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M.O.P. Super Posteur
Inscrit le: 11 Mar 2004 Messages: 3224
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M.O.P. Super Posteur
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Posté le: Ven 28 Juin 2019 10:55 Sujet du message: The human pursuit of artificial intelligence | Thore Graepel |
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The human pursuit of artificial intelligence | Thore Graepel | TEDxExeter
https://youtu.be/wTSbvYBx4eg
Citation: | What is intelligence? And how can we create it in machines? Thore Graepel takes us inside the world of artificial intelligence (AI) and reveals its potential to solve some of the biggest problems facing the world today. He argues that there is nothing more human than the pursuit of artificial intelligence. Thore Graepel is a research group lead at DeepMind and chair of machine learning at University College London. His research into artificial intelligence has helped to develop systems used by Xbox Live and Bing. Thore recently contributed to creating AlphaGo, the first computer program to defeat a human professional player in the full-sized game of Go. |
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M.O.P. Super Posteur
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Posté le: Sam 29 Juin 2019 00:47 Sujet du message: Will Self-Taught, A.I. Powered Robots Be the End of Us? |
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Will Self-Taught, A.I. Powered Robots Be the End of Us?
https://youtu.be/IHc5Zt7qT6o
Citation: | “Success in creating effective A.I.,” said the late Stephen Hawking, “could be the biggest event in the history of our civilization. Or the worst. We just don’t know.” Are we creating the instruments of our own destruction or exciting tools for our future survival? Once we teach a machine to learn on its own—as the programmers behind AlphaGo have done, to wondrous results—where do we draw moral and computational lines? In this program, leading specialists in A.I., neuroscience, and philosophy tackle the very questions that may define the future of humanity. PARTICIPANTS: Yann LeCun, Susan Schneider, Max Tegmark, Peter Ulric Tse MODERATOR: Tim Urban |
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M.O.P. Super Posteur
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Posté le: Ven 12 Juil 2019 08:04 Sujet du message: Interface neuronale directe |
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Interface neuronale directe
https://fr.wikipedia.org/wiki/Interface_neuronale_directe
Citation: | Une interface neuronale directe - abrégée IND ou BCI1 ou encore ICM (interface cerveau-machine, ou encore interface cerveau-ordinateur) est une interface de communication directe entre un cerveau et un dispositif externe (un ordinateur, un système électronique…). Ces systèmes peuvent être conçus dans le but d'étudier le cerveau, d'assister, améliorer ou réparer des fonctions humaines de cognition ou d'action défaillantes.
L'IND peut être unidirectionnelle ou bidirectionnelle.
Ce type de périphérique est fondamentalement différent de toute autre interface homme-machine : une telle liaison ne requiert en effet aucune transformation préalable du signal électrique émis par l’activité cérébrale en activité musculaire (psychomotrice), cette dernière étant usuellement traduite en signal d’entrée pour la machine.
En s’affranchissant de la chaîne de réaction « cerveau, nerfs, muscles, interface conventionnelle homme-machine », les temps de réponse peuvent être écourtés de plusieurs dixièmes de seconde dans le cas d’interaction urgente. De plus, ils laissent les organes vitaux (mains, pieds, yeux, etc.) libres et disponibles pour d’autres types de commandes simultanées. |
L'Entreprise Neuralink de l'entrepreneur d'origine sud-africaine, Elon Musk: Neuralink
https://fr.wikipedia.org/wiki/Neuralink
https://twitter.com/neuralink
https://neuralink.com/
Elon Musk’s Neuralink to livestream special project update on July 16
https://www.teslarati.com/neuralink-project-demo-event-livestream-july-16/
Neuralink and the Brain’s Magical Future
https://waitbutwhy.com/2017/04/neuralink.html
Elon Musk Plans to Beat Artificial Intelligence by Merging With it - Neuralink
https://youtu.be/pn_2LIdxxRA _________________ La vie est un privilege, elle ne vous doit rien!
