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jlao

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15-440 with Andersen and Bryant was one of my favorite classes I took at CMU. I took it the first time it was taught in Go. I fell in love with Go and still miss it. I didn't find the language that difficult to learn. As he noted, not having to write your own data marshalling code and RPC let me focus more on the core algorithms.

Their website has a better description of how it works that is less ambiguous: http://gallantlab.org/

The description of the first video: "The left clip is a segment of the movie that the subject viewed while in the magnet. The right clip shows the reconstruction of this movie from brain activity measured using fMRI. The reconstruction was obtained using only each subject's brain activity and a library of 18 million seconds of random YouTube video that did not include the movies used as stimuli. Brain activity was sampled every one second, and each one-second section of the viewed movie was reconstructed separately."

So they gathered a lot of fMRI data from people watching several hours of YouTube videos (the training set). They then use this to train some sort of machine learning algorithm to make a model. The pictures you see in the article are from a running the model on a test set which does not contain any of the videos from the training set.

Current CMU student here. All students are required to 15-123 (Introduction to C & Unix), 15-213 (Introduction to Systems) and another low level systems course of your choice (which to my knowledge almost all require C and/or x86 assembly).