IAS Seminar "Data and Power Efficient Intelligence with Neuromorphic Hardware"

Speaker:

Emre Neftci, PhD, Assistant Professor, Neuromorphic Machine Intelligence Lab, Department of Cognitive Sciences, University of California Irvine, USA

Abstract:

The potential of machine learning and deep learning to advance artificial intelligence is driving a quest to build dedicated systems that accelerate such workloads at a large scale and in an autonomous fashion. A natural approach is to take inspiration from the brain by building neuromorphic hardware that emulates the biological processes of the brain using digital or mixed-signal technologies.

In this talk, I will present interdisciplinary approaches anchored in machine learning theory and computational neurosciences that enable the applicability of neuromorphic technologies to real-world, human-centric tasks. In particular I’ll discuss the following related challenges and their possible solutions:

(1) The models and tools of deep learning apply to neuromorphic hardware, but physical implementations of neural networks call for novel, continual and local learning algorithms;

(2) Neuromorphic technologies have potential advantages over conventional computers on tasks where real-time adaptability, autonomy or energy efficiency are necessary, but applications and benchmarks benefiting from these qualities are not yet identified;

(3) Challenges in memory technologies, compounded by a tradition of bottom-up approaches in the field and the lack of large-scale simulation environments block the road to major breakthroughs.

The recent algorithmic results I will present solve some of these challenges and pave the way toward the co-design of brain-inspired computing systems and algorithms with a mathematical viewpoint. These solutions enable the roadmap towards building a software framework for neuromorphic hardware with a Tensorflow-like workflow and leveraging the scalable, distributed, low-latency and energy- efficient nature of neuromorphic hardware.

Emre Neftci was invited by Dr. Jenia Jitsev (JSC).