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M.O.P. Super Posteur
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Posté le: Sam 27 Juil 2019 09:42 Sujet du message: GO champ Ke Jie talks about his match with Google's AI |
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2017: GO champ Ke Jie talks about his match with Google's AI
https://youtu.be/UHU8lCctC-Q
Citation: | The future belongs to artificial intelligence (AI), said the Chinese Go prodigy Ke Jie after he was defeated by the Google-owned AlphaGo computer program.
The world's number one Go player gave an exclusive interview to CGTN on Sunday, a day after his defeat in the town of Wuzhen, east China's Zhejiang Province. |
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M.O.P. Super Posteur
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Posté le: Dim 01 Sep 2019 13:18 Sujet du message: |
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Yann LeCun: Deep Learning, Convolutional Neural Networks, and Self-Supervised Learning | AI Podcast
https://youtu.be/SGSOCuByo24
Citation: |
Lex Fridman, 31.08.2019
Yann LeCun is one of the fathers of deep learning, the recent revolution in AI that has captivated the world with the possibility of what machines can learn from data. He is a professor at New York University, a Vice President & Chief AI Scientist at Facebook, co-recipient of the Turing Award for his work on deep learning. He is probably best known as the founding father of convolutional neural networks, in particular their early application to optical character recognition. This conversation is part of the Artificial Intelligence podcast. |
https://www.youtube.com/user/lexfridman/videos _________________ La vie est un privilege, elle ne vous doit rien!
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M.O.P. Super Posteur
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Posté le: Dim 01 Sep 2019 20:38 Sujet du message: |
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Jeff Hawkins: Thousand Brains Theory of Intelligence | Artificial Intelligence (AI) Podcast
https://youtu.be/-EVqrDlAqYo
Citation: | Lex Fridman, 01.07.2019
Jeff Hawkins is the founder of Redwood Center for Theoretical Neuroscience in 2002 and Numenta in 2005. In his 2004 book titled On Intelligence, and in his research before and after, he and his team have worked to reverse-engineer the neocortex and propose artificial intelligence architectures, approaches, and ideas that are inspired by the human brain. These ideas include Hierarchical Temporal Memory (HTM) from 2004 and The Thousand Brains Theory of Intelligence from 2017. This conversation is part of the Artificial Intelligence podcast. Audio podcast version is available on https://lexfridman.com/ai/ |
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M.O.P. Super Posteur
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Posté le: Jeu 05 Sep 2019 13:18 Sujet du message: Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTM |
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Juergen Schmidhuber: Godel Machines, Meta-Learning, and LSTMs | Artificial Intelligence (AI) Podcast
https://youtu.be/3FIo6evmweo
Citation: | Lex Fridman, 23.12.2018
Juergen Schmidhuber is the co-creator of long short-term memory networks (LSTMs) which are used in billions of devices today for speech recognition, translation, and much more.
Over 30 years, he has proposed a lot of interesting, out-of-the-box ideas in artificial intelligence including a formal theory of creativity.
This conversation is part of the Artificial Intelligence podcast and the MIT course 6.S099: Artificial General Intelligence. The conversation and lectures are free and open to everyone. Audio podcast version is available on https://lexfridman.com/ai/ |
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Posté le: Sam 28 Sep 2019 11:37 Sujet du message: La fabrique du cerveau | ARTE |
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La fabrique du cerveau | ARTE
https://youtu.be/891NUdFbB04 _________________ La vie est un privilege, elle ne vous doit rien!
