PPT-THE MIND-BRAIN, BIG DATA, AND AUTONOMOUS LEARNING

Dr Leonid Perlovsky Northeastern University lperlrcncom Tutorial IJCNN 2015 12 July 2015 OUTLINE The fundamental principles of the mindbrain The mind is more powerful than standard algorithms. . Vehicles. Let the . car. do the . driving. !. P&O 2010 Dennis Bevers. Recent . Projects. Audi TTS . High speed . Pikes. . Peak. . hillclimb. Top . Gear. BMW 330i. Self. . driving. . predefined. Lecture 4.3 :. Kinematics and Dynamics. Jürgen . Sturm. Technische. . Universität. . München. Kinematics. Describes . the motion of rigid bodies. Position. Velocity. Acceleration. Jürgen Sturm. The intentional stance, the. interface problem. Tuesday introduction. Fredrik Stjernberg. IKK Philosophy. Linköping University. fredrik.stjernberg@liu.se. Intentionality. Every mental phenomenon is characterized by what the Scholastics of the Middle Ages called the intentional (or mental) inexistence of an object, and what we might call, though not wholly unambiguously, reference to a content, direction toward an object (which is not to be understood here as meaning a thing), or immanent objectivity. . Amato Evan. Scripps Institution of Oceanography, University of California San Diego, USA. Key Questions. What are the spatial, temporal, and microphysical characteristics of dust over California, and what are the primary source regions for these mineral aerosols?. Autonomous/Assisted Driving. Where We Are. Where We’re Going. Who Is Going to Win. Autonomous/Assisted Driving. NHTSA defines vehicle automation as having five levels. : (May 2013).. No-Automation (Level 0):. Development. New Motor Vehicle Board 10. th. Industry Roundtable. March 14, . 2013. 1. Discussion Topics. Key provisions of SB 1298 (. Chapter 570, Statutes of . 2012). High-level. overview of the approach to developing autonomous vehicle regulations. Lecture 3.1:. 3D Geometry. Jürgen . Sturm. Technische. . Universität. . München. Points in 3D. 3D . point. Augmented . vector. Homogeneous coordinates. Jürgen Sturm. Autonomous Navigation for Flying Robots. Machine ethics. AV. Can a machine “decide” anything?. 2. If a small tree branch pokes out onto a highway and there’s no incoming traffic, we’d simply drift a little into the opposite lane and drive around it. But an automated car might come to a full stop, as it dutifully observes traffic laws that prohibit crossing a double-yellow line. This unexpected move would avoid bumping the object in front, but then cause a crash with the human drivers behind it. APTA Emerging Leaders Program. May 2018. APTA Emerging Leaders Program – Team 3. Nick Davidson. Transportation Planning Manager. Stark Area RTA - Canton, OH. Nick Biggar. Hayden District Director. Greater Cleveland RTA. Bernard Soriano . and . Stephanie Dougherty. California Legislation – Senate Bill 1298. As soon as practicable, but no later than Jan. 1, 2015, DMV must adopt regulations setting forth requirements for:. Jed Liu. Joe Corbett-Davies. Andrew . Ferraiuolo. Alexander Ivanov. Mulong. Luo. G. Edward Suh. Andrew C.. Myers. Mark Campbell. 4. th. ACM Workshop on Cyber-Physical Systems Security and Privacy. November 27, 2018. Miguel Acosta. Chief, Autonomous Vehicles Branch. California Department of Motor Vehicles. Safety. 37,133 . people killed in crashes on U.S. roadways (. 2017). 30% of fatalities attributed to alcohol-impaired driving. Lecture 2.3:. 2D Robot Example. Jürgen . Sturm. Technische. . Universität. . München. 2D . Robot. Robot is . located somewhere . in space. Jürgen Sturm. Autonomous Navigation for Flying Robots. The future is ďright for autonomous driving ;ADͿ ǁith the rapid technology advances in artilearning, computer vision, senso