The paper "Imagination-Augmented Agents for Deep Reinforcement Learning" is available here: https://arxiv.org/abs/1707.06203 Out Patreon page with the detail... (more…)

This post explains the maths behind a generative adversarial network (GAN) model and why it is hard to be trained. Wasserstein GAN is intended to improve GANs’ training by adopting a smooth metric for measuring the distance between two probability distrib... (more…)

In a sign of the autonomous security of the future, a $2m contest wants teams to build a system that can exploit rivals’ vulnerabilities while fixing its own... (more…)

Predict and solve problems in all of your applications using an automated log analysis solution. (more…)

Deep learning has continued to drive the computing industry's agenda in 2016. But come 2017, experts say the Artificial Intelligence community will intensify its demand for higher performance and more power efficient inference engines for deep neural netw...