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#Singularity University, les technologies exponentielles | #transhumanism

#Singularity University, les technologies exponentielles | #transhumanism | Cyborgs_Transhumanism | Scoop.it
Cette université un peu particulière, qui considère que les technologies bouleversent fondamentalement l'humanité, se délocalisera deux jours en Europe en novembre.
luiy's insight:

Cela dit, les membres de la Singularity University reconnaissent que la tâche ne sera pas aisée. Paradoxalement, le terme de « singularité », emprunté à la physique, désigne un événement sans précédent, d'une telle ampleur qu'il empêche totalement de prévoir ce qui arrivera ensuite – à l'image des phénomènes inconnus se développant aux abords d'un trou noir...

 

Neil Jacobstein n'imagine pas que les technologies exponentielles provoquent un bouleversement aussi radical, mais il entrevoit un risque majeur, déjà évoqué par Ray Kurtzweil, inventeur du concept de singularité dans cette nouvelle acception :

 

« Certains humains s'intégreront de plus en plus aux systèmes d'intelligence artificielle, selon un mode opératoire encore inédit. Par contre, ceux qui seront exclus de ce niveau d'interconnexion avec les machines ne comprendront plus du tout le nouveau monde. »

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The Duel: Timo Boll vs. KUKA Robot | #robotics

Man against machine. The unbelievably fast KUKA robot faces off against one of the best table tennis players of all time. Who has the best technique? Who wil...

Via Ionut Anton, Andrea Graziano
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dana tanase's curator insight, March 11, 2014 2:40 AM

robot fairplay

Pedro Santiago's curator insight, March 11, 2014 5:08 AM

Man against machine

thierrydenys's curator insight, March 13, 2014 3:27 AM

Film sublime....qui pose mille questions sur l'aventure homme / robot. Une poésie inaccessible (pour l'instant) aux robots ? 

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AIXI : To create a super-intelligent machine, start with an equation I #algorithms #agents

AIXI : To create a super-intelligent machine, start with an equation I #algorithms #agents | Cyborgs_Transhumanism | Scoop.it
Intelligence is a very difficult concept and, until recently, no one has succeeded in giving it a satisfactory formal definition.

Via Spaceweaver, Mlik Sahib
luiy's insight:

Universal artificial intelligence


This scientific field is called universal artificial intelligence, with AIXI being the resulting super-intelligent agent.

 

The goal of AIXI is to maximise its reward over its lifetime – that's the planning part.

In summary, every interaction cycle consists of observation, learning, prediction, planning, decision, action and reward, followed by the next cycle.

If you're interested in exploring further, AIXI integrates numerous philosophical, computational and statistical principles:

 

Ockham's razor (simplicity) principle for model selectionEpicurus principle of multiple explanations as a justification of model averagingBayes rule for updating beliefsTuring machines as universal description languageKolmogorov complexity to quantify simplicitySolomonoff's universal prior andBellman equations for sequential decision making.



Read more at: http://phys.org/news/2013-11-super-intelligent-machine-equation.html#jCp

 

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Spaceweaver's curator insight, December 2, 2013 8:52 AM

interesting! See the link to the book.

Mlik Sahib's curator insight, December 2, 2013 7:29 PM

Imagine a robot walking around in the environment. Initially it has little or no knowledge about the world, but acquires information from the world from its sensors and constructs an approximate model of how the world works.

It does that using very powerful general theories on how to learn a model from data from arbitrarily complex situations. This theory is rooted in algorithmic information theory, where the basic idea is to search for the simplest model which describes your data.

The model is not perfect but is continuously updated. New observations allow AIXI to improve its world model, which over time gets better and better. This is the learning component.

AIXI now uses this model for approximately predicting the future and bases its decisions on these tentative forecasts. AIXI contemplates possible future behaviour: "If I do this action, followed by that action, etc, this or that will (un)likely happen, which could be good or bad. And if I do this other action sequence, it may be better or worse."



Read more at: http://phys.org/news/2013-11-super-intelligent-machine-equation.html#jCp
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Réussite contestée d'un ordinateur au légendaire test de #Turing | #AI

Réussite contestée d'un ordinateur au légendaire test de #Turing | #AI | Cyborgs_Transhumanism | Scoop.it
Ce test, élaboré en 1950, est censé déterminer si un ordinateur est capable de reproduire la pensée humaine. Mais les détails de cette réussite sont très flous.
luiy's insight:

Ce n'est pas la première fois qu'un succès à ce test est annoncé, mais, selon l'université de Reading, c'est la première fois que les sujets de discussion n'étaient pas fixés à l'avance.

 

Outre des critiques de longue date concernant la validité et la portée réelle du test de Turing (ainsi que la forme qu'a voulu lui donner son créateur – notamment concernant le seuil de 30 % d'humains convaincus qui serait issu d'une interprétation un peu large d'une citation de Turing), des voix se sont élevées pourminimiser l'exploit d'Eugene. Le Daily Telegraph, notamment, pointe plusieurs biais importants :

 

- Le programme se faisait passer pour un jeune garçon, une interprétation du test qui le rend plus facile à réussir, les interlocuteurs humains étant plus susceptibles d'attribuer les défauts d'une conversation à ce jeune âge.

 

- Même type de critique concernant la nationalité prêtée au programme : n'étant pas censé être anglophone, il a été plus facile de « duper » les humains.

 

- Pour le moment, l'article scientifique détaillant ce test n'est pas paru, et l'université de Reading n'a pas voulu fournir au quotidien britannique de copie des conversations.

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▶ What Will You Do With #Watson? #AI #algorithms

▶ What Will You Do With #Watson? #AI #algorithms | Cyborgs_Transhumanism | Scoop.it
IBM Watson is defining a new era of cognitive technology. This generation of problem solvers is going to learn much faster with IBM Watson. And Watson, in tu...

Via Spaceweaver
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Paul Allen and the Machines: Teaching the next generation of artificial intelligence | #cyborgs #AI

Paul Allen and the Machines: Teaching the next generation of artificial intelligence | #cyborgs #AI | Cyborgs_Transhumanism | Scoop.it
Microsoft co-founder Paul Allen has been pondering artificial intelligence since he was a kid. In the late '60s, eerily intelligent computers were everywhere, whether it was 2001's HAL or Star Trek'...
luiy's insight:

Microsoft co-founder Paul Allen has been pondering artificial intelligence since he was a kid. In the late '60s, eerily intelligent computers were everywhere, whether it was 2001's HAL or Star Trek's omnipresent Enterprise computer. As Allen recalls in his memoir, "machines that behaved like people, even people gone mad, were all the rage back then." He would tag along to his father's job at the library, overwhelmed by the information, and daydream about "the sci-fi theme of a dying or threatened civilization that saves itself by finding a trove of knowledge." What if you could collect all the world's information in a single computer mind, one capable of intelligent thought, and be able to communicate in simple human language?

 

 

Forty years later, with nearly 9 billion dollars to Allen's name, that idea is beginning to seem like more than just fantasy. Much of the technology is already here. We talk to our phones and aren't surprised when they talk back. A web search can answer nearly any question, undergirded by a semantic understanding of the structure of online information. But while the tools are powerful, the processes behind them are still fairly basic. Siri only understands a small subset of questions, and she can't reason, or do anything you might call thinking. Even Watson, IBM's Jeopardy champ, can only handle simple questions with unambiguous phrasing. Already, Google is looking to the Star Trek computer as a guiding light for its voice search — but it's still a long way off. If technology is going to get there, we'll need computers that are better at talking and, more crucially, better at reasoning.

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