Dr. Maximilian Koegel is deeply involved with the Eclipse community. He is project lead and committer on several open-source projects including EMF Cloud, JSON Forms and …
EclipseCon Impressions - Tuesday
March 23, 2011 | 2 min ReadMy highlights on the EclipseCon today were the EMF GWT presentation by Ed Merks, the p2 talk by Ian Bull and Pascal Rapicault and the keynote on Watson by David Gondek:
Ed Merks showed how to use EMF with the Google Web Toolkit. In about a click or two, he had an EMF-based GWT application (or an GWT-based EMF application) up and running. The famous library model application was not only available locally on his demo laptop but also hosted on Google Appspot. It is still available here. Unfortunately Ed did not refresh his running browser instance during the tutorial, although many model updates had been waiting on the server…;)
Ian Bull and Pascal Rapicault presented a bunch of donts concerning p2 in a very entertaining way. I hereby promise, I will no longer unzip features and plugins directly into an Eclipse instance, I will never release with the same version twice or try to edit the p2 metadata ;). Also throwing in 1000+ plugins into the dropin folder seems to be a discouraged practice, at least if you would like to have a speedy Eclipse startup. Seriously, this was a very informative presentation and it showed how to avoid “trouble” with p2, which is in many cases trouble that we caused ourselves.
In his keynote David Gondek explained the mission of Watson and how it works. Today keyword search is widely used, but it comes with the disadvantage of putting the burden of selecting “good” keywords on the user. In general adding more keywords to a search will decrease the quality of the results. Among many interesting statistics, I found the statistics on the top 10 “What is …?” searches in Google particularly interesting. On the first place is the question “What is love?”. Consequently the question “What is autism?” is on the 7th place ;). In contrast to keyword search, Watson uses a comprehensive analysis and reasoning to answer natural language questions. For example Watson has a geographic reasoner which can relate words in terms of the geographic distance. Thereby Watson can even find answers to tricky questions in Jeopardy. The many examples in the keynote provided a lively picture of the problems building the next generation search engine.