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10 Scariest A.I. Robot Moments. Dans quelques années, vos livres préférés auront peut-être été écrits par des robots. Les robots pourront-ils bientôt remplacer les écrivains ?

Dans quelques années, vos livres préférés auront peut-être été écrits par des robots

C’est sur cette question que se sont penchés plusieurs chercheurs depuis quelques années. DGS vous propose de découvrir quelques projets fascinants, qui pourraient bientôt révolutionner la littérature traditionnelle.

Genetic algorithm (GA)

Craig W. Reynolds (AI) My interests center around using procedural models (computer programs) to simulate complex natural phenomenon.

Craig W. Reynolds (AI)

These models can aide scientific understanding of the natural system. They also allow us to recreate the phenomenon and control it for use in animation, games and the arts. Much of my work involves writing software to simulate various types of human and animal behavior. These programs control the actions of autonomous characters in virtual worlds. I started by simulating bird flocks and related group behaviors.

I am also interested in using evolutionary computation to design procedural models, such as for behavioral control and texture synthesis. I work as a software engineer at RightHook in San Jose, California. IBM produces first working chips modeled on the human brain. IBM has been shipping computers for more than 65 years, and it is finally on the verge of creating a true electronic brain.

IBM produces first working chips modeled on the human brain

Big Blue is announcing today that it, along with four universities and the Defense Advanced Research Projects Agency (DARPA), have created the basic design of an experimental computer chip that emulates the way the brain processes information. IBM’s so-called cognitive computing chips could one day simulate and emulate the brain’s ability to sense, perceive, interact and recognize — all tasks that humans can currently do much better than computers can. Dharmendra Modha (pictured below right) is the principal investigator of the DARPA project, called Synapse (Systems of Neuromorphic Adaptive Plastic Scalable Electronics, or SyNAPSE). He is also a researcher at the IBM Almaden Research Center in San Jose, Calif. We wrote about the project when IBM announced the project in November, 2008 and again when it hit its first milestone in November, 2009. The Dawn of Killer Robots (Full Length)

"Big data" / Data science

Deep Learning (AI) President Barack Obama on What AI Means for National Security. Brighterion - Management Team. Following his distinguished career of service in Her Majesty’s Royal Air Force and at Scotland Yard, Raymond Kendall joined INTERPOL in 1971.

Brighterion - Management Team

From 1985 until 2001, he served as three-time Secretary General of INTERPOL from its headquarters in Lyon, France. In addition to his leadership fulfilling the traditional mission of INTERPOL, Mr. Kendall initiated joint efforts globally with the private sector to address the growing threat of cybercrime and promoted the need for international cooperation to prevent abuses on the web. An honors degree recipient from Oxford University, Mr. Kendall has received awards from the governments of France, Spain, Finland, United States, Chile, Peru and Russia.

Brighterion. Smart Agents Are AI's DNA — Here's Why. Share Tweet Print Email Inspiration comes from anywhere and everywhere, and that goes for digital innovation in payments and commerce.

Smart Agents Are AI's DNA — Here's Why

Just ask Akli Adjaoute, CEO of Brighterion (a Mastercard company), who recently spoke with PYMNTS’ Karen Webster about the rise of smart agents, a form of artificial intelligence designed to bring more fraud prevention and customer service to financial institutions and other digital players. As Adjaoute told Webster during a recent interview centered around the launch of a new PYMNTS-Brighterion report entitled “The AI Innovation Playbook: Moving Toward a Future of Smart Agent Adoption,” his background in medical science and his service in the French military resulted in his interest and work on smart agents.

Simply put, smart agents is technology capable of unsupervised learning that can adapt to complex ecosystems and can be assigned to perform particular functions. Deux chercheurs testent virtuellement la loi El Khomri sur le marché du travail. Les Systèmes Multi-Agents. Multi-agent system. Despite considerable overlap, a multi-agent system is not always the same as an agent-based model (ABM).

Multi-agent system

The goal of an ABM is to search for explanatory insight into the collective behavior of agents (which don't necessarily need to be "intelligent") obeying simple rules, typically in natural systems, rather than in solving specific practical or engineering problems. The terminology of ABM tends to be used more often in the sciences, and MAS in engineering and technology.[1] Applications where multi-agent systems research may deliver an appropriate approach include online trading,[2] disaster response[3][4] and social structure modelling.[5] Concept[edit] Système multi-agents. Multi-agent system. Jean-Daniel Kant – The Conversation. Bienvenue sur la page de Jean-Daniel Kant. Last News Nouveau Site WorkSim Simulation du marché du travail New website WorkSim project (in French for the moment) Habilitation Thesis : "Agent-based approaches to the study of human behaviors" (pdf) Welcome to my homepage !

Bienvenue sur la page de Jean-Daniel Kant

I am currently an associate professor with Habilitation (HDR) at the University Pierre et Marie Curie (UPMC) in Paris, ranked first science University in France. I work at its Computer Science Laboratory (LIP6), one of the leaders in computer science research in France, within the SMA team, devoted to Multi-Agent Systems (MAS). I am interested in modelling and simulation of complex systems, and more particularly to the contributions of Information Technologies in the Humanities and Social Sciences. I am also the co-founder and co-leader of MAGECO, the first French network of research on Agent-Based Computational Economics.

