Ray Kurzweil spoke about his book The Age of Spiritual Machines about artificial intelligence and the future course of humanity. First published in hardcover on January 1, 1999 by Viking, it has received attention from The New York Times, The New York Review of Books and The Atlantic. In the book Kurzweil outlines his vision for how technology will progress during the 21st century.
The Artificial Intelligence Channel
Recorded January 21st, 1999
Ray Kurzweil spoke about his book The Age of Spiritual Machines about artificial intelligence and the future course of humanity. First published in hardcover on January 1, 1999 by Viking, it has received attention from The New York Times, The New York Review of Books and The Atlantic. In the book Kurzweil outlines his vision for how technology will progress during the 21st century.
Ray Kurzweil spoke about his book The Age of Spiritual Machines about artificial intelligence and the future course of humanity. First published in hardcover on January 1, 1999 by Viking, it has received attention from The New York Times, The New York Review of Books and The Atlantic. In the book Kurzweil outlines his vision for how technology will progress during the 21st century.
updated 6 years ago
Ray Kurzweil spoke about his book The Age of Spiritual Machines about artificial intelligence and the future course of humanity. First published in hardcover on January 1, 1999 by Viking, it has received attention from The New York Times, The New York Review of Books and The Atlantic. In the book Kurzweil outlines his vision for how technology will progress during the 21st century.
Recorded Oct 19th, 2018
Michael Levin
Vannevar Bush Professor
Director, Allen Discovery Center at Tufts
Director, Tufts Center for Regenerative and Developmental Biology
Morphological and behavioral information processing in living systems
Presented December 3rd, 2018
This tutorial Unsupervised Deep Learning will cover in detail, the approach to simply 'predict everything' in the data, typically with a probabilistic model, which can be seen through the lens of the Minimum Description Length principle as an effort to compress the data as compactly as possible.
Alex Graves is a research scientist at DeepMind. He did a BSc in Theoretical Physics at Edinburgh and obtained a PhD in AI under Jürgen Schmidhuber at IDSIA. He was also a postdoc at TU Munich and under Geoffrey Hinton at the University of Toronto.
This tutorial will provide a practical overview of state-of-the-art approaches for analyzing massive data sets using Bayesian statistical methods.
Prof. David Dunson
Prof. David Dunson is a statistician who is Arts and Sciences Distinguished Professor of Statistical Science, Mathematics and Electrical & Computer Engineering at Duke University. His research focuses on developing innovative statistical methods for complex and high-dimensional data.
In this talk Dr. Cassell will describe some unexpected results about the ways in which social interaction supports and improves task performance in people, and how social interactiohen can profitably be integrated into AI, with implications for the future of AI, the future of work, and the future of social interaction.
August 31st, 2018
August 23rd, 2018
Speaker: Marco Lanzagorta, Naval Research Laboratory
The National Academies of Sciences, Engineering, and Medicine organized a half-day colloquium and webcast sponsored by the Office of the Director of National Intelligence to explore some of the latest developments in quantum sensing and quantum communications. This unclassified event featured individual presentations and a panel discussion on quantum concepts and technologies as they relate to the state of the art.
Filmed July 13th, 2018.
He also talked about his book on virtual reality, Experience on Demand.
Recorded June 26th, 2018
Recorded July, 2018
Recorded June 19th, 2018
Recorded August 1st, 2018
Milind Tambe is Helen N. and Emmett H. Jones Professor in Engineering and a Professor of Computer Science and Industrial and Systems Engineering at the University of Southern California, Los Angeles.
An expert panel discussed the President's proposal to create a so-called “space force” as a sixth, new branch of defense. Panelists included former Pentagon officials who discussed the current state and structure of the nation’s extraterrestrial capabilities and the advantages and disadvantages of creating a separate space-focused branch. After panelists spoke, they took questions from the audience.
Recorded May 21st, 2018
Andrew G. Barto is a professor of computer science at University of Massachusetts Amherst, and chair of the department since January 2007. His main research area is reinforcement learning.
