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Can You Code Empathy? with Pascale Fung

#artificialintelligence

ANJA KASPERSEN: Today I am very pleased to be joined by Pascale Fung. Pascale is a;rofessor in the Department of Electronic and Computer Engineering and Department of Computer Science and Engineering at The Hong Kong University of Science and Technology. She is known globally for her pioneering work on conversational artificial intelligence (AI), computational linguistics, and was one of the earliest proponents of statistical and machine-learning approaches for natural language processing (NLP). She is now leading groundbreaking research on how to build intelligent systems that can understand and empathize with humans. I have really been looking forward to this conversation with you. Your professional accolades are many, most of which we will touch on during our conversation. However, for our listeners to get to know you a bit better, I would like us to go back to your upbringing during what I understand to be a very tenuous political period in China. I was born, spent my childhood, ...


The Morning After: Marvel's Netflix shows will reappear on Disney , but only in Canada

Engadget

Marvel's first run of TV shows set in its cinematic universe, including Daredevil and Jessica Jones, have found a new home beyond Netflix – if you live north of the border. The shows, set to disappear from Netflix on March 1st, will appear on Disney Plus in Canada, starting March 16th. However – without spoiling any surprises – some characters have managed to make notable reappearances in recent Marvel movies and shows. Hopefully, Disney can figure out exactly where to take these shows, and hey, give The Defenders the do-over it deserves. I won't be taking any questions on this matter.


State of AI Ethics Report (Volume 6, February 2022)

arXiv.org Artificial Intelligence

This report from the Montreal AI Ethics Institute (MAIEI) covers the most salient progress in research and reporting over the second half of 2021 in the field of AI ethics. Particular emphasis is placed on an "Analysis of the AI Ecosystem", "Privacy", "Bias", "Social Media and Problematic Information", "AI Design and Governance", "Laws and Regulations", "Trends", and other areas covered in the "Outside the Boxes" section. The two AI spotlights feature application pieces on "Constructing and Deconstructing Gender with AI-Generated Art" as well as "Will an Artificial Intellichef be Cooking Your Next Meal at a Michelin Star Restaurant?". Given MAIEI's mission to democratize AI, submissions from external collaborators have featured, such as pieces on the "Challenges of AI Development in Vietnam: Funding, Talent and Ethics" and using "Representation and Imagination for Preventing AI Harms". The report is a comprehensive overview of what the key issues in the field of AI ethics were in 2021, what trends are emergent, what gaps exist, and a peek into what to expect from the field of AI ethics in 2022. It is a resource for researchers and practitioners alike in the field to set their research and development agendas to make contributions to the field of AI ethics.


The Wondrous, Gloriously Absurd Spectacle of "Moonfall"

The New Yorker

"Moonfall," Roland Emmerich's latest exercise in fantasy destruction, is the second major movie to come out recently in which a huge space body is hurtling toward Earth and risks destroying all human life. In the other, "Don't Look Up," the menace is a comet, but the real story is the corruption of American politics and culture that prevents a rational response and leads to catastrophe. Whether the comet represents climate change (as the makers of "Don't Look Up" assert) or the COVID-19 pandemic (as fits the movie best), the celestial body is nonetheless only a MacGuffin, a pretext to expose the human follies that are the movie's subject. But, in "Moonfall," Emmerich is interested--really, really interested--in the moon. His obvious enthusiasm for the gloriously absurd science-fiction reconception of the moon drives the directorial pleasure principle, and it's infectious.


Challenges of Artificial Intelligence -- From Machine Learning and Computer Vision to Emotional Intelligence

arXiv.org Artificial Intelligence

Artificial intelligence (AI) has become a part of everyday conversation and our lives. It is considered as the new electricity that is revolutionizing the world. AI is heavily invested in both industry and academy. However, there is also a lot of hype in the current AI debate. AI based on so-called deep learning has achieved impressive results in many problems, but its limits are already visible. AI has been under research since the 1940s, and the industry has seen many ups and downs due to over-expectations and related disappointments that have followed. The purpose of this book is to give a realistic picture of AI, its history, its potential and limitations. We believe that AI is a helper, not a ruler of humans. We begin by describing what AI is and how it has evolved over the decades. After fundamentals, we explain the importance of massive data for the current mainstream of artificial intelligence. The most common representations for AI, methods, and machine learning are covered. In addition, the main application areas are introduced. Computer vision has been central to the development of AI. The book provides a general introduction to computer vision, and includes an exposure to the results and applications of our own research. Emotions are central to human intelligence, but little use has been made in AI. We present the basics of emotional intelligence and our own research on the topic. We discuss super-intelligence that transcends human understanding, explaining why such achievement seems impossible on the basis of present knowledge,and how AI could be improved. Finally, a summary is made of the current state of AI and what to do in the future. In the appendix, we look at the development of AI education, especially from the perspective of contents at our own university.


