That's because, to paraphrase Amazon's Jeff Bezos, artificial intelligence (AI) is "not just in the first inning of a long baseball game, but at the stage where the very first batter comes up." Look around, and you will find AI everywhere--in self driving cars, Siri on your phone, online customer support, movie recommendations on Netflix, fraud detection for your credit cards, etc. To be sure, there's more to come. Featuring 30 lectures, MIT's course "introduces students to the basic knowledge representation, problem solving, and learning methods of artificial intelligence." It includes interactive demonstrations designed to "help students gain intuition about how artificial intelligence methods work under a variety of circumstances."
A robot has just set a new record for the fastest-solved Rubik's Cube, according to its makers. The Sub1 Reloaded robot took just 0.637 seconds to analyse the toy and make 21 moves, so that each of the cube's sides showed a single colour. That beats a previous record of 0.887 seconds, which was achieved by an earlier version of the same machine using a different processor. Infineon provided its chip to highlight advancements in self-driving car tech. But one expert has questioned the point of the stunt.
Once you enrolled into this course you'll get an introduction of AI and walkthroughs of concepts such as Machine learning, Robotics, Game Theory, Computer vision and Natural Language Processing. You'll also learn about Machine learning algorithms, Applications of AI in Natural Language Processing, Robotics, Computer vision etc, This course is developed by Meassachusetts Institute of Technology. This course introduces the basic knowledge representation, Problem solving and learning methods of Artificial Intelligence. At the same time you'll learn the AI concepts such as knowledge representation, computer vision, Natural language processing and machine learning.
For robots to successfully perceive and understand their environment, they must be taught to act in a goal-directed way. While mapping environments geometry is a necessary prerequisite for many mobile robot applications, understanding the semantics of the environment will enable novel applications, which require more advanced cognitive abilities. Sven Behnke, Head of Autonomous Intelligent Systems Group at the University of Bonn, is tackling this area of robotics by combining dense geometric modelling and semantic categorization. Through this, 3D semantic maps of the environment are built. Sven's team have demonstrated the utility of semantic environment perception with cognitive robots in multiple challenging application domains, including domestic service, space exploration, search and rescue, and bin picking.
Recent innovations around the autonomous car have shaken up the automotive industry. Manufacturers and their suppliers are all accelerating their work on the cars of the future, both regular human-operated cars as well as driverless or semi-autonomous vehicles. But beyond just issues of autonomy, these cars of the future are undergoing a fundamental shift in human-machine interaction. Consumers today crave more relational and conversational interactions with devices, as evidenced by the popularity of chatbots and virtual assistants like Siri and Alexa – and the automotive industry has taken notice. As such, next-generation cars are emerging as advanced artificial intelligence (AI) systems that will power an entirely new automotive experience in which cars will become conversational interfaces between the driver, passengers, the vehicle itself and its controls -- all connected to the IoT and mobile devices we use.