How algorithms shape our world – TED talk by Kevin Slavin, Jul 2011
Snippets
How iTunes Genius Really Works – Apple engineer Erik Goldman, June 2010
Uses an algorithm based on Term Frequency – Inverse Document Frequency (tf-idf) <- same approach as SharePoint’s original probabilistic ranking algorithm
The Shortest Path and Dijkstra’s algorithm – Janie Chang, MS Research, Jul 2009
The shortest-path problem, one of the fundamental quandaries in computing and graph theory, is intuitive to understand and simple to describe. In mapping terms, it is the problem of finding the quickest way to get from one location to another. Expressed more formally, in a graph in which vertices are joined by edges and in which each edge has a value, or cost, it is the problem of finding the lowest-cost path between two vertices. There are already several graph-search algorithms that solve this basic challenge and its variations, so why is shortest path perennially fascinating to computer scientists?
Designing emergent AI – Christopher M. Park, Games by Design, Jun 2009
Covers decision trees, strategic tiers, fuzzy logic and others.
Godel’s Incompleteness Theorum – summary of works, Mar 2009
Gödel’s Theorem has been used to argue that a computer can never be as smart as a human being because the extent of its knowledge is limited by a fixed set of axioms, whereas people can discover unexpected truths … It plays a part in modern linguistic theories, which emphasize the power of language to come up with new ways to express ideas.
Pursuing the next level of artificial intelligence – John Markoff, MYTimes, May 2008
Called the Bayesian approach, it centers on a formula for updating the probabilities of events based on repeated observations. The Bayes rule, named for the 18th-century mathematician Thomas Bayes, describes how to transform a current assumption about an event into a revised, more accurate assumption after observing further evidence.
Logic and Artificial Intelligence – Stanford Encyclopedia of Philosophy, May 2008
Artificial Intelligence (AI) is a subfield of Computer Science devoted to developing programs that enable computers to display behavior that can (broadly) be characterized as intelligent. Most research in AI is devoted to fairly narrow applications, such as planning or speech-to-speech translation in limited, well defined task domains. But substantial interest remains in the long-range goal of building generally intelligent, autonomous agents… thumper article all about AI
Links
- Bayes Net by Example using Python and Khan Academy Data – Derandomized, Mar 2012
- How to build a naive Bayes classifier – bionicspirit.com, Feb 2012
- How Bayesian probability models can make CLV predictions 12x more accurate – Custora, Feb 2012