Projet WorkSim - simulation marche du travail. Après l’intelligence artificielle, l’intelligence « étendue » Intervenant dans un débat en ligne du New York Times autour des enjeux de l’IA, Joi Ito (@joi), le directeur du Media Lab du MIT, expliquait que même très bien intentionné, l’usage des technologies peut mal tourner. « La majeure partie de la recherche en IA se concentre sur l’apprentissage profond : des ingénieurs « entraînent » des machines pour augmenter l’intelligence collective de nos gouvernements, de nos marchés et de nos sociétés ».

Après l’intelligence artificielle, l’intelligence « étendue »

Les Rendez-vous du Futur - Paul Jorion. Une machine peut-elle créer de la musique ? Intelligence Artificielle : Au lieu De Supprimer Des Emplois, L'IA en Crée. Robots dance for the audience on the expo.

Intelligence Artificielle : Au lieu De Supprimer Des Emplois, L'IA en Crée

On Jul. 8th, | BEIJING, CHINA - 2017/07/08: Robots dance for the audience on the expo. On Jul. 8th, Beijing International Consumer electronics Expo was held in Beijing China National Convention Center. AlphaGo Zero : la nouvelle version de l’IA de Go se suffit à elle même. AlphaGo continue sur sa lancée : l’intelligence artificielle développée par Deepmind, la branche intelligence artificielle de Google, est parvenue à se surpasser elle-même grâce au développement d’une nouvelle version baptisée AlphaGo Zero.

AlphaGo Zero : la nouvelle version de l’IA de Go se suffit à elle même

Dans un post de blog, l’équipe chargée du développement du programme présente les résultats de sa nouvelle version et ceux-ci sont éloquents : AlphaGo Zero est parvenu à dominer la version précédente de l’IA, qui avait pourtant damé le pion aux plus grands champions humains de Go en 2016. Cette nouvelle version d’AlphaGo est décrite avec plus de détails dans un article publié par la revue scientifique Science. IA, des robots pour mettre de l’ordre dans le chaos de l’info. Vous avez une formation de journaliste. Pouvez-vous nous retracer votre parcours et ce qui vous amené à développer cette appétence pour l’innovation digitale et les médias ? Benoît Raphaël : J’ai commencé mon parcours dans les radios locales et la presse quotidienne régionale, Le Dauphiné Libéré...

Ensuite, j’ai créé un certain nombre de médias participatifs en ligne innovants, comme Le Post.fr, pour Le Monde. Pour profiter de la technologie, faisons la disparaître. Rand Hindi - Comment j'ai fait perdre son job à mon père - Intelligence artificielle #convapm17. Que devient l’IA symbolique ?

IA & Meeting

Akli Adjaoute (AI) AI oops. De l'ombre à la lumière // Luc Julia - Co-créateur de Siri. Rencontre avec Luc Julia, l’IA n’existe pas !⎜ORLM-363. Conférence - L'intelligence artificielle n'existe pas. Luc Julia : l'intelligence artificielle n'existe pas ? "L'intelligence artificielle n'existe pas" : interview de Luc Julia, le cocréateur de Siri. - Accueil. Conférence inspirante avec Bruno Maisonnier : L'Organic AI. Another Brain. Will the next generation of AI fly us to the stars? Bruno Maisonnier. Bruno Maisonnier (Aldebaran, Another Brain) : Approche différente de l'intelligence artificielle. Passer d'une IA qui APPREND à une IA qui COMPREND ?

Ai ethic

How to Move Beyond a Monolithic Data Lake to a Distributed Data Mesh. Becoming a data-driven organization remains one of the top strategic goals of many companies I work with. My clients are well aware of the benefits of becoming intelligently empowered: providing the best customer experience based on data and hyper-personalization; reducing operational costs and time through data-driven optimizations; and giving employees super powers with trend analysis and business intelligence.

They have been investing heavily in building enablers such as data and intelligence platforms. Despite increasing effort and investment in building such enabling platforms, the organizations find the results middling. I agree that organizations face a multi-faceted complexity in transforming to become data-driven; migrating from decades of legacy systems, resistance of legacy culture to rely on data, and ever competing business priorities.

However what I would like to share with you is an architectural perspective that underpins the failure of many data platform initiatives. Data Mesh Principles and Logical Architecture. The original writeup, How to Move Beyond a Monolithic Data Lake to a Distributed Data Mesh - which I encourage you to read before joining me back here - empathized with today’s pain points of architectural and organizational challenges in order to become data-driven, use data to compete, or use data at scale to drive value. It offered an alternative perspective which since has captured many organizations’ attention, and given hope for a different future. While the original writeup describes the approach, it leaves many details of the design and implementation to one’s imagination.

I have no intention of being too prescriptive in this article, and kill the imagination and creativity around data mesh implementation. However I think it’s only responsible to clarify the architectural aspects of data mesh as a stepping stone to move the paradigm forward. This article is written with the intention of a follow up. The great divide of data. How to Build a Foundation for Data Mesh: A Principled Approach (Part II) - Datanova 2021. Introduction to Data Mesh: A Paradigm Shift in Analytical Data Management (Part I) - Datanova 2021.