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Dernière édition par M.O.P. le Ven 06 Déc 2019 14:28; édité 1 fois |
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M.O.P. Super Posteur
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Posté le: Ven 11 Oct 2019 09:17 Sujet du message: multitask-learning-in-the-wilderness |
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Andrej Karpathy, Tesla: Multi-Task Learning in the Wilderness, Jun 15, 2019
https://slideslive.com/38917690/multitask-learning-in-the-wilderness
Citation: | Driven by progress in deep learning, the machine learning community is now able to tackle increasingly more complex problems—ranging from multi-modal reasoning to dexterous robotic manipulation—all of which typically involve solving nontrivial combinations of tasks. Thus, designing adaptive models and algorithms that can efficiently learn, master, and combine multiple tasks is the next frontier. AMTL workshop aims to bring together machine learning researchers from areas ranging from theory to applications and systems, to explore and discuss:
* advantages, disadvantages, and applicability of different approaches to learning in multitask settings,
* formal or intuitive connections between methods developed for different problems that help better understand the landscape of multitask learning techniques and inspire technique transfer between research lines,
* fundamental challenges and open questions that the community needs to tackle for the field to move forward. |
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M.O.P. Super Posteur
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Posté le: Jeu 14 Nov 2019 07:06 Sujet du message: Re: Elon Musk: Tesla Autopilot | Artificial Intelligence (AI |
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Part2-
Elon Musk: Neuralink, AI, Autopilot, and the Pale Blue Dot | Artificial Intelligence (AI) Podcast
https://youtu.be/smK9dgdTl40
M.O.P. a écrit: | Elon Musk: Tesla Autopilot | Artificial Intelligence (AI) Podcast
https://youtu.be/dEv99vxKjVI
Citation: | Elon Musk is the CEO of Tesla, SpaceX, Neuralink, and a co-founder of several other companies. This conversation is part of the Artificial Intelligence podcast. The series includes leading researchers in academia and industry, including CEO's and CTO's of automotive, robotics, AI, and technology companies. See the comments I make in the introduction to this video below in text form. |
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M.O.P. Super Posteur
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Posté le: Sam 16 Nov 2019 09:28 Sujet du message: Re: multitask-learning-in-the-wilderness |
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PyTorch at Tesla - Andrej Karpathy, Tesla
https://youtu.be/oBklltKXtDE
Citation: | Hear from Andrej Karpathy on how Tesla is using PyTorch to develop full self-driving capabilities for its vehicles, including AutoPilot and Smart Summon. |
M.O.P. a écrit: | Andrej Karpathy, Tesla: Multi-Task Learning in the Wilderness, Jun 15, 2019
https://slideslive.com/38917690/multitask-learning-in-the-wilderness
Citation: | Driven by progress in deep learning, the machine learning community is now able to tackle increasingly more complex problems—ranging from multi-modal reasoning to dexterous robotic manipulation—all of which typically involve solving nontrivial combinations of tasks. Thus, designing adaptive models and algorithms that can efficiently learn, master, and combine multiple tasks is the next frontier. AMTL workshop aims to bring together machine learning researchers from areas ranging from theory to applications and systems, to explore and discuss:
* advantages, disadvantages, and applicability of different approaches to learning in multitask settings,
* formal or intuitive connections between methods developed for different problems that help better understand the landscape of multitask learning techniques and inspire technique transfer between research lines,
* fundamental challenges and open questions that the community needs to tackle for the field to move forward. |
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M.O.P. Super Posteur
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Posté le: Dim 17 Nov 2019 08:37 Sujet du message: In the Age of AI |
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In the Age of AI
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M.O.P. Super Posteur
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Posté le: Sam 14 Mar 2020 18:38 Sujet du message: |
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DeepMind: The Podcast
https://www.youtube.com/playlist?list=PLqYmG7hTraZBiUr6_Qf8YTS2Oqy3OGZEj
https://deepmind.com/blog/article/welcome-to-the-deepmind-podcast
Citation: | Over the past 12 months, mathematician and broadcaster Hannah Fry has explored our headquarters in London to get an inside look at artificial intelligence (AI) research and where it is going. The result - DeepMind: the Podcast - offers diverse perspectives from scientists, researchers and engineers. Along the way, she explores what they are working on, how they’re approaching the science of AI and some of the tricky decisions the whole field is wrestling with at the moment. |
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