I attended one talk during the 2008 IST Graduate Symposium this year and it was the opening keynote from Google's Dr. Peter Norvig, director of research. I was hoping to hear more about the new Google Research project that would support eScience and large data sets. Instead I got a talk that appealed to the Computer Scientist in my (ah, 211). He covered what was in the description of the keynote, the amazing ability of simple algorithms to identify images and natural language text... just because of BILLIONS of data points. Test their ability to draw semantic links between ideas from words with Google Sets.
Some gems of insight:
"Don't make algorithms that work well, make algorithms that work well with large enough data"
We can model the entire world by "using the world as it's own model"
We don't need to define rules because "the rules are in the data"
Comments (1)
David Weinberger makes a lot of the same points in defense of tagging in Everything is Miscellaneous; they may look noisy at first, but the signal gets much stronger as more tags are added because the malicious or irrelevant tags are drowned out by the good ones.
Posted by Kevin | February 7, 2008 10:24 AM
Posted on February 7, 2008 10:24