If you want to give a credit to this webinar series use the following entry when citing (BibTeX). 

Vector Symbolic Architectures (VSA), which is also known as hyperdimensional computing (HDC) is a subclass of cognitive computing architectures, which is rooted in the observation that key aspects of human memory, perception and cognition can be explained by the mathematical properties of high-dimensional spaces. In VSA, information is represented in vectors of extremely large dimensionality (several thousand bits). Such vectors can then be mathematically manipulated for implementing AI functions of binding, association and other types of cognitive operations in a straightforward manner.

With the emergence of novel brain-inspired computational technology like memristive devices, spiking microprocessors, which do not rely on exact computations the actuality of approximate computing methods grows high. The recent applications of VSA computing in robotics and energy-efficient realisation of conventional neural network architectures show its great potential for implementing AI functionality on such novel computing platforms. 

VSAONLINE has grown out of the initiative from  two groups at Luleå University of Technology (Sweden) and UC Berkeley (USA) to organise a physical workshop in March 2020, empowered by the grant from Swedish Foundation for Internationalization of Research and Higher Education (STINT).  During May - July 2020 we ran the first series of online webinars, which then became a regular event. Currently we have completed seven full seasons. The past events are available in menu "2020-2023".