veyepar: Building Vector-Symbolic Architectures with Python

Author(s):	Fabio Cumbo
Location	Calypso
Date	jul Sun 28	Days Raw Files
Start	14:00	First Raw Start	13:39
Duration	00:30:00	Offset	0:20:44
End	14:30	Last Raw End	14:39
Chapters	00:00 0:00:14 0:08:43
Total cuts_time	26 min.

https://www.pyohio.org/2024/program/talks/building-vector-symbolic-architectures-with-python
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Vector\-Symbolic Architectures (a.k.a. Hyperdimensional Computing) is a relatively new computational paradigm that involves the use of random vectors in a high\-dimensional space to represent and process information. As a computational paradigm, it finds applications in a wide range of fields, including artificial intelligence, natural language processing, internet\-of\-things, robotics, bioinformatics, and other scientific domains.

Here we are going to introduce some fundamental concepts at the base of Hyperdimensional Computing, following a presentation of *hdlib*, a library for building Vector\-Symbolic Architectures with Python. Finally, we are going to see how to easily build a machine learning model based on the Hyperdimensional Computing paradigm as a practical use case.

As a reference, *hdlib* is open\-source, it is available on GitHub at [https://github.com/cumbof/hdlib](https://github.com/cumbof/hdlib), and it is published on the Journal of Open Source Software at [[https://doi.org/10\.21105/joss.05704](https://doi.org/10.21105/joss.05704)](https://doi.org/10.21105/joss.05704).

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