pair with Katya Gorchinskaya’s “Birth of a Nation”
“Romaniţa”, str. N. Testimiţeanu, 21/2, Kishinev, Moldova
“But the rejection of identitarianism can only be achieved by the re-assertion of class. A left that does not have class at its core can only be a liberal pressure group. Class consciousness is always double: it involves a simultaneous knowledge of the way in which class frames and shapes all experience, and a knowledge of the particular position that we occupy in the class structure. It must be remembered that the aim of our struggle is not recognition by the bourgeoisie, nor even the destruction of the bourgeoisie itself. It is the class structure–a structure that wounds everyone, even those who materially profit from it–that must be destroyed. The interests of the working class are the interests of all; the interests of the bourgeoisie are the interests of capital, which are the interests of no-one. Our struggle must be towards the construction of a new and surprising world, not the preservation of identities shaped and distorted by capital.”
Daniel Mendelsohn on myth, Greek tragedy, and the J.F.K. story: http://nyr.kr/18WxDor
“The end of the Iliad is, in other words, a narrative about grief yielding to mourning, about the way in which civilization responds to violence and horror. This dark solace is one that only culture can provide. Our endless need to replay the events of November, 1963—by which I mean all of the events, from Friday to Monday—is not only about a perverse, almost infantile need to revisit a scene of primal horror. It also bears witness to our desire to hear once again a very old tale that is not only the story of a fallen warrior and how he died but the story of what we did after he fell, of how the bloodied body is washed and anointed and clothed and grandly entombed and eulogized.”
Google no longer understands how its “deep learning” decision-making computer systems have made themselves so good at recognizing things in photos.
This means the internet giant may need fewer experts in future as it can instead rely on its semi-autonomous, semi-smart machines to solve problems all on their own.
The claims were made at the Machine Learning Conference in San Francisco on Friday by Google software engineer Quoc V. Le in a talk in which he outlined some of the ways the content-slurper is putting “deep learning” systems to work.
"Deep learning" involves large clusters of computers ingesting and automatically classifying data, such as pictures. Google uses the technology for services like Android voice-controlled search, image recognition, and Google translate, among others. […]
What stunned Quoc V. Le is that the machine has learned to pick out features in things like paper shredders that people can’t easily spot – you’ve seen one shredder, you’ve seen them all, practically. But not so for Google’s monster.
Learning “how to engineer features to recognize that that’s a shredder – that’s very complicated,” he explained. “I spent a lot of thoughts on it and couldn’t do it.” […]
This means that for some things, Google researchers can no longer explain exactly how the system has learned to spot certain objects, because the programming appears to think independently from its creators, and its complex cognitive processes are inscrutable. This “thinking” is within an extremely narrow remit, but it is demonstrably effective and independently verifiable.”