Year : 2022, Volume : 13, Issue : 3
First page : ( 43) Last page : ( 52)
Print ISSN : 0975-8070. Online ISSN : 0975-8089. Published online : 2022  10.
Article DOI : 10.5958/0975-8089.2022.00005.7

An insight into the interesting world of RBMs - restricted boltzmann machines based monitoring of smart devices [SD] + IoT + high performance computing systems in heterogeneous complex AI environments involving : Cubesats/other space related hi-tech instruments

Kumar Nirmal Tej^1,*, Shmavonyan Gagik²

¹Senior Scientist, Informatics R&D, Current Member, antE Inst UTD, Dallas, TX, USA

²Professor/Director, Senior Scientist, Consultant, NPUA - Department of Physics - Yerevan - Armenia

^*Corresponding author email id: hmfg2014@gmail.com

Online Published on 10 May, 2023.

Received:  08  ,  2022; Accepted:  10  December,  2022.

Abstract

Deep Learning [DL] meets Physics i.e. Restricted Boltzmann Machines -> Theory & Implementation behind Restricted Boltzmann Machines -> A Powerful Tool for Recommender Systems involving : Space + Medicine + Telecoms + Military + HPC Systems - High Performance Computing Applications. A Simple and Short Technical Communication is presented on Using C/C++/Rust/Java/Python/Scala/Java/Ruby/ Dr. Racket Programming Languages involving : AI + IoT Informatics + BIG DATA + Theorem Proving. Finally, we are interested in understanding : “What is Embedded AI in the context of IoT Environments ? “ & “Can RBMs provide us with some sort of solution/s in evaluating Embedded AI”?

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Keywords

RBM, Programming languages, Deep learning, Informatics, BIG DATA, IoT.

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