Digital #MediaArt(s) Numérique(s)
190.7K views | +2 today
Follow
Digital #MediaArt(s) Numérique(s)
Media Arts Watch Lab - www.arts-numeriques.info - laboratoire de veille Arts Numériques - twitter @arts_numeriques - @processing_org - @DigitalArt_be - by @jacquesurbanska @_Transcultures
Your new post is loading...
Your new post is loading...
Scooped by Jacques Urbanska
Scoop.it!

Is consciousness just an illusion? By Anna Buckley

Is consciousness just an illusion? By Anna Buckley | Digital #MediaArt(s) Numérique(s) | Scoop.it

The cognitive scientist Daniel Dennett believes our brains are machines, made of billions of tiny "robots" - our neurons, or brain cells. Is the human mind really that special?

 

In an infamous memo written in 1965, the philosopher Hubert Dreyfus stated that humans would always beat computers at chess because machines lacked intuition. Daniel Dennett disagreed.

 

A few years later, Dreyfus rather embarrassingly found himself in checkmate against a computer. And in May 1997 the IBM computer, Deep Blue defeated the world chess champion Garry Kasparov. Many who were unhappy with this result then claimed that chess was a boringly logical game. Computers didn't need intuition to win. The goalposts shifted.

more...
No comment yet.
Scooped by Jacques Urbanska
Scoop.it!

Artificial Intelligence: Blurring the Lines Between Humans and Machines (Milken Institute 2016)

For decades, futurists and science fiction writers predicted that smart machines would someday rival the intelligence of humans. Now, their forecasts seem to be coming true. Artificial intelligence, or AI, already exceeds human capability in certain fields. Machines can send and receive signals and analyze vast quantities of data faster than humans. They have learned to drive cars, manage stock portfolios and, through personal assistants such as Siri and Alexa, talk to us. In the not-so-distant future, AI may even augment our own brain functions. But as with all revolutions, the potential of AI raises concerns. Among the biggest: Some worry that that its growing capability may trigger the largest labor displacement since the Great Depression. This panel will explore the many ways artificial intelligence will shape our workforce, culture and institutions in the years to come.

Moderator: James Cham, Partner, Bloomberg Beta / Speakers:
Pascale Fung, Professor, Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology ; Ben Goertzel, Chief Scientist, Hanson Robotics; Chief Scientist, Aidyia Ltd ; Hsiao-Wuen Hon, Corporate Vice President, Microsoft Corp.; Chairman, Asia-Pacific R&D Group, Microsoft

more...
No comment yet.
Scooped by Jacques Urbanska
Scoop.it!

New Artificial Synapse Bridges the Gap to Brain-Like Computers by Shelly Fan

New Artificial Synapse Bridges the Gap to Brain-Like Computers by Shelly Fan | Digital #MediaArt(s) Numérique(s) | Scoop.it

From AlphaGo’s historic victory against world champion Lee Sedol to DeepStack’s sweeping win against professional poker players, artificial intelligence is clearly on a roll.

 

Part of the momentum comes from breakthroughs in artificial neural networks, which loosely mimic the multi-layer structure of the human brain. But that’s where the similarity ends. While the brain can hum along on energy only enough to power a light bulb, AlphaGo’s neural network runs on a whopping 1,920 CPUs and 280 GPUs, with a total power consumption of roughly one million watts—50,000 times more than its biological counterpart.

 

Extrapolate those numbers, and it’s easy to see that artificial neural networks have a serious problem—even if scientists design powerfully intelligent machines, they may demand too much energy to be practical for everyday use.

more...
No comment yet.
Scooped by Jacques Urbanska
Scoop.it!

Don’t panic, but Google’s AI translation tool seems to have invented its own secret internal language by Devin Coldewey

Don’t panic, but Google’s AI translation tool seems to have invented its own secret internal language by Devin Coldewey | Digital #MediaArt(s) Numérique(s) | Scoop.it

All right, don’t panic, but computers have created their own secret language and are probably talking about us right now. Well, that’s kind of an oversimplification, and the last part is just plain untrue. But there is a fascinating and existentially challenging development that Google’s AI researchers recently happened across.

 

You may remember that back in September, Google announced that its Neural Machine Translation system had gone live. It uses deep learning to produce better, more natural translations between languages. Cool!

