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colah.github.io | ||
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www.paepper.com
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| | | | | Recent advances in training deep neural networks have led to a whole bunch of impressive machine learning models which are able to tackle a very diverse range of tasks. When you are developing such a model, one of the notable downsides is that it is considered a "black-box" approach in the sense that your model learns from data you feed it, but you don't really know what is going on inside the model. | |
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coen.needell.org
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| | | | | In my last post on computer vision and memorability, I looked at an already existing model and started experimenting with variations on that architecture. The most successful attempts were those that use Residual Neural Networks. These are a type of deep neural network built to mimic specific visual structures in the brain. ResMem, one of the new models, uses a variation on ResNet in its architecture to leverage that optical identification power towards memorability estimation. M3M, another new model, ex... | |
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marcospereira.me
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| | | | | In this post we summarize the math behind deep learning and implement a simple network that achieves 85% accuracy classifying digits from the MNIST dataset. | |
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blog.fastforwardlabs.com
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| | | Image from Social Soul, an immersive experience of being inside a social media stream, by Lauren McCarthy and Kyle McDonald A few weeks ago, theCUBE stopped by the Fast Forward Labs offices to interview us about our approach to innovation. In the interview, we highlighted that artists have an important role to play in shaping the future of machine intelligence. Unconstrained by market demands and product management requirements, artists are free to probe the potential of new technologies. And by optimizing for intuitive power or emotional resonance over theoretical accuracy or usability, they open channels to understand how machine intelligence is always, at its essence, a study of our own humanity.One provocative artist exploring the creative potential of new machine learning tools is Kyle McDonald. McDonald has seized the deep learning moment, undertaking projects that use neural networks to document a stroll down the Amsterdam canals, recreate images in the style of famous painters, or challenge our awareness of what we hold to be reality. We interviewed Kyle to understand how he understands his work. Keep reading for highlights: | ||
