Understanding the limits of deep learning

Neural networks were invented in the '60s, but recent boosts in big data and computational power made them actually useful. A new discipline called "deep learning" has arisen that can apply complex neural network architectures to model patterns in data more accurately than ever before. The results are undeniably impressive. Computers can now recognize objects in images and video and transcribe speech to text better than humans can. Google replaced Google Translate's architecture with neural networks, and now machine translation is also closing in on human performance.