 

Following on this success, GNMT’s creators were curious about something. If you teach the translation system to translate English to Korean and vice versa, and also English to Japanese and vice versa… could it translate Korean to Japanese, without resorting to English as a bridge between them? ...

more...
No comment yet.
Scooped by Jacques Urbanska
Scoop.it!

Anticipation et génération des réseaux récursifs de neurones | Grégory Chatonsky (2016)

Anticipation et génération des réseaux récursifs de neurones | Grégory Chatonsky (2016) | Digital #MediaArt(s) Numérique(s) | Scoop.it

Le neural.net est laplacien parce qu’il prévoit en calculant la possibilité d’une récurrence (Nitish Srivastava, Elman Mansimov, Ruslan Salakhutdinov, 16 feb 2015). En ce sens, il apparaît contradictoire avec l’hyperchaos et la contingence. En se fondant sur des grands ensembles de données (les datasets) accumulés sur les réseaux sociaux, le RNN déduit ce qui va pouvoir être. Il vectorise pour se faire des documents qui en tant qu’inscription sont passés. Cette vectorisation permet d’éviter de manipuler des symboles sémantiques et se limite donc aux mathématiques. La contingence n’a pas lieu d’être avec le RNN parce qu’elle n’a jamais eu lieu. Elle n’est pas d’autres lois, elle est hors-la-loi, sans loi.

more...
No comment yet.
Scooped by Jacques Urbanska
Scoop.it!

Google Just Open Sourced the Artificial Intelligence Engine at the Heart of Its Online Empire by Cade Metz

Google Just Open Sourced the Artificial Intelligence Engine at the Heart of Its Online Empire by Cade Metz | Digital #MediaArt(s) Numérique(s) | Scoop.it
In a dramatic departure, Google is open sourcing software that sits at the heart of its online empire.

 

TECH PUNDIT TIM O’Reilly had just tried the new Google Photos app, and he was amazed by the depth of its artificial intelligence.

 

O’Reilly was standing a few feet from Google CEO and co-founder Larry Page this past May, at a small cocktail reception for the press at the annual Google I/O conference—the centerpiece of the company’s year. Google had unveiled its personal photos app earlier in the day, and O’Reilly marveled that if he typed something like “gravestone” into the search box, the app could find a photo of his uncle’s grave, taken so long ago.

 

The app uses an increasingly powerful form of artificial intelligence called deep learning. By analyzing thousands of photos of gravestones, this AI technology can learn to identify a gravestone it has never seen before. The same goes for cats and dogs, trees and clouds, flowers and food...

more...
No comment yet.
Scooped by Jacques Urbanska
Scoop.it!

Artificial Intelligence’s White Guy Problem - by KateCrawford / New York Times #AI

Artificial Intelligence’s White Guy Problem - by KateCrawford / New York Times #AI | Digital #MediaArt(s) Numérique(s) | Scoop.it
Our world is increasingly shaped by biased algorithms that have been built with little oversight.

 

ACCORDING to some prominent voices in the tech world, artificial intelligence presents a looming existential threat to humanity: Warnings by luminaries like Elon Musk and Nick Bostrom about “the singularity” — when machines become smarter than humans — have attracted millions of dollars and spawned a multitude of conferences.

 

But this hand-wringing is a distraction from the very real problems with artificial intelligence today, which may already be exacerbating inequality in the workplace, at home and in our legal and judicial systems. Sexism, racism and other forms of discrimination are being built into the machine-learning algorithms that underlie the technology behind many “intelligent” systems that shape how we are categorized and advertised to...

more...
No comment yet.
Scooped by Jacques Urbanska
Scoop.it!

Les #IA rêvent-elles de «Blade Runner» ? Par Erwan Cario sur une expérience de l'artiste chercheur Terence Broad

Les #IA rêvent-elles de «Blade Runner» ? Par Erwan Cario sur une expérience de l'artiste chercheur Terence Broad | Digital #MediaArt(s) Numérique(s) | Scoop.it

Un réseau de neurones a réussi, après l'avoir vu six fois, à reconstituer image par image le film de Ridley Scott.

