Ars Erotica: The Lost Art of the Love

ars-erotica

The most important elements of an erotic art linked to our knowledge about sexuality are not to be sought in the ideal, promised to us by medicine, of a healthy sexuality, nor in the humanist dream of a complete and flourishing sexuality, and certainly not in the lyricism of orgasm and the good feelings of bio-energy (these are but aspects of its normalizing utilization), but in this multiplication and intensification of pleasures connected to the production of the truth about sex. The learned volumes, written and read; the consultations and examinations; the anguish of answering questions and the delights of having one’s words interpreted; all the stories told oneself and to others, so much curiosity, so many confidences offered in the face of scandal, sustained – but not without trembling a little – by the obligation of truth; the profusion of secret fantasies and the dearly paid right to whisper them to whoever is able to hear them; in short, the formidable ‘pleasure of analysis’ (in the widest sense of the latter term) which the West has been cleverly fostering for several centuries: all this constitutes something like the errant fragments of an erotic art that is secretly transmitted by confession and the science of sex. Must we conclude that our scientia sexualis is but an extraordinarily subtle form of ars erotica, and that it is the Western, sublimated version of that seemingly lost tradition?

—Michel Foucault, The History of Sexuality

Into the Mystic: Capitalism and the Structuralization of Spirituality

Edmund Berger gives us a secret history of our information processing era and how the corporatocracy has at each stage been able to reincorporate the negative and opposing shifts of the Left into its ongoing initiatives. His knowledge of this era is unique and details out in this one post a part of his ongoing project. A must read for those who want to know the secret history of capitalism during the twentieth century…

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In his fantastic book The Closed World: Computers and the Politics of Discourse in Cold War America, Paul N. Edwards forwards a quasi-literary reading of the way power and subjectivity operate in the age of the computer, focusing primarily on the lineage running from the Vannevar Bush’s  Office of Scientific Research and Development (OSRD) to the birth of cybernetics and their proliferation during the Macy Conferences to the electronic battlefields of Vietnam, and, finally, to the Reagan administration’s Strategic Defense Initiative – the “Star Wars” program that propelled the growth of Silicon Valley and its corollary Californian Ideology, as well as the globalization of information technology across the 1990s. For Edwards the collision of massive government subsidies and steering of computer research and the geopolitical imperatives of the Cold War – dressed in the rhetoric of “containment” – produced the metaphoric construct for which the book is titled: the…

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Machine Learning: Pattern Recognition and Predictive Behavior

Connection between human and the virtual world

Jobs and robots

One report recently suggest that machine learning and new AI personal assistants will cost 7% job loss in the U.S. market alone over the next 10 years. According to Forrester, 16 per cent of US jobs will be lost in the U.S. over the next decade as the result of the rise of artificial intelligence and technology, although it also believes that 13.6 million jobs will be created during that time due to the trend.

The Future of Jobs, 2025: Working Side by Side with Robots” has been written by J.P Gownder, vice president and principal analyst serving Infrastructure & Operations Professionals for Forrester, who is attempted to dispel the often quoted statistic study from Oxford academics Fry and Osborne that found that almost half (47 per cent) of US jobs would be exposed to job losses from computerisation.

Gownder wrote in a blog about the study; “Cultural anxieties about robots (as seen in the novel Robopocalypse, or the Battlestar Galatica reboot) create an atmosphere in which people readily believe the worst case scenario. But the scariest numbers have the least specific timeframes and outcomes associated with them; even Frey and Osborne write of their estimate that at-risk jobs are merely ‘potentially automatable’ (emphasis mine) and that their timeframe is ‘over some unspecified number of years, perhaps a decade or two.’ And aggregate economic productivity numbers don’t suggest that automation is moving the needle toward human redundancy.”

Predictive Pattern recognition and fashion markets

In a report by Amir Mizroch on Digits that Amazon is once again expanding its Big Data initiative. This time their rolling out its sophisticated big-data-crunching platform for developers in Europe, and is also hiring scientists for its research teams in New York and Berlin who specialize in getting machines to do things like make sales predictions and predict fraud.

“Machine-learning software predicts what a customer is likely to do in the next five seconds or in the next five weeks. It’s pattern recognition at scale,” said Ralf Herbrich, European Union director of machine learning at Amazon and managing director of the Amazon Development Center in Germany. Herbrich previously worked at Microsoft Research and Facebook, showing how AI experts are in high demand at global tech firms.

What’s happening is the infiltration of AI Platforms for commercial use in a global corporate market that Amazon is planning to monopolize if they can. As they describe it their new platform of machine learning algorithms offers a “set of visualization tools and wizards that allow nontechnical users to create predictions based on their businesses’ historical data.”

Aliyun, the cloud computing unit of Alibaba Group, is launching an artificial intelligence service that it claims is the first in China. Called DT PAI, the platform combines algorithms used by Alibaba with machine and deep learning techniques and presents them in a simple drag-and-drop interface. Aliyun says developers can use DT PAI to predict user behavior without having to write new code.

The platform’s applications, however, go beyond e-commerce. For example, genomic research institute BGI used it in 2013 to sequence genes more quickly. ODPS has also been used to track weather patterns and pharmaceutical drugs sold in China.

“In the past, the field of artificial intelligence was only open to a very small number of qualified developers and required the use of specialized tools. Such an approach was prone to error and redundancy,” said Aliyun senior product expert Xiao Wei in a press release. “However, DT PAI allows developers with little or no experience in the field to construct a data application from scratch in a much shorter period of time. What used to take days can be completed within minutes.”

The moment that nontechnical users such as mid-level management, stock brokers, sales execs, specialized scientists, schools, civic governments, military and NSA analysts etc. can have their executives use such platforms we’re going to see a great intake of revenue to drive further and further exponential economics into this niche market. Whether we like it or not what’s driving technology as it always has is economics. If AI emerges out of this it will be due to this influx of the market driven economy not the academic and scientific treadmill of disinterested knowledge. Today technology and its innovation is coming out of the private corporate competitive systems of capitalism. Companies like Amazon or collaborates for DARPA systems. The government is aligned with big corporate systems for their war-machine and other technological initiatives.

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