"You have to hate technology in order to love it." Jaron Lanier
A very interesting story in Wired Magazine, How Google Retooled Android With Help From Your Brain. First Google taught its computers to recognize cats. A discussion of neural network algorithms and cognitive mapping.
Google’s software first tries to pick out the individual parts of speech — the different types of vowels and consonants that make up words. That’s one layer of the neural network. Then it uses that information to build more sophisticated guesses, each layer of these connections drives it closer to figuring out what’s being said.
Neural network algorithms can be used to analyze images too. “What you want to do is find little pieces of structure in the pixels, like for example like an edge in the image,” says Hinton. “You might have a layer of feature-detectors that detect things like little edges. And then once you’ve done that you have another layer of feature detectors that detect little combinations of edges like maybe corners. And once you’ve done that, you have another layer and so on.”
This type of network has always interested me, the potential for systems like voice recognition to self correct. This technology is getting better, faster and do I daresay, more human, whatever that means.
Dienekes posted a couple interesting stories recently. I don't have academic permission to get beyond the abstracts but conceptually they are thought provoking.
Automated reconstruction of proto-languages
Automated reconstruction of ancient languages using probabilistic models of sound change
Alexandre Bouchard-Côté et al.
One of the oldest problems in linguistics is reconstructing the words that appeared in the protolanguages from which modern languages evolved. Identifying the forms of these ancient languages makes it possible to evaluate proposals about the nature of language change and to draw inferences about human history. Protolanguages are typically reconstructed using a painstaking manual process known as the comparative method. We present a family of probabilistic models of sound change as well as algorithms for performing inference in these models. The resulting system automatically and accurately reconstructs protolanguages from modern languages. We apply this system to 637 Austronesian languages, providing an accurate, large-scale automatic reconstruction of a set of protolanguages. Over 85% of the system’s reconstructions are within one character of the manual reconstruction provided by a linguist specializing in Austronesian languages.
And on a similar line, Clustering Folk Tales. The etymology of folk tales and their relationship to population genetics, geographic distance and cluster. Like the old game of telephone, 700 variants of a tale in 31 distinct linguistic populations. And I assume that the authors can analyze and mathematically model the data variants and draw all kinds of interesting conclusions traveling through time and space.
Proc. R. Soc. B 7 April 2013 vol. 280 no. 1756
Population structure and cultural geography of a folktale in Europe
Robert M. Ross et al.
Despite a burgeoning science of cultural evolution, relatively little work has focused on the population structure of human cultural variation. By contrast, studies in human population genetics use a suite of tools to quantify and analyse spatial and temporal patterns of genetic variation within and between populations. Human genetic diversity can be explained largely as a result of migration and drift giving rise to gradual genetic clines, together with some discontinuities arising from geographical and cultural barriers to gene flow. Here, we adapt theory and methods from population genetics to quantify the influence of geography and ethnolinguistic boundaries on the distribution of 700 variants of a folktale in 31 European ethnolinguistic populations. We find that geographical distance and ethnolinguistic affiliation exert significant independent effects on folktale diversity and that variation between populations supports a clustering concordant with European geography. This pattern of geographical clines and clusters parallels the pattern of human genetic diversity in Europe, although the effects of geographical distance and ethnolinguistic boundaries are stronger for folktales than genes. Our findings highlight the importance of geography and population boundaries in models of human cultural variation and point to key similarities and differences between evolutionary processes operating on human genes and culture.
And using evolutionary-linguistic phylogenetic statistical methods to date Homeric epics.
And in a similar vein, the automatic language time machine from Berkeley, actually a rehash of the first.
Neil Freeman configuring fifty new states with equal populations.
A look to the future with predictive analytics.
United Nations calls Hormone Disrupters a global threat.
“These chemicals are what we call ‘pseudo persistent,” said Tracey Woodruff, a professor at the University of California, San Francisco, and a report co-author. “They don’t stay in the environment long but people are exposed to them all the time so it’s the same effect as if they were persistent.”
Stoned fish get the munchies.