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Learning Go for 960 hours straight up to a superb level is kinda cool, but... extremely dorky.
The annual top chess engine competition is under way. No Google or IBM products there, because staying behind an open source champion would be bad marketing.
I've been considering bitcoin and npm "block chain" theory and praxis as emulations of "best practices" in computing R&D. And I am not persuaded this method can or will obtain efficiencies in production or "innovation" to either human or machine benefit searches. The I/O and iteration are chiefly copies of prior "art." That is, the "system" lacks discriminating purpose. Diversity is the key to economic and political evolution.
(I walk to my stacks, pull out Shapiro and Varian, Information Rules, a Strategic Guide to the Network Economy (1999) and Dolan and Simon,Power Pricing (1996)... grimace at Tho. Stewart, Wealth of Knowledge (2001)... return)
World of coders now equipped to transform 'barriers to entry' into moats. Diversity is the key to economic and political evolution.
Corporations are AI entities already, Romney could say.
Its debatable whether the aims are achievable, but it's absolutely clear that the development of independent, self-enhancing intelligence - which transcends the abilities of its developers - is a core aim.
And the aim has been attained in minor ways across many fields. Google's AlphaGo developers didn't need to understand Go to master level to be able build a system capable of beating a master.
The only difference with general AI is that the goal is to automate learning itself, not to solve specific problems in one limited domain.
Of course this requires the design of a system with discrimination and abstraction - not necessarily a purpose in human terms, but still an explicit meta-goal.
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