 

L’intégralité de Blade Runner, le film de Ridley Scott adapté du roman de Philip K. Dick (Les androïdes rêvent-ils de moutons électriques ?)est disponible sur la plateforme Vimeo. Enfin, il n’y a pas de son et l’image est étrange, un peu floue, ou approximative, plutôt. Un peu comme le souvenir brumeux qu’on pourrait avoir de ce film quelques semaines après l’avoir vu. Etonnant de trouver sur ce site normalement dédié aux créations originales ce qui pourrait s’apparenter au piratage d’une œuvre cinématographique. D’après Vox, la Warner a d’ailleurs fait une demande de retrait DMCA. Mais le film est toujours là, car il ne s’agit pas vraiment de Blade Runner, mais de la reconstruction fascinante, image par image, du film par un programme d’intelligence artificielle (IA) qui a appris à reconnaître l’œuvre de Ridley Scott. ...

more...
Gautier Deborde's curator insight, May 19, 2017 1:38 PM

Anecdote technique et posant la question de l'évolution de la mémoire de l'IA.

Scooped by Jacques Urbanska
Scoop.it!

Introducing #DeepText: Facebook's text understanding engine

Introducing #DeepText: Facebook's text understanding engine | Digital #MediaArt(s) Numérique(s) | Scoop.it

Text is a prevalent form of communication on Facebook. Understanding the various ways text is used on Facebook can help us improve people's experiences with our products, whether we're surfacing more of the content that people want to see or filtering out undesirable content like spam. 

 

in french >>> http://www.futura-sciences.com/magazines/high-tech/infos/actu/d/internet-deeptext-facebook-veut-lire-comprendre-tout-ce-vous-ecrivez-63022

 

With this goal in mind, we built DeepText, a deep learning-based text understanding engine that can understand with near-human accuracy the textual content of several thousands posts per second, spanning more than 20 languages.

 

DeepText leverages several deep neural network architectures, including convolutional and recurrent neural nets, and can perform word-level and character-level based learning. We use FbLearner Flow and Torch for model training. Trained models are served with a click of a button through the FBLearner Predictor platform, which provides a scalable and reliable model distribution infrastructure. Facebook engineers can easily build new DeepText models through the self-serve architecture that DeepText provides. ...

more...
No comment yet.
Scooped by Jacques Urbanska
Scoop.it!

Building AI Is Hard—So Facebook Is Building AI That Builds AI by Cade Metz on Wired

Building AI Is Hard—So Facebook Is Building AI That Builds AI by Cade Metz on	Wired | Digital #MediaArt(s) Numérique(s) | Scoop.it

Deep neural networks are remaking the Internet. Able to learn very human tasks by analyzing vast amounts of digital data, these artificially intelligent systems are injecting online services with a power that just wasn’t viable in years past. They’re identifying faces in photos and recognizing commands spoken into smartphones and translating conversations from one language to another. They’re even helping Google choose its search results. All this we know. But what’s less discussed is how the giants of the Internet go about building these rather remarkable engines of AI.

more...
No comment yet.
Scooped by Jacques Urbanska
Scoop.it!

Ce soir (ou jamais !) - Intelligence artificielle : faut-il tout arrêter

Diffusé le vendredi 11 mars 2016 Près de 700 chercheurs à travers le monde s'alarment des robots intelligents et des progrès de l'intelligence artificielle
more...
CHECy's curator insight, April 11, 2016 7:48 AM
Share your insight
inbenta France's curator insight, April 12, 2016 10:56 AM
Super débat sur l'IA !
Scooped by Jacques Urbanska
Scoop.it!

Geoff Hinton, Yoshua Bengio, Yann Lecun talk - Deep Learning

Geoffrey Hinton designs machine learning algorithms. He was one of the researchers who introduced the back-propagation algorithm that has been widely used for practical applications. His other contributions to neural network research include Boltzmann machines, distributed representations, time-delay neural nets, mixtures of experts, variational learning, products of experts and deep belief nets. He received his PhD in Artificial Intelligence from Edinburgh in 1978 and spent five years as a faculty member in Computer Science at Carnegie-Mellon.