Deep Reinforcement Learning

arXiv.org Artificial Intelligence

Deep reinforcement learning has gathered much attention recently. Impressive results were achieved in activities as diverse as autonomous driving, game playing, molecular recombination, and robotics. In all these fields, computer programs have taught themselves to solve difficult problems. They have learned to fly model helicopters and perform aerobatic manoeuvers such as loops and rolls. In some applications they have even become better than the best humans, such as in Atari, Go, poker and StarCraft. The way in which deep reinforcement learning explores complex environments reminds us of how children learn, by playfully trying out things, getting feedback, and trying again. The computer seems to truly possess aspects of human learning; this goes to the heart of the dream of artificial intelligence. The successes in research have not gone unnoticed by educators, and universities have started to offer courses on the subject. The aim of this book is to provide a comprehensive overview of the field of deep reinforcement learning. The book is written for graduate students of artificial intelligence, and for researchers and practitioners who wish to better understand deep reinforcement learning methods and their challenges. We assume an undergraduate-level of understanding of computer science and artificial intelligence; the programming language of this book is Python. We describe the foundations, the algorithms and the applications of deep reinforcement learning. We cover the established model-free and model-based methods that form the basis of the field. Developments go quickly, and we also cover advanced topics: deep multi-agent reinforcement learning, deep hierarchical reinforcement learning, and deep meta learning.


If You Think "Don't Look Up" Is Just an Allegory About Climate Change, You're Missing Something

Mother Jones

This story was originally published by Slate and is reproduced here as part of the Climate Desk collaboration. It also contains spoilers for the film Don't Look Up. Streaming just in time for Christmas, Adam McKay's decidedly uncheery Netflix comedy, Don't Look Up, finds Jennifer Lawrence and Leonardo DiCaprio playing a pair of intrepid astronomers as they try (and mostly fail) to warn the world about a planet-killing comet that's hurtling toward Earth. From the beginning, the scientists' efforts are marked by futility, encapsulated in an early scene in which Kate Dibiasky (Lawrence) and Randall Mindy (DiCaprio) are brought to the White House to debrief President Janie Orlean (Meryl Streep) on the impending extinction-level event. Predictably, the meeting goes disastrously.


Most Shocking Deepfake Videos Of 2021

#artificialintelligence

Only, it was a deepfake. So was the video of Donald Trump taunting Belgium for remaining in the Paris climate agreement and Barack Obama's public service announcement as posted by Buzzfeed. These great examples of deepfakes are the 21st Century's answer to Photoshopped images and videos. Synthetic media, deepfakes, use artificial intelligence (AI) -- deep learning technology, to replace an existing person in an image or video with someone else. One reason for the widespread use of deepfake technology in popular celebrities is that these personalities have a large number of pictures available on the internet, allowing AI to train and learn from.


em Don't Look Up /em Is About Much More Than Climate Change

Slate

This article contains spoilers for the film Don't Look Up. Streaming just in time for Christmas, Adam McKay's decidedly uncheery Netflix comedy, Don't Look Up, finds Jennifer Lawrence and Leonardo DiCaprio playing a pair of intrepid astronomers as they try (and mostly fail) to warn the world about a planet-killing comet that's hurtling toward Earth. From the beginning, the scientists' efforts are marked by futility, encapsulated in an early scene in which Kate Dibiasky (Lawrence) and Randall Mindy (DiCaprio) are brought to the White House to debrief President Janie Orlean (Meryl Streep) on the impending extinction-level event. Predictably, the meeting goes disastrously. The president's son and chief of staff (played by Jonah Hill) lounges on the couch, nurses a bad case of coke sniffles, and proclaims to be "so bored" by all the world-ending comet talk.


Your CEO Isn't Real: How to Deal With Deep Fakes

#artificialintelligence

The history of deep fake technology is surprisingly long. Researchers at academic institutions have been developing deep fake tech since the early 1990s. The idea is even older, as popular science fiction--like the 1987 film The Running Man--can attest. But deep fakes are no longer relegated to the realm of sci-fi; they are, in fact, more present in our daily lives than you might realize. It's easy to think of deep fakes as some sort of advanced CGI used to create highly realistic animated films or to replace established actors in a film or television series, especially in cases where actors pass away unexpectedly before filming is complete.