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September 30 2013

Faut-il parier sur l'intelligence du lecteur ? - La République Des Livres par Pierre Assouline

Faut-il parier sur l’intelligence du lecteur ? - La République Des Livres par Pierre Assouline
http://larepubliquedeslivres.com/faut-il-parier-sur-lintelligence-du-lecteur/#comment-105208

http://larepubliquedeslivres.com/wp-content/uploads/2013/09/vargas.jpg

Faut-il parier sur l’intelligence du lecteur ?
LE 30 SEPTEMBRE 2013
Mais oui, c’est possible : des traducteurs peuvent se réunir trois jours durant sans qu’il soit question de éternel dilemme « Fidélité ou trahison « , ou de « L’intraductibilité de la poésie », et sans que s’affrontent « ciblistes » et « sourcistes ». Ca change ! C’était ce week-end au Moulin de la Tuilerie sis à Gif-sur-Yvette (Essonne), la première édition du Festival VO-VF organisé par des libraires Sylvie Melchiori (La Vagabonde à Versailles), Hélène Pourquié et Pierre Morize (Liragif à Gif-sur-Yvette), avec une équipe de bénévoles constituée de leurs plus fidèles clients. Songez qu’à la table commune, parmi ceux qui avaient mis la main à la pâte, c’est le cas de le dire, un astrophysicien avait roulé la semoule du couscous du dîner samedi, ce qui ne fut certainement pas étranger à sa légèreté aérienne. Trois jours durant, si des traducteurs étaient bien à la tribune, ils étaient minoritaires dans le public constitué pour l’essentiel d’amateurs de littérature étrangère. A glaner des échanges d’un débat à l’autre des préoccupations communes surgissaient autour de quelques thèmes.

Faut-il parier sur l’intelligence du lecteur ? Si c’est un problème pour l’auteur, ca l’est plus encore pour un traducteur. Alors vous imaginez si les deux se superposent. Un double pari. L’américaniste Claro avait déjà donné le ton la veille sur son blog Le Clavier cannibale par un billet consacré à l’angoisse du traducteur au moment de la note en bas de page : la mettre ou pas ? Il esquissait la remarque à propos d’un roman turc dans lequel sa consoeur se demandait s’il fallait traduire simit par une note indiquant qu’il s’agit d’un petit pain en couronne couvert de graines de sesame, ou s’abstenir et faire confiance à sa compétence ? Dès lors qu’il ne s’agit pas d’un hapax, et que le contexte peut à plusieurs reprises l’expliquer, pourquoi pas ?

Johan-Frédérik El-Guedj, fut confronté à un problème semblable en traduisant de l’anglais Le seigneur de Bombay écrit en hindi par Vikram Chandra qui truffa sa langue d’argot pendjabi. Perplexe, le traducteur, qui n’hésita pas à trouver des mots que les Indiens souvent ignorent, usa alternativement de deux solutions : soit glisser une rapide périphrase au sein de la phrase, soit ne pas traduire et laisser le mot original en italiques : « Grâce à sa récurrence, le lecteur finit par le comprendre. Il faut parier sur son intelligence ». On peut en tout cas parier sur celle du traducteur qui, pour s’approprier le lexique argotique indien, s’est inspiré du lexique de cooptation mafieuse des films de Martin Scorcese, car les logiques claniques y sont les mêmes. A noter que rien ne vieillit comme l’argot, tous les traducteurs présents en convinrent ; c’est même ce qui date très vite un texte, lequel vieillit mal à cause de cette concession à l’air du temps. Cela dit, bien malin sera le lecteur qui décèlera dans trois chapitres du Seigneur de Bombay des références cryptées au Bruit et la fureur de Faulkner…

#littérature
#lecteur
#intelligence
#traducteurs
#titre

August 29 2013

While the dishonest and the stupid are attempting to railroad everyone into military endeavours…

While the dishonest and the stupid are attempting to railroad everyone into military endeavours devoid of public benefit, let us remember that France stood out of the Iraq war because it had independent orbital imaging capabilities showing that the WMD claims were nonsense... Meanwhile, the USA took for a ride all the blind ones who had decided that US imagery was cheaper and good enough.