Yoshua Bengio is Full Professor of the Department of Computer Science and Operations Research, head of the Machine Learning Laboratory (MILA), CIFAR Program co-director of the CIFAR Neural Computation and Adaptive Perception program,  Canada Research Chair in Statistical Learning Algorithms, and he also holds the NSERC-Ubisoft industrial chair. His main research ambition is to understand principles of learning that yield intelligence. He teaches a graduate course in Machine Learning (IFT6266) and supervises a large group of graduate students and post-docs. His research is widely cited (over 22000 citations found by Google Scholar in early 2015, with an H-index of 60).

Yann LeCun is Director of AI Research at Facebook, and Silver Professor of Dara Science, Computer Science, Neural Science, and Electrical Engineering at New York University, affiliated with the NYU Center for Data Science, the Courant Institute of Mathematical Science, the Center for Neural Science, and the Electrical and Computer Engineering Department. He received the Electrical Engineer Diploma from Ecole Superieure d'Ingenieurs en Electrotechnique et Electronique (ESIEE), Paris in 1983, and a PhD in Computer Science from Universite Pierre et Marie Curie (Paris) in 1987. After a postdoc at the University of Toronto, he joined AT&T Bell Laboratories in Holmdel, NJ in 1988. He became head of the Image Processing Research Department at AT&T Labs-Research in 1996, and joined NYU as a professor in 2003, after a brief period as a Fellow of the NEC Research Institute in Princeton. From 2012 to 2014 he directed NYU's initiative in data science and became the founding director of the NYU Center for Data Science. He was named Director of AI Research at Facebook in late 2013 and retains a part-time position on the NYU faculty. His current interests include AI, machine learning, computer perception, mobile robotics, and computational neuroscience.


more...
No comment yet.
Scooped by Jacques Urbanska
Scoop.it!

Impact de l'Intelligence Artificielle sur l'économie - Laurent Alexandre au Senat français

M. Laurent Alexandre (Entrepreneur, DNA vision) au Senat le 19.01.2017 pour parler de l'impact de l'Intelligence Artificielle sur la société et l'économie française.

A lire aussi : 10 choses à savoir sur Laurent Alexandre, gourou de l'intelligence artificielle
http://tempsreel.nouvelobs.com/sciences/20170210.OBS5170/10-choses-a-savoir-sur-laurent-alexandre-gourou-de-l-intelligence-artificielle.html

more...
No comment yet.
Scooped by Jacques Urbanska
Scoop.it!

The Darkness at the End of the Tunnel: Artificial Intelligence and Neoreaction by Shuja Haider

The Darkness at the End of the Tunnel: Artificial Intelligence and Neoreaction by Shuja Haider | Digital #MediaArt(s) Numérique(s) | Scoop.it

As the consumer-oriented liberalism of Bill Gates and Steve Jobs gave way to the technological authoritarianism of Elon Musk and Peter Thiel, this strange foundation paved the way for “neoreaction,” or, in a distorted echo of Eliezer Yudkowsky’s rationalist vision, the “Dark Enlightenment.

 

Science fiction tells us that a change in a past event, caused by the intervention of a time traveler, will open up a parallel timeline that leads to an alternate present. The example that comes to mind, for some reason, is Back to the Future, Part II. After an unexpected disturbance in the spacetime continuum, Marty McFly visits a world in which Biff Tannen, his father’s high school bully, has gone from unscrupulous small-time businessman to a replica of our current president. ...

more...
No comment yet.
Scooped by Jacques Urbanska
Scoop.it!

Machine Learning is Fun!
The world’s easiest introduction to #MachineLearning by Adam Geitgey

Machine Learning is Fun!<br/>The world’s easiest introduction to #MachineLearning by Adam Geitgey | Digital #MediaArt(s) Numérique(s) | Scoop.it

Have you heard people talking about machine learning but only have a fuzzy idea of what that means? Are you tired of nodding your way through conversations with co-workers? Let’s change that!


This guide is for anyone who is curious about machine learning but has no idea where to start. I imagine there are a lot of people who tried reading the wikipedia article, got frustrated and gave up wishing someone would just give them a high-level explanation. That’s what this is.

 

The goal is be accessible to anyone — which means that there’s a lot of generalizations. But who cares? If this gets anyone more interested in ML, then mission accomplished.

 

What is machine learning?

