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Algorithm AI-Cognition

interview by   -   November 11, 2019


In this episode, we hear from Brad Hayes, Assistant Professor of Computer Science at the University of Colorado Boulder, who directs the university’s Collaborative AI and Robotics lab. The lab’s work focuses on developing systems that can learn from and work with humans—from physical robots or machines, to software systems or decision support tools—so that together, the human and system can achieve more than each could achieve on their own.

Our interviewer Audrow caught up with Dr. Hayes to discuss why collaboration may at times be preferable to full autonomy and automation, how human naration can be used to help robots learn from demonstration, and the challenges of developing collaborative systems, including the importance of shared models and safety to allow adoption of such technologies in future.

interview by   -   October 29, 2019


In this episode Lilly Clark interviews Nicholas Roy, Professor of Aeronautics and Astronautics at MIT, about the Quest for Intelligence initiative and his research in robust robotics. Roy discusses how cognitive science pushes artificial intelligence, further pushing the capabilities of engineering tools and services, and speaks about the importance of explainable and ethical AI. He explains the challenges of capturing context and semantics in useful models of a system, and designing unmanned aerial vehicles and robots which interact with humans.

interview by   -   October 7, 2019

In this episode, Lauren Klein speaks with Dr. Rand Voorhies, co-founder and CTO of inVia Robotics. In a world where consumers expect fast home delivery of a variety of goods, inVia’s mission is to help warehouse workers package diverse sets of products quickly using a system of autonomous mobile robots. Voorhies describes how inVia’s robots operate to pick and deliver boxes or totes of products to and from people workers in a warehouse environment eliminating the need for people to walk throughout the warehouse, and how the actions of the robots are optimized.

interview by   -   June 24, 2019


In this episode, Audrow Nash interviews Bilge Mutlu, Associate Professor at the University of Wisconsin–Madison, about design-thinking in human-robot interaction. Professor Mutlu discusses design-thinking at a high-level, how design relates to science, and he speaks about the main areas of his work: the design space, the evaluation space, and how features are used within a context. He also gives advice on how to apply a design-oriented mindset.

interview by   -   October 28, 2018



 

In this episode, Audrow Nash interviews Caitlyn Clabaugh, PhD Candidate at the University of Southern California, about lessons learned about putting robots in people’s homes for human-robot interaction research.  Clabaugh speaks about her work to date, the expectations in human-subjects research, and gives general advice for PhD students.

 

interview by   -   October 16, 2018


In this episode, Audrow Nash interviews Patrick Tresset, a London based artist, on robots that draw people using a pen and paper in a way that is similar to the drawing process for humans. Tresset discusses his background in painting and programming, how his robot artists work, how he creates an experience for the person being drawn by the robots, about art history with robots, and about his future direction with robot artists.

interview by   -   October 1, 2018
Image from adarit.com/


 

In this episode, Audrow Nash interviews Robert Williamson, a Professor at the Australian National University, who speaks about a mathematical approach to ethics. This approach can get us started implementing robots that behave ethically. Williamson goes through his logical derivation of a mathematical formulation of ethics and then talks about the cost of fairness. In making his derivation, he relates bureaucracy to an algorithm. He wraps up by talking about how to work ethically.

interview by   -   May 29, 2018

In this episode, Abate interviews Andrew Stein from Anki. At Anki they developed an engaging robot called Cozmo which packs sophisticated robotic software inside a lifelike, palm sized, robot. Cozmo recognizes people and objects around him and plays games with them. Cozmo is unique in that a large amount of development has been implemented to make his animations and behavior feel natural, in addition to focusing on classical robotic elements such as computer vision and object manipulation.

interview by   -   April 14, 2018
Toyota HSR Trained with DART to Make a Bed.

In this episode, Audrow Nash speaks with Michael Laskey, PhD student at UC Berkeley, about a method for robust imitation learning, called DART. Laskey discusses how DART relates to previous imitation learning methods, how this approach has been used for folding bed sheets, and on the importance of robotics leveraging theory in other disciplines.

interview by   -   March 31, 2018



In this interview, Audrow speaks with Andrea Bajcsy and Dylan P. Losey about a method that allows robots to infer a human’s objective through physical interaction. They discuss their approach, the challenges of learning complex tasks, and their experience collaborating between different universities.

interview by   -   March 19, 2018



In this episode, Audrow Nash speaks with Maja Matarić, a professor at the University of Southern California and the Chief Science Officer of Embodied, about socially assistive robotics. Socially assistive robotics aims to endow robots with the ability to help people through individual non-contact assistance in convalescence, rehabilitation, training, and education. For example, a robot could help a child on the autism spectrum to connect to more neurotypical children and could help to motivate a stroke victim to follow their exercise routine for rehabilitation (see the videos below). In this interview, Matarić discusses the care gap in health care, how her work leverages research in psychology to make robots engaging, and opportunities in socially assistive robotics for entrepreneurship.

As AI surpasses human abilities in Go and poker – two decades after Deep Blue trounced chess grandmaster Garry Kasparov – it is seeping into our lives in ever more profound ways. It affects the way we search the web, receive medical advice and whether we receive finance from our banks.

We are only in the earliest stages of so-called algorithmic regulation – intelligent machines deploying big data, machine learning and artificial intelligence (AI) to regulate human behaviour and enforce laws – but it already has profound implications for the relationship between private citizens and the state.

by   -   July 20, 2017

Given a still image of a dish filled with food, CSAIL team’s deep-learning algorithm recommends ingredients and recipes.

By Christoph Salge, Marie Curie Global Fellow, University of Hertfordshire

How do you stop a robot from hurting people? Many existing robots, such as those assembling cars in factories, shut down immediately when a human comes near. But this quick fix wouldn’t work for something like a self-driving car that might have to move to avoid a collision, or a care robot that might need to catch an old person if they fall. With robots set to become our servants, companions and co-workers, we need to deal with the increasingly complex situations this will create and the ethical and safety questions this will raise.



Using Natural Language in Human-Robot Collaboration
November 11, 2019


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