In our latest maintenance release, version 0.10.1.48, we have fixed numerous bugs and support the newly released NVIDIA CUDA 10.1 with cuDNN 7.5. You can now use Neural Style Transfer, Policy Gradient based reinforcement learning, Char-RNN LSTM based learning and much more with CUDA 10.1. New Features The following new features have been added to …
Continue reading “Maintenance Release with CUDA 10.1/cuDNN 7.5 Support.”
In our latest release, version 0.10.1.21, we have added support for the newly released NVIDIA CUDA 10.1 with cuDNN 7.5. You can now use Neural Style Transfer, Policy Gradient based reinforcement learning, Char-RNN LSTM based learning and much more with CUDA 10.1. New Features The following new features have been added to this release. Added …
In our latest release, version 0.10.0.190, we have added Neural Style Transfer as described by [1] using the VGG model [2]. With Neural Style Transfer, the style of one photo (such as Vincent Van Gogh’s Starry Night) is learned by the AI model and applied to a content photo (such as the photo of train …
Continue reading “Neural Style Transfer now supported with cuDNN 7.4.2!”
In our latest release, version 0.10.0.140, we have added CUDNN engine support to the LSTM layer to solve the Char-RNN 5x faster than when using the CAFFE engine. As described in our last post, the CAFFE version (originally created by Donahue et al. [1]) uses an internal Unrolled Net to implement the recurrent nature of …
Continue reading “cuDNN LSTM Engine Now Supported to learn Shakespeare 5x faster!”
In our latest release, version 0.10.0.122, we now support Recurrent Learning with both the LSTM [1] and LSTM_SIMPLE [2] layers to solve the Char-RNN as described by [3] and inspired by adepierre [4] and create a Shakespeare sonnet, and do so with the recently released CUDA 10.0.130/cuDNN 7.4.1. The thought of his but is the …
In our latest release, version 0.10.0.76, we now support multi-threaded, Policy Gradient Reinforcement Learning on the Arcade-Learning-Environment [4] (based on the ATARI 2600 emulator [5]) as described by Andrej Karpathy[1][2][3], and do so with the recently released CUDA 10.0.130/cuDNN 7.3.1. Using the simple Sigmoid based policy gradient reinforcement learning model shown below… … the SignalPop …
In our latest release, version 0.10.0.24, we now support multi-threaded, SoftMax based Policy Gradient Reinforcement Learning as described by Andrej Karpathy[1][2][3], and do so with the recently released CUDA 10.0.130/cuDNN 7.3. Using the simple SoftMax based policy gradient reinforcement learning model shown below… … the SignalPop AI Designer uses the MyCaffeTrainerRL to train the model …
Continue reading “Softmax based Policy Gradient Reinforcement Learning Now Supported with CUDA 10!”
In our latest release, version 0.9.2.188, we now support Policy Gradient Reinforcement Learning as described by Andrej Karpathy[1][2][3], and do so with the recently released CUDA 9.2.148 (p1)/cuDNN 7.2.1. For training, we have also added a new Gym infrastructure to the SignalPop AI Designer, where the dataset in each project can either be a standard …
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You can now easily mine Ethereum with our newly released SignalPop Universal Miner™ where all that you need to do is control your ambient temperature – we take care of the rest! Built entirely for Windows bases systems (Windows 10 highly recommended), the Universal Miner carefully monitors your GPU’s and keeps their temperatures within a …
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In our latest release, version 0.9.2.122, we now support deep convolutional auto-encoders with pooling as described by [1], and do so with the new ly released CUDA 9.2.148/cuDNN 7.1.4. Auto-encoders are models that learn how to re-create the input fed into them. In our example shown here, the MNIST dataset is fed into our model,… …
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