Researchers used deep learning to create a new laser-based system that can image around corners in real time. The systems might one day let self-driving cars "look" around parked cars or busy intersections.
Paralyzed people can learn to walk again with the aid of electromechanical exoskeletons. However, it's not easy. It takes a lot of engineering and hard training.
Deep learning is a machine learning technique that teaches computers to learn by example just as we learned as a child. We see this technology in autonomous vehicles.
Machine vision is used in a variety of industrial processes, such as material inspection, object recognition, pattern recognition, electronic component analysis, along with the recognition of signatures, optical characters, and currency.
SCA refers to the Smart Compliant Actuator independently developed by INNFOS. SCA integrates the underlying servo driver, high-precision encoder, high-power brushless motor, and light-weight gear reducer. It is the very foundation of the XR-1 intelligent service robot.
It is only an imagination in which robots are behaving like humans and getting smarter day by day. However, the distance between imagination and reality has reduced considerably.
Silicon Valley and Toronto Labs to Drive Evolution of Advanced AI Technologies Across Multiple Touchpoints
Duncan Geere for Tech Radar: Now researchers from Universit© Paris-Saclay are attempting to bestow the same benefits onto robots. Adriana Tapus and her colleagues are aiming to develop a humanoid robot that's sensitive to tactile stimulation in the same way people are.
Remi El-Ouazzane for Intel: The First Vision Processing Unit with a Dedicated Neural Compute Engine will Give Devices the Ability to See, Understand and Interact with the World Around Them in Real Time
Steve LeVine for AXIOS: Musk, along with Bill Gates and Stephen Hawking, has been one of the leading voices warning of a dystopian, machine-led future if humans are not careful.
Catherine Clifford for CNBC: "There certainly will be job disruption. Because what's going to happen is robots will be able to do everything better than us. ... I mean all of us,"
Adam Conner-Simons, CSAIL via MIT News: CSAIL approach allows robots to learn a wider range of tasks using some basic knowledge and a single demo.
Alma Mundi Ventures is a venture capital firm focused on technology-based companies, which emphasizes business to business models that are raising their series A or B rounds. They invest between $500,000 and $5 million in each company through their first fund.
Steve Arar for All About Circuits: Humans use language to tap into the knowledge of others and learn skills faster. This helps us hone our intuition and go through our daily activities more efficiently. Inspired by this, Google Research, DeepMind (its UK artificial intelligence lab), and Google X have decided to allow their robots share their experiences. Sharing the learning process among multiple robots, the research team has considerably expedited general-purpose skill acquisition of robots. Using an artificial neural network, we can teach a robot to achieve a goal by analyzing the result of its previous experiences. At first, the robot may seem to act randomly simply working based on trial and error. However, it examines the result of each trial and, if satisfactory, focuses on similar experiments during the next trials. Making a connection between each experience and the obtained result, the robot would be able to gradually make better choices. Cont'd...
Deep-Domain Conversational AI describes the AI technology which is required to build voice and chat assistants which can demonstrate deep understanding of any knowledge domain.
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The industry's first comprehensive Robot Integrator Program saves robot integrators significant time and cost investments by allowing them to mark each cell compliant with ANSI/RIA R15.06 with the TUV Rheinland Mark. As opposed to a traditional certification or an on-site field labeling, T√úV Rheinland's Robot Integrator Program certifies the knowledge and skill-set of robot integrators in addition to testing robotic cells and processes against ANSI/RIA R15.06. This reduces the need for frequent onsite or off site testing and allows manufacturers to apply a single T√úV Rheinland label to multiple cells. The Robot Integrator Program individually assesses a robot integrator's understanding of the ANSI/RIA R15.06 standard along with the ability to consistently produce compliant robot cells. Following the requirements and procedures of the new program will enable robot integrators to produce individually compliant robotic cells under one serialized T√úV Rheinland Mark, which meets the national electric code and allows acceptance by Authorities Having Jurisdiction (AHJ) and end users.