Recorded June 11th, 2018
Yann LeCun is the Chief AI Scientist for Facebook AI Research (FAIR), joining Facebook in December 2013. He is also a Silver Professor at New York University on a part time basis, mainly affiliated with the NYU Center for Data Science, and the Courant Institute of Mathematical Science.
Max Tegmark is a Professor doing physics and AI research at MIT, and advocates for positive use of technology as President of the Future of Life Institute. He is the author of over 200 publications as well as the New York Times bestsellers “Life 3.0: Being Human in the Age of Artificial Intelligence” and “Our Mathematical Universe: My Quest for the Ultimate Nature of Reality”. His work with the Sloan Digital Sky Survey on galaxy clustering shared the first prize in Science magazine’s “Breakthrough of the Year: 2003.”
This tutorial Machine Learning in Automated Mechanism Design for Pricing and Auctions will cover the rapidly growing area of automated mechanism design for revenue maximization.
Presented by Nina Balcan (CMU), Tuomas Sandholm (CMU) and Ellen Vitercik (CMU)
Rony Paz is an associate professor (tenured) in the Dept. of Neurobiology at the Weizmann Institute of Science.
https://www.weizmann.ac.il
Sen. Marco Rubio, a member of the Intelligence Committee, gave a speech on the impact of artificial intelligence technology that can distort the audio and video images of individuals. He discussed the implications of this for U.S. elections when domestic entities or foreign governments can use it as part of disinformation campaigns. Following his remarks, a panel of technology and policy experts further discussed the issue including the role of social media platforms and privacy implications.
Witnesses testify at a House Financial Services subcommittee on the whether the government should consider cryptocurrencies as money and their potential domestic and global uses.
Presented by Yisong Yue (Caltech) and Hoang M Le (Caltech)
"In this tutorial, we aim to present to researchers and industry practitioners a broad overview of imitation learning techniques and recent applications. Imitation learning is a powerful and practical alternative to reinforcement learning for learning sequential decision-making policies. Also known as learning from demonstrations or apprenticeship learning, imitation learning has benefited from recent progress in core learning techniques, increased availability and fidelity of demonstration data, as well as the computational advancements brought on by deep learning. We expect the tutorial to be highly relevant for researchers & practitioners who have interests in reinforcement learning, structured prediction, planning and control. The ideal audience member should have familiarity with basic supervised learning concepts. No knowledge of reinforcement learning techniques will be assumed."
Joshua Tenenbaum is Professor of Cognitive Science and Computation at the Massachusetts Institute of Technology. He is known for contributions to mathematical psychology and Bayesian cognitive science.
icml.cc/Conferences/2018/Schedule?showEvent=1867
Lee developed the world's first speaker-independent, continuous speech recognition system as his Ph.D. thesis at Carnegie Mellon. He later worked as an executive, first at Apple, then SGI, Microsoft, and then Google.
He became the focus of a 2005 legal dispute between Google and Microsoft, his former employer, due to a one-year non-compete agreement that he signed with Microsoft in 2000 when he became its corporate vice president of interactive services. - June 2018
Shimon Ullman is a professor of computer science at the Weizmann Institute of Science, Israel. Ullman's main research area is the study of vision processing by both humans and machines.
https://www.weizmann.ac.il
Aaron P. Batista, University of Pittsburgh
When we learn, the brain changes at nearly every level of organization. Synapses form and strengthen, individual neurons change their tuning properties, and cortical maps expand. My research examines how learning alters the coordinated activity of populations of neurons. This is a particularly important level at which to study learning because it is the action of populations of neurons that drive behavior, generate perceptions, and undergird our cognition.
February 2018
Dr. Tim Persons, chief scientist, GAO
Mr. Greg Brockman, co-founder and chief technology officer, OpenAI
Dr. Fei-Fei Li, chairperson of the board and co-founder, AI4ALL
OpenAI was founded by Elon Musk and Sam Altman
With recent technological advances, we can now record neural activity from the brain, and manipulate this activity with electrical or optogenetic stimulation in real time. These capabilities have brought the concept of brain-machine interfaces (BMI) closer to clinical viability than ever before. BMIs are systems that monitor and interact with the brain to restore lost function, treat neurological disorders, or enhance human performance.
