- Hlynur Jónsson
- Giovanni Cherubini
- et al.
- 2020
- Entropy
Neuromorphic Computing
Neuro-inspired AI to optimize learning and computing efficiency of next generation AI.
Overview
The trends of next generation AI demand advanced features of cognition and are challenging the boundaries of what is possible in terms of compute capabilities, energy efficiency and flexibility. Moreover, the model sizes are continuously growing but with sustainability becoming a key priority, the need to drastically increase the computational efficiency requires innovative computing paradigms.
Neuromorphic computing aims to address the challenges of the next-gen AI by providing a brain-inspired energy-efficient computing paradigm. At IBM Research Europe – Zurich, we explore this neuromorphic computing paradigm focusing on unique tactics inspired by biological systems to optimize the learning and computing efficiency of next generation AI.
IBM Research Neuro-inspired AI Toolkit
Leveraging inspiration from biology combined with advances in machine learning:
Publications
- 2020
- Nature Machine Intelligence
- Stanislaw Wozniak
- Angeliki Pantazi
- et al.
- 2018
- IJCNN 2018
- Stanislaw Wozniak
- Angeliki Pantazi
- et al.
- 2017
- IEEE TCAS-II
- Stanislaw Wozniak
- Angeliki Pantazi
- et al.
- 2017
- IJCNN 2017
- Tomas Tuma
- Angeliki Pantazi
- et al.
- 2016
- Nature Nanotechnology
- Angeliki Pantazi
- Stanislaw Wozniak
- et al.
- 2016
- Nanotechnology
- Stanislaw Wozniak
- Tomas Tuma
- et al.
- 2016
- ISCAS 2016
