[Ground-station] IEEE talk from Dr.

[Michelle Thompson]

We support IEEE in many ways. Here's a recording of a recent talk that ORI
supported with volunteer labor.

https://youtu.be/fSOpdgQXIao

21 March 2023 Overview of Neuromorphic Computing Challenges and
Opportunities by Sakib Hasan PhD

Neuromorphic Computing promises orders of magnitude improvement in energy
efficiency compared to the traditional von Neumann computing paradigm. The
goal is to develop an adaptive, fault-tolerant, low-footprint, fast,
low-energy intelligent system by learning and emulating brain functionality
which can be realized through innovation in different abstraction layers
including material, device, circuit, architecture, and algorithm. As the
energy consumption in complex machine learning tasks keeps increasing
exponentially due to larger data sets and resource-constrained edge devices
becoming increasingly ubiquitous, neuromorphic computing approaches can be
a viable alternative to a deep convolutional neural network that is
dominating the field today. In this talk, I introduce neuromorphic
computing, outline a few representative examples from different layers of
the design stack (devices, circuits, and algorithms) and conclude with a
few important challenges and opportunities in this field.

-Michelle Thompson
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