frequencies, as well as to small and local displacements of energy. Equipped with this new measure of fit, the dictionary of note templates can be considerably simplified to a set of Dirac vectors located at the target fundamental frequencies (musical pitch values). This in turns gives ground to a very fast and simple decomposition algorithm that achieves state-of-the-art performance on real musical data.