Cognitive Class Uses Machine Learning to Help SETI Find Little Green Men

(Source: Wikipedia)   To speed up the process of developing and testing these neural network, participants were given access to GPUs on IBM PowerAI Deep Learning. PowerAI speeds up deep learning and AI using GPU..Built on IBM’s Power Systems, PowerAI is a scalable software platform that accelerates deep learning and AI with blazing performance for individual users or enterprises..The PowerAI platform supports popular machine learning libraries, and was provided through public cloud provider, NIMBIX. Participants used libraries such as Caffe, Theano, Torch, and Tensorflow..In addition, given the vast amounts of data for signal processing, participants were also given access to an IBM Apache Spark Enterprise cluster..For example, the spectrograms where calculated on several nodes as shown in figure 4..Figure 4: Example architecture used in the event..  The top team was Magic AI..This team used a wide neural net, a network that has less layers than a deep network, but more neurons per layer..According to Jerry Zhang, a Graduate Researcher at UC Berkeley Radio Astronomy Lab, the spectrogram exhibited less complex shapes then a standard image like those in Modified National Institute of Standards and Technology database (MIST), as a result less convolutional layers where required to encode features like edges..We see this by examining figure 5, the left image shows 5 spectrograms and the right image shows 5 images from MIST..The Spectrogram is colored using the standard gray scale where white represents the largest values and black represents the lowest values..We see the edges of the spectrogram are predominantly vertical and straight while the numbers exhibit horizontal lines, parallel lines, arches and circles.. More details

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