Military sovereignty is also about being able to remain peaceful - let us remember that next time the time for budget cuts come: http://fistfulofeuros.net/afoe/spies-for-europe

–----------------------------------------------------------

The original statement is in this Ken Silverstein piece (http://harpers.org/sb-creating-th-1149534425.html):

They say everyone else was wrong,” said this former official, “but we conditioned them to be wrong. We spend [tens of billions of dollars per year] on signals intelligence and when we reach a conclusion, the people who spend less than that tend to believe us. They weren’t wrong, they chose to believe us. The British, Germans, and Italians don’t have all those overhead assets, so they rely on us. Historically they have been well-served, so they believe us when we tell them the earth is round. The French have their own assets—and guess what? They didn’t go with us

Guilhem Penent, of France’s IFRI and IRSEM thinktanks, writes in the Space Review (http://www.thespacereview.com/article/2340/1) as follows:

Regarding outer space, France’s main objective is to perpetuate its autonomy and national sovereignty. As sovereignty is the state of determining itself based on its own will without depending on other nations, satellites are, first and foremost, the guarantee of France’s autonomy in assessment and thereby in decision-making

The decision not to follow the US in 2003 was thus taken by then President Jacques Chirac in accordance with intelligence based for the most part on Earth-imaging satellite HELIOS 1, whose findings were in contradiction which was being said at the UN Security Council. When the war in South Ossetia broke out in 2008 between Russia and Georgia, then President Nicolas Sarkozy, as chair of the Presidency of the Council of the European Union (EU), used images provided by HELIOS 1 and HELIOS 2 to deny Russia’s allegations about the withdrawal of its troops when those troops were actually progressing southward.

This is the first public confirmation, I believe, that the French did in fact stand out of the Iraq war because HELIOS imagery showed that the WMD claims were nonsense

#WMD #Iraq #Helios #France #war #USA #intelligence #Chirac

January 11 2013

Defining the industrial Internet

We’ve been collecting threads on what the industrial Internet means since last fall. More case studies, company profiles and interviews will follow, but here’s how I’m thinking about the framework of the industrial Internet concept. This will undoubtedly continue to evolve as I hear from more people who work in the area and from our brilliant readers.

The crucial feature of the industrial Internet is that it installs intelligence above the level of individual machines — enabling remote control, optimization at the level of the entire system, and sophisticated machine-learning algorithms that can work extremely accurately because they take into account vast quantities of data generated by large systems of machines as well as the external context of every individual machine. Additionally, it can link systems together end-to-end — for instance, integrating railroad routing systems with retailer inventory systems in order to anticipate deliveries accurately.

In other words, it’ll look a lot like the Internet — bringing industry into a new era of what my colleague Roger Magoulas calls “promiscuous connectivity.”

Optimization becomes more efficient as the size of the system being optimized grows (in theory). Your software can take into account lots of machines, learning from a much larger training set and then optimizing both within the machine and for the group of machines working together. Think of a wind farm. There are certain optimizations you need to make at the machine level: the turbine turns itself to face into the wind, the blades adjust themselves through every cycle in order to account for flex and compression, and the machine shuts down during periods of dangerously high wind.

System-wide optimization means that when you can operate each turbine in a way that minimizes air disruption to other turbines (these things create wake, just like an airplane, that can disrupt the operation of nearby turbines). When you need to increase or decrease power output across the whole farm, you can do it across lots of machines in a way that minimizes wear (i.e., curtail each machine by 5% or cut off 5% of your machines, or something in between depending on differential output and the impact of different speeds on machine wear). And by gathering data from thousands of machines, you can develop highly-detailed optimization plans.

By tying machines together, the industrial Internet will encourage “platformization.” Cars have several control systems, and until very recently they’ve been linked by point-to-point connections: when you move the windshield-wiper lever, it actuates a switch that’s connected to a small PLC that operates the windshield wipers. The brake pedal is part of the chassis-control system, and it’s connected by cable or hydraulics to the brake pads, with an electronic assist somewhere in the middle. The navigation system and radio are part of the same telematics platform, but that platform is not linked to, say, the steering wheel.

