Some applications are so inherently complicated that it is difficult to dig through the many layers of connected algorithms to expose the parts of the code ripe for optimization. This makes them a ...

State of the art systems that need to be aware of an environment must relying on sensors, radar, LIDAR, cameras and specialized computing in order to make sense of a chaotic world. Underneath all of ...

Machine learning couldn’t be hotter, with several heavy hitters offering platforms aimed at seasoned data scientists and newcomers interested in working with neural networks. Among the more popular ...

Graph theory isn’t enough. The mathematical language for talking about connections, which usually depends on networks — vertices (dots) and edges (lines connecting them) — has been an invaluable way ...

Google's open source framework for machine learning and neural networks is fast and flexible, rich in models, and easy to run on CPUs or GPUs What makes Google Google? Arguably it is machine ...

I had great fun writing neural network software in the 90s, and I have been anxious to try creating some using TensorFlow. Google’s machine intelligence framework is the new hotness right now. And ...