Progressive neural networks Rusu et al, 2016 If you've seen one Atari game you've seen them all, or at least once you've seen enough of them anyway. When we (humans) learn, we don't start from scratch with every new task or experience, instead we're able to build on what we already know. And not just ... Continue Reading

Asynchronous methods for deep reinforcement learning Mnih et al. ICML 2016 You know something interesting is going on when you see a scalability plot that looks like this: That’s a superlinear speedup as we increase the number of threads, giving a 24x performance improvement with 16 threads as compared to a single thread. The result ... Continue Reading

Why does deep and cheap learning work so well Lin & Tegmark 2016 Deep learning works remarkably well, and has helped dramatically improve the state-of-the-art in areas ranging from speech recognition, translation, and visual object recognition to drug discovery, genomics, and automatic game playing. However, it is still not fully understood why deep learning works ... Continue Reading