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To set some benchmarks for their simulator, the researchers tried out three different design algorithms working in conjunction with a deep reinforcement learning algorithm that learned to control the robots through many rounds of trial and error.

The co-designed bots performed well on the simpler tasks, like walking or carrying things, but struggled with tougher challenges, like catching and lifting, suggesting there’s plenty of scope for advances in co-design algorithms. Nonetheless, the AI-designed bots outperformed ones design by humans on almost every task.

Intriguingly, many of the co-design bots took on similar shapes to real animals. One evolved to resemble a galloping horse, while another, set the task of climbing up a chimney, evolved arms and legs and clambered up somewhat like a monkey.

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Researchers at Human Brain Project partner University of Granada in Spain have designed a new artificial neural network that mimics the structure of the cerebellum, one of the evolutionarily older parts of the brain, which plays an important role in motor coordination. When linked to a robotic arm, their system learned to perform precise movements and interact with humans in different circumstances, surpassing performance of previous AI-based robotic steering systems. The results have been published in the journal Science Robotics.

Johns Hopkins gets the grant to use artificial intelligence to promote healthy aging. The National Institute of Aging has allocated over $20M to Hopkins for them to execute their plans to promote healthy aging.

This new development will considerably help in providing a better lifestyle and living experience to senior citizens. Johns Hopkins will use the allocated funds over five years to build an AI and technology collaboratory (AITC).

The new collaboratory will have members from the Johns Hopkins University schools of medicine and nursing, the Whiting School of Engineering, and the Carey Business School. The collaboratory will also have members from various industries, senior citizens of the country, and technology developers.

Americans have become accustomed to images of Hellfire missiles raining down from Predator and Reaper drones to hit terrorist targets in Pakistan or Yemen. But that was yesterday’s drone war.

A revolution in unmanned aerial vehicles is unfolding, and the U.S. has lost its monopoly on the technology.

Some experts believe the spread of the semi-autonomous weapons will change ground warfare as profoundly as the machine gun did.

In recent years, computational tools based on reinforcement learning have achieved remarkable results in numerous tasks, including image classification and robotic object manipulation. Meanwhile, computer scientists have also been training reinforcement learning models to play specific human games and videogames.

To challenge research teams working on reinforcement learning techniques, the Neural Information Processing Systems (NeurIPS) annual conference introduced the MineRL competition, a contest in which different algorithms are tested on the same in Minecraft, the renowned computer game developed by Mojang Studios. More specifically, contestants are asked to create algorithms that will need to obtain a diamond from raw pixels in the Minecraft game.

The algorithms can only be trained for four days and on 8,000,000 samples created by the MineRL simulator, using a single GPU machine. In addition to the training dataset, participants are also provided with a large collection of human demonstrations (i.e., video frames in which the task is solved by human players).

Harvard University on Tuesday launched the Kempner Institute for the Study of Natural and Artificial Intelligence, a new University-wide initiative standing at the intersection of neuroscience and artificial intelligence, seeking fundamental principles that underlie both human and machine intelligence. The fruits of discoveries will flow in both directions, enhancing understanding of how humans think, perceive the world around them, make decisions, and learn, thereby advancing the rapidly evolving field of AI.

The institute will be funded by a $500 million gift from Priscilla Chan and Mark Zuckerberg, which was announced Tuesday by the Chan Zuckerberg Initiative. The gift will support 10 new faculty appointments, significant new computing infrastructure, and resources to allow students to flow between labs in pursuit of ideas and knowledge. The institute’s name honors Zuckerberg’s mother, Karen Kempner Zuckerberg, and her parents — Zuckerberg’s grandparents — Sidney and Gertrude Kempner. Chan and Zuckerberg have given generously to Harvard in the past, supporting students, faculty, and researchers in a range of areas, including around public service, literacy, and cures.

“The Kempner Institute at Harvard represents a remarkable opportunity to bring together approaches and expertise in biological and cognitive science with machine learning, statistics, and computer science to make real progress in understanding how the human brain works to improve how we address disease, create new therapies, and advance our understanding of the human body and the world more broadly,” said President Larry Bacow.

Working with two teams of mathematicians, DeepMind engineered an algorithm that can look across different mathematical fields and spot connections that previously escaped the human mind. The AI doesn’t do all the work—when fed sufficient data, it finds patterns. These patterns are then passed on to human mathematicians to guide their intuition and creativity towards new laws of nature.

“I was not expecting to have some of my preconceptions turned on their head,” said Dr. Marc Lackenby at the University of Oxford, one of the scientists collaborating with DeepMind, to Nature, where the study was published.

The AI comes just a few months after DeepMind’s previous triumph in solving a 50-year-old challenge in biology. This is different. For the first time, machine learning is aiming at the core of mathematics—a science for spotting patterns that eventually leads to formally-proven ideas, or theorems, about how our world works. It also emphasized collaboration between machine and man in bridging observations to working theorems.

Things get awkward when Will meets Sophia the Robot for an intimate conversation in the Cayman Islands. SUBSCRIBE: https://goo.gl/BUjQW8

Thanks to Hanson Robotics for providing Sophia! For more information, visit http://hansonrobotics.com.

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