{"id":200816,"date":"2017-06-23T06:15:47","date_gmt":"2017-06-23T10:15:47","guid":{"rendered":"http:\/\/www.euvolution.com\/prometheism-transhumanism-posthumanism\/quick-thinking-ai-camera-mimics-the-human-brain-scientific-american\/"},"modified":"2017-06-23T06:15:47","modified_gmt":"2017-06-23T10:15:47","slug":"quick-thinking-ai-camera-mimics-the-human-brain-scientific-american","status":"publish","type":"post","link":"https:\/\/www.euvolution.com\/prometheism-transhumanism-posthumanism\/ai\/quick-thinking-ai-camera-mimics-the-human-brain-scientific-american\/","title":{"rendered":"Quick-Thinking AI Camera Mimics the Human Brain &#8211; Scientific American"},"content":{"rendered":"<p><p>    Researchers in Europe are developing a camera that will    literally have a mind of its own, with brainlike algorithms    that process images and light sensors that mimic the human    retina. Its makers hope it will prove that artificial    intelligencewhich today requires large, sophisticated    computerscan soon be packed into small consumer electronics.    But as much as an AI camera would make a nifty smartphone    feature, the technologys biggest impact may actually be    speeding up the way self-driving cars and autonomous flying    drones sense and react to their surroundings.  <\/p>\n<p>    The conventional digital cameras used in self-driving and    computer-assisted cars and drones as well as in surveillance    devices capture a lot of extraneous information that eats up    precious memory space and battery life. Much of that data is    repetitive because the scene the camera is watching does not    change much from frame to frame. The new AI camera, called an    ultralow-power event-based camera, or    ULPEC, will have pixel sensors that come to life only when    the camera is ready to record a new image or event. That    memory- and power-saving feature will not slow performancethe    camera will also have new electrical components that allow it    to react to changing light or movement in a scene within    microseconds (millionths of a second), compared with    milliseconds (thousandths) in todays digital cameras, says    Ryad Benosman, a professor at the    University Pierre and Marie Curie who leads the Vision and    Natural Computation group at the Paris-based Vision Institute.    It records only when the light striking the pixel sensors    crosses a preset threshold amount, says Benosman, whose team    is developing the learning algorithms for an artificial neural    network that serves as the cameras brain. An artificial neural    network is a group of interconnected computers configured to    work like a system of flesh-and-blood neurons in the human    brain. The interconnections among the computers enable the    network to find patterns in data fed into the system, and to    filter out extraneous information via a process called machine    learning. Such a network does away with not only acquiring but    also processing irrelevant information, thus making the camera    faster and requiring lower power for computation, Benosman    says.  <\/p>\n<p>    The AI camera's photo sensorsits eyeswill consist of tiny    pieces of semiconductors and circuitry on silicon, which turn    changes in light into electrical signals sent to the neural    network. Integrated circuits and a new type of electronic    component called a memory resistor or memristor, acting as the equivalent of    synaptic connections, will process the information in those    signals, says Sren Boyn, a researcher at the    Zurich-based Swiss Federal Institute of Technology who worked    with the CNRS-Thales joint research unit that is now working    with Benosmans team. One of the biggest challenges to that    approach is that memristor technologyfirst theorized in 1971    by University of California, Berkeley, professor emeritus Leon Chua (pdf) and    later mathematically modeled by HewlettPackard Labs    researchers in 2008is still largely in the development stage,    which would explain why for the ULPEC project is not expected    to have a working device until 2020.  <\/p>\n<p>    The AI cameras memristors will consist of a thin layer of a    ferroelectric materialbismuth ferritesandwiched between two    electrodes, says Vincent Garcia, a research scientist at    French scientific research agency CNRS\/Thales, which is    developing the ULPEC memristor. Ferroelectric materials have    positive and negative sidesbut applying voltage reverses those    charges. Thus, the resistance of memristors can be tuned using    voltage, Garcia explains. Similar to our brains learning    ability that is dependent on the stimulation of synapses, which    serve as connections between our neurons, this tunable    resistance helps in making the network learn. The more the    synapse is stimulated, the more the connection is reinforced    and learning improved.  <\/p>\n<p>    The combination of bio-inspired optical sensors and neural    networks will make the camera an especially good fit for    self-driving cars and autonomous drones, says Christoph Posch,    chief technology officer of the Paris-based start-up Chronocam,    which is designing the cameras optical sensors. In    self-driving cars the onboard computer must react to changes    very quickly while navigating through traffic or determining    the movement of pedestrians, Posch explains. The ULPEC can    detect and process these changes rapidly. German automotive    equipment manufacturer Boschalso involved in the projectwill    investigate how the camera might be used as part of its    autonomous and computer-aided driving technology.  <\/p>\n<p>    The researchers plan to place 20,000 memristors on the AI    cameras microchip, says Sylvain Saighi, an associate professor of    electronics at the University of Bordeaux and head of the    $5.57-million ULPEC project.  <\/p>\n<p>    Getting all of the components of a memristor neural network    onto a single microchip would be a big step, says Yoeri van de Burgt, an assistant professor    of microsystems at Eindhoven University of Technology in the    Netherlands, whose research includes building artificial    synapses. Since it is performing the computation locally, it    will be more secure and can be dedicated for specific tasks    like cameras in drones and self-driving cars, adds van de    Burgt, who was not involved in the ULPEC project.  <\/p>\n<p>    Assuming the researchers can pull it off, such a chip would be    useful well beyond smart cameras because it would be able to    perform a variety of complicated computations itself, rather    than off-loading that work to a supercomputer via the cloud. In    this way, Posch says, the camera is an important step toward    determining whether the underlying memristors and other    technology will work, and how they might be integrated into    future consumer devices. The camera, with its innovative    sensors and memristor neural network, could demonstrate that AI    can be built into a device in order to make it both smart and    more energy efficient.  <\/p>\n<p><!-- Auto Generated --><\/p>\n<p>See the article here:<\/p>\n<p><a target=\"_blank\" rel=\"nofollow\" href=\"https:\/\/www.scientificamerican.com\/article\/quick-thinking-ai-camera-mimics-the-human-brain\/\" title=\"Quick-Thinking AI Camera Mimics the Human Brain - Scientific American\">Quick-Thinking AI Camera Mimics the Human Brain - Scientific American<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p> Researchers in Europe are developing a camera that will literally have a mind of its own, with brainlike algorithms that process images and light sensors that mimic the human retina. Its makers hope it will prove that artificial intelligencewhich today requires large, sophisticated computerscan soon be packed into small consumer electronics. But as much as an AI camera would make a nifty smartphone feature, the technologys biggest impact may actually be speeding up the way self-driving cars and autonomous flying drones sense and react to their surroundings.  <a href=\"https:\/\/www.euvolution.com\/prometheism-transhumanism-posthumanism\/ai\/quick-thinking-ai-camera-mimics-the-human-brain-scientific-american\/\">Continue reading <span class=\"meta-nav\">&rarr;<\/span><\/a><\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[187743],"tags":[],"class_list":["post-200816","post","type-post","status-publish","format-standard","hentry","category-ai"],"_links":{"self":[{"href":"https:\/\/www.euvolution.com\/prometheism-transhumanism-posthumanism\/wp-json\/wp\/v2\/posts\/200816"}],"collection":[{"href":"https:\/\/www.euvolution.com\/prometheism-transhumanism-posthumanism\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.euvolution.com\/prometheism-transhumanism-posthumanism\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.euvolution.com\/prometheism-transhumanism-posthumanism\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.euvolution.com\/prometheism-transhumanism-posthumanism\/wp-json\/wp\/v2\/comments?post=200816"}],"version-history":[{"count":0,"href":"https:\/\/www.euvolution.com\/prometheism-transhumanism-posthumanism\/wp-json\/wp\/v2\/posts\/200816\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.euvolution.com\/prometheism-transhumanism-posthumanism\/wp-json\/wp\/v2\/media?parent=200816"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.euvolution.com\/prometheism-transhumanism-posthumanism\/wp-json\/wp\/v2\/categories?post=200816"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.euvolution.com\/prometheism-transhumanism-posthumanism\/wp-json\/wp\/v2\/tags?post=200816"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}