February 2018
June 2017
Xavier Puig ; Kevin Ra ; Marko Boben ; Jiaman Li ; Tingwu Wang ; Sanja Fidler ; Antonio Torralba
Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video Interpolation
Huaizu Jiang ; Deqing Sun ; Varun Jampani ; Ming-Hsuan Yang ; Erik Learned-Miller ; Jan Kautz
arxiv.org/abs/1712.00080
"Do visual tasks have a relationship, or are they unrelated? For instance, could having surface normals simplify estimating the depth of an image? Intuition answers these questions positively, implying existence of a "structure" among visual tasks. Knowing this structure has notable values; it is the concept underlying transfer learning and provides a principled way for identifying redundancies across tasks, e.g., to seamlessly reuse supervision among related tasks or solve many tasks in one system without piling up the complexity. "
http://taskonomy.stanford.edu/
Amir R. Zamir, Alexander Sax*, William B. Shen*
Leonidas Guibas, Jitendra Malik, Silvio Savarese
Anthony John Goldbloom is the founder and CEO of Kaggle, a Silicon Valley start-up which has used predictive modeling competitions to solve problems for NASA, Wikipedia, Ford and Deloitte.
“The Enhanced Human: Risks and Opportunities” was co-presented by the New York Academy of Sciences, the Aspen Brain Institute, and The Hastings Center on May 21, 2018. For more information, please visit: nyas.org/EnhancedHuman
Enhanced humans walk among us. Over the course of human history, people have sought to alter their bodies not only to restore their health, but also to augment their abilities. Some enhancements have been commonplace for centuries, like a simple cup of coffee to remain alert or eyeglasses to improve sight.
More recent developments are ever more complex, from prosthetic devices to restore lost functions, like robotic limbs or cochlear implants, to the DIY biohackers movement to create cognitive and body enhancers. As we move deeper into the 21st century, human enhancement technologies are being developed at an increasingly rapid pace.
March 9th, 2018
April 10th, 2018.
February 2017
After five years of being second place to China the US has finally unveiled a supercomputer at the Oak Ridge National Laboratory in Tennessee that takes back the number one spot. Summit’s speeds, announced on Friday, boggle the mind. It can do mathematical calculations at the rate of 200 quadrillion per second, or 200 PetaFLOPS.
Prof. Cyrille J. Cohen, Bar-Ilan University
Link to clip shown at 28:40 youtu.be/rSSdZZsXmzo
We are exploring new ways to create and improve the anti-cancer response by patients’ immune cells, which could have important implications for the clinical treatment of cancer using immunotherapy approaches. Feb, 2017
Adam W. Feinberg, Carnegie Mellon University
Over the past decade, 3D bioprinting has rapidly expanded from a niche technology and in to a versatile platform for fabricating tissues with complex geometries and features ranging from the cellular to organ length scales.
February, 2017
Does Hierarchical Predictive Coding Explain Perception?
Speakers:
Andy Clark (Philosophy, University of Edinburgh)
David Heeger (Center for Neural Science, NYU)
Lucia Melloni (Neurology, Max Planck Institute / NYU)
Michael Rescorla (Philosophy, UCLA)
Predictive models of perception propose that perception works by making predictions about sensory inputs and minimizing prediction error. Hierarchical predictive coding models say that at each layer in the visual hierarchy, predictions are made about the layer below. Any differences between predicted input and actual input are propagated up the visual hierarchy by the mechanism of predictive coding, altering the system to reduce prediction errors in the future. According to some theorists, this approach portrays perception as “controlled hallucination”. This event will bring two neuroscientists and two philosophers together to debate how well this approach can explain perception.
April 18th, 2018
nickbostrom.com/fable/dragon.html