Abstract--Towards the grand challenge of achieving humanlevel manipulation in robots, playing piano is a compelling testbed that requires strategic, precise, and flowing movements. Over the years, several works demonstrated hand-designed controllers on real world piano playing, while other works evaluated robot learning approaches on simulated piano scenarios. In this paper, we develop the first piano playing robotic system that makes use of learning approaches while also being deployed on a real world dexterous robot. Specifically, we make use of Sim2Real to train a policy in simulation using reinforcement learning before deploying the learned policy on a real world dexterous robot. In our experiments, we thoroughly evaluate the interplay between domain randomization and the accuracy of the dynamics model used in simulation. Moreover, we evaluate the robot's performance across multiple songs with varying complexity to study the generalization of our learned policy. Experimental results show that the robot can learn Playing the piano requires humans to master contact-rich to play several simple pieces successfully, after training exclusively hand movements dictated by the timing and tone they intend in simulation. This mastery is not learned quickly but through extensive practice, which requires humans to control their actions based on the haptic and auditory feedback received the natural movements of human hands. This makes it an ideal with each key pressed on the piano. In addition, human hands scenario for exploring Sim2Real transfer, where the objective are an extraordinary research subject due to their unmatched is to train an agent in simulation capable of performing in the dexterity, precision, and adaptability.

Simply put, AI is a computer system (or machine) that can perform tasks or solve problems that ordinarily require human intelligence -- as opposed to simple programming, where humans input the end result into a machine. Now, AI is so prevalent that it's used in many apps. And this one can teach you how to play the piano. Skoove provides interactive piano and keyboard lessons for beginners, intermediate and advanced players alike. And you can even learn without a piano on-site.

At the Artificial Intelligence Conference in New York, Kathryn Hume pointed me to Ellen Ullman's excellent book, Life in Code: A Personal History of Technology. In Part 3 of her book "Life, Artificial," Ullman talks about artificial intelligence, robotics, and the desire to create artificial life. What these views of human sentience have in common, and why they fail to describe us, is a certain disdain for the body: the utter lack of a body in early AI and in later formulations like Kurzweil's (the lonely cortex, scanned and downloaded, a brain-in-a-jar); and the disregard for this body, this mammalian flesh, in robotics and ALife [Artificial Life]. By connecting the poverty of AI with its denial of the body, Ullman follows an important thread in feminist theory: our thinking needs to be connected to bodies, to physical human process, to blood and meat. The male-dominated Western tradition is all about abstraction, for which Plato is the poster child.

It has been more than half a year since Google Inc. first revealed a piano-playing artificial intelligence that can take a few notes and turn them into a song. Now the search giant has decided to share the experience with the world with its AI Duet web app. Yotam Mann is the musician and coder behind the new AI, which he created with help from Google's Magenta and Creative Labs teams. In a video, Mann explained the process behind the AI and how it manages to play along with new music on the fly. "Making music using code isn't a new thing at all, but machine learning gives us a different way to go about it," said Mann. "If I was trying to make AI Duet with more traditional programming, I'd have to write out lots of rules."