The evolution of computer science: Connecting top-down and bottom-up

David Krakauer from the Santa Fe Institute asks “what is intelligence?” and discusses the rift in the field of computer science between the top down, symbolic approach to cognition (how can we make a machine play chess?)  and the bottom-up, inferential approach (how can we evolve a general-intelligence machine?).  He suggests that the singularity – when machines will outpace human beings – will occur only when machines master both aspects.  But is it a good idea to trust them?

This is a typical SFI talk, sweeping over evolving brain size, poetry, the Turing test, Evolution, the Matrix, Blade Runner and Doctor Strangelove. Fantastically, Krakauer mentions my work on a cultural singularity that I blogged about here!

Ultimately, his point is very similar to Adam Curtis’ documentary All Watched Over by Machines of Loving Grace, which is also brilliant.

See Krakauer’s talk here.

The Bilingual paradox in Language Evolution: Top down versus bottom up approaches

When thinking about bilingualism and language evolution, there appears to be a paradox:  Children are adept at learning more than one language at a time  and there are many bilingual societies in the world.  However, pressures on memory and redundancy makes it unclear what the adaptive advantage of a cognitive capacity for learning multiple languages at an early stage of language evolution would be.  For instance, Hagen (2008) has argued that a bilingual ability would not have been adaptive in early societies and so could not have been selected for.  Furthermore, many models have suggested that bilingualism is an unstable trait in a society (e.g. Castello et al., 2008).  How can we account for the evolution of this ability?  Would an early population of language users most likely be monolingual or bilingual?  Here, I take a top down and a bottom up approach and show that they tends to lead to two different conclusions.

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