Imperial College London
Alternate

Professor Themis Prodromakis

Faculty of Engineering, Department of Electrical and Electronic Engineering

Honorary Research Fellow
 
 
 
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Contact

 

+44 (0)20 7594 0840t.prodromakis Website

 
 
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Location

 

B422Bessemer BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Alexantrou:2020:10.1109/ICEIC49074.2020.9051149,
author = {Alexantrou, S and Prodromakis, T},
doi = {10.1109/ICEIC49074.2020.9051149},
title = {Hierarchical AI - From neurons to psychology},
url = {http://dx.doi.org/10.1109/ICEIC49074.2020.9051149},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - The undeniable successes of deep learning (and more generally statistical learning) in bringing pattern matching to the market is still just the tip of the iceberg of AI. In this talk we will look at a very high level overview of AI as a whole and see how it can be interpreted at very different levels of abstraction. Each level of abstraction boasts its own vocabulary and is suited to understanding different aspects of the general problem of artificial intelligence. We will walk through four 'levels of abstraction of AI' ranging from physical implementation all the way to semantic processing, and will investigate how memory technologies can play a vital role in their successful implementation. The aim is to show how innovation in the domain of memory tech can unlock the potential of AI to attack problems much more general than simple pattern matching and thus pave the way to the next wave of AI on the market.
AU  - Alexantrou,S
AU  - Prodromakis,T
DO  - 10.1109/ICEIC49074.2020.9051149
PY  - 2020///
TI  - Hierarchical AI - From neurons to psychology
UR  - http://dx.doi.org/10.1109/ICEIC49074.2020.9051149
ER  -
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