Probabilistic software

Turing (probabilistic programming)

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r u even turing complete?

What does it mean to be Turing Complete? Is HTML & CSS Turing Complete? #shorts #compsci #programming #math

From playlist CS101

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Turing Machines and The Halting Problem (Part 2)

The Halting Problem has fascinated thousands of computer scientists from around the world. A major part of Computing Logic, the proof of the halting problem proves that computers can't do everything. Check out the video to learn more about why computers work the way they do! For Turing Ma

From playlist Math

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Probabilistic logic programming and its applications - Luc De Raedt, Leuven

Probabilistic programs combine the power of programming languages with that of probabilistic graphical models. There has been a lot of progress in this paradigm over the past twenty years. This talk will introduce probabilistic logic programming languages, which are based on Sato's distrib

From playlist Logic and learning workshop

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When somebody tells you they passed the Turing Test, keep your hand on your wallet [Lecture]

This is a single lecture from a course. If you you like the material and want more context (e.g., the lectures that came before), check out the whole course: https://boydgraber.org/teaching/CMSC_470/ (Including homeworks and reading.) Music: https://soundcloud.com/alvin-grissom-ii/review

From playlist Computational Linguistics I

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Turing Machines

Theory of Computation 12. Turing Machines ADUni

From playlist [Shai Simonson]Theory of Computation

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Turing Machines & The Halting Problem (Part 1)

In the year 1900, David Hilbert gave a list of 23 mathematics problems for the mathematicians of the new generation. His tenth problem proved to be an enigma for many years until Alan Turing solved it while simultaneously creating the modern computer. Watch the video to see how Alan Turi

From playlist Math

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Functional Programming for Beginners: Pure Functions Explained

Why is it that pure functions can’t use mutable states in most cases, and how do you fight mutability by working with immutable values? Check it out in this live coding session by Michal Plachta, the author of Grokking Functional Programming. Watch the full video at: http://mng.bz/J24a 📚

From playlist Functional Programming

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Professor Mark Girolami: "Probabilistic Numerical Computation: A New Concept?"

The Turing Lectures: The Intersection of Mathematics, Statistics and Computation - Professor Mark Girolami: "Probabilistic Numerical Computation: A New Concept?" Click the below timestamps to navigate the video. 00:00:09 Introduction by Professor Jared Tanner 00:01:38 Profess

From playlist Turing Lectures

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23. Probabilistic Computation, BPP

MIT 18.404J Theory of Computation, Fall 2020 Instructor: Michael Sipser View the complete course: https://ocw.mit.edu/18-404JF20 YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP60_JNv2MmK3wkOt9syvfQWY Quickly reviewed last lecture. Defined probabilistic Turing machines

From playlist MIT 18.404J Theory of Computation, Fall 2020

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NATS & Turing EPSRC Prosperity Partnership - Tim Dodwell

Introduction The Innovation Symposium was established in 2019 as part of the ongoing collaboration between Accenture and The Alan Turing Institute. Our recently launched strategic partnership has the following goals: - Delivering value from AI and data - Enabling safe and robust applicat

From playlist Innovation Symposium 2021

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Building Machines that Learn & Think Like People - Prof. Josh Tenenbaum ICML2018

Recorded July 13th, 2018 at the 2018 International Conference on Machine Learning 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. htt

From playlist AI talks

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22C3: On working memory and mental imagery

Speaker: Victor Eliashberg How does the brain learn to think? A representation of an untrained human brain, call it B(0), is encoded in the human genome -- its size can hardly exceed a few megabytes. In contrast, a representation of a trained brain, B(t), after big enough time t (say t=2

From playlist 22C3: Private Investigations

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Proof synthesis and differential linear logic

Linear logic is a refinement of intuitionistic logic which, viewed as a functional programming language in the sense of the Curry-Howard correspondence, has an explicit mechanism for copying and discarding information. It turns out that, due to these mechanisms, linear logic is naturally r

From playlist Talks

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Enrichment student panel discussion

Kate Highnam - Enrichment Student at The Alan Turing Institute and postgraduate researcher at the Imperial College London Giuseppe Degan Di Dieco - Enrichment Student at The Alan Turing Institute and PhD student at the University of Bristol Rachel Pirie - Enrichment Student at The Alan T

From playlist Enrichment Scheme Open Event

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Cryptography - Seminar 3 - Protocols

This seminar series is about the mathematical foundations of cryptography. In this seminar Eleanor McMurtry gives the formal definitions of machines, protocols, execution and UC-emulation in the context of universal composability, the foundations of cryptography that are being presented in

From playlist Metauni

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Fellow Short Talks: Professor Zoubin Ghahramani, University of Cambridge

Bio Zoubin Ghahramani FRS is Professor of Information Engineering at the University of Cambridge, where he leads the Machine Learning Group, and The Alan Turing Institute’s University Liaison Director for Cambridge. He is also the Deputy Academic Director of the Leverhulme Centre for the

From playlist Short Talks

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James Clift - Turing and Intelligent Machinery

In this talk James introduces Turing's notion of unorganised machines, which are randomly constructed machines that acquire useful characteristics through a process of training. He details the A-type and B-type machines, and shows how a probabilistic variant of the B-type machines realises

From playlist Deep reinforcement learning seminar

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The Architecture of Biological Complexity - Sydney Brenner

Speaker : Sydney Brenner Venue : J.N. Tata Auditorium, IISc, Bangalore Date and Time : 18 Oct 12, 18:00 In his paper "On Computable Numbers" Turing proposed a way of performing mechanical procedures on binary inputs to test whether mathematical functions could be computed from a set of s

From playlist Public Lectures

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Turing Lecture: Provably beneficial AI

Is it reasonable to expect that AI capabilities will eventually exceed those of humans across a range of real-world-decision making scenarios? Should this be a cause for concern, as Elon Musk, Stephen Hawking, and others have suggested? While some in the mainstream AI community dismiss the

From playlist Turing Lectures

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Turing Complete - Computerphile

What does it mean for something to be Turing Complete? Professor Brailsford explains. Turing Machine Primer: https://youtu.be/DILF8usqp7M Turing Machines Explained: https://youtu.be/dNRDvLACg5Q Chomsky Hierarchy: https://youtu.be/224plb3bCog What on Earth is Recursion?: https://youtu.be/

From playlist Subtitled Films

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Probabilistic programming