Neurobiologically inspired robotics goes by many names: brain-based devices, cognitive robots, neurorobots, and neuromorphic robots, to name a few. The field has grown into an exciting area of research and engineering.
The common goal is twofold: Firstly, developing a system that demonstrates some level of cognitive ability can lead to a better understanding of the neural machinery that realizes cognitive function.
Big data is much more than storage of and access to data. Analytics plays an important role in making sense of that data and exploiting its value. But learning from big data has become a significant challenge and requires development of new types of algorithms. Most machine learning algorithms encounter theoretical challenges in scaling up to big data. Plus there are challenges of high dimensionality, velocity and variety for all types of machine learning algorithms. The neural network field has historically focused on algorithms that learn in an online, incremental mode without requiring in-memory access to huge amounts of data.