English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Man-Computer Symbiosis (MCS) was originally envisioned by the famous computerpioneer J.C.R. Licklider in 1960, as a logical evolution of the then inchoaterelationship between computer and humans. In his paper, Licklider provided aset of criteria by which to judge if a Man-Computer System is a symbiotic one,and also provided some predictions about such systems in the near and farfuture. Since then, innovations in computer networks and the invention of theInternet were major developments towards that end. However, with most systemsbased on conventional logical algorithms, many aspects of Licklider's MCSremained unfulfilled. This paper explores the extent to which modern machinelearning systems in general, and deep learning ones in particular bestexemplify MCS systems, and why they are the prime contenders to achieve a trueMan-Computer Symbiosis as described by Licklider in his original paper in thefuture. The case for deep learning is built by illustrating each point of theoriginal criteria as well as the criteria laid by subsequent research into MCSsystems, with specific examples and applications provided to strengthen thearguments. The efficacy of deep neural networks in achieving Artificial GeneralIntelligence, which would be the perfect version of an MCS system is alsoexplored.

Modern Machine and Deep Learning Systems as a way to achieve Man-Computer Symbiosis