Theoretical computer scientists
Ray Solomonoff (July 25, 1926 – December 7, 2009) was the inventor of algorithmic probability, his General Theory of Inductive Inference (also known as Universal Inductive Inference), and was a founder of algorithmic information theory. He was an originator of the branch of artificial intelligence based on machine learning, prediction and probability. He circulated the first report on non-semantic machine learning in 1956. Solomonoff first described algorithmic probability in 1960, publishing the theorem that launched Kolmogorov complexity and algorithmic information theory. He first described these results at a conference at Caltech in 1960, and in a report, Feb. 1960, "A Preliminary Report on a General Theory of Inductive Inference." He clarified these ideas more fully in his 1964 publications, "A Formal Theory of Inductive Inference," Part I and Part II. Algorithmic probability is a mathematically formalized combination of Occam's razor, and the Principle of Multiple Explanations.It is a machine independent method of assigning a probability value to each hypothesis (algorithm/program) that explains a given observation, with the simplest hypothesis (the shortest program) having the highest probability and the increasingly complex hypotheses receiving increasingly small probabilities. Solomonoff founded the theory of universal inductive inference, which is based on solid philosophical foundations and has its root in Kolmogorov complexity and algorithmic information theory. The theory uses algorithmic probability in a Bayesian framework. The universal prior is taken over the class of all computable measures; no hypothesis will have a zero probability. This enables Bayes' rule (of causation) to be used to predict the most likely next event in a series of events, and how likely it will be. Although he is best known for algorithmic probability and his general theory of inductive inference, he made many other important discoveries throughout his life, most of them directed toward his goal in artificial intelligence: to develop a machine that could solve hard problems using probabilistic methods. (Wikipedia).
INTERVIEW AT CIRM: PETER SARNAK
Peter Sarnak is a South African-born mathematician with dual South-African and American nationalities. He has been Eugene Higgins Professor of Mathematics at Princeton University since 2002, succeeding Andrew Wiles, and is an editor of the Annals of Mathematics. He is known for his work in
From playlist Jean-Morlet Chair's guests - Interviews
Marvin Minsky Toshiba Professor of Media Arts and Sciences and Computer Science and Engineering, emeritus Head, Society of Mind Group Marvin Minsky was the Toshiba professor of media arts and sciences and computer science and engineering emeritus at MIT. Professor Minsky was a pioneer in
From playlist AI talks
Berry's Paradox - An Algorithm For Truth
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From playlist Math
Math Park - 11/01/2014 - Yann Ollivier, Mathématiques, raisonnements inductifs et...
Les problèmes de raisonnement inductif ou d'extrapolation comme « deviner la suite d'une série de nombres », ou plus généralement, « comprendre la structure cachée dans des observations », sont fondamentaux si l'on veut un jour construire une intelligence artificielle. On pourrait avoir l'
From playlist Séminaire Mathematic Park
Shannon 100 - 27/10/2016 - Jean Louis DESSALLES
Information, simplicité et pertinence Jean-Louis Dessalles (Télécom ParisTech) Claude Shannon fonda la notion d’information sur l’idée de surprise, mesurée comme l’inverse de la probabilité (en bits). Sa définition a permis la révolution des télécommunications numériques. En revanche, l’
From playlist Shannon 100
Nexus Trimester - Péter Gács (Boston University)
Péter Gács (Boston University) Relation between monotonic complexity and algorithmic probability February 03, 2016 Abstract: Some versions of Kolmogorov complexity are better suited than others when regarding finite sequences as starting segments of infinite sequences. Levin and Schnorr
From playlist Nexus Trimester - 2016 - Distributed Computation and Communication Theme
Nexus Trimester - Péter Gács (Boston University) 2/2
Relation between monotonic complexity and algorithmic probability Péter Gács (Boston University) February 04, 2016 Abstract: Some versions of Kolmogorov complexity are better suited than others when regarding finite sequences as starting segments of infinite sequences. Levin and Schnorr
From playlist Nexus Trimester - 2016 - Distributed Computation and Communication Theme
Physics & Astrophysics of Gamma-Ray Bursts Lecture 3 by Frédéric Daigne
PROGRAM: GRAVITATIONAL WAVE ASTROPHYSICS (ONLINE) ORGANIZERS : Parameswaran Ajith, K. G. Arun, Sukanta Bose, Bala R. Iyer, Resmi Lekshmi and B Sathyaprakash DATE: 18 May 2020 to 22 May 2020 VENUE: Online Due to the ongoing COVID-19 pandemic, the original program has been cancelled. Howe
From playlist Gravitational Wave Astrophysics (Online) 2020
AI for physics & physics for AI
Max Tegmark, MIT Abstract: After briefly reviewing how machine learning is becoming ever-more widely used in physics, I explore how ideas and methods from physics can help improve machine learning, focusing on automated discovery of mathematical formulas from data. I present a method for u
From playlist AI talks
Murat Erdemsel & Sigrid Van Tilbeurgh - Vals
From playlist Tango
Murat Erdemsel & Sigrid van Tilbeurg, Vals performance, Tango Soul Festival
Wellington, NZ, 24/03/2018
From playlist Tango
Help us caption & translate this video! http://amara.org/v/FGii/
From playlist MWRC 2009
MIT 6.868J The Society of Mind, Fall 2011 View the complete course: http://ocw.mit.edu/6-868JF11 Instructor: Marvin Minsky In this lecture, students discuss Chapter 4 of The Emotion Machine, covering topics such as the relationship between pain, hurt, and perception, and how the mind expl
From playlist MIT 6.868J The Society of Mind, Fall 2011
El Banat \ אל בנאת \ ديوان البنات - Maagalim מעגלים
Ma'aglim by El Banat Original song written and composed by Ofri Zidner Film Director: Nitai Shalom Music Producer: Liad Mor Executive Producer: Noya Yifat Tamar Bloch - Singer Noya Yifat - Persian Tar Ofri Zidner - Turkish Baglama Liad Mor - Bass Gilad Amsalem - Percussion and Doumb
From playlist World
Quantum Fields: The Real Building Blocks of the Universe - with David Tong
According to our best theories of physics, the fundamental building blocks of matter are not particles, but continuous fluid-like substances known as 'quantum fields'. David Tong explains what we know about these fields, and how they fit into our understanding of the Universe. Watch the Q&
From playlist Quantum Mechanics Prof. Susskind & Feynman
Philosophy of Math: What math would aliens know? (Clement Hongler) | Ep. 12
Clement Hongler is a professor of mathematics at EPFL in Lausanne, Switzerland. We discuss some issues in the philosophy of mathematics, namely the relationship of mathematics to the real world, how math can be "natural" or historically contingent, the prospects of fundamental or unified t
From playlist Daniel Rubin Show, Full episodes
TEDxCaltech - Stephen Hawking, John Preskill, Rives, Kip Thorne - Finding Things Out
Stephen Hawking is a theoretical physicist and cosmologist, whose scientific books and public appearances have made him an academic celebrity. He is known for his contributions to the fields of cosmology and quantum gravity, especially in the context of black holes. He has also achieved su
From playlist TEDxCaltech - 1/14/11