Foresight Update 23.32: Prospect of a universal learning machine - August 6, 2009
Yesterday I wrote that we don't have a clue how learning works. If that were as categorically true as I made it sound, the prospects of AGI would be pretty much sunk. AGI requires getting up to the universal level of a learning machine: one that can in theory learn anything any other learning machine can learn…
From Open Source Sensing:
In 1902, H. G Wells penned a book, remarkably prophetic in some respects, that can be taken as the definition of the fin de siecle take on the probable course of the 20th century. It was called Anticipations of the Reaction of Mechanical and Scientific Progress Upon Human Life and Thought…
There's a very nice post at IEET by Marcelo Rinesi entitled Education and Learning: Still in the Middle Ages. He points out that we're pretty damn bad at education compared to the improvements we've seen in most other endeavors…
Engineering and analysis in the field of SRMs is unusual in many ways. Eric Drexler has posted a paper about differences in evolutionary capacity in mechanical and biological systems that's worth a look.
Purely coincidentally, we at Foresight have been discussing self-replication in the context of the Feynman Path and I came up with an example that shows just how counter-intuitive self-replication, if you try to view it as a capability, can be…
—Nanodot posts by J. Storrs Hall
From Open Source Sensing:
Principled sensing will often involve getting permission from those being sensed. We can get some ideas about how to think about this process from the paper Affective Sensors, Privacy, and Ethical Contracts by two MIT Media lab researchers, Carson Reynolds (now at U. Tokyo) and Prof. Rosalind Picard…
—Open Source Sensing posts by Christine Peterson
August 20-22, 2009
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