Game Over

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Go is done, as a side-effect of general machinic ‘beating humans at stuff’ capability:

“This is a really big result, it’s huge,” says Rémi Coulom, a programmer in Lille, France, who designed a commercial Go program called Crazy Stone. He had thought computer mastery of the game was a decade away.

The IBM chess computer Deep Blue, which famously beat grandmaster Garry Kasparov in 1997, was explicitly programmed to win at the game. But AlphaGo was not preprogrammed to play Go: rather, it learned using a general-purpose algorithm that allowed it to interpret the game’s patterns, in a similar way to how a DeepMind program learned to play 49 different arcade games.

This means that similar techniques could be applied to other AI domains that require recognition of complex patterns, long-term planning and decision-making, says Hassabis. “A lot of the things we’re trying to do in the world come under that rubric.”

UF emphasis (to celebrate one of the most unintentionally comedic sentences in the history of the earth).

We’re entering the mopping-up stage at this point.

Eliezer Yudkowsky is not amused.

The Wired story.

Quotable (#135)

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Craig Hickman on deepening neuro-technological darkness:

The convergence of knowledge and technology for the benefit or enslavement of society (CKTS) is the core aspect of 21st century science initiatives across the global system, which is based on five principles: (1) the interdependence of all components of nature and society (the so called network society, etc.), (2) enhancement of creativity and innovation through evolutionary processes of convergence that combine existing principles, and divergence that generates new ones (control of creativity and innovation by corporate power), (3) decision analysis for research and development based on system-logic deduction (data-analysis, machine learning, AI, etc.), (4) higher-level cross-domain languages to generate new solutions and support transfer of new knowledge (new forms of non-representational systems and mappings, topological, etc.). As civilization and societal challenges become more and more dependent on external and internalized artificial mechanisms and technological systems we are faced with the convergence of “NBIC” technological reorganization of corporate and socio-cultural fields of business, inquiry, and research into: nanotechnology, biotechnology, information technology, and cognitive and neruosciences. But it is the neuroscientific breakthroughs and initiatives that will underpin the forms of global governance: political and economic systems of rules, negotiations, and navigation systems of impersonal and indifferent regulatory and reason-based imperialism of the future capitalist regimes as they begin to marshal every aspect of life into a data-centric vision of command and control.

The subsequent list of ‘neuro-‘ prefixed social management disciplines, accompanied by short introductions, is a treasure.

ADDED: Highly relevant.

Quotable (#134)

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In The New Yorker, John Cassidy lucidly rehearses the core game theoretic model of economic crisis:

… deciding whether to invest in financial assets or any other form of capital can be viewed as a huge n-person game (one involving more than two participants), in which there are two options: trust in a good outcome, which will lead you to make the investment, or defect from the game and sit on your money. If you don’t have a firm idea about what is going to happen and the payoffs are extremely uncertain, the optimal strategy may well be to defect rather than to trust. And if everybody defects, bad things result.

Does anybody seriously expect honesty from the status quo within this context? ‘Optimism’ is a fundamental building-block of regime stability. Expect it to be very carefully nurtured, with whatever epistemological flexibility is found helpful.

(Stay to the end of the article for the ominous nonlinear dynamics that correspond to narrative dike-breaking.)