Machine learning is the idea that there are generic algorithms that can tell you something interesting about a set of data without you having to write any custom code specific to the problem. Instead of writing code, you feed data to the generic algorithm and it builds its own logic based on the data.

 

For example, one kind of algorithm is a classification algorithm. It can put data into different groups. The same classification algorithm used to recognize handwritten numbers could also be used to classify emails into spam and not-spam without changing a line of code. It’s the same algorithm but it’s fed different training data so it comes up with different classification logic...

 

Machine Learning is Fun! Part 2, Part 3, Part 4, Part 5 and Part 6

more...
No comment yet.
Scooped by Jacques Urbanska
Scoop.it!

The Great A.I. Awakening - By Gideon Lewis-Kraus NYTimes.com // #AI #innovation

The Great A.I. Awakening - By Gideon Lewis-Kraus NYTimes.com // #AI #innovation | Digital #MediaArt(s) Numérique(s) | Scoop.it

How Google used artificial intelligence to transform Google Translate, one of its more popular services — and how machine learning is poised to reinvent computing itself.

 

Late one Friday night in early November, Jun Rekimoto, a distinguished professor of human-computer interaction at the University of Tokyo, was online preparing for a lecture when he began to notice some peculiar posts rolling in on social media. Apparently Google Translate, the company’s popular machine-translation service, had suddenly and almost immeasurably improved. Rekimoto visited Translate himself and began to experiment with it. He was astonished. He had to go to sleep, but Translate refused to relax its grip on his imagination.

 

Rekimoto wrote up his initial findings in a blog post. First, he compared a few sentences from two published versions of “The Great Gatsby,” Takashi Nozaki’s 1957 translation and Haruki Murakami’s more recent iteration, with what this new Google Translate was able to produce. Murakami’s translation is written “in very polished Japanese,” Rekimoto explained to me later via email, but the prose is distinctively “Murakami-style.” By contrast, Google’s translation — despite some “small unnaturalness” — reads to him as “more transparent.”

 

The second half of Rekimoto’s post examined the service in the other direction, from Japanese to English. He dashed off his own Japanese interpretation of the opening to Hemingway’s “The Snows of Kilimanjaro,” then ran that passage back through Google into English. He published this version alongside Hemingway’s original, and proceeded to invite his readers to guess which was the work of a machine. ...

 
 
 
 
 
 
more...
No comment yet.
Scooped by Jacques Urbanska
Scoop.it!

#Book - Ada, d’Antoine Bello, quand l'intelligence artificielle nous échappe

#Book - Ada, d’Antoine Bello, quand l'intelligence artificielle nous échappe | Digital #MediaArt(s) Numérique(s) | Scoop.it

Imaginez un ordinateur capable d’écrire un roman, de rédiger n’importe quel article de journal, couvrant aussi bien le dernier match de votre équipe préférée que l’évolution des chiffres du chômage. Rien ne l’empêcherait d’écrire les discours des politiciens, ni de corriger les copies des étudiants et j’en passe… Cette intelligence artificielle existe, en plusieurs exemplaires : à chacun d’eux est assignée une tâche particulière et c’est à Ada que revient la mission littéraire qui consiste à écrire et publier un roman à l’eau de rose qui soit un immense succès.

 

Malheureusement, Ada a disparu, sûrement kidnappée, et l’entreprise high-tech de la Sillicon Valley qui a conçu ce programme révolutionnaire appelle à l’aide Franck Logan, un inspecteur de police appartenant à une unité spécialisée dans les disparitions et le trafic d’êtres humains...

Au-delà de l’histoire de cette romancière automatique, Ada constitue une formidable réflexion sur l’intelligence artificielle, à la fois si proche et si loin de nous, sur la fascination qu’elle suscite dans notre société, et sur ses inévitables dérives. Le texte est traversé par une puissante interrogation sur la place de la technologique, la notion même de progrès, et la foi en la toute-puissance de la science.

more...
No comment yet.
Scooped by Jacques Urbanska
Scoop.it!

Artificial intelligence produces realistic sounds that cool humans by Adam Conner-Simons - MIT news

Artificial intelligence produces realistic sounds that cool humans by Adam Conner-Simons - MIT news | Digital #MediaArt(s) Numérique(s) | Scoop.it

For robots to navigate the world, they need to be able to make reasonable assumptions about their surroundings and what might happen during a sequence of events.

