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UC Berkeley shows off accelerated learning that puts robots on their feet in minutes – TechCrunch

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Robots relying on AI to learn a new task generally require a laborious and repetitious training process. University of California, Berkeley researchers are attempting to simplify and shorten that with an innovative learning technique that has the robot filling in the gaps rather than starting from scratch. The team shared several lines of work with TechCrunch to show at TC Sessions: Robotics today and in the video below you can hear about them -- first from UC Berkeley researcher Stephen James. "The technique we're employing is a kind of contrastive learning setup, where it takes in the YouTube video and it kind of patches out a bunch of areas, and the idea is that the robot is then trying to reconstruct that image," James explained. "It has to understand what could be in those patches in order to then generate the idea of what could be behind there; it has to get a really good understand of what's going on in the world." Of course it doesn't learn just from watching YouTube, as common as that is in the human world.


Technology Ethics in Action: Critical and Interdisciplinary Perspectives

arXiv.org Artificial Intelligence

This special issue interrogates the meaning and impacts of "tech ethics": the embedding of ethics into digital technology research, development, use, and governance. In response to concerns about the social harms associated with digital technologies, many individuals and institutions have articulated the need for a greater emphasis on ethics in digital technology. Yet as more groups embrace the concept of ethics, critical discourses have emerged questioning whose ethics are being centered, whether "ethics" is the appropriate frame for improving technology, and what it means to develop "ethical" technology in practice. This interdisciplinary issue takes up these questions, interrogating the relationships among ethics, technology, and society in action. This special issue engages with the normative and contested notions of ethics itself, how ethics has been integrated with technology across domains, and potential paths forward to support more just and egalitarian technology. Rather than starting from philosophical theories, the authors in this issue orient their articles around the real-world discourses and impacts of tech ethics--i.e., tech ethics in action.


Deep learning helps robots grasp and move objects with ease

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In the past year, lockdowns and other COVID-19 safety measures have made online shopping more popular than ever, but the skyrocketing demand is leaving many retailers struggling to fulfill orders while ensuring the safety of their warehouse employees. Researchers at the University of California, Berkeley, have created new artificial intelligence software that gives robots the speed and skill to grasp and smoothly move objects, making it feasible for them to soon assist humans in warehouse environments. The technology is described in a paper published online today (Wednesday, Nov. 18) in the journal Science Robotics. Automating warehouse tasks can be challenging because many actions that come naturally to humans--like deciding where and how to pick up different types of objects and then coordinating the shoulder, arm and wrist movements needed to move each object from one location to another--are actually quite difficult for robots. Robotic motion also tends to be jerky, which can increase the risk of damaging both the products and the robots. "Warehouses are still operated primarily by humans, because it's still very hard for robots to reliably grasp many different objects," said Ken Goldberg, William S. Floyd Jr. Distinguished Chair in Engineering at UC Berkeley and senior author of the study.


Deep learning helps robots grasp and move objects with ease

#artificialintelligence

In the past year, lockdowns and other COVID-19 safety measures have made online shopping more popular than ever, but the skyrocketing demand is leaving many retailers struggling to fulfill orders while ensuring the safety of their warehouse employees. Researchers at the University of California, Berkeley, have created new artificial intelligence software that gives robots the speed and skill to grasp and smoothly move objects, making it feasible for them to soon assist humans in warehouse environments. The technology is described in a paper published online today (Wednesday, Nov. 18) in the journal Science Robotics. Automating warehouse tasks can be challenging because many actions that come naturally to humans -- like deciding where and how to pick up different types of objects and then coordinating the shoulder, arm and wrist movements needed to move each object from one location to another -- are actually quite difficult for robots. Robotic motion also tends to be jerky, which can increase the risk of damaging both the products and the robots.


UC Berkeley's AI-Powered Robot Teaches Itself to Drive Off-Road

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A new robot learning system that can learn about physical attributes of the environment through its own experiences in the real world, without the need for simulations or human supervision. University of California, Berkeley (UC Berkeley) researchers have developed a robot learning system that can learn about physical attributes of the environment through its own experiences in the real world, without the need for simulations or human supervision. BADGR: the Berkeley Autonomous Driving Ground Robot autonomously collects data and automatically labels it. The system uses that data to train an image-based neural network predictive model, and applies that model to plan and execute actions that will lead the robot to accomplish a desired navigational task. UC Berkeley's Gregory Kahn wrote, "The key insight behind BADGR is that by autonomously learning from experience directly in the real world, BADGR can learn about navigational affordances, improve as it gathers more data, and generalize to unseen environments."


Prepare the Economy for Impact of AI & Automation, UC Berkeley Professor Robert Reich

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Professor Reich comes to Google to discuss the impact of automation & artificial intelligence on our economy. He also provides a recommendation on how we can ensure future technologies benefit the entire economy, not just those at the top.It might be universal basic income or robot taxes. Robert Reich is the Chancellor's Professor of Public Policy at the University of California, Berkeley and Senior Fellow at the Blum Center for Developing Economies. He served as Secretary of Labor in the Clinton administration, for which Time Magazine named him one of the ten most effective cabinet secretaries of the twentieth century. He is also a founding editor of the American Prospect magazine, chairman of Common Cause, a member of the American Academy of Arts and Sciences, co-founder of the nonprofit Inequality Media, and co-creator of the award-winning documentary, Inequality for All.


NVIDIA Delivers AI Supercomputer to Berkeley NVIDIA Blog

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NVIDIA CEO Jen-Hsun Huang earlier this year delivered our NVIDIA DGX-1 AI supercomputer in a box to the University of California, Berkeley's Berkeley AI Research Lab (BAIR). BAIR's over two dozen faculty and more than 100 graduate students are at the cutting edge of multi-modal deep learning, human-compatible AI and connecting AI with other scientific disciplines and the humanities. "I'm delighted to deliver one of the first ones to you," Jen-Hsun told a group of researchers at BAIR celebrating the arrival of their DGX-1. The team at BAIR are working on a dazzling array of AI problems across a huge array of fields -- and they're eager to experiment with as many different approaches as possible. To do that, they need speed, explains Pieter Abbeel, an associate professor at UC Berkeley's Department of Electrical Engineering and Computer Science.