Conventional, stored program architecture systems are designed for algorithmic and exact calculations. However, problems with highest impact involve large, noisy and incomplete data sets that do not lend themselves to convenient solutions by current systems. Our task is to build upon the convergence among neuroscience, microelectronics and computational systems to develop new architectures and approaches designed to handle the hardest challenges.
Key Outcomes
Value proposition for Neuro-inspired / Neuromorphic Computing Systems:
Why would you use these new systems to solve the hardest problems?
Pathways for building, evaluating and improving new learning, analysis, prediction and control systems.
niceworkshop.org/