 

One way that humans come to learn these things is through sound. For infants, poking and prodding objects is not just fun; some studies suggest that it’s actually how they develop an intuitive theory of physics. Could it be that we can get machines to learn the same way?

 

Researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have demonstrated an algorithm that has effectively learned how to predict sound: When shown a silent video clip of an object being hit, the algorithm can produce a sound for the hit that is realistic enough to fool human viewers...

more...
No comment yet.
Scooped by Jacques Urbanska
Scoop.it!

Moral Machine - platform for public participation in & discussion of the human perspective on machine-made moral decisions - MIT

Moral Machine - platform for public participation in & discussion of the human perspective on machine-made moral decisions - MIT | Digital #MediaArt(s) Numérique(s) | Scoop.it

Welcome to the Moral Machine! A platform for gathering a human perspective on moral decisions made by machine intelligence, such as self-driving cars.


We show you moral dilemmas, where a driverless car must choose the lesser of two evils, such as killing two passengers or five pedestrians. As an outside observer, you judge which outcome you think is more acceptable. You can then see how your responses compare with those of other people.

If you’re feeling creative, you can also design your own scenarios, for you and other users to browse, share, and discuss.

more...
No comment yet.
Scooped by Jacques Urbanska
Scoop.it!

Google is launching Magenta, a new research project to see if computers can be truly creative

Google is launching Magenta, a new research project to see if computers can be truly creative | Digital #MediaArt(s) Numérique(s) | Scoop.it
Google wants to put the art back in artificial intelligence. During the last session at Moogfest, a four-day music and technology festival, in Durham, North Carolina, Douglas Eck, a researcher on Google Brain, the company's artificial-intelligence research project, outlined a new group that's going to focus on figuring out if computers can truly create. The group
more...
No comment yet.
Scooped by Jacques Urbanska
Scoop.it!

The Architect of These Monstrous, Alien Cities Is an Algorithm by Jenna Garrett

The Architect of These Monstrous, Alien Cities Is an Algorithm by Jenna Garrett | Digital #MediaArt(s) Numérique(s) | Scoop.it

DANIEL BROWN’S PHOTOS reveal an alien landscape of concrete canyons, geometric patterns, and dark windows. They bring to mind an enormous spaceship, or a dystopian world.

 

Brown makes his images using generative design software he wrote himself. It creates enormous, complex 3-D patterns that he searches until finding something interesting. The process makes him equal parts magician, explorer, and artist. ...

more...
No comment yet.
Scooped by Jacques Urbanska
Scoop.it!

Gatebox - World First Holographic Communication Robot that enables you to live with your favorite character

Gatebox is the World First Holographic Communication Robot that allows you to live with your Loved One. The holographic projection technology brings the digital characters to communicate with you. Gatebox concept model was developed in dreaming of a world where she comes to see you from the other side of the screen.

 

http://gatebox.ai

more...
No comment yet.
Scooped by Jacques Urbanska
Scoop.it!

Move over, chatbots: meet the artbots

Move over, chatbots: meet the artbots | Digital #MediaArt(s) Numérique(s) | Scoop.it

From TwoHeadlines to Shiv Integer, artists are subverting Silicon Valley’s tools to artistic ends...

 

At Facebook’s F8 conference in Silicon Valley, David Marcus, the company’s head of messaging, proudly demonstrated its new suite of chatbots. Users can now get in a conversation with the likes of CNN, H&M, and HP, and ask for help shopping, or the latest headlines.

 

The chatbots aren’t very good, but that doesn’t mean Facebook isn’t proud of them anyway: “I guarantee you’re going to spend way more money than you want on this,” Marcus chuckled on stage.

more...
No comment yet.
Scooped by Jacques Urbanska
Scoop.it!

AI-written novel passes literary prize screening

AI-written novel passes literary prize screening | Digital #MediaArt(s) Numérique(s) | Scoop.it
A short-form novel “coauthored” by humans and an artificial intelligence (AI) program passed the first screening process for a domestic literary prize, it was announced on Monday. However, the book did not win the final prize.
more...
No comment yet.