A few weeks ago we had a heatwave and we were thinking if the hotter a place the poorer it is. We could collect data to test our hypothesis thanks to the recent advances in open data and scraping technologies.
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We love reading news but who’s got the time to read ALL articles? Luckily, the Global Database of Events, Language, and Tone, GDELT for short, scrapes tons of news articles and other sources of information. And yes, you can access their data via an API or very convenient Python and R SDKs.
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Can machines think? 
What is consciousness? These questions are too important to leave to AI researchers. Cognitive scientists, psychologists, philosophers, and neuroscientists have investigated these questions for ages and came up with frameworks to think about such questions. Here we focus on two things, the philosophical critique of AI (both symbolic and connectionist) and various approaches to consciousness (or intelligence, or minds).
Recently a linguistic search engine overturned the federal mask mandate in the US, the recent issue of The Economist says “Huge “foundation models” are turbo-charging AI progress” and Gary Marcus seems to be the only person who bets against the success of AI. But can we trust empiricism and big data? A large language model can decide the debate over the common or right usage of words?
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Overpass API is an incredible data source. We used pydeck and Blender to visualize the frequency of various OSM features (aka categories) in Hungary.
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We made a photogrammetry-based 3D model of the recently demolished National Electric Load Distributor for the 6th International Architectural Mock-up Festival in collaboration with Urbanum and Urbanum Lab.
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The interest in functional programming languages has been increasing recently. The success of Scala and Spark is apparent, but the demand for Haskell, Clojure, and OCaml programmers is also rising. Lisp is still alive and there are successful companies devoted to it. Learning functional programming languages is complex, and the knowledge of “traditional” languages is of little help, but the good news is that you can get started with excellent study materials.
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You can learn more about ESPnet at our upcoming online meetup on May 25 6:00 pm CET.
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Join us to learn more about graph neural networks and PyTorch Geometric on 5th May! The online event is free and open to everyone.
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