SICS Data Science Day 2015 | SICS
https://www.sics.se/events/sics-data-science-day-2015, posted 2015 by peter in ai conference stockholm sweden
Come and get the latest news on Data Analytics! We will talk about Deep Learning, Machine Learning, the next-generation distribution of Apache Hadoop for "normal people", and other new technology you want to know about. This is a half day seminar event.
Top 10 data mining algorithms in plain English | rayli.net
rayli.net/blog/data/top-10-data-mining-algorithms-in-plain-english/, posted 2015 by peter in ai list reference
Today, I’m going to explain in plain English the top 10 most influential data mining algorithms as voted on by 3 separate panels in this survey paper.
On the Origin of Circuits
www.damninteresting.com/on-the-origin-of-circuits/, posted 2015 by peter in ai evolution hardware science toread
The informatics researcher began his experiment by selecting a straightforward task for the chip to complete: he decided that it must reliably differentiate between two particular audio tones. A traditional sound processor with its hundreds of thousands of pre-programmed logic blocks would have no trouble filling such a request, but Thompson wanted to ensure that his hardware evolved a novel solution. To that end, he employed a chip only ten cells wide and ten cells across— a mere 100 logic gates. He also strayed from convention by omitting the system clock, thereby stripping the chip of its ability to synchronize its digital resources in the traditional way.
Inceptionism: Going Deeper into Neural Networks
googleresearch.blogspot.com/2015/06/inceptionism-going-deeper-into-neural.html, posted 2015 by peter in ai graphics science
One way to visualize what goes on is to turn the network upside down and ask it to enhance an input image in such a way as to elicit a particular interpretation. Say you want to know what sort of image would result in “Banana.” Start with an image full of random noise, then gradually tweak the image towards what the neural net considers a banana (see related work in , , , ). By itself, that doesn’t work very well, but it does if we impose a prior constraint that the image should have similar statistics to natural images, such as neighboring pixels needing to be correlated.
probcomp.csail.mit.edu/bayesdb/, posted 2013 by peter in ai database development software statistics toread
BayesDB, a Bayesian database table, lets users query the probable implications of their data as easily as a SQL database lets them query the data itself. Using the built-in Bayesian Query Language (BQL), users with no statistics training can solve basic data science problems, such as detecting predictive relationships between variables, inferring missing values, simulating probable observations, and identifying statistically similar database entries.
K-tree - a height balanced tree structured vector quantizer
ktree.sourceforge.net/, posted 2013 by peter in ai development text
K-tree is a tree structured clustering algorithm. It is also refered to as a Tree Structured Vector Quantizer (TSVQ). The goal of cluster analysis is to group objects based on similarity. Each object in a K-tree is represented by an n-dimensional vector. All vectors in the tree must have the same number of dimensions.
Programmer Creates An AI To (Not Quite) Beat NES Games | TechCrunch
techcrunch.com/2013/04/14/nes-robot/, posted 2013 by peter in ai automation emulation game hack video
Programmer and CMU PhD Tom Murphy created a function to “beat” NES games by watching the score. When the computer did things that raised the score it would learn how to reproduce them again and again, resulting, ultimately, in what amounts to a Super Mario Brothers-playing robot. The program, called a “technique for automating NES games,” can take on nearly every NES game, but it doesn’t always win. [Pretty cool. Reminds me of when I hex-edited saved games in Snake in the 1980s to simulate playing the game "perfectly".]
Researchers Develop Surveillance System that can Watch & Predict - ParityNews.com: ...Because Technology Matters
paritynews.com/science/item/455-researchers-develop-surveillance-system-that-can-watch--predict, posted 2012 by peter in ai fascism msm privacy science security terrorism
Carnegie Mellon university researchers have developed a surveillance system that can not only recognize human activities but can also predict what might happen next.
Researchers, through the Army-funded research dubbed Mind's Eye, have created intelligent software that recognizes human activities in video and can predict what might just happen next; sounding an alarm if it detects anomalous behavior.
Fast Artificial Neural Network Library (FANN)
leenissen.dk/fann/wp/, posted 2012 by peter in ai c development free opensource software
Fast Artificial Neural Network Library is a free open source neural network library, which implements multilayer artificial neural networks in C with support for both fully connected and sparsely connected networks. Cross-platform execution in both fixed and floating point are supported. It includes a framework for easy handling of training data sets. It is easy to use, versatile, well documented, and fast. Bindings to more than 15 programming languages are available. An easy to read introduction article and a reference manual accompanies the library with examples and recommendations on how to use the library. Several graphical user interfaces are also available for the library.
Genius Swedish computer program has IQ of 150
www.gizmag.com/swedish-program-150iq/21465/, posted 2012 by peter in ai cognition math science
The Gothenburg group has developed a psychological model of patterns as seen and selected by humans, and incorporated it in their IQ test solving programs. The result is a program that attacks abstract problems using approaches similar to those a very smart person would use.
"Our programs are beating the conventional math programs because we are combining mathematics and psychology. Our method can potentially be used to identify patterns in any data with a psychological component, such as financial data. But it is not as good at finding patterns in more science-type data, such as weather data, since then the human psyche is not involved," says Strannegård.
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