The car as enabled by the industrial Internet will be a platform — a bus, in the computing sense — built by the car manufacturer, with other systems communicating with each other through the platform. The brake pedal is an actuator that sends a “brake” signal to the car’s brake controller. The navigation system is able to operate the steering wheel and has access to the same brake controller. Some of these systems will be driven by third-party-built apps that sit on top of the platform.

This will take some time to happen in cars because it takes 10 or 15 years to renew the American auto fleet, because cars are maintained by a vast network of independent mechanics that need change to happen slowly, and because car development works incrementally.

But it’s already happening in commercial aircraft, which often come from clean-sheet designs (as with the Boeing 787 and Airbus A350), and which are maintained under very different circumstances than passenger cars. In Bombardier’s forthcoming C-series midsize jet, for instance, the jet engines do nothing but propel the plane and generate electricity (they don’t generate hydraulic pressure or compress air for the cabin; these are handled by electrically-powered compressors). The plane acts as a giant hardware platform on which all sorts of other systems sit: the landing-gear switch communicates with the landing gear through the aircraft’s bus, rather than by direct connection to the landing gear’s PLC.

The security implications of this sort of integration — in contrast to effectively air-gapped isolation of systems — are obvious. The industrial Internet will need its own specially-developed security mechanisms, which I’ll look into in another post.

The industrial Internet makes it much easier to deploy and harvest data from sensors, which goes back to the system-wide intelligence point above. If you’re operating a wind farm, it’s useful to have wind-speed sensors distributed across the country in order to predict and anticipate wind speeds and directions. And because you’re operating machine-learning algorithms at the system-wide level, you’re able to work large-scale sensor datasets into your system-wide optimization.

That, in turn, will help the industrial Internet take in previously-uncaptured data that’s made newly useful. Venkatesh Prasad, from Ford, pointed out to me that the windshield wipers in your car are a sort of human-actuated rain API. When you turn on your wipers, you’re acting as a sensor — you see water on your windshield, in a quantity sufficient to cause you to want your wipers on, and you set your wipers to a level that’s appropriate to the amount of water on your windshield.

In isolation, all you’re doing is turning on your windshield wipers. But if your car is networked, then it can send a signal to a cloud-based rain-detection service that geocorrelates your car with nearby cars whose wipers are on and makes an assumption about the presence of rain in the area and its intensity. That service could then turn on wipers in other cars nearby or do more sophisticated things — anything from turning on their headlights to adjusting the assumptions that self-driving cars make about road adhesion.

This is an evolving conversation, and I want to hear from readers. What should be included in the definition of the industrial Internet? What examples define, for you, the boundaries of the field?


This is a post in our industrial Internet series, an ongoing exploration of big machines and big data. The series is produced as part of a collaboration between O’Reilly and GE.

Related

Defining the industrial Internet

We’ve been collecting threads on what the industrial Internet means since last fall. More case studies, company profiles and interviews will follow, but here’s how I’m thinking about the framework of the industrial Internet concept. This will undoubtedly continue to evolve as I hear from more people who work in the area and from our brilliant readers.

The crucial feature of the industrial Internet is that it installs intelligence above the level of individual machines — enabling remote control, optimization at the level of the entire system, and sophisticated machine-learning algorithms that can work extremely accurately because they take into account vast quantities of data generated by large systems of machines as well as the external context of every individual machine. Additionally, it can link systems together end-to-end — for instance, integrating railroad routing systems with retailer inventory systems in order to anticipate deliveries accurately.

In other words, it’ll look a lot like the Internet — bringing industry into a new era of what my colleague Roger Magoulas calls “promiscuous connectivity.”

