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ESCHER'S DRAWING HAND. "The idea of programs that write programs is inherent in the concept of the universal Turing machine, set forth by Alan M. Turing in 1936. He showed that any computation can be described in terms of a machine shifting among a finite number of states in response to a sequence of symbols read and written one at a time on a potentially infinite tape." https://lnkd.in/d854b7f View in LinkedIn

SMALL BEGINNINGS. "Code that's capable of altering its own instructions while it's still executing has been around for a while. Typically, it's done to reduce the instruction path length and improve performance, or to simply reduce repetitively similar code. But for all intents and purposes, there are no self-aware, self-improving AI systems today." https://lnkd.in/dp3ZKye View in LinkedIn

EMERGENT PHENOMENA. "The jumps — saltations, in complexity parlance — appear to be non-linear emergent phenomena, the result of networked interactions that produce self-organization at ever higher levels. From this perspective, Darwinian evolution is a mechanism of a higher universal law, perhaps even a variant on the second law of thermodynamics." https://lnkd.in/ezFxqyc View in LinkedIn

BIOLOGICAL LEAPS. "A growing number of scientists do say that neo-Darwinian evolution doesn’t explain certain jumps in biological complexity: from single-celled to multicellular organisms, from single organisms to entire communities." https://lnkd.in/ezFxqyc View in LinkedIn

GREY ZONE THRESHOLD. "An artificial intelligence could rewrite its code from scratch — it could change the underlying dynamics of optimization. Such an optimization process would wrap around much more strongly than either evolution accumulating adaptations or humans accumulating knowledge. The key implication for our purposes is that AI might make a huge jump in intelligence after reaching some threshold of criticality." https://lnkd.in/dp3ZKye View in LinkedIn

LIPSON'S EUREQUA was capable of "deriving Newton's second law of motion from a data set of positions and velocities of a double pendulum." Breathtaking achievement. Read again. https://lnkd.in/dHKcrCf View in LinkedIn

CODE VERSUS DATA. "Self-modifying code weakens the distinction between program code and data." https://lnkd.in/dHTSZ_H View in LinkedIn

PROFESSOR HOD LIPSON. "Beginning in 2009, he and his Cornell University graduate student Michael Schmidt developed software named Eureqa capable of deriving equations, mathematical relationships and laws of nature from sets of data." https://lnkd.in/dHKcrCf View in LinkedIn

FEW LIMITS. "Metalearning (or Meta-Learning) means learning the credit assignment method itself through self-modifying code. Metalearning may be the most ambitious but also the most rewarding goal of machine learning. There are few limits to what a good metalearner will learn." https://lnkd.in/dgfxJ_E View in LinkedIn

MACHINE LEARNING. "The Pentagon is particularly interested in this game. Through DARPA, its hoping to develop a computer that can teach itself. Ultimately, it wants to create machines that are able to perform a number of complex tasks, like unsupervised learning, vision, planning, and statistical model selection. https://lnkd.in/dp3ZKye View in LinkedIn