Optimization becomes more efficient as the size of the system being optimized grows (in theory). Your software can take into account lots of machines, learning from a much larger training set and then optimizing both within the machine and for the group of machines working together. Think of a wind farm. There are certain optimizations you need to make at the machine level: the turbine turns itself to face into the wind, the blades adjust themselves through every cycle in order to account for flex and compression, and the machine shuts down during periods of dangerously high wind.

System-wide optimization means that when you can operate each turbine in a way that minimizes air disruption to other turbines (these things create wake, just like an airplane, that can disrupt the operation of nearby turbines). When you need to increase or decrease power output across the whole farm, you can do it across lots of machines in a way that minimizes wear (i.e., curtail each machine by 5% or cut off 5% of your machines, or something in between depending on differential output and the impact of different speeds on machine wear). And by gathering data from thousands of machines, you can develop highly-detailed optimization plans.

By tying machines together, the industrial Internet will encourage “platformization.” Cars have several control systems, and until very recently they’ve been linked by point-to-point connections: when you move the windshield-wiper lever, it actuates a switch that’s connected to a small PLC that operates the windshield wipers. The brake pedal is part of the chassis-control system, and it’s connected by cable or hydraulics to the brake pads, with an electronic assist somewhere in the middle. The navigation system and radio are part of the same telematics platform, but that platform is not linked to, say, the steering wheel.

The car as enabled by the industrial Internet will be a platform — a bus, in the computing sense — built by the car manufacturer, with other systems communicating with each other through the platform. The brake pedal is an actuator that sends a “brake” signal to the car’s brake controller. The navigation system is able to operate the steering wheel and has access to the same brake controller. Some of these systems will be driven by third-party-built apps that sit on top of the platform.

This will take some time to happen in cars because it takes 10 or 15 years to renew the American auto fleet, because cars are maintained by a vast network of independent mechanics that need change to happen slowly, and because car development works incrementally.

But it’s already happening in commercial aircraft, which often come from clean-sheet designs (as with the Boeing 787 and Airbus A350), and which are maintained under very different circumstances than passenger cars. In Bombardier’s forthcoming C-series midsize jet, for instance, the jet engines do nothing but propel the plane and generate electricity (they don’t generate hydraulic pressure or compress air for the cabin; these are handled by electrically-powered compressors). The plane acts as a giant hardware platform on which all sorts of other systems sit: the landing-gear switch communicates with the landing gear through the aircraft’s bus, rather than by direct connection to the landing gear’s PLC.

The security implications of this sort of integration — in contrast to effectively air-gapped isolation of systems — are obvious. The industrial Internet will need its own specially-developed security mechanisms, which I’ll look into in another post.

The industrial Internet makes it much easier to deploy and harvest data from sensors, which goes back to the system-wide intelligence point above. If you’re operating a wind farm, it’s useful to have wind-speed sensors distributed across the country in order to predict and anticipate wind speeds and directions. And because you’re operating machine-learning algorithms at the system-wide level, you’re able to work large-scale sensor datasets into your system-wide optimization.

That, in turn, will help the industrial Internet take in previously-uncaptured data that’s made newly useful. Venkatesh Prasad, from Ford, pointed out to me that the windshield wipers in your car are a sort of human-actuated rain API. When you turn on your wipers, you’re acting as a sensor — you see water on your windshield, in a quantity sufficient to cause you to want your wipers on, and you set your wipers to a level that’s appropriate to the amount of water on your windshield.

In isolation, all you’re doing is turning on your windshield wipers. But if your car is networked, then it can send a signal to a cloud-based rain-detection service that geocorrelates your car with nearby cars whose wipers are on and makes an assumption about the presence of rain in the area and its intensity. That service could then turn on wipers in other cars nearby or do more sophisticated things — anything from turning on their headlights to adjusting the assumptions that self-driving cars make about road adhesion.

This is an evolving conversation, and I want to hear from readers. What should be included in the definition of the industrial Internet? What examples define, for you, the boundaries of the field?


This is a post in our industrial Internet series, an ongoing exploration of big machines and big data. The series is produced as part of a collaboration between O’Reilly and GE.

Related

March 16 2009

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Global Terrorism: The FBI`s Role

March 10 2009

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